<?xml version="1.0" encoding="UTF-8"?><!DOCTYPE article PUBLIC "-//NLM//DTD JATS (Z39.96) Journal Publishing DTD v1.2 20190208//EN" "http://jats.nlm.nih.gov/publishing/1.2/JATS-journalpublishing1.dtd"><article xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink" article-type="research-article" dtd-version="1.2" xml:lang="en">
    <front>
        <journal-meta>
            <journal-id journal-id-type="pmc">F1000Research</journal-id>
            <journal-title-group>
                <journal-title>F1000Research</journal-title>
            </journal-title-group>
            <issn pub-type="epub">2046-1402</issn>
            <publisher>
                <publisher-name>F1000 Research Limited</publisher-name>
                <publisher-loc>London, UK</publisher-loc>
            </publisher>
        </journal-meta>
        <article-meta>
            <article-id pub-id-type="doi">10.12688/f1000research.146907.3</article-id>
            <article-categories>
                <subj-group subj-group-type="heading">
                    <subject>Research Article</subject>
                </subj-group>
                <subj-group>
                    <subject>Articles</subject>
                </subj-group>
            </article-categories>
            <title-group>
                <article-title>Prognostic significance of tumor budding in pancreatic carcinoma: Digitalized image approach evaluation using artificial intelligence.</article-title>
                <fn-group content-type="pub-status">
                    <fn>
                        <p>[version 3; peer review: 2 approved]</p>
                    </fn>
                </fn-group>
            </title-group>
            <contrib-group>
                <contrib contrib-type="author" corresp="yes">
                    <name>
                        <surname>Ben Rejeb</surname>
                        <given-names>Sarra</given-names>
                    </name>
                    <role content-type="http://credit.niso.org/">Conceptualization</role>
                    <role content-type="http://credit.niso.org/">Investigation</role>
                    <role content-type="http://credit.niso.org/">Methodology</role>
                    <role content-type="http://credit.niso.org/">Writing &#x2013; Original Draft Preparation</role>
                    <role content-type="http://credit.niso.org/">Writing &#x2013; Review &amp; Editing</role>
                    <uri content-type="orcid">https://orcid.org/0000-0001-9150-3444</uri>
                    <xref ref-type="corresp" rid="c1">a</xref>
                    <xref ref-type="aff" rid="a1">1</xref>
                </contrib>
                <contrib contrib-type="author" corresp="no">
                    <name>
                        <surname>Yaacoubi</surname>
                        <given-names>Jasser</given-names>
                    </name>
                    <role content-type="http://credit.niso.org/">Data Curation</role>
                    <role content-type="http://credit.niso.org/">Formal Analysis</role>
                    <xref ref-type="aff" rid="a1">1</xref>
                </contrib>
                <aff id="a1">
                    <label>1</label>Pathology, Security Forces hospital Tunisia, Tunis, Tunisia</aff>
            </contrib-group>
            <author-notes>
                <corresp id="c1">
                    <label>a</label>
                    <email xlink:href="mailto:sarrabenrejeb88@yahoo.fr">sarrabenrejeb88@yahoo.fr</email>
                </corresp>
                <fn fn-type="conflict">
                    <p>No competing interests were disclosed.</p>
                </fn>
            </author-notes>
            <pub-date pub-type="epub">
                <day>2</day>
                <month>9</month>
                <year>2025</year>
            </pub-date>
            <pub-date pub-type="collection">
                <year>2024</year>
            </pub-date>
            <volume>13</volume>
            <elocation-id>282</elocation-id>
            <history>
                <date date-type="accepted">
                    <day>26</day>
                    <month>8</month>
                    <year>2025</year>
                </date>
            </history>
            <permissions>
                <copyright-statement>Copyright: &#x00a9; 2025 Ben Rejeb S and Yaacoubi J</copyright-statement>
                <copyright-year>2025</copyright-year>
                <license xlink:href="https://creativecommons.org/licenses/by/4.0/">
                    <license-p>This is an open access article distributed under the terms of the Creative Commons Attribution Licence, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.</license-p>
                </license>
            </permissions>
            <self-uri content-type="pdf" xlink:href="https://f1000research.com/articles/13-282/pdf"/>
            <abstract>
                <sec>
                    <title>Introduction</title>
                    <p>Pancreatic carcinoma (PC) is a highly malignant and lethal tumor characterized by a dismal prognosis which raised the need to identify other prognostic factors for better patient risk stratification. Tumor budding (TB), defined as isolated single cancer cells or small clusters of up to four cells at the invasive front, is an emerging histoprognostic factor associated with aggressiveness in various malignancies. This study investigated the prognostic significance of tumor budding (TB) in pancreatic carcinoma using artificial intelligence.</p>
                </sec>
                <sec>
                    <title>Methods</title>
                    <p>In this retrospective multicenter study, we collected all cases of PC diagnosed (2008-2022). TB was assed using 2 methods: manual on hematoxylin-eosin (HE) slides and semi-automated using QUPATH software. The selected slide for each case was digitalized using 
                        <uri xlink:href="https://www.mvi-inc.com/wp-content/uploads/NIS_4.00_D_User_Guide.pdf">NIS software</uri> version 4.00 connected to the microscope NIKON (Eclipse Ni-U). The pathological images were then incorporated into QUPATH. The budds were counted using cell count functionality based on the nucleus size and pixel variability, and TB scores were categorized as BUDD1(0-4), BUDD2(5-9) and BUDD3(&#x2265;10). We analyzed the association between the TB score and prognostic clinicopathological factors and overall survival.</p>
                </sec>
                <sec>
                    <title>Results</title>
                    <p>25 patients were included (mean age:62.3years;male-to-female ratio:2.57). TB was found in 100%of cases and a high TB score (BUDD2-3) was observed in 56%of cases (using QUPATH versus 48% using HE slides); statistical analysis showed no significant difference between the two methods (p=0.589). A high TB score was associated with older age (&gt;72 years), ductal histological subtype and advanced stage (pT&gt;2).53.8% of patients with lymph node metastasis or advanced stage had high TB score. Multivariate analysis revealed that TB score was strongly and independently associated with overall survival (OS), with a hazard ratio of 2.35.</p>
                </sec>
                <sec>
                    <title>Conclusion</title>
                    <p>TB is an additional prognostic factor in PC, and using artificial intelligence via QUPATH software offers a promising and accessible tool for pathologists to evaluate TB and to improve risk stratification in patients with PC.</p>
                </sec>
            </abstract>
            <kwd-group kwd-group-type="author">
                <kwd>Pancreatic cancer (PC)</kwd>
                <kwd>tumor budding (TB)</kwd>
                <kwd>prognosis</kwd>
                <kwd>overall survivor (OS)</kwd>
                <kwd>artificial intelligence.</kwd>
            </kwd-group>
            <funding-group>
                <award-group id="fund-1">
                    <funding-source>None</funding-source>
                </award-group>
                <funding-statement>The author(s) declared that no grants were involved in supporting this work.</funding-statement>
            </funding-group>
        </article-meta>
        <notes>
            <sec sec-type="version-changes">
                <label>Revised</label>
                <title>Amendments from Version 2</title>
                <p>This revised article on tumor budding in pancreatic carcinoma includes key updates from peer review, such as expanded introductions and abstracts with added context on TB's prognostic role, restructured sentences for clarity, and corrections for spelling and grammar issues. Methods sections have been refined by merging criteria and emphasizing the relevance of QUPATH for accessible digital analysis. The discussion now elaborates on TB's links to poor prognosis with more recent citations, enhancing overall rigor and alignment with current literature without changing core results.</p>
            </sec>
        </notes>
    </front>
    <body>
        <sec id="sec5" sec-type="intro">
            <title>Introduction</title>
            <p>Pancreatic carcinoma (PC) is an aggressive malignancy, representing the fourth leading cause of cancer-related deaths in developed countries, with an increasing incidence projected to make it the second leading cause by 2030.
                <sup>
                    <xref ref-type="bibr" rid="ref1">1</xref>
                </sup> It is often diagnosed at advanced stages (stages III-IV in over 80% of cases, where only 15-20% of patients are candidates for curative surgery.
                <sup>
                    <xref ref-type="bibr" rid="ref2">2</xref>
                </sup> Despite complete resection as the primary treatment for resectable disease, PC exhibits rapid progression and high recurrence rates (up to 90% within 5 years), even in node-negative cases, resulting in a 5-year survival rate of approximately 13% overall and 44% for localized, resected tumors. Although tumor resectability and stage remain the most relevant prognostic factors, there is an increasing need to focus on novel histo-prognostic factors that would enable better risk stratification for patients.
                <sup>
                    <xref ref-type="bibr" rid="ref1">1</xref>
                </sup>
            </p>
            <p>Tumor budding (TB), defined as the presence of isolated single cancer cells or clusters of up to four cancer cells at the invasive tumor front, has been recognized as an emerging marker of aggressiveness related to the epithelial to mesenchymal process in patients with colorectal cancer. Thus, TB has been introduced as a routine prognostic marker in colorectal cancer to stratify patients for adjuvant chemotherapy for stage II tumors.
                <sup>
                    <xref ref-type="bibr" rid="ref3">3</xref>
                </sup>
                <sup>,</sup>
                <sup>
                    <xref ref-type="bibr" rid="ref4">4</xref>
                </sup>
            </p>
            <p>In PC, although it has been reported that TB has a clear association with adverse prognosis, TB is still not systematically reported by pathologists, and there are no clearly defined recommendations on TB counting in PC.
                <sup>
                    <xref ref-type="bibr" rid="ref5">5</xref>
                </sup>
                <sup>&#x2013;</sup>
                <sup>
                    <xref ref-type="bibr" rid="ref8">8</xref>
                </sup>
            </p>
            <p>This study aimed to assess the tumor budding score in PC using artificial intelligence and to explore the association of TB clinicopathological prognostic factors.</p>
        </sec>
        <sec id="sec6" sec-type="methods">
            <title>Methods</title>
            <sec id="sec7">
                <title>Study design</title>
                <p>This retrospective, bicentric, cross-sectional study was approved by the Biomedical Research Ethics Committee of our institution (Approval number12/23).</p>
            </sec>
            <sec id="sec8">
                <title>Patient cohort and clinic-pathological data</title>
                <p>

                    <bold>Inclusion criteria:</bold>
                </p>
                <p>All patients with primary pancreatic adenocarcinoma diagnosed on surgical specimens or pancreatic biopsies in the pathology departments of the Security Forces and Charles Nicolles Hospitals over a period of 14 years (March 2008-December 2022) were included.</p>
                <p>

                    <bold>Exclusion criteria:</bold>
                </p>
                <p>The following cases were excluded:
                    <list list-type="bullet">
                        <list-item>
                            <label>&#x2022;</label>
                            <p>Patients with intraductal papillary mucinous tumors without invasive foci</p>
                        </list-item>
                        <list-item>
                            <label>&#x2022;</label>
                            <p>Other histological types (neuroendocrine or mesenchymal tumors)</p>
                        </list-item>
                        <list-item>
                            <label>&#x2022;</label>
                            <p>Patients with ampullary, gallbladder, or bile duct adenocarcinoma; patients with unusable clinical records</p>
                        </list-item>
                        <list-item>
                            <label>&#x2022;</label>
                            <p>Small and non-representative biopsy samples</p>
                        </list-item>
                        <list-item>
                            <label>&#x2022;</label>
                            <p>Biopsy samples of suboptimal technical quality that created artifacts during image digitization</p>
                        </list-item>
                    </list>
                </p>
            </sec>
            <sec id="sec9">
                <title>Tumor budding counting</title>
                <p>

                    <underline>

                        <italic toggle="yes">Pathological HE slides analysis</italic>
</underline>
                </p>
                <p>All hematoxylin and eosin (HE)-stained slides were reviewed by two pathologists to select the most representative slides for tumor budding assessment.</p>
                <p>Tumor budding was assessed according to the recommendations of the International Tumor Budding Consensus Conference (ITBCC) for colorectal cancer.
                    <sup>
                        <xref ref-type="bibr" rid="ref9">9</xref>
                    </sup> TB was identified as a single tumor cell or a cluster of &lt;5 cells. For each selected HE-stained slide, hotspot areas either at the invasion front or within the tumor center were identified at 10-fold magnification. TB was counted by two pathologists over a field of 0.785 mm
                    <sup>2</sup> at 20-fold magnification.</p>
                <p>

                    <underline>

                        <italic toggle="yes">Digital assessed approach</italic>
</underline>
                </p>
                <p>The slides that were selected for TB counting at 20-fold magnification were digitalized using NIS image scope software, which was connected to a Nikon microscope (Eclipse Ni-U) (
                    <xref ref-type="fig" rid="f1">
Figure 1</xref>).</p>
                <fig fig-type="figure" id="f1" orientation="portrait" position="float">
                    <label>
Figure 1. </label>
                    <caption>
                        <title>Screenshot of digitalizing an HE X 20 slide on NIS software.</title>
                    </caption>
                    <graphic id="gr1" orientation="portrait" position="float" xlink:href="https://f1000research-files.f1000.com/manuscripts/187231/d041a617-fdc7-4aae-9aa2-7f085af2b0c7_figure1.gif"/>
                </fig>
                <p>These images were exported in GIF format and then uploaded to open-source software QUPATH (version v0.4.3, 
                    <ext-link ext-link-type="uri" xlink:href="https://qupath.github.io/">https://qupath.github.io/</ext-link>) for digital pathology.
                    <sup>
                        <xref ref-type="bibr" rid="ref10">10</xref>
                    </sup> TB was assessed and evaluated using a semi-automated method according to the methodology of Budeau et al.
                    <sup>
                        <xref ref-type="bibr" rid="ref11">11</xref>
                    </sup> In this study, the authors assessed TB in a cohort of 92 patients with intrahepatic cholangiocarcinoma. Firstly, Tumor budding was identified in one tissue slide on the basis of the recommendations of the International Tumor Budding Consensus Conference 2016.
                    <sup>
                        <xref ref-type="bibr" rid="ref9">9</xref>
                    </sup> The HE slides were then digitalized and all images were analyzed in QuPath 16 (Version 0.1.2) (
                    <ext-link ext-link-type="uri" xlink:href="https://qupath.github.io/">https://qupath.github.io/</ext-link>). Ten rectangles of H&amp;E stained tissue slides were evaluated for both, the tumor-host interface and the tumor center. Each rectangle was standardized for an area of 0.785 mm
                    <sup>2</sup> as recommended. The function &#x201c;cell detection&#x201d; facilitates the manual differentiation of tumor buds from larger tumor groups by detecting individual cells and only having to assess the number of cells.
                    <sup>
                        <xref ref-type="bibr" rid="ref11">11</xref>
                    </sup> In the present study, according to this methodological approach, we used the annotation functionality of QUPATH to highlight tumor cells (red color). Each 20-fold magnification digitalized slide was segmented into five rectangles, each rectangle corresponded to an area of 0.785 mm.
                    <sup>
                        <xref ref-type="bibr" rid="ref4">4</xref>
                    </sup>
                    <sup>,</sup>
                    <sup>
                        <xref ref-type="bibr" rid="ref10">10</xref>
                    </sup> We used the &#x201c;cell detection&#x201d; functionality to circumscribe tumor cells based on nucleus sigma between 3 and 8. The TB score was counted manually for each rectangle, and the final TB score for each case was defined as the average of the five rectangles (
                    <xref ref-type="fig" rid="f2">
Figure 2a</xref>, 
                    <xref ref-type="fig" rid="f2">
b</xref> and 
                    <xref ref-type="fig" rid="f2">
c</xref>).</p>
                <fig fig-type="figure" id="f2" orientation="portrait" position="float">
                    <label>
Figure 2. </label>
                    <caption>
                        <title>(a, b and c) Detection of single tumor cells and small clusters on QUPATH software.</title>
                    </caption>
                    <graphic id="gr2" orientation="portrait" position="float" xlink:href="https://f1000research-files.f1000.com/manuscripts/187231/d041a617-fdc7-4aae-9aa2-7f085af2b0c7_figure2.gif"/>
                </fig>
                <p>

                    <underline>

                        <italic toggle="yes">Classification of tumor budding</italic>
</underline>
                </p>
                <p>For both morphological and semi-automated methods, the final TB score for each case was categorized into four groups according to the recommendations of ITBCC
                    <sup>
                        <xref ref-type="bibr" rid="ref4">4</xref>
                    </sup>:

                    <list list-type="bullet">
                        <list-item>
                            <label>&#x2713;</label>
                            <p>BD0: no budds</p>
                        </list-item>
                        <list-item>
                            <label>&#x2713;</label>
                            <p>BD1: 1-4 Budds</p>
                        </list-item>
                        <list-item>
                            <label>&#x2713;</label>
                            <p>BD2: 5-10 Budds</p>
                        </list-item>
                        <list-item>
                            <label>&#x2713;</label>
                            <p>BD3:&gt;10Budds</p>
                        </list-item>
                    </list>
                </p>
                <p>&#x2192; The final TB score is calculated as follows:
                    <list list-type="bullet">
                        <list-item>
                            <label>&#x27a2;</label>
                            <p>Low: BD0-BD1</p>
                        </list-item>
                        <list-item>
                            <label>&#x27a2;</label>
                            <p>High: BD2-BD3</p>
                        </list-item>
                    </list>
                </p>
            </sec>
            <sec id="sec10">
                <title>Statistical analysis</title>
                <p>Statistical analysis was performed using SPSS21 software [(IBM Corp. Released 2021. IBM SPSS Statistics for Windows, Version 28.0. Armonk, NY: IBM Corp) The statistical analyses performed in this article using SPSS21 software can be conducted using the freely accessible software Jamovi 
                    <ext-link ext-link-type="uri" xlink:href="https://www.jamovi.org">https://www.jamovi.org</ext-link>. The user manual is available at the following link. 
                    <ext-link ext-link-type="uri" xlink:href="https://lsj.readthedocs.io/ru/latest/Ch03/Ch03_jamoviIntro_1.html">https://lsj.readthedocs.io/ru/latest/Ch03/Ch03_jamoviIntro_1.html</ext-link>. We first used the Kolmogorov-Smirnov test to evaluate the normal distribution and variance homogeneity tests on all continuous variables. Qualitative variables were summarized using frequencies and percentages. Quantitative parameters were summarized using medians and standard deviations. We used Fisher&#x2019;s exact test to assess the relationship between TB and clinical and pathological parameters. A p-value of less than 5% was considered statistically significant or nearly significant for p [0.05-0.08], considering the small sample size.</p>
                <p>Survival data were analyzed by generating survival curves using the Kaplan-Meier method and compared using the Log-rank test in univariate analysis.</p>
            </sec>
        </sec>
        <sec id="sec11" sec-type="results">
            <title>Results</title>
            <p>25 cases patients were included in this study. The mean age of the patients was 62.3years old the male-to-female ratio was 2.57. Alcohol consumption and smoking were found in 36% and 56% of the patients, respectively. Clinical signs included abdominal pain (96%), loss of body weight and condition (80%), jaundice (72%), transit disorder (28%), dark urine (64%), discolored stool (44%), pruritus (36%), and fever (16%). On physical examination, a palpable gallbladder was found in 36% and ascites in 12% of patients. Laboratory tests revealed anemia in 64%, elevated CA19.9 in 76%, cytolysis in 52%, and cholestasis in 76%. Surgery was performed in 80% of the cases: cephalic duodeno-pancreatectomy (75%), caudal pancreatectomy (20%), and double bypass (5%). Neoadjuvant therapy was performed in 12% of patients, adjuvant treatment in 56%, and palliative care in 28%. Local recurrence occurred in 44% of patients, distant metastases in 38.9%, and death in 72%. The pathological findings are summarized in 
                <xref ref-type="table" rid="T1">
Table 1</xref>.</p>
            <table-wrap id="T1" orientation="portrait" position="float">
                <label>
Table 1. </label>
                <caption>
                    <title>Pathological features of patients.</title>
                </caption>
                <table content-type="article-table" frame="hsides">
                    <thead>
                        <tr>
                            <th align="left" colspan="3" rowspan="1" valign="top"/>
                            <th align="left" colspan="1" rowspan="1" valign="top">
Percentage</th>
                        </tr>
                    </thead>
                    <tbody>
                        <tr>
                            <td align="left" colspan="2" rowspan="3" valign="top">Histological subtype</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">
                                <bold>Ductal</bold>
</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">
                                <bold>85%</bold>
</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">
                                <bold>Intestinal</bold>
</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">10%</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">
                                <bold>Adeno-squamous
</bold>
</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">5%</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="2" rowspan="2" valign="top">Grade</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">
                                <bold>Low</bold>
</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">72%</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">
                                <bold>High</bold>
</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">28%</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="2" rowspan="2" valign="top">Peri-neural invasion</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">
                                <bold>Positive</bold>
</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">80%</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">
                                <bold>Negative</bold>
</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">20%</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="2" rowspan="2" valign="top">Vascular invasion</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">
                                <bold>Positive</bold>
</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">
                                <bold>55</bold>%</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">
                                <bold>Negative</bold>
</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">45%</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="2" rowspan="2" valign="top">Surgical margins</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">
                                <bold>Positive</bold>
</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">
                                <bold>80%</bold>
</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">
                                <bold>Negative</bold>
</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">20%</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="8" valign="top">TNM stagging</td>
                            <td align="left" colspan="1" rowspan="4" valign="top">
                                <bold>T</bold>
</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">
                                <bold>T1</bold>
</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">5%</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">
                                <bold>T2</bold>
</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">45%</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">
                                <bold>T3</bold>
</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">40%</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">
                                <bold>T4</bold>
</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">10%</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="3" valign="top">
                                <bold>N</bold>
</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">
                                <bold>N0</bold>
</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">45%</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">
                                <bold>N1</bold>
</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">45%</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">
                                <bold>N2</bold>
</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">10%</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">
                                <bold>M</bold>
</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">
                                <bold>M0</bold>
</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">100%</td>
                        </tr>
                    </tbody>
                </table>
            </table-wrap>
            <p>Tumor budding was found in 
                <bold>100%</bold> of cases using the morphological method and 
                <bold>84%</bold> using the digitalized approach. The number varied from 1 to 37 (mean: 8.04, median:4) using the morphological method and from 0 to 19 (mean: 5.92, median: 6) using the QUPATH software. Tumor budding counts are summarized in 
                <xref ref-type="table" rid="T2">
Table 2</xref>.</p>
            <table-wrap id="T2" orientation="portrait" position="float">
                <label>
Table 2. </label>
                <caption>
                    <title>Tumor budding counting with both methods.</title>
                </caption>
                <table content-type="article-table" frame="hsides">
                    <thead>
                        <tr>
                            <th align="left" colspan="1" rowspan="1" valign="top">Budding</th>
                            <th align="left" colspan="1" rowspan="1" valign="top">Morphological method</th>
                            <th align="left" colspan="1" rowspan="1" valign="top">
Semi-automated method</th>
                        </tr>
                    </thead>
                    <tbody>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">BUD 1 (0 &#x2013; 4 buds)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">52%(13)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">44%(11)</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">BUD 2 (5 &#x2013; 9 buds)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">16%(4)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">44%(11)</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">BUD 3 (&#x2265;10 buds)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">32%(8)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">12%(3)</td>
                        </tr>
                    </tbody>
                </table>
            </table-wrap>
            <p>A high TB score (BUDD2-3) was found in 48% of the cases using the morphological method and 56% using the semi-automated QUPATH method. No statistically significant differences were observed between the two methods (p=0.589).</p>
            <sec id="sec12">
                <title>Univariate analysis</title>
                <p>Using morphological TB score, a statistically significant association was found between high TB score and advanced age &gt;72 ans (p=0.03). Considering the small sample size, 84.6% of tumors with the ductal subtype had a high TB score, and the difference was nearly statistically significant (p=0.07).</p>
                <p>53.8% of patients with lymph node invasion or advanced pT stage had high TB score (p=0.53 and p=0.32).</p>
                <p>76.9 Of the patients with perineural invasion, 76.9% had high TB scores. The association between tumor budding and clinicopathological features of pancreatic carcinoma is summarized in 
                    <xref ref-type="table" rid="T3">
Table 3</xref>.</p>
                <table-wrap id="T3" orientation="portrait" position="float">
                    <label>
Table 3. </label>
                    <caption>
                        <title>Association of clinic-pathological characteristics with tumor budding.</title>
                    </caption>
                    <table content-type="article-table" frame="hsides">
                        <thead>
                            <tr>
                                <th align="left" colspan="1" rowspan="1" valign="top"/>
                                <th align="left" colspan="1" rowspan="1" valign="top">Low TB (n=12)</th>
                                <th align="left" colspan="1" rowspan="1" valign="top">High TB (n=13)</th>
                                <th align="left" colspan="1" rowspan="1" valign="top">
p</th>
                            </tr>
                        </thead>
                        <tbody>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">Age &gt;72 ans</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">0</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">4</td>
                                <td align="left" colspan="1" rowspan="2" valign="top">
                                    <bold>0.03</bold>
</td>
                            </tr>
                            <tr>
                                <td colspan="1" rowspan="1"/>
                                <td align="left" colspan="1" rowspan="1" valign="top">0%</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">30.7%</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">Male</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">10</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">8</td>
                                <td align="left" colspan="1" rowspan="2" valign="top">0.22</td>
                            </tr>
                            <tr>
                                <td colspan="1" rowspan="1"/>
                                <td align="left" colspan="1" rowspan="1" valign="top">83.3%</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">61.5%</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">Smoking</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">9</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">5</td>
                                <td align="left" colspan="1" rowspan="2" valign="top">0.07</td>
                            </tr>
                            <tr>
                                <td colspan="1" rowspan="1"/>
                                <td align="left" colspan="1" rowspan="1" valign="top">75%</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">35.7%</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">Ascitis</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">0</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">3</td>
                                <td align="left" colspan="1" rowspan="2" valign="top">0.09</td>
                            </tr>
                            <tr>
                                <td colspan="1" rowspan="1"/>
                                <td align="left" colspan="1" rowspan="1" valign="top">0%</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">23%</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">High tumor size</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">9</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">8</td>
                                <td align="left" colspan="1" rowspan="2" valign="top">0.38</td>
                            </tr>
                            <tr>
                                <td colspan="1" rowspan="1"/>
                                <td align="left" colspan="1" rowspan="1" valign="top">75%</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">61.5%</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">Subtype</td>
                                <td colspan="1" rowspan="1"/>
                                <td colspan="1" rowspan="1"/>
                                <td colspan="1" rowspan="1"/>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">Ductal</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">6</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">11</td>
                                <td align="left" colspan="1" rowspan="2" valign="top">
                                    <bold>0.07</bold>
</td>
                            </tr>
                            <tr>
                                <td colspan="1" rowspan="1"/>
                                <td align="left" colspan="1" rowspan="1" valign="top">50%</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">

                                    <bold>84.6%</bold>
</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">Intestinal</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">2</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">0</td>
                                <td align="left" colspan="1" rowspan="2" valign="top">0.22</td>
                            </tr>
                            <tr>
                                <td colspan="1" rowspan="1"/>
                                <td align="left" colspan="1" rowspan="1" valign="top">16.6%</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">0.0%</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">Adenosquamous</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">0</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">1</td>
                                <td align="left" colspan="1" rowspan="2" valign="top">0.52</td>
                            </tr>
                            <tr>
                                <td colspan="1" rowspan="1"/>
                                <td align="left" colspan="1" rowspan="1" valign="top">0.0%</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">7.6%</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">Surgical margins</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">1</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">3</td>
                                <td align="left" colspan="1" rowspan="2" valign="top">0.46</td>
                            </tr>
                            <tr>
                                <td colspan="1" rowspan="1"/>
                                <td align="left" colspan="1" rowspan="1" valign="top">8.3%</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">23%</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">Peri-neural invasion</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">6</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">10</td>
                                <td align="left" colspan="1" rowspan="2" valign="top">0.53</td>
                            </tr>
                            <tr>
                                <td colspan="1" rowspan="1"/>
                                <td align="left" colspan="1" rowspan="1" valign="top">50%</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">

                                    <bold>76.9%</bold>
</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">Vascular invasion</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">3</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">8</td>
                                <td align="left" colspan="1" rowspan="2" valign="top">0.20</td>
                            </tr>
                            <tr>
                                <td colspan="1" rowspan="1"/>
                                <td align="left" colspan="1" rowspan="1" valign="top">25%</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">

                                    <bold>61.5%</bold>
</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">High Grade</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">1</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">4</td>
                                <td align="left" colspan="1" rowspan="2" valign="top">0.61</td>
                            </tr>
                            <tr>
                                <td colspan="1" rowspan="1"/>
                                <td align="left" colspan="1" rowspan="1" valign="top">8.3%</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">30.7%</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">T &gt;2</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">6</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">4</td>
                                <td align="left" colspan="1" rowspan="2" valign="top">
                                    <bold>0.08</bold>
</td>
                            </tr>
                            <tr>
                                <td colspan="1" rowspan="1"/>
                                <td align="left" colspan="1" rowspan="1" valign="top">50%</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">30.7%</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">N+</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">4</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">7</td>
                                <td align="left" colspan="1" rowspan="2" valign="top">0.53</td>
                            </tr>
                            <tr>
                                <td colspan="1" rowspan="1"/>
                                <td align="left" colspan="1" rowspan="1" valign="top">25%</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">

                                    <bold>53.8%</bold>
</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">M+</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">6</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">5</td>
                                <td align="left" colspan="1" rowspan="2" valign="top">0.56</td>
                            </tr>
                            <tr>
                                <td colspan="1" rowspan="1"/>
                                <td align="left" colspan="1" rowspan="1" valign="top">50%</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">38.4%</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">Advanced stage</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">7</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">7</td>
                                <td align="left" colspan="1" rowspan="2" valign="top">0.32</td>
                            </tr>
                            <tr>
                                <td colspan="1" rowspan="1"/>
                                <td align="left" colspan="1" rowspan="1" valign="top">58.3%</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">

                                    <bold>53.8%</bold>
</td>
                            </tr>
                        </tbody>
                    </table>
                </table-wrap>
            </sec>
            <sec id="sec13">
                <title>Multivariate analysis</title>
                <p>On multivariate analysis, tumor grade, vascular invasion, and tumor budding affected overall survival (p=0.04, p=0.07, p=0.016, respectively) (
                    <xref ref-type="fig" rid="f3">
Figures 3</xref>, 
                    <xref ref-type="fig" rid="f4">4</xref>, 
                    <xref ref-type="fig" rid="f5">5</xref>).</p>
                <fig fig-type="figure" id="f3" orientation="portrait" position="float">
                    <label>
Figure 3. </label>
                    <caption>
                        <title>Tumoral budding impact on overall survival (time of death).</title>
                    </caption>
                    <graphic id="gr3" orientation="portrait" position="float" xlink:href="https://f1000research-files.f1000.com/manuscripts/187231/d041a617-fdc7-4aae-9aa2-7f085af2b0c7_figure3.gif"/>
                </fig>
                <fig fig-type="figure" id="f4" orientation="portrait" position="float">
                    <label>
Figure 4. </label>
                    <caption>
                        <title>Vascular invasion impact on local recurrence.</title>
                    </caption>
                    <graphic id="gr4" orientation="portrait" position="float" xlink:href="https://f1000research-files.f1000.com/manuscripts/187231/d041a617-fdc7-4aae-9aa2-7f085af2b0c7_figure4.gif"/>
                </fig>
                <fig fig-type="figure" id="f5" orientation="portrait" position="float">
                    <label>
Figure 5. </label>
                    <caption>
                        <title>Tumor grade impact on recurrence.</title>
                    </caption>
                    <graphic id="gr5" orientation="portrait" position="float" xlink:href="https://f1000research-files.f1000.com/manuscripts/187231/d041a617-fdc7-4aae-9aa2-7f085af2b0c7_figure5.gif"/>
                </fig>
            </sec>
        </sec>
        <sec id="sec14" sec-type="discussion">
            <title>Discussion</title>
            <p>In the present study, tumor budding was found in 100%of cases using morphological methods and 84% of cases using the digitalized approach. The difference observed between both methods suggests that using a semi-automated approach may offer greater analytical precision by reducing false positives. These cases likely corresponded to atypical mesenchymal fibroblastic or myofibroblastic cells or poorly differentiated tumor glands that were mistaken for isolated tumor cells on microscopic evaluation.</p>
            <p>Overall, according to our results, tumor budding is observed at a high frequency in pancreatic carcinoma, which is consistent with previous reports indicating that TB is reported in approximately 85-100% of specimens with pancreatic carcinoma.
                <sup>
                    <xref ref-type="bibr" rid="ref5">5</xref>
                </sup>
                <sup>,</sup>
                <sup>
                    <xref ref-type="bibr" rid="ref7">7</xref>
                </sup>
                <sup>,</sup>
                <sup>
                    <xref ref-type="bibr" rid="ref8">8</xref>
                </sup> This fact raises the hypothesis that TB is a relatively constant finding that could also be a pervasive feature of pancreatic carcinoma, especially in biopsy specimens.
                <sup>
                    <xref ref-type="bibr" rid="ref5">5</xref>
                </sup>
            </p>
            <p>In our study, a high TB score was found in 48% morphologically, and in 56% using QUPATH. Hence, using the QUPATH software reduced the number of cases classified as high BUDD3 with the morphological approach. This is due to the software&#x2019;s precision in distinguishing between isolated tumor cells or clusters of fewer than 5 cells, which meet the definition of tumor budding, as opposed to poorly differentiated carcinoma clusters or remnants of neuroendocrine islets that were misdiagnosed as TB on HE slides examination and were probably false positives. Indeed, the annotation option in QUPATH software allows for the identification and deselection of false positives.</p>
            <p>In the present study, the rates of high TB were slightly lower than that reported in previous studies reporting a high TB score in about 56 to 80% of cases.
                <sup>
                    <xref ref-type="bibr" rid="ref5">5</xref>
                </sup>
                <sup>,</sup>
                <sup>
                    <xref ref-type="bibr" rid="ref7">7</xref>
                </sup>
                <sup>,</sup>
                <sup>
                    <xref ref-type="bibr" rid="ref8">8</xref>
                </sup> These disparities may be partly explained by the differences in TB counting methods, the surface of the HPF, and the use of immunohistochemistry in some studies to identify CK+-stained tumor cells. TB is defined as single cells or clusters of &lt;5 cells at the tumor invasion front.
                <sup>
                    <xref ref-type="bibr" rid="ref4">4</xref>
                </sup>
                <sup>,</sup>
                <sup>
                    <xref ref-type="bibr" rid="ref9">9</xref>
                </sup> This quantifiable histological feature has gained attention over the last 10years and has proven its prognostic value in many cancers. The International Tumor Budding Consensus Conference (ITBCC) proposed a scoring system for tumor buds in colorectal carcinomas that was later applied to other cancers such as hepatocellular, oral squamous cell, and bladder cancers.
                <sup>
                    <xref ref-type="bibr" rid="ref9">9</xref>
                </sup>
                <sup>,</sup>
                <sup>
                    <xref ref-type="bibr" rid="ref11">11</xref>
                </sup> However, there is still no standardized method for reporting tumor budding in PC, and various approaches are available to count tumor buds either on HE slides or using pathological image analysis softwares.
                <sup>
                    <xref ref-type="bibr" rid="ref11">11</xref>
                </sup>
                <sup>,</sup>
                <sup>
                    <xref ref-type="bibr" rid="ref12">12</xref>
                </sup> In the present study, we first assessed tumor budding in pancreatic carcinoma specimens according to the recommendations of the ITBCC at 20-fold magnification for a field of 0.785 mm
                <sup>2</sup>, either at the tumor front or within the tumor center. Then, similar to the published study of Budeau et al.,
                <sup>
                    <xref ref-type="bibr" rid="ref11">11</xref>
                </sup> we extrapolated the ITBCC counting approach on an optic microscope to a digital image analysis system using QUPATH, an open-access software for digital image analysis. QUPATH is completely free, which enables pathologists in low-income countries to have access to digital pathology analysis.
                <sup>
                    <xref ref-type="bibr" rid="ref10">10</xref>
                </sup> The tumor cell detection functionality of the QUPATH software facilitates distinguishing between tumor cells and small clusters from a larger group of cells. In addition, compared to &#x201c;analog&#x201d; microscopy, QUAPTH offers the possibility of re-evaluating tumor buds at anytimes higher than those of other pathologists.
                <sup>
                    <xref ref-type="bibr" rid="ref11">11</xref>
                </sup> Although a high TB score was found in 48% of patients using the first method compared with 56% using the digitalized approach, the difference was not statistically significant (p=0.589). Hence, QUPATH could be an interesting, costless, and accurate alternative for pathologists, which would considerably reduce the work time and facilitate TB counting. This approach is particularly relevant for enhancing reproducibility and efficiency in TB scoring, potentially standardizing its use in clinical pathology worldwide, especially in low-resource settings.</p>
            <p>According to the recommendations of ITBCC, the TB score is categorized as a three-tier grading system for patient risk stratification.
                <sup>
                    <xref ref-type="bibr" rid="ref9">9</xref>
                </sup>
                <sup>,</sup>
                <sup>
                    <xref ref-type="bibr" rid="ref11">11</xref>
                </sup> In the present study, similar to the study published by Tanaka et al.,
                <sup>
                    <xref ref-type="bibr" rid="ref12">12</xref>
                </sup> we first graded the TB score as low (BUDD1), intermediate (BUDD2), and high (BUDD3) but later combined BUDD2 and BUDD3 groups into high TB scores for statistical analysis purpose. Consequently, we compared the high and low TB score groups using clinicopathological and survival data.</p>
            <p>Using the morphological method results, we demonstrated a statistically significant (or nearly significant) association between high tumor budding and advanced age &gt;72 years (p=0.03), ductal subtype (p=0.07), and advanced-stage pT&gt;pT2 (p=0.08). These results are consistent with those of previous studies that demonstrated an association between high TB and prognostic factors such as poor differantiation, lympho-vascular invasion, peri-neural invasion. Regarding prognosis, high TB was independently associated with worse OS (HR 2.35), reflecting its role in EMT, promoting metastasis and recurrence.
                <sup>
                    <xref ref-type="bibr" rid="ref13">13</xref>
                </sup> Multiple meta-analyses and systematic reviews have consistently established high-grade TB as a robust, independent predictor of poor outcomes in PDAC, including reduced overall survival (pooled HR 2.13, 95% CI 1.63-2.78) and disease-free survival (pooled HR 1.85, 95% CI 1.45-2.36), even after adjusting for stage, grade, and lymph node status.
                <sup>
                    <xref ref-type="bibr" rid="ref14">14</xref>
                </sup>
                <sup>&#x2013;</sup>
                <sup>
                    <xref ref-type="bibr" rid="ref16">16</xref>
                </sup>
            </p>
            <p>In some studies, high TB was linked to adverse clinicopathologic features such as lymphovascular invasion, perineural invasion, higher tumor grade, and nodal metastasis, which contribute to its prognostic impact.
                <sup>
                    <xref ref-type="bibr" rid="ref13">13</xref>
                </sup>
                <sup>,</sup>
                <sup>
                    <xref ref-type="bibr" rid="ref17">17</xref>
                </sup> Recent studies, including those in neoadjuvant therapy settings, showed that TB remains prognostic, with high budding indicating increased risk of recurrence and metastasis, supporting its use for identifying patients who may benefit from intensified adjuvant therapies or closer surveillance.
                <sup>
                    <xref ref-type="bibr" rid="ref5">5</xref>
                </sup>
                <sup>,</sup>
                <sup>
                    <xref ref-type="bibr" rid="ref18">18</xref>
                </sup>
                <sup>&#x2013;</sup>
                <sup>
                    <xref ref-type="bibr" rid="ref20">20</xref>
                </sup> Furthermore, TB&#x2019;s association with EMT markers suggests it represents a biologically aggressive phenotype, advocating for its routine inclusion in pathology reports to enhance risk stratification and personalize treatment in PDAC.
                <sup>
                    <xref ref-type="bibr" rid="ref14">14</xref>
                </sup>
                <sup>,</sup>
                <sup>
                    <xref ref-type="bibr" rid="ref21">21</xref>
                </sup> In a study published by O&#x2019;Connor et al.,
                <sup>
                    <xref ref-type="bibr" rid="ref7">7</xref>
                </sup> high-grade budding (&gt; 10 buds in 10 HPFs) was associated with a high tumor grade, lymphovascular invasion, and perineural invasion. In our study, 53.8% of patients with lymph node invasion or advanced stage had a high TB score; likewise, 76.9% of patients with perineural invasion had a high TB score. However, these findings were not statistically significant (p=0.53, p=0.32, and p=0.53, respectively), which could be related to the small sample size in our study.</p>
            <p>Of note, regardless of the method used, many other studies on pancreatic cancer did not reveal a statistically significant association between TB and prognostic factors.
                <sup>
                    <xref ref-type="bibr" rid="ref5">5</xref>
                </sup>
                <sup>,</sup>
                <sup>
                    <xref ref-type="bibr" rid="ref7">7</xref>
                </sup>
                <sup>,</sup>
                <sup>
                    <xref ref-type="bibr" rid="ref22">22</xref>
                </sup>
                <sup>&#x2013;</sup>
                <sup>
                    <xref ref-type="bibr" rid="ref24">24</xref>
                </sup>
            </p>
            <p>In the present study, the authors described a statistically significant association between tumor budding and overall survival (p=0.016) in the multivariate analysis after adjusting for other significant variables. This finding is consistent with previous reports that support the prognostic value of the TB score in pancreatic carcinoma for better patient stratification and treatment guiding.
                <sup>
                    <xref ref-type="bibr" rid="ref5">5</xref>
                </sup>
                <sup>,</sup>
                <sup>
                    <xref ref-type="bibr" rid="ref7">7</xref>
                </sup>
                <sup>,</sup>
                <sup>
                    <xref ref-type="bibr" rid="ref8">8</xref>
                </sup> Although these results are promising, there are still many discrepancies in the TB counting methods. First, some authors only considered TB at the tumor-host interface
                <sup>
                    <xref ref-type="bibr" rid="ref7">7</xref>
                </sup>; however, there is increasing evidence that intra-tumor and peri-tumor buds have comparable prognostic significance.
                <sup>
                    <xref ref-type="bibr" rid="ref9">9</xref>
                </sup>
                <sup>,</sup>
                <sup>
                    <xref ref-type="bibr" rid="ref11">11</xref>
                </sup>
                <sup>&#x2013;</sup>
                <sup>
                    <xref ref-type="bibr" rid="ref13">13</xref>
                </sup>
                <sup>,</sup>
                <sup>
                    <xref ref-type="bibr" rid="ref18">18</xref>
                </sup>
                <sup>,</sup>
                <sup>
                    <xref ref-type="bibr" rid="ref22">22</xref>
                </sup>
                <sup>&#x2013;</sup>
                <sup>
                    <xref ref-type="bibr" rid="ref26">26</xref>
                </sup> Second, some authors suggested that tumor budding evaluation is more accurate and reproducible using immunohistochemistry with anti-CK antibody
                <sup>
                    <xref ref-type="bibr" rid="ref3">3</xref>
                </sup>; however, in a multicenter study, Hacking S et al,
                <sup>
                    <xref ref-type="bibr" rid="ref27">27</xref>
                </sup> demonstrated that although immunohistochemical staining facilitates the detection of tumor cells, it has comparable intra- and inter-observatory reproducibility to the HE slides TB counting approach. Finally, in the era of artificial intelligence, using digital pathology for TB assessment is an interesting alternative approach that could considerably reduce the examination time and offer better accuracy and reproducibility. In this context, many studies have demonstrated a high range of diagnostic concordance (90-99%) between digital slides and conventional glass slides.
                <sup>
                    <xref ref-type="bibr" rid="ref28">28</xref>
                </sup>
                <sup>&#x2013;</sup>
                <sup>
                    <xref ref-type="bibr" rid="ref30">30</xref>
                </sup> Many digital pathology image software packages have been developed; however, access to these platforms remains difficult for some pathologists.
                <sup>
                    <xref ref-type="bibr" rid="ref31">31</xref>
                </sup>
                <sup>,</sup>
                <sup>
                    <xref ref-type="bibr" rid="ref32">32</xref>
                </sup> Hence, QUPATH software could be an interesting alternative for integrating digital pathology in routine practice. A consensus on tumor budding counting and reporting on digitalized slides in pancreatic carcinoma is necessary to definitively integrate TB in pathology reports.</p>
        </sec>
        <sec id="sec15" sec-type="conclusions">
            <title>Conclusions</title>
            <p>Our results demonstrated that tumor budding either assessed manually on HE slides or semi-automated on digitalized images is a relatively constant finding in pancreatic carcinoma, with a high score in about 50% of cases. Our findings also showed a high concordance of both methods in TB assessment, supporting the benefits of integrating digital pathology in routine practice. Finally, our results provide further evidence for the potential prognostic value of TB in pancreatic carcinoma. However, our study has some limitations, such as its retrospective design and small sample size. Further studies on TB counting using QUAPATH in pancreatic carcinoma are needed to integrate this method into routine practice for better risk stratification.</p>
        </sec>
        <sec id="sec16">
            <title>Ethics approval</title>
            <p>This research was conducted following the ethical guidelines outlined by the Ethics committee of the Internal Security Forces Hospital (Obtained on 1 
                <sup>st</sup> December 2023, approval number 12/23). All procedures involving human tissues were approved by the committee and were performed in accordance with the ethical standards laid down in the 1964 Declaration of Helsinki and its later amendments as well as the National Medical Code of Ethics (Title VI, Article 99 to 111). Verbal informed consent was obtained at admission from all individual participants included in the study. The majority of patients were illiterate, unable to read or write, therefore verbal consent was preferred. Confidentiality and anonymity of participants were strictly maintained throughout the study. Any potential conflicts of interest have been disclosed and managed appropriately. Confidentiality and anonymity of participants were strictly maintained throughout the study. Any potential conflicts of interest have been disclosed and managed appropriately.</p>
            <p>Link to National Medical Code of Ethics: chrome-extension://efaidnbmnnnibpcajpcglclefindmkaj/ 
                <ext-link ext-link-type="uri" xlink:href="http://www.atds.org.tn/Decretdeontologiemedicale93.pdf">http://www.atds.org.tn/Decretdeontologiemedicale93.pdf</ext-link>
            </p>
        </sec>
        <sec id="sec17">
            <title>Authors contribution</title>
            <p>Sarra Ben Rejeb: Conceptualization Investigation; Methodology Writing Validation;</p>
            <p>Jasser yaacoubi: Data curation; Formal analysis;</p>
        </sec>
    </body>
    <back>
        <sec id="sec18" sec-type="data-availability">
            <title>Data availability statement</title>
            <sec id="sec19">
                <title>Underlying data</title>
                <p>Figshare: Tumor budding in pancreatic carcinoma, 
                    <ext-link ext-link-type="uri" xlink:href="https://doi.org/10.6084/m9.figshare.25265755.v2">https://doi.org/10.6084/m9.figshare.25265755.v2</ext-link>.
                    <sup>
                        <xref ref-type="bibr" rid="ref33">33</xref>
                    </sup>
                </p>
                <p>Data are available under the terms of the 
                    <ext-link ext-link-type="uri" xlink:href="https://creativecommons.org/licenses/by/4.0/">Creative Commons Attribution 4.0 International license</ext-link> (CC-BY 4.0).</p>
            </sec>
            <sec id="sec20">
                <title>Extended data</title>
                <p>figshare: STROBE Checklist for Tumor budding in pancreatic carcinoma, 
                    <ext-link ext-link-type="uri" xlink:href="https://doi.org/10.6084/m9.figshare.25265755.v2">https://doi.org/10.6084/m9.figshare.25265755.v2</ext-link>.
                    <sup>
                        <xref ref-type="bibr" rid="ref33">33</xref>
                    </sup>
                </p>
                <p>Data are available under the terms of the 
                    <ext-link ext-link-type="uri" xlink:href="https://creativecommons.org/licenses/by/4.0/">Creative Commons Attribution 4.0 International license</ext-link> (CC-BY 4.0).</p>
                <p>Software availability statement: The statistical analyses performed in this article using SPSS21 software can be conducted using the freely accessible software Jamovi 
                    <ext-link ext-link-type="uri" xlink:href="https://www.jamovi.org">https://www.jamovi.org</ext-link>
                </p>
                <p>Source code available from: 
                    <ext-link ext-link-type="uri" xlink:href="https://github.com/jamovi/jamovi/tree/v2.2.4">https://github.com/jamovi/jamovi/tree/v2.2.4</ext-link>
                </p>
                <p>Archived software available from: [DOI specific to version 2.2.4, typically accessible from Zenodo]</p>
                <p>License: OSI approved open license software is under GPL-3.0 License</p>
                <p>The user manual is available at the following link. 
                    <ext-link ext-link-type="uri" xlink:href="https://lsj.readthedocs.io/ru/latest/Ch03/Ch03_jamoviIntro_1.html">https://lsj.readthedocs.io/ru/latest/Ch03/Ch03_jamoviIntro_1.html</ext-link>
                </p>
            </sec>
        </sec>
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        <front-stub>
            <article-id pub-id-type="doi">10.5256/f1000research.187231.r411215</article-id>
            <title-group>
                <article-title>Reviewer response for version 3</article-title>
            </title-group>
            <contrib-group>
                <contrib contrib-type="author">
                    <name>
                        <surname>Singh</surname>
                        <given-names>Bipneet</given-names>
                    </name>
                    <xref ref-type="aff" rid="r411215a1">1</xref>
                    <xref ref-type="aff" rid="r411215a2">2</xref>
                    <role>Referee</role>
                    <uri content-type="orcid">https://orcid.org/0009-0008-6147-9584</uri>
                </contrib>
                <aff id="r411215a1">
                    <label>1</label>University of Kentucky (Ringgold ID: 4530), Lexington, Kentucky, USA</aff>
                <aff id="r411215a2">
                    <label>2</label>Henry Ford Health System, Detroit, Michigan, USA</aff>
            </contrib-group>
            <author-notes>
                <fn fn-type="conflict">
                    <p>
                        <bold>Competing interests: </bold>No competing interests were disclosed.</p>
                </fn>
            </author-notes>
            <pub-date pub-type="epub">
                <day>13</day>
                <month>10</month>
                <year>2025</year>
            </pub-date>
            <permissions>
                <copyright-statement>Copyright: &#x00a9; 2025 Singh B</copyright-statement>
                <copyright-year>2025</copyright-year>
                <license xlink:href="https://creativecommons.org/licenses/by/4.0/">
                    <license-p>This is an open access peer review report distributed under the terms of the Creative Commons Attribution Licence, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.</license-p>
                </license>
            </permissions>
            <related-article ext-link-type="doi" id="relatedArticleReport411215" related-article-type="peer-reviewed-article" xlink:href="10.12688/f1000research.146907.3"/>
            <custom-meta-group>
                <custom-meta>
                    <meta-name>recommendation</meta-name>
                    <meta-value>approve</meta-value>
                </custom-meta>
            </custom-meta-group>
        </front-stub>
        <body>
            <p>Authors have made modifications per the feedback. In the current status, I am comfortable with the indexing.</p>
            <p>Is the work clearly and accurately presented and does it cite the current literature?</p>
            <p>Yes</p>
            <p>If applicable, is the statistical analysis and its interpretation appropriate?</p>
            <p>I cannot comment. A qualified statistician is required.</p>
            <p>Are all the source data underlying the results available to ensure full reproducibility?</p>
            <p>Yes</p>
            <p>Is the study design appropriate and is the work technically sound?</p>
            <p>Partly</p>
            <p>Are the conclusions drawn adequately supported by the results?</p>
            <p>Partly</p>
            <p>Are sufficient details of methods and analysis provided to allow replication by others?</p>
            <p>Yes</p>
            <p>Reviewer Expertise:</p>
            <p>Gastroenterology, Hepatology, Oncology</p>
            <p>I confirm that I have read this submission and believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard.</p>
        </body>
    </sub-article>
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            <article-id pub-id-type="doi">10.5256/f1000research.176229.r399399</article-id>
            <title-group>
                <article-title>Reviewer response for version 2</article-title>
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                <contrib contrib-type="author">
                    <name>
                        <surname>Singh</surname>
                        <given-names>Bipneet</given-names>
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                    <xref ref-type="aff" rid="r399399a2">2</xref>
                    <role>Referee</role>
                    <uri content-type="orcid">https://orcid.org/0009-0008-6147-9584</uri>
                </contrib>
                <aff id="r399399a1">
                    <label>1</label>University of Kentucky (Ringgold ID: 4530), Lexington, Kentucky, USA</aff>
                <aff id="r399399a2">
                    <label>2</label>Henry Ford Health System, Detroit, Michigan, USA</aff>
            </contrib-group>
            <author-notes>
                <fn fn-type="conflict">
                    <p>
                        <bold>Competing interests: </bold>No competing interests were disclosed.</p>
                </fn>
            </author-notes>
            <pub-date pub-type="epub">
                <day>23</day>
                <month>8</month>
                <year>2025</year>
            </pub-date>
            <permissions>
                <copyright-statement>Copyright: &#x00a9; 2025 Singh B</copyright-statement>
                <copyright-year>2025</copyright-year>
                <license xlink:href="https://creativecommons.org/licenses/by/4.0/">
                    <license-p>This is an open access peer review report distributed under the terms of the Creative Commons Attribution Licence, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.</license-p>
                </license>
            </permissions>
            <related-article ext-link-type="doi" id="relatedArticleReport399399" related-article-type="peer-reviewed-article" xlink:href="10.12688/f1000research.146907.2"/>
            <custom-meta-group>
                <custom-meta>
                    <meta-name>recommendation</meta-name>
                    <meta-value>approve-with-reservations</meta-value>
                </custom-meta>
            </custom-meta-group>
        </front-stub>
        <body>
            <p>
                <list list-type="order">
                    <list-item>
                        <p>Give a line about tumor budding in the abstract introduction</p>
                    </list-item>
                    <list-item>
                        <p>&#x201c;Manuel&#x201d; is misspelled</p>
                    </list-item>
                    <list-item>
                        <p>&#x201c;25patients&#x201d;, there has to be a space here</p>
                    </list-item>
                    <list-item>
                        <p>&#x201c;Pancreatic carcinoma (PC) is an aggressive malignancy with a high rate of recurrence and a 5-year survival rate of &lt;10% even after complete resection and negative lymph nodes status.&#x201d; Kindly restructure the sentence. The sentence can be split into 2-3 parts, explaining the staging, progression, treatment, and relapse rates.</p>
                    </list-item>
                    <list-item>
                        <p>&#x201c;Although tumor resectability and stage remain the most relevant prognostic factors, there is an increasing need to focus on novel histo-prognostic factors that would enable better risk stratification for patients.&#x201d; Take &#x201c;need of&#x201d; out of the sentence.</p>
                    </list-item>
                    <list-item>
                        <p>&#x201c;resecability&#x201d; is spelled wrong.</p>
                    </list-item>
                    <list-item>
                        <p>&#x201c;In PC, although it has been reported that TB has a clear association with adverse prognosis.&#x201d; This requires a citation.</p>
                    </list-item>
                    <list-item>
                        <p>The introduction needs to be expanded.</p>
                    </list-item>
                    <list-item>
                        <p>&#x201c;We included in this study all patients with primary pancreatic adenocarcinoma diagnosed on surgical specimens or pancreatic biopsies in the pathology departments of the Security Forces and Charles Nicolles Hospitals over a period of 14 years (March 2008-December 2022).&#x201d; Remove &#x201c;in this study&#x201d;</p>
                    </list-item>
                    <list-item>
                        <p>Why are there two separate non-inclusion and exclusion criteria?</p>
                    </list-item>
                    <list-item>
                        <p>&#x201c;author&#x2019;s&#x201d; to be replaced with &#x201c;authors&#x201d;</p>
                    </list-item>
                    <list-item>
                        <p>&#x201c;&#x00a0;In the present study, we first assessed tumor budding in pancreatic carcinoma specimens according to the recommendations of the ITBCC at 20-fold magnification for a field of 0.785 mm
                            <sup>2</sup>, either at the tumor front or within the tumor center. Then, similar to the published study of Budeau et al.,
                            <sup>
                                <ext-link ext-link-type="uri" xlink:href="https://f1000research.com/articles/13-282/v2#ref6">6</ext-link>
                            </sup>&#x00a0;we extrapolated the ITBCC counting approach on an optic microscope to a digital image analysis system using QUPATH, an open-access software for digital image analysis. QUPATH is completely free, which enables pathologists in low-income countries to have access to digital pathology analysis.
                            <sup>
                                <ext-link ext-link-type="uri" xlink:href="https://f1000research.com/articles/13-282/v2#ref5">5</ext-link>
                            </sup>&#x00a0;The tumor cell detection functionality of the QUPATH software facilitates distinguishing between tumor cells and small clusters from a larger group of cells. In addition, compared to &#x201c;analog&#x201d; microscopy, QUAPTH offers the possibility of re-evaluating tumor buds at anytime higher than those of other pathologists.
                            <sup>
                                <ext-link ext-link-type="uri" xlink:href="https://f1000research.com/articles/13-282/v2#ref6">6</ext-link>
                            </sup>&#x00a0;Although a high TB score was found in 48% of patients using the first method compared with 56% using the digitalized approach, the difference was not statistically significant (p=0.589). Hence, QUPATH could be an interesting, costless, and accurate alternative for pathologists, which would considerably reduce the work time and facilitate TB counting.&#x201d; Relevance?</p>
                    </list-item>
                    <list-item>
                        <p>Expand on the relation between TB and prognosis in the discussion.</p>
                    </list-item>
                </list>
            </p>
            <p>Is the work clearly and accurately presented and does it cite the current literature?</p>
            <p>Yes</p>
            <p>If applicable, is the statistical analysis and its interpretation appropriate?</p>
            <p>I cannot comment. A qualified statistician is required.</p>
            <p>Are all the source data underlying the results available to ensure full reproducibility?</p>
            <p>Yes</p>
            <p>Is the study design appropriate and is the work technically sound?</p>
            <p>Partly</p>
            <p>Are the conclusions drawn adequately supported by the results?</p>
            <p>Partly</p>
            <p>Are sufficient details of methods and analysis provided to allow replication by others?</p>
            <p>Yes</p>
            <p>Reviewer Expertise:</p>
            <p>Gastroenterology, Hepatology, Oncology</p>
            <p>I confirm that I have read this submission and believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard, however I have significant reservations, as outlined above.</p>
        </body>
        <sub-article article-type="response" id="comment14434-399399">
            <front-stub>
                <contrib-group>
                    <contrib contrib-type="author">
                        <name>
                            <surname>Ben Rejeb</surname>
                            <given-names>Sarra </given-names>
                        </name>
                        <aff>Pathology, Universite de Tunis, Tunis, Tunis, Tunisia</aff>
                    </contrib>
                </contrib-group>
                <author-notes>
                    <fn fn-type="conflict">
                        <p>
                            <bold>Competing interests: </bold>None</p>
                    </fn>
                </author-notes>
                <pub-date pub-type="epub">
                    <day>25</day>
                    <month>8</month>
                    <year>2025</year>
                </pub-date>
            </front-stub>
            <body>
                <p>
                    <bold>Dear Reviewer, we greatly appreciate the valuable feedback you provided which has significantly improved the clarity, depth, and scientific rigor of our work.</bold>
                </p>
                <p> 
                    <bold>In response to the your comments, we have made the following revisions:</bold> 
                    <list list-type="order">
                        <list-item>
                            <p>
                                <bold>Added: "Tumor budding (TB), defined as isolated single cancer cells or small clusters of up to four cells at the invasive front, is an emerging histoprognostic factor associated with aggressiveness in various malignancies."</bold>
                            </p>
                        </list-item>
                        <list-item>
                            <p>
                                <bold>Corrected to "manual" in the Methods section.</bold>
                            </p>
                        </list-item>
                        <list-item>
                            <p>
                                <bold>Corrected to "25 patients" in the Results section.</bold>
                            </p>
                        </list-item>
                        <list-item>
                            <p>
                                <bold>&#x201c;Pancreatic carcinoma (PC) is an aggressive malignancy with a high rate of recurrence and a 5-year survival rate of &lt;10% even after complete resection and negative lymph nodes status.&#x201d; Kindly restructure the sentence. The sentence can be split into 2-3 parts, explaining the staging, progression, treatment, and relapse rates.: &#x21d2; We restructured and expanded with updated data.</bold>
                            </p>
                        </list-item>
                        <list-item>
                            <p>
                                <bold>&#x201c;Although tumor resectability and stage remain the most relevant prognostic factors, there is an increasing need to focus on novel histo-prognostic factors that would enable better risk stratification for patients.&#x201d; Take &#x201c;need of&#x201d; out of the sentence.: Corrected to "there is an increasing need to focus".</bold>
                            </p>
                        </list-item>
                        <list-item>
                            <p>
                                <bold>Resecability is spelled wrong.: Corrected to "resectability".</bold>
                            </p>
                        </list-item>
                        <list-item>
                            <p>
                                <bold>&#x201c;In PC, although it has been reported that TB has a clear association with adverse prognosis.&#x201d; This requires a citation.: Added citations from recent studies.</bold>
                            </p>
                        </list-item>
                        <list-item>
                            <p>
                                <bold>The introduction needs to be expanded.: Expanded with epidemiology, TB in other cancers, biological mechanisms (e.g., EMT), and specific studies on TB in PC.</bold>
                            </p>
                        </list-item>
                        <list-item>
                            <p>
                                <bold>We included in this study all patients with primary pancreatic adenocarcinoma diagnosed on surgical specimens or pancreatic biopsies in the pathology departments of the Security Forces and Charles Nicolles Hospitals over a period of 14 years (March 2008-December 2022).&#x201d; Remove &#x201c;in this study&#x201d;: Removed "in this study".</bold>
                            </p>
                        </list-item>
                        <list-item>
                            <p>
                                <bold>Why are there two separate non-inclusion and exclusion criteria? &#x21d2; We Combined into a single "Exclusion Criteria" section for clarity.</bold>
                            </p>
                        </list-item>
                        <list-item>
                            <p>
                                <bold>&#x201c;author&#x2019;s&#x201d; to be replaced with &#x201c;authors&#x201d;: Corrected to "authors".</bold>
                            </p>
                        </list-item>
                        <list-item>
                            <p>
                                <bold>The paragraph on QUPATH methods and relevance?: Retained with added relevance statement.</bold>
                            </p>
                        </list-item>
                        <list-item>
                            <p>
                                <bold>Expand on the relation between TB and prognosis in the discussion.: Further expanded with evidence from recent meta-analyses and studies (e.g., 2019-2024), including specific associations with OS, DFS, HRs (e.g., pooled HR 2.13 for OS), links to EMT, neoadjuvant therapy contexts, and recommendations for routine reporting and risk stratification. Incorporated new citations from literature search.</bold>
                            </p>
                        </list-item>
                    </list>
                </p>
            </body>
        </sub-article>
    </sub-article>
    <sub-article article-type="reviewer-report" id="report358161">
        <front-stub>
            <article-id pub-id-type="doi">10.5256/f1000research.176229.r358161</article-id>
            <title-group>
                <article-title>Reviewer response for version 2</article-title>
            </title-group>
            <contrib-group>
                <contrib contrib-type="author">
                    <name>
                        <surname>Oz</surname>
                        <given-names>Ozden</given-names>
                    </name>
                    <xref ref-type="aff" rid="r358161a1">1</xref>
                    <role>Referee</role>
                    <uri content-type="orcid">https://orcid.org/0000-0001-5601-1567</uri>
                </contrib>
                <aff id="r358161a1">
                    <label>1</label>Izmir Bozyaka Training and Research Hospital, University of Health Sciences, Izmir, Turkey</aff>
            </contrib-group>
            <author-notes>
                <fn fn-type="conflict">
                    <p>
                        <bold>Competing interests: </bold>No competing interests were disclosed.</p>
                </fn>
            </author-notes>
            <pub-date pub-type="epub">
                <day>21</day>
                <month>1</month>
                <year>2025</year>
            </pub-date>
            <permissions>
                <copyright-statement>Copyright: &#x00a9; 2025 Oz O</copyright-statement>
                <copyright-year>2025</copyright-year>
                <license xlink:href="https://creativecommons.org/licenses/by/4.0/">
                    <license-p>This is an open access peer review report distributed under the terms of the Creative Commons Attribution Licence, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.</license-p>
                </license>
            </permissions>
            <related-article ext-link-type="doi" id="relatedArticleReport358161" related-article-type="peer-reviewed-article" xlink:href="10.12688/f1000research.146907.2"/>
            <custom-meta-group>
                <custom-meta>
                    <meta-name>recommendation</meta-name>
                    <meta-value>approve</meta-value>
                </custom-meta>
            </custom-meta-group>
        </front-stub>
        <body>
            <p>The explanations made on the suggestions I made are sufficient.</p>
            <p> </p>
            <p> My best&#x00a0;</p>
            <p> </p>
            <p> M.D. Ozden oz</p>
            <p>Is the work clearly and accurately presented and does it cite the current literature?</p>
            <p>Partly</p>
            <p>If applicable, is the statistical analysis and its interpretation appropriate?</p>
            <p>Yes</p>
            <p>Are all the source data underlying the results available to ensure full reproducibility?</p>
            <p>Yes</p>
            <p>Is the study design appropriate and is the work technically sound?</p>
            <p>Yes</p>
            <p>Are the conclusions drawn adequately supported by the results?</p>
            <p>Yes</p>
            <p>Are sufficient details of methods and analysis provided to allow replication by others?</p>
            <p>Yes</p>
            <p>Reviewer Expertise:</p>
            <p>clinic pathology</p>
            <p>I confirm that I have read this submission and believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard.</p>
        </body>
    </sub-article>
    <sub-article article-type="reviewer-report" id="report305079">
        <front-stub>
            <article-id pub-id-type="doi">10.5256/f1000research.161038.r305079</article-id>
            <title-group>
                <article-title>Reviewer response for version 1</article-title>
            </title-group>
            <contrib-group>
                <contrib contrib-type="author">
                    <name>
                        <surname>Oz</surname>
                        <given-names>Ozden</given-names>
                    </name>
                    <xref ref-type="aff" rid="r305079a1">1</xref>
                    <role>Referee</role>
                    <uri content-type="orcid">https://orcid.org/0000-0001-5601-1567</uri>
                </contrib>
                <aff id="r305079a1">
                    <label>1</label>Izmir Bozyaka Training and Research Hospital, University of Health Sciences, Izmir, Turkey</aff>
            </contrib-group>
            <author-notes>
                <fn fn-type="conflict">
                    <p>
                        <bold>Competing interests: </bold>No competing interests were disclosed.</p>
                </fn>
            </author-notes>
            <pub-date pub-type="epub">
                <day>9</day>
                <month>8</month>
                <year>2024</year>
            </pub-date>
            <permissions>
                <copyright-statement>Copyright: &#x00a9; 2024 Oz O</copyright-statement>
                <copyright-year>2024</copyright-year>
                <license xlink:href="https://creativecommons.org/licenses/by/4.0/">
                    <license-p>This is an open access peer review report distributed under the terms of the Creative Commons Attribution Licence, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.</license-p>
                </license>
            </permissions>
            <related-article ext-link-type="doi" id="relatedArticleReport305079" related-article-type="peer-reviewed-article" xlink:href="10.12688/f1000research.146907.1"/>
            <custom-meta-group>
                <custom-meta>
                    <meta-name>recommendation</meta-name>
                    <meta-value>approve-with-reservations</meta-value>
                </custom-meta>
            </custom-meta-group>
        </front-stub>
        <body>
            <p>First of all, it is a well-designed study and seems applicable.</p>
            <p> Major</p>
            <p> 1. The criteria by which patients were selected should be written in more detail.&#x00a0;</p>
            <p> None of the patients appear to have metastases (table 1). Was a selection made in this regard?</p>
            <p> 2. It should be discussed why tumor budding could not be found in 16% of the patients&#x00a0;with QUPATH&#x00a0;method.</p>
            <p> </p>
            <p> 3. It should be discussed why a higher TB degree 3 was found with the morphological method.</p>
            <p> </p>
            <p> 5. Figure 3.4.5&#x00a0;Univariate analysis (Kaplan-Meier) ? or multivariate Cox?&#x00a0; It must be clear</p>
            <p> </p>
            <p> </p>
            <p> Minor&#x00a0;</p>
            <p> 1. Details of tumor budding in pancreatic cancer should be more supported by literature.&#x00a0;</p>
            <p> Such as:</p>
            <p> DOI:&#x00a0;
                <ext-link ext-link-type="uri" xlink:href="https://doi.org/10.4103/ijpm.ijpm_905_21">10.4103/ijpm.ijpm_905_21</ext-link> etc.</p>
            <p>Is the work clearly and accurately presented and does it cite the current literature?</p>
            <p>Partly</p>
            <p>If applicable, is the statistical analysis and its interpretation appropriate?</p>
            <p>Yes</p>
            <p>Are all the source data underlying the results available to ensure full reproducibility?</p>
            <p>Yes</p>
            <p>Is the study design appropriate and is the work technically sound?</p>
            <p>Yes</p>
            <p>Are the conclusions drawn adequately supported by the results?</p>
            <p>Yes</p>
            <p>Are sufficient details of methods and analysis provided to allow replication by others?</p>
            <p>Yes</p>
            <p>Reviewer Expertise:</p>
            <p>clinic pathology</p>
            <p>I confirm that I have read this submission and believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard, however I have significant reservations, as outlined above.</p>
        </body>
        <back>
            <ref-list>
                <title>References</title>
                <ref id="rep-ref-305079-1">
                    <label>1</label>
                    <mixed-citation publication-type="journal">
                        <person-group person-group-type="author"/>:
                        <article-title>Evaluation and prognostic significance of tumor budding in pancreatic ductal adenocarcinomas.</article-title>
                        <source>
                            <italic>Indian J Pathol Microbiol</italic>
                        </source>.<year>2023</year>;<volume>66</volume>(<issue>1</issue>) :
                        <elocation-id>10.4103/ijpm.ijpm_905_21</elocation-id>
                        <fpage>38</fpage>-<lpage>43</lpage>
                        <pub-id pub-id-type="pmid">36656208</pub-id>
                        <pub-id pub-id-type="doi">10.4103/ijpm.ijpm_905_21</pub-id>
                    </mixed-citation>
                </ref>
                <ref id="rep-ref-305079-2">
                    <label>2</label>
                    <mixed-citation publication-type="journal">
                        <person-group person-group-type="author"/>:
                        <article-title>The Significance of Tumor Budding and Immunohistochemical Axl Expression in Gallbladder Adenocarcinomas.</article-title>
                        <source>
                            <italic>Balkan Med J</italic>
                        </source>.<year>2022</year>;<volume>39</volume>(<issue>3</issue>) :
                        <elocation-id>10.4274/balkanmedj.galenos.2022.2021-9-37</elocation-id>
                        <fpage>199</fpage>-<lpage>208</lpage>
                        <pub-id pub-id-type="pmid">35430785</pub-id>
                        <pub-id pub-id-type="doi">10.4274/balkanmedj.galenos.2022.2021-9-37</pub-id>
                    </mixed-citation>
                </ref>
            </ref-list>
        </back>
        <sub-article article-type="response" id="comment12788-305079">
            <front-stub>
                <contrib-group>
                    <contrib contrib-type="author">
                        <name>
                            <surname>Ben Rejeb</surname>
                            <given-names>Sarra </given-names>
                        </name>
                        <aff>Pathology, Universite de Tunis, Tunis, Tunis, Tunisia</aff>
                    </contrib>
                </contrib-group>
                <author-notes>
                    <fn fn-type="conflict">
                        <p>
                            <bold>Competing interests: </bold>None</p>
                    </fn>
                </author-notes>
                <pub-date pub-type="epub">
                    <day>6</day>
                    <month>11</month>
                    <year>2024</year>
                </pub-date>
            </front-stub>
            <body>
                <p>Response to Reviewer 1:&#x00a0;</p>
                <p> Dear Reviewer, thank you for your valuable&#x00a0; comments.&#x00a0;</p>
                <p> 
                    <underline>
                        <bold>1- Regarding our inclusion criteria:</bold>
                    </underline> we included all cases of primary pancreatic adenocarcinoma diagnosed on surgical specimens or biopsies in the pathology departments of the security forces hospital and Charles Nicolles Hospital, regardless of the stage of the disease, whether metastatic or localized. However, at the time of data collection, none of our patients had known metastases at diagnosis by mere coincidence. This was not a selection criterion. It is worth noting, however, that during follow-up, 20% of the patients developed metastases .</p>
                <p> </p>
                <p> 
                    <bold>
                        <underline>2-&#x00a0;To further clarify our inclusion criteria:</underline>
                    </bold>
                </p>
                <p> 
                    <bold>2.1. Inclusion Criteria:</bold>
                </p>
                <p> We included in this study all patients with primary pancreatic adenocarcinoma diagnosed on surgical specimens or pancreatic biopsies in the Department of Pathology and Cytology at FSI Hospital and HCN during the study period.</p>
                <p> </p>
                <p> 
                    <bold>2.2. Non-inclusion Criteria:</bold>
                </p>
                <p> The following cases were not included in this study: 
                    <list list-type="bullet">
                        <list-item>
                            <p>Patients with intraductal papillary mucinous tumors without invasive foci.</p>
                        </list-item>
                        <list-item>
                            <p>Other histological types (neuroendocrine or mesenchymal tumors).</p>
                        </list-item>
                        <list-item>
                            <p>Patients with ampullary, gallbladder, or bile duct adenocarcinoma.</p>
                        </list-item>
                    </list> 
                    <bold>2.3. Exclusion Criteria:</bold>
                </p>
                <p> We excluded from our study: 
                    <list list-type="bullet">
                        <list-item>
                            <p>Patients with unusable clinical records.</p>
                        </list-item>
                        <list-item>
                            <p>Small and non-representative biopsy samples.</p>
                        </list-item>
                        <list-item>
                            <p>Biopsy samples of suboptimal technical quality that created artifacts during image digitization</p>
                        </list-item>
                    </list> 
                    <bold>3-&#x00a0; Regarding tumor budding using QUPATH:</bold>
                </p>
                <p> Through our study, tumor budding was observed in 100% of cases by morphological analysis and in 84% with the QUPATH software. This suggests that using a semi-automated approach may offer greater analytical precision by reducing false positives. These cases likely corresponded to atypical mesenchymal fibroblastic or myofibroblastic cells or poorly differentiated tumor glands that were mistaken for isolated tumor cells</p>
                <p> </p>
                <p> 
                    <bold>4- High TB on morphological method :&#x00a0;</bold>
                </p>
                <p> Similarly, using the QUPATH software reduced the number of cases classified as high BUDD3 with the morphological approach. This is due to the software's precision in distinguishing between isolated tumor cells or clusters of fewer than 5 cells, which meet the definition of tumor budding, as opposed to poorly differentiated carcinoma clusters or remnants of neuroendocrine islets that were misdiagnosed as TB on HE slides examination and were&#x00a0; sofalse positives. Indeed, with its annotation features, the QUPATH software allows for the identification and deselection of false positives</p>
                <p> </p>
                <p> 
                    <bold>5- Survival curves :</bold>&#x00a0;Survival data were analyzed by generating survival curves using the Kaplan-Meier method and compared using the Log-rank test in univariate analysis</p>
                <p> </p>
                <p> 
                    <italic>
                        <bold>Minor Revisions:</bold>
                    </italic>
                </p>
                <p> 1- This publication was not found during the literature search and manuscript writing, but it is highly relevant to our research topic.</p>
            </body>
        </sub-article>
    </sub-article>
</article>
