Keywords
Ovarian tumours, Frozen section analysis, Diagnostic accuracy, Histopathology, Gynecologic oncology, Surgical management
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Garapati J and Jajoo S. A cross-sectional study approach towards management of ovarian tumour by frozen section at laparotomy and assessing its validity by gold standards of histopathology [version 1; peer review: awaiting peer review]. F1000Research 2024, 13:353 (https://doi.org/10.12688/f1000research.143651.1)
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Study Protocol
A cross-sectional study approach towards management of ovarian tumour by frozen section at laparotomy and assessing its validity by gold standards of histopathology
[version 1; peer review: awaiting peer review]
PUBLISHED 23 Apr 2024
OPEN PEER REVIEW
REVIEWER STATUS
This article is included in the Datta Meghe Institute of Higher Education and Research collection.
Abstract
Corresponding author:
Jyotsna Garapati
Competing interests:
No competing interests were disclosed.
Grant information:
The author(s) declared that no grants were involved in supporting this work.
Copyright:
© 2024 Garapati J and Jajoo S.
This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
How to cite: Garapati J and Jajoo S. A cross-sectional study approach towards management of ovarian tumour by frozen section at laparotomy and assessing its validity by gold standards of histopathology [version 1; peer review: awaiting peer review]. F1000Research 2024, 13:353 (https://doi.org/10.12688/f1000research.143651.1)
First published: 23 Apr 2024, 13:353 (https://doi.org/10.12688/f1000research.143651.1)
Latest published: 23 Apr 2024, 13:353 (https://doi.org/10.12688/f1000research.143651.1)
Introduction
Ovarian tumours present a complex and multifaceted challenge in gynecologic oncology. Accurate and timely diagnosis is pivotal for optimal patient management, as it informs critical decisions regarding surgical intervention and treatment planning. Frozen section analysis, a rapid intraoperative diagnostic tool, has assisted in real-time decision-making during laparotomy for ovarian tumours.1
Ovarian tumours encompass a broad spectrum of lesions, ranging from benign cysts to aggressive malignancies. Given the diversity in clinical presentation and radiographic appearance, providing an immediate and accurate diagnosis during surgery is paramount. Frozen section analysis, involving the quick examination of tissue samples taken during the surgical procedure, can guide the extent of surgery and enable fertility preservation when appropriate.2
However, the utility and reliability of frozen section analysis in this context warrant a rigorous investigation. Questions surrounding its sensitivity, specificity, positive predictive value, negative predictive value, and overall diagnostic accuracy necessitate empirical evaluation. Furthermore, critically examining its concordance with the gold standard, final histopathological diagnosis, is crucial to ascertain its validity as a diagnostic tool.3
This study, conducted over two years at the Department of Obstetrics and Gynaecology, AVBRH Hospital, Wardha, India, seeks to answer these questions. Through a systematic collection of data from eligible patients with ovarian masses, comprehensive clinical assessments, and comparative analyses of frozen section diagnoses with final histopathological results, this study endeavours to shed light on the clinical implications of frozen section analysis in ovarian tumour management.
The findings from this study hold the potential to significantly influence clinical practice by refining the diagnostic process for ovarian tumours. They may aid surgeons and oncologists in making real-time decisions that are accurate and tailored to each patient’s specific needs. Ultimately, this investigation aspires to enhance patient care and advance our understanding of ovarian tumour management.
Aim
To assess the diagnostic accuracy, sensitivity, specificity, and predictive values of frozen section analysis in managing ovarian tumours during laparotomy and to evaluate its validity against the gold standard of histopathology.
Objectives
1. Categorize ovarian neoplasms into benign, borderline, and malignant using frozen section analysis during laparotomy.
2. Determine the accuracy of frozen section diagnoses by comparing them with paraffin-embedded hematoxylin and eosin-stained sections, which serve as the gold standard histopathological diagnosis.
Methods
Ethics
The Institutional Ethics Committee of Datta Meghe Institute of Higher Education and Research (DU) has granted its approval to the study protocol (Reference number: DMIHER (DU)/IEC/2022/108). Before commencing the study, we will obtain written informed consent from all participants, providing them with a comprehensive explanation of the study’s objectives.
Study design
The study will employ a cross-sectional study design, and the study population will be made up of women with ovarian masses who are candidates for surgery and meet the inclusion criteria. The study will be conducted at the Department of Obstetrics and Gynaecology, AVBRH Hospital, Sawangi, Meghe, Wardha, from 2022 to 2024.
Bias considerations
• To minimise selection bias, only patients meeting the clearly defined inclusion criteria will be enrolled.
• Efforts will be made to obtain informed consent from all eligible participants.
• To address information bias, data will be collected consistently and systematically using standardised forms and questionnaires.
• Frozen section analysis will be conducted by pathologists blinded to the final histopathological diagnosis to reduce observer bias.
Enrollment
1. Potential study participants who meet the inclusion criteria will be identified from the gynaecology department of AVBRH Hospital.
2. Informed written consent will be obtained from eligible patients.
3. Patients with clinically benign-looking tumours on preoperative imaging or intraoperative inspection, those with a history of malignancy at another site, and young patients with ovarian neoplasms desiring fertility preservation will undergo frozen section analysis.
Data collection
Informed written consent will be secured from all study participants. The utilisation of frozen section analysis will be reserved for specific patient groups, including those with clinically benign-appearing tumours based on preoperative imaging or intraoperative inspection, individuals with adnexal masses who possess a prior history of malignancy at a different anatomical site, and young patients with ovarian neoplasms who express a desire for fertility preservation.
Patient history will be meticulously documented, encompassing comprehensive demographic information, presenting symptoms, menstrual and marital history, any history of exposure to high-risk factors, and personal and family medical history. Ultrasonography, performed by a seasoned operator, will be employed to discern the characteristics of detected ovarian tumours. Patients presenting with complex ovarian masses suggestive of extraovarian involvement, ureteric involvement, lymph nodal involvement, and moderate to massive ascites will undergo computed tomography (CT) scanning.4 Frozen section analysis will be universally conducted in all cases of ovarian tumors with uncertain pathological features following an initial inspection during staging laparotomy. The surgical approach will be tailored according to the outcomes of the frozen section analysis.
The staging laparotomy will entail the initial removal of the tumour, followed by the immediate transfer of the unfixed tumour specimen to the frozen section laboratory, accompanied by a comprehensive record of the patient’s clinical details. Upon gross examination of the tumour, sections will be judiciously obtained from representative areas at the pathologist’s discretion. The number of sections subjected to freezing will be determined based on the tumour type and size, typically ranging from 1 to 4 sections. In all instances of tumors diagnosed as borderline, a minimum of two sections will be designated for frozen analysis. This process will be executed using a Cryostat, with resulting sections measuring 7 to 8 μm in thickness and subsequently stained with hematoxylin and eosin (H&E) and toluidine blue.5 Each section will undergo meticulous microscopic evaluation under low and high power, overseen by two pathologists.
The frozen section diagnosis will be expeditiously communicated to the surgical team, guiding them in selecting the most appropriate surgical intervention. The average duration for the entire procedure, from specimen submission to result acquisition, is estimated to be approximately 20 minutes. The frozen section diagnosis will be categorised into one of the following categories:
1. Primary epithelial ovarian neoplasm – benign, borderline, or malignant.
2. Primary ovarian germ cell tumour, metastatic carcinoma of the ovary.
3. Benign non-neoplastic conditions or cases where a definitive opinion is not feasible.
The frozen section diagnosis for validation will be compared to the final paraffin section diagnosis.
Sample size
The estimated sample size for this study is 50, which has been determined based on the prevalence of ovarian tumours in the Wardha region of India.6 The calculation of the sample size follows the Cochran Formula for Sample Size, which is expressed as:
In this formula:
• Zα/2 represents the significance level at 5%, corresponding to a 95% confidence interval and equal to 1.96.
• P stands for the incidence of ovarian tumours, which is 0.0106 per 1000 population.
• E represents the margin of error, set at 5%, or 0.05.
Plugging in these values: n = 1.962 * 0.0106 * (1-0.0106) / 0.052 n ≈ 16.11
Therefore, the required sample size for this study is approximately 16.11, rounded up to 50 patients.
Study outcome
Diagnostic Accuracy: The study aims to determine the diagnostic accuracy of frozen section analysis in categorising ovarian neoplasms as benign, borderline, or malignant during laparotomy. The primary outcome will include sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and overall accuracy.
1. Comparison with Gold Standard: The study will assess the concordance between frozen section diagnoses and final histopathological diagnoses, which serve as the gold standard. This comparison will help evaluate the reliability and validity of frozen section analysis as a diagnostic tool.
2. Clinical Implications: The findings will have direct clinical implications for managing ovarian tumours. Depending on the accuracy of frozen section analysis, surgical decisions can be guided in real-time, potentially leading to more appropriate and tailored interventions for patients.
3. Research Contribution: The study’s results will contribute to gynecologic oncology and surgical pathology knowledge. They will be valuable for clinicians and researchers seeking to optimise the diagnostic process for ovarian tumours.
4. Patient Outcomes: Ultimately, the study’s outcomes will impact patient care by reducing the need for multiple surgeries or the extent of surgery required, thus improving the overall quality of care and patient outcomes in ovarian tumour management.
5. Future Directions: The study may also identify areas for further research or refinement of diagnostic protocols, potentially leading to advancements in gynecologic oncology.
Statistical methods
The statistical plan for this study involves several vital components. Firstly, we will conduct descriptive statistical analyses to summarise demographic and clinical data, including measures such as means, medians, standard deviations, and frequencies. The primary focus of our analysis will be to assess the diagnostic accuracy of frozen section analysis in categorising ovarian neoplasms as benign, borderline, or malignant. We will calculate sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and overall accuracy as primary outcome metrics. Furthermore, we will compare the frozen section diagnoses with the gold standard final paraffin section diagnoses, utilising statistical tests and measures like Cohen’s Kappa statistic to assess agreement. Subgroup analyses will be performed if relevant, and 95% confidence intervals will be computed to quantify the precision of our estimates. The results will be presented in tables and graphs, maintaining the level of statistical significance at p < 0.05 using SPSS version 23.
Limitation
Several limitations need to be considered in interpreting the findings of this study. Firstly, the relatively small sample size of 50 patients may limit the generalizability of the results to larger populations, and there is a possibility of selection bias as participants were recruited from a single tertiary care hospital in Wardha, India. Additionally, the study’s retrospective design may introduce inherent biases, and the reliance on frozen section analysis as an immediate diagnostic tool during surgery could be influenced by intraoperative conditions, potentially impacting the accuracy of results. Furthermore, the study’s two-year duration may not capture long-term outcomes or trends. Finally, while efforts will be made to minimise observer bias during pathological evaluations, variations between pathologists may still exist. These limitations underscore the need for caution in applying the study’s findings to broader clinical contexts and emphasise the importance of further research with larger, more diverse patient populations and prospective study designs to validate the diagnostic utility of frozen section analysis in ovarian tumour management.
Discussion
Ovarian tumours continue to present intricate diagnostic challenges in gynecologic oncology, necessitating the exploration of innovative diagnostic strategies to improve patient outcomes.7 Frozen section analysis, offering real-time intraoperative diagnostic information, has emerged as a potential solution to these challenges. This study protocol has delineated a rigorous investigation into the diagnostic accuracy of frozen section analysis for ovarian tumors. It has also evaluated its validity against the gold standard of histopathological diagnosis.8
Our findings are expected to contribute significantly to the ongoing discourse in this field. Firstly, determining the diagnostic accuracy of frozen section analysis will offer clinicians a better understand of its utility in categorising ovarian neoplasms as benign, borderline, or malignant. Sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and overall accuracy will be quantified, providing concrete metrics to assess its performance.9
These metrics are crucial in clinical decision-making. Frozen section analysis’s ability to accurately distinguish between benign and malignant tumours in real-time can guide the extent of surgery, a paramount consideration in ovarian cancer management. Our study aligns with previous research that underscores the clinical relevance of frozen section analysis in ovarian tumour management.10
Furthermore, the concordance analysis comparing frozen section diagnoses with final histopathological diagnoses is an essential facet of our investigation. This step is critical in establishing the validity of frozen section analysis as a diagnostic tool. Past studies have emphasised the importance of achieving a high level of agreement between frozen sections and final histopathological diagnoses to ensure clinical utility.11
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how to cite this article
Garapati J and Jajoo S. A cross-sectional study approach towards management of ovarian tumour by frozen section at laparotomy and assessing its validity by gold standards of histopathology [version 1; peer review: awaiting peer review]. F1000Research 2024, 13:353 (https://doi.org/10.12688/f1000research.143651.1)
NOTE: If applicable, it is important to ensure the information in square brackets after the title is included in all citations of this article.
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