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Systematic Review
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Hormonal Influences on ADC Values in Breast Tissues: A Scoping Review of DWI in Pre- and Post-menopausal Women

[version 3; peer review: 2 approved]
Winniecia Dkhar
https://orcid.org/0000-0001-5963-3230
1, Rajagopal Kadavigere
https://orcid.org/0000-0003-3486-8740
2, Sneha Ravichandran
https://orcid.org/0000-0002-4421-038X
1, Abhimanyu Pradhan1, Suresh Sukumar
https://orcid.org/0000-0001-9345-9790
1, Neil Barnes Abraham1
Winniecia Dkhar
https://orcid.org/0000-0001-5963-3230
1, Rajagopal Kadavigere
https://orcid.org/0000-0003-3486-8740
2, [...] Sneha Ravichandran
https://orcid.org/0000-0002-4421-038X
1, Abhimanyu Pradhan1, Suresh Sukumar
https://orcid.org/0000-0001-9345-9790
1, Neil Barnes Abraham1
PUBLISHED 27 Jan 2025
Author details Author details
OPEN PEER REVIEW
REVIEWER STATUS

This article is included in the Manipal Academy of Higher Education gateway.

This article is included in the The Multifaceted Aspects of Menopause collection.

Abstract

Background

Breast cancer remains a significant global health concern, with early diagnosis and risk factor identification crucial for improving outcomes. Diffusion-Weighted Imaging (DWI) and Apparent Diffusion Coefficient (ADC) measurements have emerged as promising tools in breast cancer diagnostics. However, the influence of hormonal status on these measurements remains unclear.

Objective

This scoping review aims to synthesize current evidence on how hormonal changes in pre- and post-menopausal women influence ADC values of benign, malignant, and fibroglandular breast tissues.

Method

Following the Arksey and O’Malley framework, we conducted a comprehensive search of Scopus, Embase, and PubMed databases for relevant studies published between January 2000 and 2021. Inclusion criteria encompassed 1.5 Tesla MRI studies reporting ADC values in female subjects, considering menopausal status.

Results

Six studies meeting the inclusion criteria, involving 612 patients, were analyzed. Findings suggest that menopausal status may influence ADC values, with postmenopausal women generally showing lower ADC values in both normal fibroglandular tissue and breast lesions. The impact of menstrual cycle phases on ADC values was less consistent across studies.

Conclusions

This review highlights the potential influence of hormonal status on ADC values in breast tissues. While DWI with ADC mapping shows promise as a reliable diagnostic tool across different hormonal states, further research is needed to fully understand and account for hormonal influences on ADC measurements. Future studies should focus on longitudinal designs, standardization of DWI protocols, and integration of hormonal status information into breast cancer risk assessment models.

Keywords

Breast cancer, Diffusion-Weighted Imaging, Apparent Diffusion Coefficient, hormonal influence, menopause, scoping review

Corresponding authors: Winniecia Dkhar, Sneha Ravichandran
Competing interests: No competing interests were disclosed.
Grant information: The author(s) declared that no grants were involved in supporting this work.
Copyright:  © 2025 Dkhar W et al. 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: Dkhar W, Kadavigere R, Ravichandran S et al. Hormonal Influences on ADC Values in Breast Tissues: A Scoping Review of DWI in Pre- and Post-menopausal Women [version 3; peer review: 2 approved]. F1000Research 2025, 13:857 (https://doi.org/10.12688/f1000research.153999.3) First published: 01 Aug 2024, 13:857 (https://doi.org/10.12688/f1000research.153999.1) Latest published: 27 Jan 2025, 13:857 (https://doi.org/10.12688/f1000research.153999.3)

Revised Amendments from Version 2

To improve the clarity and accuracy of the manuscript, several improvements have been made. In the introduction section, the fourth line of the first paragraph was revised by rephrasing the sentence “increased breast cancer incidence is partly due to increased life expectancy” to “due to increased awareness of the screening program.” Similarly, in the fourth and fifth paragraphs of the introduction section, “hormonal fluctuations” were rephrased to “hormonal phases” to reflect a more appropriate terminology. In the PRISMA flow chart, a correction was made to the step “Study excluded N = 1 *Study was based on 3T MRI,” as this study should have been excluded in a prior step.

See the authors' detailed response to the review by Manna Debnath

1. Introduction

Breast cancer continues to be one of the most prevalent and deadly diseases affecting women worldwide. According to the World Health Organization, breast cancer is the most common cancer in women, with an estimated 2.3 million new cases diagnosed globally in 2020.1 Increased breast cancer incidence is partly due to increased awareness of the screening programme.2 However, this rising incidence underscores the critical importance of early detection and accurate diagnosis in reducing mortality rates and improving patient outcomes.3–6

In recent years, significant advancements have been made in breast cancer diagnostics, with imaging techniques playing a pivotal role. Among these, Magnetic Resonance Imaging (MRI) has emerged as a powerful tool, offering high sensitivity in detecting breast lesions. Within the realm of MRI, Diffusion-Weighted Imaging (DWI) has gained particular attention for its ability to provide functional information about tissue microstructure without the need for contrast agents.7,8

DWI is based on the principle of measuring the random Brownian motion of water molecules within tissues.9 The degree of water diffusion can be quantified using the Apparent Diffusion Coefficient (ADC), which provides a numerical value reflecting tissue cellularity and integrity of cell membranes. In the context of breast imaging, ADC values have shown promise in differentiating between benign and malignant lesions, as malignant tissues typically demonstrate restricted diffusion due to increased cellularity, resulting in lower ADC values.9,10

However, the interpretation of ADC values in breast tissue is complex, as these values can be influenced by various factors beyond the presence or absence of malignancy. One crucial factor that has garnered increasing attention is the potential influence of hormonal status on ADC measurements. The female breast undergoes significant physiological changes throughout a woman’s lifetime, largely driven by hormonal phases.10 These changes are particularly pronounced during the menstrual cycle, pregnancy, and the transition to menopause.

The hormonal milieu plays a vital role in breast tissue composition and structure. Estrogen and progesterone, the primary female sex hormones, influence the growth and development of breast tissue, affecting both the glandular and stromal components. During the menstrual cycle, phases in these hormones lead to cyclic changes in breast tissue, including variations in water content, vascularity, and cellular proliferation. Similarly, the transition to menopause is marked by a significant decline in ovarian hormone production, leading to involution of glandular tissue and an increase in adipose tissue within the breast.10

Given these hormone-driven changes in breast tissue composition and microstructure, it is plausible that hormonal status could influence DWI measurements and, consequently, ADC values. Understanding these potential influences is crucial for several reasons:

  • 1. Diagnostic Accuracy: If hormonal status significantly affects ADC values, it could impact the accuracy of DWI in differentiating between benign and malignant lesions. Establishing hormone-specific reference ranges or correction factors might be necessary to optimize diagnostic performance.

  • 2. Risk Assessment: Hormonal exposure is a known risk factor for breast cancer. If ADC values reliably reflect hormone-induced changes in breast tissue, they could potentially serve as imaging biomarkers for assessing breast cancer risk.

  • 3. Treatment Monitoring: For patients undergoing hormonal therapies (e.g., hormone replacement therapy or endocrine therapy for breast cancer), understanding how these treatments affect ADC values could be valuable for monitoring treatment response and tissue changes.

  • 4. Personalized Screening: Knowledge of how hormonal status influences ADC values could inform more personalized screening protocols, potentially optimizing the timing of MRI examinations based on a woman’s menstrual cycle or menopausal status.

Despite the potential importance of this topic, the relationship between hormonal status and ADC values in breast tissue remains incompletely understood. While several studies have investigated this relationship, results have been inconsistent, and a comprehensive synthesis of the available evidence is lacking.3,5,11–13 This scoping review aims to address this gap by systematically exploring and synthesizing the current literature on how hormonal changes in pre- and post-menopausal women influence the ADC values of benign, malignant, and fibroglandular breast tissues. By mapping the existing evidence, identifying key concepts, and highlighting knowledge gaps, this review seeks to provide a foundation for future research and clinical applications of DWI in breast imaging.

The specific objectives of this scoping review are:

  • • To summarize the current evidence on the relationship between hormonal status (including menstrual cycle phases and menopausal status) and ADC values in breast tissues.

  • • To identify patterns or trends in how ADC values vary with hormonal changes across different studies.

  • • To explore the potential implications of hormonal influences on ADC values for breast cancer diagnosis, risk assessment, and treatment monitoring.

  • • To highlight gaps in the current knowledge and propose directions for future research.

By addressing these objectives, this scoping review aims to contribute to a more nuanced understanding of DWI in breast imaging and to inform future studies and clinical practices in this rapidly evolving field.

2. Methods

This scoping review was conducted following the methodological framework proposed by Arksey and O’Malley (2005) and further refined by Levac et al. (2010). This framework consists of five key stages: 1. identifying the research question, 2. identifying relevant studies, 3. study selection, 4. charting the data, and 5. collating, summarizing, and reporting the results. Additionally, we incorporated the optional sixth stage of consultation with stakeholders to enhance the review’s relevance and uptake.

2.1 Identifying the research question

The primary research question guiding this scoping review was: “How do hormonal changes in pre- and post-menopausal women influence the ADC values of benign, malignant, and fibroglandular breast tissues as measured by Diffusion-Weighted Imaging?”

This question was developed through an iterative process involving discussions among the research team and preliminary literature searches. The question was designed to be broad enough to capture the range of relevant literature while maintaining a clear focus on the relationship between hormonal status and ADC values in breast tissues.

2.2 Identifying relevant studies

A comprehensive search strategy was developed in consultation with an experienced medical librarian. The following electronic databases were searched: Scopus, Embase, and PubMed. The search was limited to studies published between January 2000 and December 2021, reflecting the period during which DWI became increasingly used in breast imaging.

The search strategy included a combination of controlled vocabulary (MeSH terms) and free-text terms. Key search terms included:

  • - “Diffusion Weighted Imaging” OR “DWI” OR “Diffusion Weighted MR Imaging”

  • - “Apparent Diffusion Coefficient” OR “ADC”

  • - “Magnetic Resonance Imaging” OR “MRI”

  • - “Breast cancer” OR “breast” OR “fibroglandular tissue”

  • - “Premenopausal” OR “postmenopausal” OR “menstrual cycle”

2.3 Study selection

Inclusion criteria

The inclusion criteria for this study encompassed several specific requirements. Only studies utilizing 1.5 Tesla MRI scanners and focusing exclusively on female subjects were considered. Additionally, the research had to employ Diffusion-Weighted Imaging sequences and report Apparent Diffusion Coefficient (ADC) values for benign and/or malignant lesions and/or fibroglandular tissue. Studies that took into account pre- and/or post-menopausal status were also included. Lastly, the review was limited to peer-reviewed articles published in English. These criteria were designed to ensure a focused and relevant selection of studies for analysis.

Exclusion criteria

Studies using 3 Tesla MRI scanners were excluded to maintain consistency in imaging parameters across the reviewed research. Any studies involving subjects undergoing neoadjuvant treatment were also omitted from consideration. The review excluded studies that did not report separate mean ADC values for benign and malignant lesions, as well as those not directly related to the diagnostic performance of Diffusion-Weighted Imaging (DWI). To focus on primary research findings, the review also excluded preclinical studies, case reports, letters, review articles, and unpublished articles. These exclusion criteria were implemented to ensure a more homogeneous and relevant dataset for analysis, focusing on studies that directly addressed the research question using comparable methodologies.

The study selection process was conducted in two phases. In the first phase, two reviewers independently screened the titles and abstracts of all retrieved articles against the inclusion and exclusion criteria. In the second phase, the full texts of potentially eligible articles were obtained and independently reviewed by the same two reviewers. Any disagreements were resolved through discussion, with a third reviewer consulted when necessary.

The study selection process followed the PRISMA guidelines. Initially, database searches yielded 487 records. After removing duplicates, 342 unique articles remained for screening. The titles and abstracts of these articles were reviewed, resulting in the exclusion of 314 articles that did not meet the inclusion criteria. The remaining 28 articles were assessed for eligibility through full-text review. During this stage, 22 articles were excluded for various reasons, such as irrelevant outcomes, inappropriate study design, or use of 3T MRI. Ultimately, 6 studies met all inclusion criteria and were included in the qualitative synthesis for this scoping review. No additional studies were identified through other sources. This systematic approach ensured a comprehensive and unbiased selection of relevant studies for the review.

2.4 Charting the data

A standardized data charting form was developed in Microsoft Excel to systematically extract relevant information from the included studies. This form was initially piloted on a sample of five studies and subsequently refined based on team discussions to ensure its effectiveness and comprehensiveness.

The data extraction process captured a wide range of information, including study characteristics (author, year, country, and study design), participant characteristics (sample size, age range, and menopausal status), and MRI characteristics (scanner manufacturer and b-values used). Detailed information about ADC measurement techniques, such as regions of interest and measurement methods, was also collected.

Importantly, the form captured quantitative data on ADC values, including mean and standard deviation for benign lesions, malignant lesions, and normal fibroglandular tissue. Any reported relationships between hormonal status and ADC values were noted, along with key findings and conclusions from each study.

To ensure accuracy and completeness, two reviewers independently extracted data from each included study. The extracted data were then cross-checked, providing a robust and reliable dataset for subsequent analysis.

2.5 Collating, summarizing, and reporting the results

The extracted data were analysed using a narrative synthesis approach. We organized the findings according to key themes and concepts that emerged from the data. Quantitative data (e.g., ADC values) were summarized using descriptive statistics where appropriate. We also created tables and figures to present the key characteristics and findings of the included studies.

In synthesizing the results, we focused on identifying patterns and trends in the relationship between hormonal status and ADC values, as well as highlighting any inconsistencies or gaps in the current evidence base. The PRISMA-ScR check list was used for reporting the data.15

3. Results

3.1 Search Results and Study Characteristics

The initial database search yielded a total of 487 articles. After removing duplicates, 342 unique articles remained for title and abstract screening. Based on the screening, 28 articles were selected for full-text review. After applying the inclusion and exclusion criteria to the full texts, 6 studies were ultimately included in this scoping review. The study selection process is illustrated in Figure 1 (PRISMA flow diagram).

9ac38fd5-48f5-4a82-b2f6-efbfe011e699_figure1.gif

Figure 1. PRISMA chart.

The six included studies were published between 2001 and 2018, representing a span of nearly two decades of research in this area. All studies used 1.5 Tesla MRI scanners, as per our inclusion criteria. The studies were conducted in various countries: two from the United States, two from South Korea, one from Italy, and one from the United Kingdom. The total number of participants across all studies was 612, with individual study sample sizes ranging from 6 to 288 participants. Table 1 provides the summary of the articles reviewed for this study.

Table 1. Summarizes the key characteristics of the included studies.

AuthorYearCountryMRI (T)Companyb- valueMean AgeNos. Of PatientsNos Of PremenopausalNos Of Post Menopausal ADC FGT ADC of Lesions
Joao V. Horvat142018USA3TGE0,60049288158140-Pre: B-1.541 0.256
M-1.044 0.211
Postl: B-1.515 0.272
M-1.108
0.212
Jin You Kim62016South Korea3TSiemen0,100050.8572928Pre: 1.75 ± 0.27
Post: 1.60 ± 0.30		Pre: 1.06 ± 0.35
Post: 0.91 ± 0.18
Suyoung Shin52015South Korea1.5 TPhillips0,750PRE-45
POST-56		1347351Pre: 1.640
Post: 1.480		Pre: 0.644
Post: 0.648
C innou42014Italy1.5T, 3TGE0.100052(median)9696--Pre: B-1.49 median
M-1.01 median
A. M. O’Flynn32012UK3TPhillips120045.9311318Pre- 1.84±0.26
Post- 1.46±0.3		-
Savannah P132001USA1.5GE0,5782766-Pre:1.69
Post: 0.19		-

3.2 ADC values and hormonal status

3.2.1 Menstrual Cycle, Menopausal Status and ADC Values

All studies examined the relationship between hormonal status (either menstrual cycle phase or menopausal status) and ADC values. The findings showed some consistencies but also notable variations:

  • 1. Menopausal Status:

    • - Horvat et al. (2018) found no significant difference in ADC sensitivity or specificity between pre- and post-menopausal groups.

    • - Kim et al. (2016), Shin et al. (2015), and O’Flynn et al. (2012) reported significantly lower ADC values in postmenopausal women compared to premenopausal women for both normal fibroglandular tissue and malignant lesions.

    • - Iacconi et al. (2014) noted that postmenopausal status was associated with lower ADC values in normal breast tissue.

  • 2. Menstrual Cycle:

    • - Kim et al. (2016) found no significant differences in ADC values between follicular and luteal phases for normal fibroglandular tissue or malignant lesions.

    • - Partridge et al. (2001) observed minimal fluctuations in ADC values across the menstrual cycle, with slightly lower values in the second week.

    • - O’Flynn et al. (2012) reported no significant differences in ADC values between different phases of the menstrual cycle.

All studies examined the relationship between menopausal status and ADC values, while three studies also investigated the influence of menstrual cycle phases:

Horvat et al. (2018) found no significant difference in ADC sensitivity or specificity between pre- and post-menopausal groups, with mean ADC values for benign lesions being 1.541 ± 0.256 × 10−3 mm2/s in premenopausal women and 1.515 ± 0.272 × 10−3 mm2/s in postmenopausal women. Kim et al. (2016) reported significantly lower ADC values in postmenopausal women compared to premenopausal women for both normal fibroglandular tissue (1.60 ± 0.30 vs. 1.75 ± 0.27 × 10−3 mm2/s, p < 0.05) and malignant lesions (0.91 ± 0.18 vs. 1.06 ± 0.35 × 10−3 mm2/s, p < 0.05). Similarly, Shin et al. (2015) observed lower ADC values in postmenopausal women for normal fibroglandular tissue (1.480 vs. 1.640 × 10−3 mm2/s, p < 0.001) and malignant lesions (0.648 vs. 0.644 × 10−3 mm2/s, p = 0.031). Additionally, O’Flynn et al. (2012) reported significantly lower mean ADC values in postmenopausal breasts compared to premenopausal breasts for normal fibroglandular tissue (1.46 ± 0.3 vs. 1.84 ± 0.26 × 10−3 mm2/s, p < 0.001). While Iacconi et al. (2014) primarily focused on premenopausal women, they also noted that postmenopausal status was associated with lower ADC values in normal breast tissue.

Regarding menstrual cycle influences, Partridge et al. (2001) found no significant variations in ADC values across different phases of the menstrual cycle in their study of six premenopausal volunteers. O’Flynn et al. (2012) reported no significant difference in ADC values between follicular and luteal phases in premenopausal women. Kim et al. (2016) observed slightly higher ADC values in the second half of the menstrual cycle for both normal fibroglandular tissue and breast lesions, but these differences were not statistically significant.

The consistency in findings across these studies, despite variations in sample sizes and specific ADC values, suggests a trend towards lower ADC values in postmenopausal women, particularly in normal fibroglandular tissue. This trend was observed in both benign and malignant lesions, although the difference was more pronounced and consistent for normal tissue. In contrast, the influence of menstrual cycle phases on ADC values appears to be minimal or inconsistent across studies.

The consistency in findings across these studies, despite variations in sample sizes and specific ADC values, suggests a trend towards lower ADC values in postmenopausal women, particularly in normal fibroglandular tissue. This trend was observed in both benign and malignant lesions, although the difference was more pronounced and consistent for normal tissue. In contrast, the influence of menstrual cycle phases on ADC values appears to be minimal, with most studies reporting no significant variations across different phases.

3.3 Influence of other factors on ADC values

Several studies investigated additional factors that might influence ADC values in breast tissues:

  • 1. Background Parenchymal Enhancement (BPE): Horvat et al. (2018) investigated the impact of BPE on ADC values and found no significant influence on the sensitivity or specificity of ADC in distinguishing between benign and malignant lesions. This suggests that BPE, despite its known association with hormonal status, may not significantly affect the diagnostic performance of DWI.

  • 2. Fibroglandular Tissue (FGT): Iacconi et al. (2014) reported that the amount of FGT had a significant influence on the quantitative measurement of ADC in normal breast tissue. They found that breasts with higher amounts of FGT tended to have higher ADC values. This relationship was observed in both pre- and post-menopausal women, although the effect was more pronounced in premenopausal subjects.

  • 3. Age: While not directly related to hormonal status, age was found to be a potential confounding factor in several studies. O’Flynn et al. (2012) noted a negative correlation between age and ADC values in normal fibroglandular tissue, which may partly explain the lower ADC values observed in postmenopausal women.

  • 4. Lesion Type: All studies that included both benign and malignant lesions consistently reported lower ADC values for malignant lesions compared to benign ones, regardless of menopausal status. This finding reinforces the potential of ADC as a diagnostic tool in differentiating between benign and malignant breast lesions.

3.4 Technical considerations and measurement variability

The review revealed several technical factors that could contribute to variability in ADC measurements across studies:

  • 1. b-values: The studies used different b-values for DWI acquisition, ranging from 0 and 600 s/mm2 (Horvat et al., 2018) to 0 and 1000 s/mm2 (Kim et al., 2016). This variation in b-values could potentially affect the calculated ADC values and their sensitivity to tissue microstructure.

  • 2. Region of Interest (ROI) Selection: The method of ROI selection varied among studies. Some studies used a single ROI (e.g., Partridge et al., 2001), while others used multiple ROIs or whole-lesion measurements (e.g., Shin et al., 2015). This variability in ROI selection could contribute to differences in reported ADC values across studies.

  • 3. Scanner Variability: Although all included studies used 1.5 Tesla MRI scanners, there were differences in scanner manufacturers (e.g., GE, Siemens, Philips). While the impact of scanner variability on ADC measurements was not directly assessed in these studies, it represents a potential source of inconsistency across studies.

3.5 Diagnostic performance of ADC

Despite the potential influences of hormonal status and other factors on ADC values, several studies reported on the overall diagnostic performance of ADC in differentiating between benign and malignant lesions:

  • 1. Horvat et al. (2018) found that ADC demonstrated high sensitivity (84%) and specificity (84%) in distinguishing between benign and malignant lesions, regardless of BPE, FGT, or menopausal status.

  • 2. Kim et al. (2016) reported that using an ADC cutoff value of 1.23 × 10−3 mm2/s resulted in a sensitivity of 86.7% and specificity of 86.4% for diagnosing malignant lesions in premenopausal women. For postmenopausal women, a cutoff value of 1.12 × 10−3 mm2/s yielded a sensitivity of 92.3% and specificity of 86.7%.

  • 3. Shin et al. (2015) found that the optimal ADC cutoff for differentiating benign from malignant lesions was 1.108 × 10−3 mm2/s in premenopausal women (sensitivity 87.7%, specificity 86.8%) and 1.025 × 10−3 mm2/s in postmenopausal women (sensitivity 80.6%, specificity 82.9%).

These findings suggest that while hormonal status may influence absolute ADC values, the diagnostic performance of ADC in differentiating between benign and malignant lesions remains robust across different hormonal states when appropriate cutoff values are used.

3.6 Longitudinal changes in ADC values

Only one study, Partridge et al. (2001), attempted to track longitudinal changes in ADC values across the menstrual cycle. Despite the small sample size, this study provided valuable insights into the potential for cyclic variations in ADC values. The observed minimal fluctuations suggest that the timing of DWI examinations within the menstrual cycle may not significantly impact diagnostic accuracy. However, more extensive longitudinal studies are needed to confirm this finding.

3.7 Correlation with hormonal levels

None of the included studies directly measured hormone levels and correlated them with ADC values. The assessment of hormonal status was primarily based on self-reported menstrual history or menopausal status. This represents a significant gap in the current literature, as direct correlations between specific hormone levels and ADC values could provide more precise insights into the relationship between hormonal status and diffusion properties of breast tissues.

In summary, the results of this scoping review reveal a complex relationship between hormonal status and ADC values in breast tissues. While there is evidence suggesting lower ADC values in postmenopausal women, particularly in normal fibroglandular tissue, the impact of menstrual cycle phases appears minimal. The influence of other factors such as BPE and FGT on ADC values adds further complexity to the interpretation of DWI results. Despite these variations, the diagnostic performance of ADC in differentiating between benign and malignant lesions appears to remain robust across different hormonal states, suggesting its potential as a valuable tool in breast cancer diagnosis.

4. Discussion

This scoping review synthesizes the current evidence on the influence of hormonal status on Apparent Diffusion Coefficient (ADC) values in breast tissues. The findings reveal a complex interplay between hormonal factors and diffusion properties of breast tissue, with implications for the interpretation and application of Diffusion-Weighted Imaging (DWI) in breast cancer diagnostics.

4.1 Menopausal status and ADC values

One of the most consistent findings across the reviewed studies was the tendency for lower ADC values in postmenopausal women compared to premenopausal women, particularly in normal fibroglandular tissue. This trend was observed in four out of five studies that examined menopausal status,3–6 with only Horvat et al. (2018)14 reporting no significant difference.

The lower ADC values in postmenopausal breast tissue can be explained by the physiological changes that occur during menopause. The decline in estrogen levels leads to a reduction in breast tissue vascularity and an increase in fatty tissue replacement of glandular tissue (involution). These changes could result in decreased water diffusivity, manifesting as lower ADC values.

However, it’s important to note that while the trend was consistent, the magnitude of the difference varied across studies. This variability could be attributed to differences in study populations, imaging protocols, or measurement techniques. Moreover, the study by Horvat et al. (2018), which had the largest sample size, found no significant difference in ADC values between pre- and postmenopausal women. This discrepancy highlights the need for larger, standardized studies to definitively establish the relationship between menopausal status and ADC values.

4.2 Menstrual cycle and ADC values

In contrast to the findings on menopausal status, the evidence for menstrual cycle-related changes in ADC values was less conclusive. The three studies that examined this relationship (Kim et al., 2016; Partridge et al., 2001; O’Flynn et al., 2012) consistently found minimal or no significant variations in ADC values across different phases of the menstrual cycle.

This lack of significant menstrual cycle-related changes is somewhat surprising, given the known cyclic changes in breast tissue due to fluctuating levels of estrogen and progesterone. These hormonal fluctuations lead to changes in breast volume, water content, and vascularity throughout the menstrual cycle. The absence of corresponding changes in ADC values suggests that these cyclic variations may not substantially affect water diffusivity at the microstructural level detectable by current DWI techniques.

However, it’s important to note that the studies examining menstrual cycle effects had relatively small sample sizes and may have lacked the statistical power to detect subtle changes. Furthermore, the timing of MRI examinations in relation to menstrual cycle phases was based on self-reported menstrual history rather than direct hormonal measurements, which could introduce inaccuracies.

4.3 Implications for breast cancer diagnosis

Despite the observed variations in ADC values related to menopausal status, the diagnostic performance of ADC in differentiating between benign and malignant lesions appears to remain robust. Several studies (Horvat et al., 2018; Kim et al., 2016; Shin et al., 2015) reported high sensitivity and specificity for ADC in distinguishing malignant from benign lesions, regardless of menopausal status.

This maintained diagnostic performance suggests that while absolute ADC values may vary with hormonal status, the relative difference between benign and malignant lesions remains sufficiently large for accurate differentiation. However, the optimal ADC cutoff values for diagnosing malignancy may differ between pre- and postmenopausal women, as demonstrated by Kim et al. (2016) and Shin et al. (2015). This finding underscores the importance of considering menopausal status when interpreting ADC values in clinical practice.

4.4 Influence of other factors

The review highlighted several other factors that may influence ADC values, including the amount of fibroglandular tissue (FGT) and background parenchymal enhancement (BPE). The study by Iacconi et al. (2014) found that breasts with higher amounts of FGT tended to have higher ADC values, an effect that was more pronounced in premenopausal women. This finding suggests that breast composition, which is influenced by hormonal status, can affect ADC measurements independently of the presence or absence of lesions.

Interestingly, Horvat et al. (2018) found that BPE did not significantly impact the diagnostic performance of ADC. This is noteworthy because BPE is known to be influenced by hormonal status and has been associated with breast cancer risk. The lack of significant impact on ADC performance suggests that DWI may offer advantages in terms of consistent diagnostic accuracy across varying levels of BPE.

4.5 Technical considerations and standardization

The review revealed considerable variability in technical aspects of DWI acquisition and ADC measurement across studies. Differences in b-values, ROI selection methods, and scanner manufacturers could all contribute to variations in reported ADC values. This lack of standardization presents a challenge for comparing results across studies and for establishing universal ADC thresholds for clinical use.

Future research should aim to standardize DWI protocols and ADC measurement techniques to improve the comparability and reproducibility of results. This standardization should include consensus on optimal b-values, ROI selection methods, and strategies for minimizing the impact of scanner variability.

4.6 Limitations

Several limitations in the current body of evidence were identified:

  • 1. Limited direct measurement of hormone levels: None of the reviewed studies directly measured hormone levels and correlated them with ADC values. Future studies incorporating direct hormonal measurements could provide more precise insights into the relationship between specific hormone levels and breast tissue diffusivity.

  • 2. Lack of longitudinal studies: With the exception of Partridge et al. (2001), which had a very small sample size, there was a lack of longitudinal studies tracking ADC changes over time in individual women. Such studies could provide valuable information on intra-individual variations in ADC values across hormonal states.

  • 3. Limited exploration of other hormonal influences: The review focused primarily on menopausal status and menstrual cycle effects. Other hormonal factors, such as the use of hormonal contraceptives or hormone replacement therapy, were not extensively explored in the included studies.

  • 4. Potential selection bias: The inclusion of only English-language publications and the focus on 1.5 Tesla MRI studies may have led to the exclusion of relevant data.

5. Conclusion and Future Direction

This scoping review provides a comprehensive overview of the current evidence on the influence of hormonal status on ADC values in breast tissues. The findings suggest that menopausal status may significantly impact ADC values, with postmenopausal women generally showing lower ADC values in normal fibroglandular tissue. However, the influence of menstrual cycle phases on ADC values appears to be minimal.

Despite these hormonal influences on absolute ADC values, the diagnostic performance of ADC in differentiating between benign and malignant lesions remains robust across different hormonal states. This suggests that DWI and ADC measurements continue to be valuable tools in breast cancer diagnosis, regardless of a woman’s hormonal status.

However, the review also highlights significant gaps in the current literature, including a lack of standardization in DWI protocols, limited longitudinal data, and an absence of studies directly correlating hormone levels with ADC values. Addressing these gaps in future research will be crucial for fully understanding the complex relationship between hormonal status and breast tissue diffusivity.

Based on these limitations and the findings of this review, several directions for future research can be proposed:

  • 1. Large-scale, multi-centre studies with standardized protocols to definitively establish the relationship between hormonal status and ADC values.

  • 2. Longitudinal studies tracking ADC changes across the menstrual cycle and through menopausal transition in individual women.

  • 3. Studies incorporating direct measurements of hormone levels to correlate with ADC values.

  • 4. Investigation of the effects of exogenous hormones (e.g., oral contraceptives, hormone replacement therapy) on ADC values.

  • 5. Exploration of advanced DWI techniques, such as intravoxel incoherent motion (IVIM) or diffusion kurtosis imaging, to potentially capture more subtle hormone-related changes in breast tissue microstructure.

  • 6. Development and validation of hormone status-specific ADC thresholds for breast cancer diagnosis.

Data availability statement

No data are associated with this article.

Extended data

Reporting guidelines

The checklist is added in the repository in the link: Dkhar, Winniecia, 2024, “Hormonal Influences on ADC Values in Breast Tissues: A Scoping Review of DWI in Pre- and Post-menopausal Women”, https://doi.org/10.7910/DVN/WFX1DQ, Harvard Dataverse, V1.15

References

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  • 3.  O’Flynn EAM, Morgan VA, Giles SL, et al.: Diffusion weighted imaging of the normal breast: reproducibility of apparent diffusion coefficient measurements and variation with menstrual cycle and menopausal status. Eur. Radiol. 2012 Jul 26; 22(7): 1512–1518. PubMed Abstract | Publisher Full Text
  • 4.  Iacconi C, Thakur SB, Dershaw DD, et al.: Impact of fibroglandular tissue and background parenchymal enhancement on diffusion weighted imaging of breast lesions. Eur. J. Radiol. 2014 Dec; 83(12): 2137–2143. PubMed Abstract | Publisher Full Text
  • 5.  Shin S, Ko ES, Kim RB, et al.: Effect of menstrual cycle and menopausal status on apparent diffusion coefficient values and detectability of invasive ductal carcinoma on diffusion-weighted MRI. Breast Cancer Res. Treat. 2015 Feb 1; 149(3): 751–759. PubMed Abstract | Publisher Full Text
  • 6.  Kim JY, Suh HB, Kang HJ, et al.: Apparent diffusion coefficient of breast cancer and normal fibroglandular tissue in diffusion-weighted imaging: the effects of menstrual cycle and menopausal status. Breast Cancer Res. Treat. 2016 May 18; 157(1): 31–40. PubMed Abstract | Publisher Full Text
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  • 15.  Dkhar W: Hormonal Influences on ADC Values in Breast Tissues: A Scoping Review of DWI in Pre- and Post-menopausal Women. Harvard Dataverse. 2024; V1. Publisher Full Text

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Dkhar W, Kadavigere R, Ravichandran S et al. Hormonal Influences on ADC Values in Breast Tissues: A Scoping Review of DWI in Pre- and Post-menopausal Women [version 3; peer review: 2 approved]. F1000Research 2025, 13:857 (https://doi.org/10.12688/f1000research.153999.3)
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Version 3
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Reviewer Report 29 Jan 2025
Avantsa Rohini, Department of Radiodiagnosis and Imaging, MNR Medical College, Sangareddy, Telangana, India 
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https://doi.org/10.5256/f1000research.176915.r362771
The suggestions from the previous version were incorporated in ... Continue reading
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Rohini A. Reviewer Report For: Hormonal Influences on ADC Values in Breast Tissues: A Scoping Review of DWI in Pre- and Post-menopausal Women [version 3; peer review: 2 approved]. F1000Research 2025, 13:857 (https://doi.org/10.5256/f1000research.176915.r362771)
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Reviewer Report 28 Jan 2025
Manna Debnath, Charotar University of Science and Technology, Changa, Gujarat, India 
Approved
VIEWS 4
https://doi.org/10.5256/f1000research.176915.r362772
... Continue reading
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Debnath M. Reviewer Report For: Hormonal Influences on ADC Values in Breast Tissues: A Scoping Review of DWI in Pre- and Post-menopausal Women [version 3; peer review: 2 approved]. F1000Research 2025, 13:857 (https://doi.org/10.5256/f1000research.176915.r362772)
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Avantsa Rohini, Department of Radiodiagnosis and Imaging, MNR Medical College, Sangareddy, Telangana, India 
Approved
VIEWS 13
https://doi.org/10.5256/f1000research.170311.r355176
This is a very well written and interesting scoping review and the authors had done an excellent work. I think this contributes towards further research/alternatives. There are few suggestions the author needs to look into which might add further to ... Continue reading
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Rohini A. Reviewer Report For: Hormonal Influences on ADC Values in Breast Tissues: A Scoping Review of DWI in Pre- and Post-menopausal Women [version 3; peer review: 2 approved]. F1000Research 2025, 13:857 (https://doi.org/10.5256/f1000research.170311.r355176)
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Reviewer Report 13 Sep 2024
Manna Debnath, Charotar University of Science and Technology, Changa, Gujarat, India 
Approved
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https://doi.org/10.5256/f1000research.170311.r319001
I am satisfied with the changes authors have made to the manuscript. Author ... Continue reading
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HOW TO CITE THIS REPORT
Debnath M. Reviewer Report For: Hormonal Influences on ADC Values in Breast Tissues: A Scoping Review of DWI in Pre- and Post-menopausal Women [version 3; peer review: 2 approved]. F1000Research 2025, 13:857 (https://doi.org/10.5256/f1000research.170311.r319001)
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Reviewer Report 09 Aug 2024
Manna Debnath, Charotar University of Science and Technology, Changa, Gujarat, India 
Approved
VIEWS 13
https://doi.org/10.5256/f1000research.168971.r310441
This is a scientifically sound scoping review. The author(s) have written extremely well. However, a few minor changes need to be addressed. Once these are included, the manuscript's quality will improve even further.
Reviewers comment:
1. References are ... Continue reading
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CITE
HOW TO CITE THIS REPORT
Debnath M. Reviewer Report For: Hormonal Influences on ADC Values in Breast Tissues: A Scoping Review of DWI in Pre- and Post-menopausal Women [version 3; peer review: 2 approved]. F1000Research 2025, 13:857 (https://doi.org/10.5256/f1000research.168971.r310441)
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  • Author Response 30 Aug 2024
    Winniecia Dkhar, Medical Imaging Technology, Manipal College of Health Professions, Manipal Academy of Higher Education, Manipal, 576104, India
    30 Aug 2024
    Author Response
    Thank you for your valuable feedback on our scoping review. We appreciate your thoughtful comments and suggestions. Here is our response to each of your points:

    1. We agreed ... Continue reading
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  • Author Response 30 Aug 2024
    Winniecia Dkhar, Medical Imaging Technology, Manipal College of Health Professions, Manipal Academy of Higher Education, Manipal, 576104, India
    30 Aug 2024
    Author Response
    Thank you for your valuable feedback on our scoping review. We appreciate your thoughtful comments and suggestions. Here is our response to each of your points:

    1. We agreed ... Continue reading
    Report a concern

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Version 3
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Alongside their report, reviewers assign a status to the article:

Approved
The paper is scientifically sound in its current form and only minor, if any, improvements are suggested
Approved with reservations
A number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.
Not approved
Fundamental flaws in the paper seriously undermine the findings and conclusions

Reviewer Reports

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1 2
Version 3
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 27 Jan 25 		read read
Version 2
(revision)
 30 Aug 24 		read read
Version 1
01 Aug 24 		read
  1. Manna Debnath, Charotar University of Science and Technology, Changa, India
  2. Avantsa Rohini, Department of Radiodiagnosis and Imaging, MNR Medical College, Sangareddy, India

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    Alongside their report, reviewers assign a status to the article:
    Approved - the paper is scientifically sound in its current form and only minor, if any, improvements are suggested
    Approved with reservations - A number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.
    Not approved - fundamental flaws in the paper seriously undermine the findings and conclusions
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