Meeting Abstracts from the British Society of Breast Radiology Annual Scientific Meeting 2024

BackgroundMammographic density (MD) is a well-established breast cancer risk factor.Decreasing MD has been demonstrated to be a risk-reduction biomarker in a landmark chemoprevention study in high-risk women.A few small studies suggest that a decreasing MD in women taking adjuvant endocrine therapy (AET) may be associated with a lower risk of recurrence and breast cancer specific death.Aim This interim analysis aims to measure inter and intra-reader variability of MD classification within a current study (MEDICI) investigating whether a reduction in MD after one and/or three years in women taking AET is associated with a lower risk of breast cancer recurrence and death compared to no reduction.Methods Retrospective cohort study, generated from a subset of participants from the Mammo-50 trial.Eleven readers assessed MD using a 0 to 100% visual analogue scale (VAS), scoring mammograms from time of diagnosis and at one and three years after diagnosis.A subset of four readers re-analysed the mammograms.Inter and intra-reader agreement were estimated using intra-class correlation coefficients (ICC). ResultsEleven readers classified MD in 50 patients at three timepoints (150 mammograms), using the VAS.Four readers re-interpreted all 150 mammograms.The ICC between all 11 readers (inter-reader agreement) was 0.80 (95% confidence interval (CI): 0.77-0.84).The ICC within readers (intra-reader agreement) was 0.86 (95% CI 0.77-0.91). ConclusionInterim analysis demonstrates good inter-and intra-reader agreement for assessment of MD on VAS, suggesting validity of the human MD assessment to be performed within the MEDICI study O4.

Publication Details

Journal
Breast Cancer Research
Published
2025-06-17
DOI
https://doi.org/10.1186/s13058-025-02023-8
Primary Topic
Radiomics and Machine Learning in Medical Imaging
Type
article
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article

Meeting Abstracts from the British Society of Breast Radiology Annual Scientific Meeting 2024

Breast Cancer Research
Radiomics and Machine Learning in Medical Imaging
article

Meeting Abstracts from the British Society of Breast Radiology Annual Scientific Meeting 2024

article en

Abstract

BackgroundMammographic density (MD) is a well-established breast cancer risk factor.Decreasing MD has been demonstrated to be a risk-reduction biomarker in a landmark chemoprevention study in high-risk women.A few small studies suggest that a decreasing MD in women taking adjuvant endocrine therapy (AET) may be associated with a lower risk of recurrence and breast cancer specific death.Aim This interim analysis aims to measure inter and intra-reader variability of MD classification within a current study (MEDICI) investigating whether a reduction in MD after one and/or three years in women taking AET is associated with a lower risk of breast cancer recurrence and death compared to no reduction.Methods Retrospective cohort study, generated from a subset of participants from the Mammo-50 trial.Eleven readers assessed MD using a 0 to 100% visual analogue scale (VAS), scoring mammograms from time of diagnosis and at one and three years after diagnosis.A subset of four readers re-analysed the mammograms.Inter and intra-reader agreement were estimated using intra-class correlation coefficients (ICC). ResultsEleven readers classified MD in 50 patients at three timepoints (150 mammograms), using the VAS.Four readers re-interpreted all 150 mammograms.The ICC between all 11 readers (inter-reader agreement) was 0.80 (95% confidence interval (CI): 0.77-0.84).The ICC within readers (intra-reader agreement) was 0.86 (95% CI 0.77-0.91). ConclusionInterim analysis demonstrates good inter-and intra-reader agreement for assessment of MD on VAS, suggesting validity of the human MD assessment to be performed within the MEDICI study O4.

Breast Cancer ResearchVol. 27(S1)
Gender equality
Openalex Percentile: Top 79%
Radiomics and Machine Learning in Medical Imaging
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