Mammographic density assessed using deep learning in women at high risk of developing breast cancer: the effect of weight change on density

Objectives: High mammographic density (MD) and excess weight are associated with increased risk of breast cancer. Weight loss interventions could reduce risk, but classically defined percentage density measures may not reflect this due to disproportionate loss of breast fat. We investigate an artificial intelligence-based density method, reporting density changes in 46 women enrolled in a weight-loss study in a family history breast cancer clinic, using a volumetric density method as a comparison. Methods: We analysed data from women who had weight recorded and mammograms taken at the start and end of the 12-month weight intervention study. MD was assessed at both time points using a deep learning model, pVAS, trained on expert estimates of percent density, and VolparaTM density software. Results: The Spearman rank correlation between reduction in weight and change in density was 0.17 (-0.13 to 0.43) for pVAS and 0.59 (0.36 to 0.75) for Volpara volumetric percent density. Conclusions: pVAS percent density measurements were not significantly affected by change in weight. Percent density measured with Volpara increased as weight decreased, driven by changes in fat volume. Advances in knowledge: The effect of weight change on pVAS mammographic density predictions has not previously been published. ### Competing Interest Statement The authors have declared no competing interest. ### Clinical Trial ISRCTN16431108 ### Funding Statement The project was funded by Prevent Breast Cancer (registered charity number 1109839) and supported by the NIHR Manchester Biomedical Research Centre (IS-BRC-1215-20007) infrastructure. The funders had no role in the design, conduct, analysis or write up of the study. MH, DGE, AH , SA are supported by the NIHR Manchester Biomedical Research Centre (IS-BRC-1215-20007). ### Author Declarations I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained. Yes The details of the IRB/oversight body that provided approval or exemption for the research described are given below: The study was reviewed by the North-West - Preston Research Ethics Committee reference 17/NW/0440. Written informed consent was obtained from all participants and the study was performed in accordance with the Declaration of Helsinki. I confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals. Yes I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance). Yes I have followed all appropriate research reporting guidelines, such as any relevant EQUATOR Network research reporting checklist(s) and other pertinent material, if applicable. Yes All datasets used and analysed during the current study are available on reasonable request.