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. 2022 Sep 5;196(1):57–66. doi: 10.1007/s10549-022-06722-0

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© The Author(s) 2022

Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.

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Fig. 2 — A Biophysical Simulation Predicts Change in Volume and Morphology Throughout Treatment. Representative examples of model predictions showing how the tumor volume changes in response to therapy. A three-dimensional rendering of the breast segmentation derived from DCE-MRI depicting the tumor (blue), glandular tissue (dark gray), and the outline of the patient's body (light gray) at time of diagnosis is shown for each patient. The three-dimensional model is used as input to the model, which predicts change in volume over the treatment course. Predicted tumor volume (red) matches well with segmentations of from intra-treatment MRIs (blue). Examples of patients with residual globular (top) and multi-centric (bottom) tumors are shown, along with an example of a patient achieving pCR (middle)