Figure 1.

Graphical depiction of the integration of breast MRI data with the mathematical model for predicting tumor response and simulating alternative treatment regimens. The data from MRI scans obtained before and after one cycle of the first NAT regimen, are used to generate spatially resolved maps of tumor cell number and drug delivery (panels a and b, respectively). The model parameters are then calibrated using this early NAT imaging data (panel c), and the model is run forward to the time of the patient's third scan (panel d). The model's predictions of total cellularity, total volume, and longest axis measures are then directly compared to each patient's actual tumor outcome as determined by their scan 3 data. The model's predictions were also compared to the RECIST designations to determine accuracy in the context of clinical measures. Using the patient-specific model parameters (panel c), alternative therapy regimens adjusting the frequency and dosage of treatments (“Tx_i”, panel e) are evaluated using the model's predictions from scan 2 to 3 for each of these regimens to determine an optimal treatment schedule for each patient (panel f).