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. Author manuscript; available in PMC: 2024 Jan 5.
Published in final edited form as: Brain Multiphys. 2023 Oct 29;5:100084. doi: 10.1016/j.brain.2023.100084

Fig. 1.

Fig. 1.

Schematic of the experimental-computational framework. Panel A displays the imaging datatypes used in this study. The timeline in the bottom of panel A visualizes the imaging acquisitions, with SPECT-CT occurring during the first week and MRI after treatment with RNL. Panel B highlights the image processing techniques used in this study. The patient-specific calibration flowchart is in panel C, which starts with the processed cell maps and RNL time course, loops through the calibration sequence, and outputs a prediction to be assessed. The leave-one-out method in panel D begins with parameters from the calibrated cohort to make an initial prediction for the patient, new data is then added to improve subsequent predictions.