The invention discloses a TCP and multi-NTCP combination optimal
dose calculation method and
system based on
deep learning, relates to the technical field of radiotherapy, and aims to solve the problems of insufficient multi-
source data integration, unbalanced multi-
organ protection and low individualized precision in traditional
dose optimization. The method comprises the following steps: acquiring a CT image of a target patient, a tumor and
normal tissue dose-volume
histogram (DVH), baseline clinical data and follow-up data after radiotherapy of a
patient group; constructing a multi-
modal feature data set and an
annotation data set through spatial alignment and normalization
processing, training a
deep learning joint prediction model, synchronously outputting TCP values corresponding to candidate doses and NTCP values of at least three organs at risk, and constructing a fitting curve; and through a single-organ net income formula, a multi-organ comprehensive net income formula and an optimal dose screening formula, quantifying income-risk balance and screening an optimal dose for maximizing the comprehensive net income. According to the invention, through cooperation of
deep learning and an exclusive formula
system, dynamic quantitative balance of multi-organ unbiased protection and
tumor control is realized, individualized precision and clinical landing of
radiotherapy dose planning are improved, and the method is suitable for precise radiotherapy scenes of various
solid tumors.