Prediction of early response to antidepressant medication in MDD adolescents using radiomics analysis based on brain multiscale structural MRI

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Based on the radiomics analysis framework and using machine learning, this study constructed a multiscale structural MRI prediction model to predict the early response of MDD patients to antidepressant medication, and determined the radiomics features with high weight for SSRIs/SNRIs selection. The results showed that the baseline radiomics model after normalization can effectively predict the early treatment response of ADM in adolescent MDD patients, and is superior to the model based on conventional imaging indicators and unnormalized radiomics features. The AUC, accuracy, sensitivity and specificity of predicting SSRIs improvement and SNRIs improvement are 0.954, 89.2%, 87.4% and 88.5%, 0.942, 91.9%, 82.5% and 86.8%, respectively.