Prediction of the prognosis of liver iron burden within two years after hematopoietic stem cell transplantation based on multimodal MRI-based radiomics model

To explore the predictive value of MRI-based radiomics model for the prognosis of liver iron burden within 2 years after hematopoietic stem cell transplantation (HSCT) in thalassemia (TM) patients who had undergone HSCT the preoperative liver 3.0T/1.5T MRI images and clinical data of 360 TM patients in two medical centers (A and B) were retrospectively analyzed. AUC, accuracy, sensitivity and specificity were used to evaluate the predictive efficacy of the model. The best performance prediction model of 3.0T/1.5T radiomics in medical center A was T1_F: the AUC, accuracy, sensitivity and specificity of the training set were 0.942/0.917, 0.91/0.8, 0.941/1 and 0.9/0.772, respectively. The AUC, accuracy, sensitivity and specificity of the test set were 0.845/0.896, 0.767/0.714, 1/1 and 0.696/0.667, respectively. The optimal performance prediction models of 3.0T/1.5T radiomics in medical center B were T1_W and T1_opp, respectively. The AUC, accuracy, sensitivity and specificity of the training set were 0.855/0.94, 0.79/0.933, 0.779/0.9 and 0.8/0.938, respectively. The AUC, accuracy, sensitivity and specificity of the test set were 0.81/0.743, 0.778/0.727, 0.73/0.727 and 0.73/0.714, respectively. It is expected that different MRI prediction models with different parameters can be constructed in different medical centers to evaluate the prognosis of liver iron burden in TM patients after HSCT.