The Incremental Value of Native T1 Mapping-Derived Radiomics for The Diagnosis of Amyloid Light-Chain Cardiac Amyloidosis

Rationale and Objectives: This study aimed to assess the incremental diagnostic value of non-contrast T1 mapping-derived radiomics in patients with amyloid light-chain cardiac amyloidosis (AL-CA). Methods: We retrospectively collected 86 patients with suspected AL-CA and 28 control patients who underwent cardiac MRI at 3.0 T in our institution, and the MRI data were divided into a training set and a test set. Radiomic features were extracted based on native T1 maps using a freely available software package. We applied LASSO logistic regression method to select radiomic features with high diagnostic value of AL-CA and develop a predictive model. The diagnostic performance of the radiomics model was evaluated using receiver operating characteristic curve analysis and compared to T1 values. Results: A total of 70 people were diagnosed with AL-CA, and cardiac involvement was observed in 202 myocardial slicers. The accuracy of T1 values for the diagnosis of myocardial involvement was 0.886, with a threshold value of 1375 ms. The radiomics score comprised a total of three features. The radiomics score demonstrated significantly higher sensitivity in detecting myocardial involvement compared to T1 values in both the training set (AUC 0.886 vs. 0.924, P = 0.025) and the test set (0.862 vs 0.915, P = 0.026). The combined model comprising T1 values and a radiomic feature named S(4,-4) Correlat showed higher diagnostic performance in comparison to T1 values alone both in the training and test sets, with AUC values of 0.929 and 0.909, respectively. Conclusion: The radiomic features derived from native T1 mapping demonstrated incremental value for the diagnosis of AL-CA, which may be an alternative to T1-derived ECV to avoid the use of contrast in patients with suspected myocardial involvement in systemic amyloidosis.