Light-Chain Cardiac Amyloidosis: Cardiac Magnetic Resonance for Assessing Response to Chemotherapy.

OBJECTIVE: Cardiac magnetic resonance (CMR) is a diagnostic tool that provides precise and reproducible information about cardiac structure, function, and tissue characterization, aiding in the monitoring of chemotherapy response in patients with light-chain cardiac amyloidosis (AL-CA). This study aimed to evaluate the feasibility of CMR in monitoring responses to chemotherapy in patients with AL-CA. MATERIALS AND METHODS: In this prospective study, we enrolled 111 patients with AL-CA (50.5% male; median age, 54 [interquartile range, 49-63] years). Patients underwent longitudinal monitoring using biomarkers and CMR imaging. At follow-up after chemotherapy, patients were categorized into superior and inferior response groups based on their hematological and cardiac laboratory responses to chemotherapy. Changes in CMR findings across therapies and differences between response groups were analyzed. RESULTS: Following chemotherapy (before vs. after), there were significant increases in myocardial T2 (43.6 ± 3.5 ms vs. 44.6 ± 4.1 ms; P = 0.008), recovery in right ventricular (RV) longitudinal strain (median of -9.6% vs. -11.7%; P = 0.031), and decrease in RV extracellular volume fraction (ECV) (median of 53.9% vs. 51.6%; P = 0.048). These changes were more pronounced in the superior-response group. Patients with superior cardiac laboratory response showed significantly greater reductions in RV ECV (-2.9% [interquartile range, -8.7%-1.1%] vs. 1.7% [-5.5%-7.1%]; P = 0.017) and left ventricular ECV (-2.0% [-6.0%-1.3%] vs. 2.0% [-3.0%-5.0%]; P = 0.01) compared with those with inferior response. CONCLUSION: Cardiac amyloid deposition can regress following chemotherapy in patients with AL-CA, particularly showing more prominent regression, possibly earlier, in the RV. CMR emerges as an effective tool for monitoring associated tissue characteristics and ventricular functional recovery in patients with AL-CA undergoing chemotherapy, thereby supporting its utility in treatment response assessment.

Late gadolinium enhanced cardiac MR derived radiomics approach for predicting all-cause mortality in cardiac amyloidosis: a multicenter study.

OBJECTIVES: To evaluate the prognostic value of radiomics features based on late gadolinium enhancement (LGE) cardiac magnetic resonance (CMR) images in patients with cardiac amyloidosis (CA). METHODS: This retrospective study included 120 CA patients undergoing CMR at three institutions. Radiomics features were extracted from global and three different segments (base, mid-ventricular, and apex) of left ventricular (LV) on short-axis LGE images. Primary endpoint was all-cause mortality. The predictive performance of the radiomics features and semi-quantitative and quantitative LGE parameters were compared by ROC. The AUC was used to observe whether Rad-score had an incremental value for clinical stage. The Kaplan-Meier curve was used to further stratify the risk of CA patients. RESULTS: During a median follow-up of 12.9 months, 30% (40/120) patients died. There was no significant difference in the predictive performance of the radiomics model in different LV sections in the validation set (AUCs of the global, basal, middle, and apical radiomics model were 0.75, 0.77, 0.76, and 0.77, respectively; all p > 0.05). The predictive performance of the Rad-score of the base-LV was better than that of the LGE total enhancement mass (AUC:0.77 vs. 0.54, p < 0.001) and LGE extent (AUC: 0.77 vs. 0.53, p = 0.004). Rad-score combined with Mayo stage had better predictive performance than Mayo stage alone (AUC: 0.86 vs. 0.81, p = 0.03). Rad-score (≥ 0.66) contributed to the risk stratification of all-cause mortality in CA. CONCLUSIONS: Compared to quantitative LGE parameters, radiomics can better predict all-cause mortality in CA, while the combination of radiomics and Mayo stage could provide higher predictive accuracy. CLINICAL RELEVANCE STATEMENT: Radiomics analysis provides incremental value and improved risk stratification for all-cause mortality in patients with cardiac amyloidosis. KEY POINTS: • Radiomics in LV-base was superior to LGE semi-quantitative and quantitative parameters for predicting all-cause mortality in CA. • Rad-score combined with Mayo stage had better predictive performance than Mayo stage alone or radiomics alone. • Rad-score ≥ 0.66 was associated with a significantly increased risk of all-cause mortality in CA patients.

Diagnosis of Cardiac Amyloidosis Using a Radiomics Approach Applied to Late Gadolinium-Enhanced Cardiac Magnetic Resonance Images: A Retrospective, Multicohort, Diagnostic Study.

Objectives: To assess the potential of a radiomics approach of late gadolinium enhancement (LGE) cardiac magnetic resonance (CMR) in the diagnosis of cardiac amyloidosis (CA). Materials and Methods: This retrospective study included 200 patients with biopsy-proven light-chain (AL) amyloidosis. CA was diagnosed on the basis of systemic amyloidosis confirmed with evidence of cardiac involvement by imaging and clinical biomarkers. A total of 139 patients [54 ± 8 years, 75 (54%) men] in our institution were divided into training cohort [n = 97, mean age of 53 ± 8 years, 54 (56%) men] and internal validation cohort [n = 42, mean age: 56 ± 8 years, 21 (50%) men] with a ratio of 7:3, while 61 patients [mean age: 60 ± 9 years, 42 (69%) men] from the other two institutions were enrolled for external validation. Radiomics features were extracted from global (all short-axis images from base-to-apex) left ventricular (LV) myocardium and three different segments (basal, midventricular, and apex) on short-axis LGE images using the phase-sensitive reconstruction (PSIR) sequence. The Boruta algorithm was used to select the radiomics features. This model was built using the XGBoost algorithm. The two readers performed qualitative and semiquantitative assessment of the LGE images based on the visual LGE patterns, while the quantitative assessment was measured using a dedicated semi-automatic CMR software. The diagnostic performance of the radiomics and other qualitative and quantitative parameters were compared by a receiver operating characteristic (ROC) curve analysis. A correlation between radiomics and the degree of myocardial involvement by amyloidosis was tested. Results: A total of 1,906 radiomics features were extracted for each LV section. No statistical significance was indicated between any two slices for diagnosing CA, and the highest area under the curve (AUC) was found in basal section {0.92 [95% confidence interval (CI), 0.86-0.97] in the LGE images in the training set, 0.89 (95% CI, 0.79-1.00) in the internal validation set, and 0.92 (95% CI, 0.85-0.99) in the external validation set}, which was superior to the visual assessment and quantitative LGE parameters. Moderate correlations between global or basal radiomics scores (Rad-scores) and Mayo stage in all patients were reported (Spearman's Rho = 0.61, 0.62; all p < 0.01). Conclusion: A radiomics analysis of the LGE images provides incremental information compared with the visual assessment and quantitative parameters on CMR to diagnose CA. Radiomics was moderately correlated with the severity of CA. Further studies are needed to assess the prognostic significance of radiomics in patients with CA.