Parametric mapping using cardiovascular magnetic resonance for the differentiation of light chain amyloidosis and transthyretin-related amyloidosis.
Eur Heart J Cardiovasc Imaging
; 2024 Jun 24.
Article
in En
| MEDLINE
| ID: mdl-38912832
ABSTRACT
AIMS:
To evaluate different cardiovascular magnetic resonance (CMR) parameters for the differentiation of light chain amyloidosis (AL) and transthyretin-related amyloidosis (ATTR). METHODS ANDRESULTS:
In total, 75 patients, 53 with cardiac amyloidosis (20 patients with AL (66±12 years, 14 males [70%]) and 33 patients with ATTR (78±5 years, 28 males [88%])) were retrospectively analyzed regarding CMR parameters such as T1 and T2 mapping, extracellular volume (ECV), and late gadolinium enhancement (LGE) distribution patterns, and myocardial strain, and compared to a control cohort with other causes of left ventricular hypertrophy (LVH; 22 patients (53±16 years, 17 males [85%])). One way-ANOVA and receiver operating characteristic analysis were used for statistical analysis. ECV was the single best parameter to differentiate between cardiac amyloidosis and controls (area under the curve [AUC] 0.97, 95% confidence intervals [CI] 0.89-0.99, p<.0001, cutoff >30%). T2 mapping was the best single parameter to differentiate between AL and ATTR amyloidosis (AL 63±4 ms, ATTR 58±2 ms, p<.001, AUC 0.86, 95% CI 0.74-0.94, cutoff >61 ms). Subendocardial LGE was predominantly observed in AL patients (10/20 [50%] vs. 5/33 [15%]; p=.002). Transmural LGE was predominantly observed in ATTR patients (23/33 [70%] vs. 2/20 [10%]; p<.001). The diagnostic performance of T2 mapping to differentiate between AL and ATTR amyloidosis was further increased with the inclusion of LGE patterns (AUC 0.96, 95% CI 0.86-0.99]; p=.05).CONCLUSION:
ECV differentiates cardiac amyloidosis from other causes of LVH. T2 mapping combined with LGE differentiates AL from ATTR amyloidosis with high accuracy on a patient level.
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1
Collection:
01-internacional
Database:
MEDLINE
Language:
En
Journal:
Eur Heart J Cardiovasc Imaging
Year:
2024
Document type:
Article
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