Extracellular Volume Fraction Based on Cardiac Magnetic Resonance T1 Mapping: An Effective Way to Evaluate Cardiac Injury Caused by Cardiac Amyloidosis in Patients with Multiple Myeloma.
Minghui LiuLiang ShaoZhaoxia YangQian WangBalu WuXiaoyan LiuYalan YuTingting HuangMeixing WangYong HeGuohong LiuFuling ZhouPublished in: Journal of immunology research (2022)
Multiple myeloma (MM) is a hematological malignancy of plasma cell origin. Cardiac amyloidosis (CA) is a common form of heart damage caused by MM and is associated with a poor prognosis. This study was a prospective cohort study and was aimed at evaluating the clinical predictive value of extracellular volume fraction (ECV) based on cardiovascular magnetic resonance (CMR) T1 mapping for cardiac amyloidosis and cardiac dysfunction in MM patients. Fifty-one newly diagnosed MM patients in Zhongnan Hospital of Wuhan University were enrolled in the study. A total of 19 patients (19/51; 37.25%) developed CA. The basal ECV of CA group was significantly higher than that of the non-CA group ( p < 0.01). Multivariate logistic regression analysis showed that basal ECV (OR = 1.551, 95% CI 1.084-2.219, p < 0.05) and LDH1 level (OR = 1.150, 95% CI 1.010-1.310, p < 0.05) were two independent risk factors for CA. Further study demonstrated that basal ECV in the heart failure group was significantly higher than that of the nonheart failure group ( p < 0.01). Notably, ROC curve showed that basal ECV had a good predictive value for CA and heart failure, with AUC of 0.911 and 0.893 (all p < 0.01), and the best cutoff values of 38.35 and 37.45, respectively. Taken together, basal ECV is a good predictor of CA and heart failure for MM patients.
Keyphrases
- newly diagnosed
- heart failure
- end stage renal disease
- magnetic resonance
- left ventricular
- ejection fraction
- poor prognosis
- multiple myeloma
- chronic kidney disease
- peritoneal dialysis
- prognostic factors
- healthcare
- emergency department
- magnetic resonance imaging
- atrial fibrillation
- long non coding rna
- mass spectrometry
- bone marrow
- high density
- data analysis