Can myocardial susceptibility quantification be an imaging biomarker for cardiac amyloidosis?

Jpn J Radiol. 2022 May;40(5):500-507. doi: 10.1007/s11604-021-01228-z. Epub 2021 Nov 29.

Abstract

Purpose: This study aimed to evaluate whether quantification of myocardial susceptibility by cardiac magnetic resonance imaging (CMR) can be an imaging biomarker for cardiac amyloidosis (CA).

Materials and methods: Twenty-six patients with CA underwent CMR, including magnetic phase imaging with a 3.0-T magnetic resonance imaging scanner. Myocardial susceptibility was quantified as a phase shift slope value by magnetic phase analysis. Those values from patients with CA were compared with corresponding values from 18 controls and 15 healthy volunteers. A univariate logistic regression analysis was conducted to identify significant parameters related to CA.

Results: The phase shift slope, a quantitative parameter of myocardial susceptibility, was significantly lower in the CA group compared with the control group and compared with healthy volunteers (p < 0.01). From a total of 17 tested variables, 6 were considered to be significant predictors of CA (p ≤ 0.05) during the univariate analysis. The phase shift slope yielded the best AUC of 0.89 (95% CI = 0.79-0.98) for the prediction of CA (p < 0.01). The phase shift slope was significantly correlated with the end-diastolic thickness of the interventricular septum (r = - 0.39, p < 0.01) and posterior wall of the left ventricle (r = - 0.35, p = 0.02).

Conclusion: Myocardial susceptibility analysis by CMR helps in the diagnosis of patients with CA and can be a new quantitative imaging biomarker for CA.

Keywords: Cardiac amyloidosis; Cardiac magnetic resonance imaging; Imaging biomarker; Myocardial susceptibility.

MeSH terms

  • Amyloidosis* / diagnostic imaging
  • Amyloidosis* / pathology
  • Biomarkers
  • Cardiomyopathies* / diagnostic imaging
  • Humans
  • Magnetic Resonance Imaging, Cine / methods
  • Myocardium / pathology
  • Predictive Value of Tests

Substances

  • Biomarkers