Abstract
Objectives: Since risk stratification data represents a key domain of biomarker validation, we compared associations between outcomes and various cardiovascular magnetic resonance (CMR) metrics quantifying myocardial fibrosis (MF) in noninfarcted myocardium: extracellular volume fraction (ECV), native T1, post contrast T1, and partition coefficient.
Background: MF associates with vulnerability to adverse events e.g., mortality and hospitalization for heart failure (HHF), but investigators still debate its optimal measurements; most histologic validation data show strongest ECV correlations with MF.
Methods: We enrolled 1714 consecutive patients without amyloidosis or hypertrophic cardiomyopathy from a single CMR referral center serving an integrated healthcare network. We measured T1 (MOLLI) in noninfarcted myocardium, averaged from 2 short axis slices (basal and mid) before and 15-20 minutes after a gadolinium contrast bolus. We compared chi square (χ2) values from CMR MF measures in univariable and multivariable Cox regression models. We assessed “dose-response” relationships in Kaplan Meier curves using log-rank statistics for quartile strata. We also computed net reclassification improvement (NRI) and integrated discrimination improvement (IDI for Cox models with ECV vs. native T1.
Results: Over a median of 5.6 years, 374 events occurred after CMR (162 HHF events and 279 deaths, 67 with both). ECV yielded best separation of Kaplan-Meier curves and highest log-ranks statistics. In univariable and multivariable models, ECV associated most strongly with outcomes, demonstrating the highest χ2 values. Native T1 or post contrast T1 did not associate with outcomes in the multivariable model. ECV provided added prognostic value to models with native T1, e.g., in multivariable models IDI=0.0037 (95%CI 0.0009-0.0071), p= 0.02; NRI= 0.151 (95%CI 0.022-0.292), p=0.04. Conclusions: Analogous to histologic previously published validation data, ECV myocardial fibrosis measures exhibited more robust associations with outcomes than other surrogate CMR MF measures. Superior risk stratification by ECV supports claims that ECV optimally measures MF in noninfarcted myocardium.
Background: MF associates with vulnerability to adverse events e.g., mortality and hospitalization for heart failure (HHF), but investigators still debate its optimal measurements; most histologic validation data show strongest ECV correlations with MF.
Methods: We enrolled 1714 consecutive patients without amyloidosis or hypertrophic cardiomyopathy from a single CMR referral center serving an integrated healthcare network. We measured T1 (MOLLI) in noninfarcted myocardium, averaged from 2 short axis slices (basal and mid) before and 15-20 minutes after a gadolinium contrast bolus. We compared chi square (χ2) values from CMR MF measures in univariable and multivariable Cox regression models. We assessed “dose-response” relationships in Kaplan Meier curves using log-rank statistics for quartile strata. We also computed net reclassification improvement (NRI) and integrated discrimination improvement (IDI for Cox models with ECV vs. native T1.
Results: Over a median of 5.6 years, 374 events occurred after CMR (162 HHF events and 279 deaths, 67 with both). ECV yielded best separation of Kaplan-Meier curves and highest log-ranks statistics. In univariable and multivariable models, ECV associated most strongly with outcomes, demonstrating the highest χ2 values. Native T1 or post contrast T1 did not associate with outcomes in the multivariable model. ECV provided added prognostic value to models with native T1, e.g., in multivariable models IDI=0.0037 (95%CI 0.0009-0.0071), p= 0.02; NRI= 0.151 (95%CI 0.022-0.292), p=0.04. Conclusions: Analogous to histologic previously published validation data, ECV myocardial fibrosis measures exhibited more robust associations with outcomes than other surrogate CMR MF measures. Superior risk stratification by ECV supports claims that ECV optimally measures MF in noninfarcted myocardium.
| Original language | English |
|---|---|
| Journal | JACC: Cardiovascular Imaging |
| Early online date | 15 May 2019 |
| DOIs | |
| Publication status | E-pub ahead of print - 15 May 2019 |
