Key result
Elevated CT-ECV is linked to higher MACE risk in non-ischemic heart failure.
Why the study?
Does CT-ECV using spectral detector computed tomography correlate with CMR-ECV and predict MACE in patients with non-ischemic heart failure?
Observational (n=162)
Does CT-ECV using spectral detector computed tomography correlate with CMR-ECV and predict MACE in patients with non-ischemic heart failure?
CT-ECV derived from spectral detector computed tomography is a feasible alternative to CMR-ECV and can effectively risk-stratify patients with non-ischemic heart failure.
PURPOSE: To validate the feasibility of using late iodine enhancement (LIE)-derived ECV on iodine density images using spectral detector computed tomography (SDCT; CT-ECV) and to assess the potential of CT-ECV for risk stratification among patients with non-ischemic heart failure (NIHF). MATERIALS AND METHODS: Forty-five subjects who underwent cardiac SDCT and CMR were included in the validation group to calculate and compare CT-ECV with CMR-ECV to validate CT-ECV feasibility. Another 117 subjects (82 patients with NIHF, 35 controls) who underwent SDCT were included in the experimental group to explore the potential of CT-ECV for risk stratification. ECV was measured via iodine density images and CMR T1 mapping in accordance with American Heart Association 16-segment models. RESULTS: In the validation group, there was no significant difference between CT-ECV and CMR-ECV (P = 0.293), with an insignificant bias. In the experimental group, CT-ECV in patients with NIHF was significantly higher than in controls (P < 0.05). In 82 patients with NIHF, CT-ECV in HFrEF ( HF with reduced ejection fraction: LVEF ≤ 40%) patients was statistically higher than that of HFmEF (HF with mildly reduced ejection fraction: LVEF 41-49%) and HFpEF (HF with preserved ejection fraction: LVEF ≥ 50%) patients (P < 0.05) and a significant difference among patients with NIHF with varied New York Heart Association classes (all P < 0.05); In addition, Kaplan-Meier survival curves and Log-rank test demonstrated that NIHF patients with CT-ECV ≥ 31.29% had higher probability of MACE than NIHF patients with CT-ECV < 31.29% (P < 0.001). CONCLUSION: LIE-derived CT-ECV on iodine density images using SDCT is a promising practical alternative to CMR-ECV, with the potential to assist with risk stratification among patients with NIHF.
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Deng et al. (2025) conducted an observational in non-ischemic heart failure (n=162). CT-ECV ≥ 31.29% vs. CT-ECV < 31.29% was evaluated on Major adverse cardiovascular events (MACE) (p=<0.001). In patients with non-ischemic heart failure, a CT-ECV ≥ 31.29% was associated with a significantly higher probability of major adverse cardiovascular events compared to a CT-ECV < 31.29% (P<0.001).
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