Mode
Text Size
Log in / Sign up

Review of Visual Standardized Quantification for LGE in CardiomyopathyA new tool improves accuracy and speed for spotting heart risks in patients with cardiomyopathy

AI-generated summary of the cited source, checked by automated accuracy review. How we work

Key Takeaway
Consider VISTAQ for more reproducible LGE quantification in cardiomyopathy, but note the evidence is from a retrospective study.

This narrative review summarizes a retrospective study comparing Visual Standardized Quantification of LGE (VISTAQ) with conventional techniques for assessing myocardial fibrosis. The study included 400 patients (100 with prior myocardial infarction, 250 with hypertrophic cardiomyopathy, and 50 with other non-ischemic heart diseases) across multicenter, multivendor settings.

Key findings indicate that VISTAQ demonstrated high intra- and inter-observer reproducibility, with ICC up to 0.98 and 0.97, respectively. Inter-observer differences were significantly lower, with a median absolute difference of 1.3%. Analysis time was substantially shorter with VISTAQ (median 105 vs. 375 seconds, p<0.0001). For prognostic performance, LGE threshold >10% predicted events with higher accuracy using VISTAQ (AUC 0.90; sensitivity 85%; specificity 94%) compared with mean+6SD (AUC 0.75; sensitivity 57%; specificity 93%), with 21 hard cardiac events occurring in the HCM population over a median 5-year follow-up.

The authors note limitations, including the retrospective design and lack of reported safety data. Practice relevance was not reported, and the findings should be interpreted as associative, not causal.

Researchers looked at how well a new imaging tool called VISTAQ works compared to standard methods for analyzing heart scans. This review examined data from 400 patients, including those with hypertrophic cardiomyopathy, prior heart attacks, and other non-ischemic heart diseases. The scans were reviewed at multiple centers using different equipment. The main goal was to see if the new tool could reliably find scar tissue that predicts future heart problems.

The new method showed very high agreement between different readers, with scores up to 0.98. It also reduced differences between observers, with the average difference dropping to just 1.3%. Most importantly, the analysis took much less time, averaging 105 seconds compared to 375 seconds with older methods. This speed difference was statistically significant.

When predicting heart events, the new tool found scar tissue in over 10% of cases with high accuracy. It correctly identified events with an AUC of 0.90, compared to 0.75 for older methods. The tool also had high sensitivity and specificity. No safety issues were reported because this was a review of imaging data, not a clinical trial. Readers should note this is a retrospective study, meaning it looks back at past data. While promising, more research is needed to confirm these results in broader settings.

What this means for you:
A new imaging tool may help doctors find heart risks faster and more accurately in patients with certain heart conditions.

Study Details

Sample sizen = 400
EvidenceLevel 5
PublishedApr 2026
View Original Abstract ↓
Background: Late gadolinium enhancement (LGE) quantification by cardiovascular magnetic resonance is central to risk stratification in hypertrophic cardiomyopathy (HCM), yet conventional techniques require contour tracing and region-of-interest (ROI) placement, which may reduce reproducibility and increase analysis time. We developed a novel visual standardized approach, the Visual Standardized Quantification of LGE (VISTAQ), that does not require myocardial contouring, arbitrary ROI positioning, or dedicated post-processing software. Methods: In this multicenter, multivendor retrospective study, LGE images from 400 patients (100 prior myocardial infarction, 250 HCM, 50 other non-ischemic heart diseases) were analyzed. VISTAQ subdivides each myocardial segment into transmural mini-segments and classifies LGE visually using predefined criteria, expressing global LGE burden as the percentage of positive mini-segments. Reproducibility was assessed in 250 patients across different observer expertise levels using intraclass correlation coefficients (ICC) and Bland?Altman analysis. In 100 HCM patients, VISTAQ was compared with conventional methods (mean+2SD, +5SD, +6SD, FWHM, visual thresholding). Prognostic performance was evaluated in 250 HCM patients over a median 5-year follow-up. Results: VISTAQ demonstrated excellent intra- and inter-observer reproducibility (ICC up to 0.98 and 0.97, respectively), consistent across disease subtypes. Compared with conventional techniques, VISTAQ showed similar ICC to FWHM but significantly lower net and absolute inter-observer differences (median absolute difference 1.3%). Mean+2SD markedly overestimated LGE, whereas mean+6SD slightly underestimated LGE compared with VISTAQ, mean+5SD, FWHM, and visual thresholding. Analysis time was substantially shorter with VISTAQ (median 105 vs. 375 seconds, p<0.0001). During follow-up, 21 hard cardiac events occurred in HCM population. An LGE threshold >10% predicted events with higher accuracy using VISTAQ (AUC 0.90; sensitivity 85%; specificity 94%) compared with mean+6SD (AUC 0.75; sensitivity 57%; specificity 93%). Conclusions: VISTAQ provides highly reproducible, time-efficient LGE quantification without dedicated software and demonstrates non-inferior prognostic discrimination in HCM compared with conventional threshold-based techniques.
Free Newsletter

Clinical research that matters. Delivered to your inbox.

Join thousands of clinicians and researchers. No spam, unsubscribe anytime.