Dataset Information

Electrocardiography scar quantification correlates with scar size of hypertrophic cardiomyopathy seen by multidetector computed tomography.

ABSTRACT:

Background

Hypertrophic cardiomyopathy (HCM), a genetically transmitted disease, is the most common genetic cardiovascular disease. Current strategies to stratify risk are expensive and concentrated in wealthy centers. Twelve-lead electrocardiography (ECG) is inexpensive, universally available, and can be readily used for Selvester QRS scoring, which estimates scar size. This study aimed to establish the relation between ECG scar quantification and myocardial fibrosis (extent of myocardial delayed enhancement) in multidetector computed tomography (MDCT).

Hypothesis

There is a significant association between ECG scar quantification and the extent of myocardial delayed enhancement in MDCT.

Methods

Seventy-five patients with HCM underwent a routine clinical evaluation and echocardiography, 12-lead ECG, and MDCT study. Patients with and without an implantable cardioverter-defibrillator were included.

Results

The estimated Selvester QRS score of myocardial fibrosis was correlated significantly (R = 0.70; P < 0.01) with the quantified MDCT fibrosis. Compared with MDCT, the QRS score had 84.8% sensitivity and 88.8% specificity. Myocardial fibrosis was present in 88% of these patients with HCM (fibrotic mass, 9.87 ±10.8 g) comprising 5.66% ±6.16% of the total myocardial mass seen on the MDCT images. The Selvester QRS score reliably predicted the fibrotic mass in 76% of patients, which estimated 8.44% ±7.39% of the total myocardial mass.

Conclusions

The Selvester QRS score provides reliable quantification of myocardial fibrosis and was well correlated with MDCT in patients with HCM.

SUBMITTER: Bignoto TC

PROVIDER: S-EPMC6489858 | biostudies-literature | 2018 Jun

REPOSITORIES: biostudies-literature

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Publications

Electrocardiography scar quantification correlates with scar size of hypertrophic cardiomyopathy seen by multidetector computed tomography.

Bignoto Tiago Costa TC Bignoto Tiago Costa TC Moreira Dalmo Antônio Ribeiro DAR Habib Ricardo Garbe RG de Barros Correia Edileide E Amarante Ricardo Carneiro RC Jatene Tannas T Nunes Mario Barbosa Guedes MBG Senra Tiago T Mastrocolla Luiz Eduardo LE

Clinical cardiology 20180612 6

<h4>Background</h4>Hypertrophic cardiomyopathy (HCM), a genetically transmitted disease, is the most common genetic cardiovascular disease. Current strategies to stratify risk are expensive and concentrated in wealthy centers. Twelve-lead electrocardiography (ECG) is inexpensive, universally available, and can be readily used for Selvester QRS scoring, which estimates scar size. This study aimed to establish the relation between ECG scar quantification and myocardial fibrosis (extent of myocardi ...[more]

PMID: 29671882

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Project description:BackgroundThe ability to distinguish dysfunctional but viable myocardium from nonviable tissue has important prognostic implications after myocardial infarction. The purpose of this study was to validate the accuracy of contrast-enhanced multidetector computed tomography (MDCT) for quantifying myocardial necrosis, microvascular obstruction, and chronic scar after occlusion/reperfusion myocardial infarction.Methods and resultsTen dogs and 7 pigs underwent balloon occlusion of the left anterior descending coronary artery (LAD) followed by reperfusion. Contrast-enhanced (Visipaque, 150 mL, 325 mg/mL) MDCT (0.5 mm x 32 slice) was performed before occlusion and 90 minutes (canine) or 8 weeks (porcine) after reperfusion. MDCT images were analyzed to define infarct size/extent and microvascular obstruction and compared with postmortem myocardial staining (triphenyltetrazolium chloride) and microsphere blood flow measurements. Acute and chronic infarcts by MDCT were characterized by hyperenhancement, whereas regions of microvascular obstruction were characterized by hypoenhancement. MDCT infarct volume compared well with triphenyltetrazolium chloride staining (acute infarcts 21.1+/-7.2% versus 20.4+/-7.4%, mean difference 0.7%; chronic infarcts 4.15+/-1.93% versus 4.92+/-2.06%, mean difference -0.76%) and accurately reflected morphology and the transmural extent of injury in all animals. Peak hyperenhancement of infarcted regions occurred approximately 5 minutes after contrast injection. MDCT-derived regions of microvascular obstruction were also identified accurately in acute studies and correlated with reduced flow regions as measured by microsphere blood flow.ConclusionsThe spatial extent of acute and healed myocardial infarction can be determined and quantified accurately with contrast-enhanced MDCT. This feature, combined with existing high-resolution MDCT coronary angiography, may have important implications for the comprehensive assessment of cardiovascular disease.

Project description:Background Cardiac MRI late gadolinium enhancement (LGE) scar volume is an important marker for outcome prediction in patients with hypertrophic cardiomyopathy (HCM); however, its clinical application is hindered by a lack of measurement standardization. Purpose To develop and evaluate a three-dimensional (3D) convolutional neural network (CNN)-based method for automated LGE scar quantification in patients with HCM. Materials and Methods We retrospectively identified LGE MRI data in a multicenter (n = 7) and multivendor (n = 3) HCM study obtained between November 2001 and November 2011. A deep 3D CNN based on U-Net architecture was used for LGE scar quantification. Independent CNN training and testing data sets were maintained with a 4:1 ratio. Stacks of short-axis MRI slices were split into overlapping substacks that were segmented and then merged into one volume. The 3D CNN per-site and per-vendor performances were evaluated with respect to manual scar quantification performed in a core laboratory setting using Dice similarity coefficient (DSC), Pearson correlation, and Bland-Altman analyses. Furthermore, the performance of 3D CNN was compared with that of two-dimensional (2D) CNN. Results This study included 1073 patients with HCM (733 men; mean age, 49 years ± 17 [standard deviation]). The 3D CNN-based quantification was fast (0.15 second per image) and demonstrated excellent correlation with manual scar volume quantification (r = 0.88, P < .001) and ratio of scar volume to total left ventricle myocardial volume (%LGE) (r = 0.91, P < .001). The 3D CNN-based quantification strongly correlated with manual quantification of scar volume (r = 0.82-0.99, P < .001) and %LGE (r = 0.90-0.97, P < .001) for all sites and vendors. The 3D CNN identified patients with a large scar burden (>15%) with 98% accuracy (202 of 207) (95% confidence interval [CI]: 95%, 99%). When compared with 3D CNN, 2D CNN underestimated scar volume (r = 0.85, P < .001) and %LGE (r = 0.83, P < .001). The DSC of 3D CNN segmentation was comparable among different vendors (P = .07) and higher than that of 2D CNN (DSC, 0.54 ± 0.26 vs 0.48 ± 0.29; P = .02). Conclusion In the hypertrophic cardiomyopathy population, a three-dimensional convolutional neural network enables fast and accurate quantification of myocardial scar volume, outperforms a two-dimensional convolutional neural network, and demonstrates comparable performance across different vendors. © RSNA, 2019 Online supplemental material is available for this article.

Dataset Information

Electrocardiography scar quantification correlates with scar size of hypertrophic cardiomyopathy seen by multidetector computed tomography.

Background

Hypothesis

Methods

Results

Conclusions

Publications

Electrocardiography scar quantification correlates with scar size of hypertrophic cardiomyopathy seen by multidetector computed tomography.

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