Correlation between quantification of myocardial area at risk and ischemic burden at cardiac computed tomography

Driest, F Y van; Bijns, C. M.; Geest, Rob J. van der; Broersen, Alexander; Dijkstra, Jouke; Jukema, J. Wouter; Scholte, Arthur J.

doi:10.1016/j.ejro.2022.100417

Cited by 3 publications

(4 citation statements)

References 30 publications

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“…Furthermore, Voronoi's CT-derived myocardial mass is highly reproducible and correlates with the ischemic burden. 16 In the present study, resting and hyperemic pressure ratios after PCI were equally affected by the myocardial mass subtended by the vessel.…”

Section: Discussionsupporting

confidence: 47%

“…The specific territory Voronoi's algorithm has been validated in the swine model and showed excellent accuracy in measuring myocardial mass at risk. Furthermore, Voronoi's CT‐derived myocardial mass is highly reproducible and correlates with the ischemic burden 16 …”

Section: Discussionmentioning

confidence: 99%

“…Vessel‐specific myocardial mass was quantified from the CCTA images using Voronoi's algorithm with dedicated software (3D Synapse 3D; Fujifilm Healthcare Solutions; Holdings America Corporation) 9 . Briefly, in Voronoi's algorithm voxels in the left ventricle (LV) myocardium are partitioned into perfusion volumes according to their distance to the closest supplying coronary artery and then linked to the nearest voxel on the adjacent coronary artery 10,15,16 . Subsequently, the algorithm automatically calculates the territory by aggregating all myocardial voxels associated with the voxels of the coronary artery that are distal to the seed point.…”

Section: Methodsmentioning

confidence: 99%

“…and then linked to the nearest voxel on the adjacent coronary artery. 10,15,16 Subsequently, the algorithm automatically calculates the territory by aggregating all myocardial voxels associated with the voxels of the coronary artery that are distal to the seed point.…”

Section: Myocardial Mass Quantificationmentioning

confidence: 99%

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Relationship between coronary volume, myocardial mass, and post‐PCI fractional flow reserve

Mileva

Ohashi

Paolisso

et al. 2023

Cathet Cardio Intervent

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Background Fractional flow reserve (FFR) measured after percutaneous coronary intervention (PCI) carries prognostic information. Yet, myocardial mass subtended by a stenosis influences FFR. We hypothesized that a smaller coronary lumen volume and a large myocardial mass might be associated with lower post‐PCI FFR. Aim We sought to assess the relationship between vessel volume, myocardial mass, and post‐PCI FFR. Methods This was a subanalysis with an international prospective study of patients with significant lesions (FFR ≤ 0.80) undergoing PCI. Territory‐specific myocardial mass was calculated from coronary computed tomography angiography (CCTA) using the Voronoi's algorithm. Vessel volume was extracted from quantitative CCTA analysis. Resting full‐cycle ratio (RFR) and FFR were measured before and after PCI. We assessed the association between coronary lumen volume (V) and its related myocardial mass (M), and the percent of total myocardial mass (%M) with post‐PCI FFR. Results We studied 120 patients (123 vessels: 94 left anterior descending arteries, 13 left Circumflex arteries, 16 right coronary arteries). Mean vessel‐specific mass was 61 ± 23.1 g (%M 39.6 ± 11.7%). The mean post‐PCI FFR was 0.88 ± 0.06 FFR units. Post‐PCI FFR values were lower in vessels subtending higher mass (0.87 ± 0.05 vs. 0.89 ± 0.07, p = 0.047), and with lower V/M ratio (0.87 ± 0.06 vs. 0.89 ± 0.07, p = 0.02). V/M ratio correlated significantly with post‐PCI RFR and FFR (RFR r = 0.37, 95% CI: 0.21−0.52, p < 0.001 and FFR r = 0.41, 95% CI: 0.26−0.55, p < 0.001). Conclusion Post‐PCI RFR and FFR are associated with the subtended myocardial mass and the coronary volume to mass ratio. Vessels with higher mass and lower V/M ratio have lower post‐PCI RFR and FFR.

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Section: Discussionsupporting

confidence: 47%

Section: Discussionmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Section: Myocardial Mass Quantificationmentioning

confidence: 99%

See 2 more Smart Citations

Relationship between coronary volume, myocardial mass, and post‐PCI fractional flow reserve

Mileva

Ohashi

Paolisso

et al. 2023

Cathet Cardio Intervent

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Comparison of left ventricular mass and wall thickness between cardiac computed tomography angiography and cardiac magnetic resonance imaging using machine learning algorithms

van Driest,

van der Geest,

Omara

et al. 2024

European Heart Journal - Imaging Methods and Practice

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Introduction Cardiac magnetic resonance imaging (MRI) is the gold standard in the assessment of left ventricle (LV) mass and wall thickness. In recent years, cardiac computed tomography angiography (CCTA) has gained widespread usage as an imaging modality. Despite this, limited previous investigations have specifically addressed the potential of CCTA as an alternative modality for quantitative LV assessment. The aim of this study was to compare CCTA derived LV mass and wall thickness with cardiac MRI utilizing machine learning algorithms. Methods Fifty-seven participants who underwent both CCTA and cardiac MRI were identified. LV mass and wall thickness was calculated using LV contours which were automatically placed using in-house developed machine learning models. Pearson’s correlation coefficients were calculated along with Bland-Altman plots to assess the agreement between the LV mass and wall thickness per region on CCTA and cardiac MRI. Inter-observer correlations were tested using Pearson’s correlation coefficient. Results Average LV mass and wall thickness for CCTA and cardiac MRI were 127 grams,128 grams, 7mm and 8mm respectively. Bland-Altman plots demonstrated mean differences and corresponding 95% limits of agreement of -1.26 (25.06; -27.58) and -0.57 (1.78; -2.92), for LV mass and average LV wall thickness, respectively. Mean differences and corresponding 95% limits of agreement for wall thickness per region were -0.75 (1.34; -2.83), -0.58 (2.14; -3.30) and -0.29 (3.21; -3.79) for the basal, mid and apical regions, respectively. Interobserver correlations were excellent. Conclusion Quantitative assessment of LV mass and wall thickness on CCTA using machine learning algorithms seems feasible and shows good agreement with cardiac MRI.

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Relationship between Coronary Volume, Myocardial Mass and Post-PCI Fractional Flow Reserve

et al. 2022

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Correlation between quantification of myocardial area at risk and ischemic burden at cardiac computed tomography

Cited by 3 publications

References 30 publications

Relationship between coronary volume, myocardial mass, and post‐PCI fractional flow reserve

Relationship between coronary volume, myocardial mass, and post‐PCI fractional flow reserve

Comparison of left ventricular mass and wall thickness between cardiac computed tomography angiography and cardiac magnetic resonance imaging using machine learning algorithms

Relationship between Coronary Volume, Myocardial Mass and Post-PCI Fractional Flow Reserve

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