Photon-counting CT myocardial extracellular volume: A non-invasive biomarker for fibrosis in patients with hypertrophic cardiomyopathy - 13/09/25
, Benjamin Longere a, b, Saad Bechrouri a, Helene Ridon c, Aimee Rodriguez Musso a, Mehdi Haidar a, Cedric Croisille d, David Montaigne b, c, Pascal De Groote e, Francois Pontana a, bCet article a été publié dans un numéro de la revue, cliquez ici pour y accéder
Highlights |
• | Extracellular volume calculation using iodine maps from late enhancement cardiac dual-source photon-counting CT predicts fibrosis severity in hypertrophic cardiomyopathy. |
• | Excellent correlation is found between photon-counting detector CT and magnetic resonance imaging for the estimation of extracellular volume in patients with hypertrophic cardiomyopathy. |
• | Photon-counting detector CT provides a comprehensive evaluation of coronary artery disease and predicts outcomes in patients with hypertrophic cardiomyopathy. |
Abstract |
Purpose |
The purpose of this study was to evaluate the diagnostic performance of myocardial extracellular volume (ECV) quantification using dual-source photon-counting detector computed tomography (PCCT) compared to cardiac magnetic resonance imaging (MRI) for assessing the severity of myocardial fibrosis in patients with hypertrophic cardiomyopathy (HCM).
Materials and methods |
Patients with HCM due to sarcomere mutations underwent cardiac computed tomography angiography (CCTA) using a first-generation PCCT scanner, followed by comprehensive cardiac MRI. The CCTA protocol included a late iodine enhancement acquisition in spectral mode, 5 min after contrast media injection. ECV was calculated from the iodine ratio of the myocardium and blood pool on late iodine enhancement PCCT images. Cardiac MRI biomarkers included T1 mapping, ECV, and late gadolinium enhancement percentage (LGE). Diagnostic capabilities of PCCT were estimated using sensitivity, specificity, accuracy, interobserver agreement for myocardial fibrosis, area under the receiver operating characteristic curve (AUC) analyses for optimal thresholds, and correlations between tissue characteristics, functional capacity, and biomarkers.
Results |
Thirty patients were retrospectively included. There were 22 men and eight women with a mean age of 59 ± 13.8 (standard deviation [SD]). The mean dose length product of late enhancement PCCT scanning was 105 ± 45 (SD) mGy.cm. No significant differences were found between global PCCT-derived ECV (30.0 ± 4.8 [SD] %) and MRI-derived ECV (30.62 ± 4.2 [SD] %) ( P = 0.59). Linear regression revealed a strong segmental correlation between PCCT and MRI (basal, r = 0.89; mid-ventricular, r = 0.85; apical, r = 0.85; P < 0.001). An optimal PCCT-derived ECV threshold of 33.4 % allowed the diagnosis of LGE ≥ 15 % with 80 % sensitivity, 76 % specificity, and an AUC of 0.77, not significantly different from MRI-derived ECV (threshold 33.9 %; sensitivity, 80 %; specificity, 76 %, AUC, 0.80; P = 0.176). PCCT-derived ECV correlated with peak VO₂ ( r = -0.76) and NT-proBNP levels ( r = 0.59).
Conclusion |
PCCT-derived ECV shows promise for quantifying myocardial fibrosis in HCM, offering a valuable non-invasive alternative to cardiac MRI, especially for patients with contraindications or those requiring combined CCTA and myocardial assessment.
Le texte complet de cet article est disponible en PDF.Keywords : Computed tomography, Dual-source photon counting CT, Extracellular volume, Hypertrophic cardiomyopathy, Myocardial fibrosis
Abbreviations : AUC, CAD, CCTA, CI, ECV, HCM, ICC, LGE, LIE, LV, MRI, PCCT, ROC, SD, VO₂
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