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Photon-counting CT myocardial extracellular volume: A non-invasive biomarker for fibrosis in patients with hypertrophic cardiomyopathy - 02/01/26

Doi : 10.1016/j.diii.2025.09.001 
Christos Gkizas a, , 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, b
a Department of Cardiovascular Imaging, Heart and Lung Institute, University Hospital of Lille, 59000, Lille, France 
b INSERM UMR 1011, Institute Pasteur of Lille, EGID (European Genomic Institute for Diabetes), FR3508; Univ Lille, 59000, Lille, France 
c Department of Cardiovascular Explorations & Physiology, Heart and Lung Institute, University Hospital of Lille, 59000, Lille, France 
d Siemens Healthineers, 33600, Bordeaux, France 
e Department of Cardiology, Heart and Lung Institute, University Hospital of Lille, 59000, Lille, France 

Corresponding author.

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.

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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.

Il testo completo di questo articolo è disponibile in 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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© 2025  The Author(s). Pubblicato da Elsevier Masson SAS. Tutti i diritti riservati.
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