CT pericoronary adipose tissue density predicts coronary allograft vasculopathy and adverse clinical outcomes after cardiac transplantation.

Coronary Allograft Vasculopathy Coronary Computed Tomography Angiography Heart Transplantation Pericoronary Adipose Tissue Density

Journal

European heart journal. Cardiovascular Imaging
ISSN: 2047-2412
Titre abrégé: Eur Heart J Cardiovasc Imaging
Pays: England
ID NLM: 101573788

Informations de publication

Date de publication:
17 Mar 2024
Historique:
received: 08 12 2023
accepted: 26 02 2024
medline: 17 3 2024
pubmed: 17 3 2024
entrez: 17 3 2024
Statut: aheadofprint

Résumé

To assess pericoronary adipose tissue (PCAT) density on Coronary Computed Tomography Angiography (CCTA) as a marker of inflammatory disease activity in coronary allograft vasculopathy (CAV). PCAT density, lesion volumes, and total vessel volume-to-myocardial mass ratio (V/M) were retrospectively measured in 126 CCTAs from 94 heart transplant patients (mean age 49 [SD 14.5] years, 40% female) who underwent imaging between 2010 to 2021; age and sex-matched controls; and patients with atherosclerosis. PCAT density was higher in transplant patients with CAV (n = 40; -73.0 HU [SD 9.3]) than without CAV (n = 86; -77.9 HU [SD 8.2]), and controls (n = 12; -86.2 HU [SD 5.4]), p < 0.01 for both. Unlike patients with atherosclerotic coronary artery disease (n = 32), CAV lesions were predominantly non-calcified, comprised of mostly fibrous or fibrofatty tissue. V/M was lower in patients with CAV than without (32.4 mm3/g [SD 9.7] vs. 41.4 mm3/g [SD 12.3], p < 0.0001). PCAT density and V/M improved the ability to predict CAV from AUC 0.75 to 0.85 when added to donor age and donor hypertension status (p < 0.0001). PCAT density above -66 HU was associated with a greater incidence of all-cause mortality (OR 18.0 [95%CI 3.25-99.6], p < 0.01) and the composite endpoint of death, CAV progression, acute rejection, and coronary revascularization (OR 7.47 [95%CI 1.8-31.6], p = 0.01) over 5.3 (SD 2.1) years. Heart transplant patients with CAV have higher PCAT density and lower V/M than those without. Increased PCAT density is associated with adverse clinical outcomes. These CCTA metrics could be useful for diagnosis and monitoring of CAV severity.

Identifiants

pubmed: 38493483
pii: 7630591
doi: 10.1093/ehjci/jeae069
pii:
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Informations de copyright

© The Author(s) 2024. Published by Oxford University Press on behalf of the European Society of Cardiology.

Auteurs

Christopher Wall (C)

Section of Cardiorespiratory Medicine, University of Cambridge, Cambridge, UK.

Jonathan Weir-McCall (J)

Department of Radiology, University of Cambridge, Cambridge, UK.
Department of Radiology, Royal Papworth Hospital, Cambridge, UK.

Katharine Tweed (K)

Department of Radiology, Royal Papworth Hospital, Cambridge, UK.

Stephen P Hoole (SP)

Department of Cardiology, Royal Papworth Hospital, Cambridge, UK.

Deepa Gopalan (D)

Department of Radiology, Cambridge University Hospitals NHS Trust, Cambridge, UK.
Department of Radiology, Imperial College Healthcare NHS Trust, London, UK.

Yuan Huang (Y)

Section of Cardiorespiratory Medicine, University of Cambridge, Cambridge, UK.

Andrej Corovic (A)

Section of Cardiorespiratory Medicine, University of Cambridge, Cambridge, UK.

Marta Peverelli (M)

Section of Cardiorespiratory Medicine, University of Cambridge, Cambridge, UK.

Damini Dey (D)

Departments of Biomedical Sciences and Medicine, Cedars-Sinai Medical Center, Biomedical Imaging Research Institute, Los Angeles, California.

Martin R Bennett (MR)

Section of Cardiorespiratory Medicine, University of Cambridge, Cambridge, UK.

James H F Rudd (JHF)

Section of Cardiorespiratory Medicine, University of Cambridge, Cambridge, UK.

Anna Kydd (A)

Transplant Unit, Royal Papworth Hospital, Cambridge, UK.

Sai Bhagra (S)

Transplant Unit, Royal Papworth Hospital, Cambridge, UK.

Jason M Tarkin (JM)

Section of Cardiorespiratory Medicine, University of Cambridge, Cambridge, UK.

Classifications MeSH