Automated Quantitative Stress Perfusion Cardiac Magnetic Resonance in Pediatric Patients

Cian M. Scannell, Hadeer Hasaneen, Gerald Greil, Tarique Hussain, Reza Razavi, Jack Lee, Kuberan Pushparajah, Phuoc Duong, Amedeo Chiribiri

Research output: Contribution to journalArticlepeer-review

Abstract

Background: Myocardial ischemia occurs in pediatrics, as a result of both congenital and acquired heart diseases, and can lead to further adverse cardiac events if untreated. The aim of this work is to assess the feasibility of fully automated, high resolution, quantitative stress myocardial perfusion cardiac magnetic resonance (CMR) in a cohort of pediatric patients and to evaluate its agreement with the coronary anatomical status of the patients. Methods: Fourteen pediatric patients, with 16 scans, who underwent dual-bolus stress perfusion CMR were retrospectively analyzed. All patients also had anatomical coronary assessment with either CMR, CT, or X-ray angiography. The perfusion CMR images were automatically processed and quantified using an analysis pipeline previously developed in adults. Results: Automated perfusion quantification was successful in 15/16 cases. The coronary perfusion territories supplied by vessels affected by a medium/large aneurysm or stenosis (according to the AHA guidelines), induced by Kawasaki disease, an anomalous origin, or interarterial course had significantly reduced myocardial blood flow (MBF) (median (interquartile range), 1.26 (1.05, 1.67) ml/min/g) as compared to territories supplied by unaffected coronaries [2.57 (2.02, 2.69) ml/min/g, p < 0.001] and territories supplied by vessels with a small aneurysm [2.52 (2.45, 2.83) ml/min/g, p = 0.002]. Conclusion: Automatic CMR-derived MBF quantification is feasible in pediatric patients, and the technology could be potentially used for objective non-invasive assessment of ischemia in children with congenital and acquired heart diseases.

Original languageEnglish (US)
Article number699497
JournalFrontiers in Pediatrics
Volume9
DOIs
StatePublished - Sep 3 2021

Keywords

  • automated quantitative stress perfusion
  • cardiac magnetic resonance
  • deep learning
  • Kawasaki disease
  • pediatrics

ASJC Scopus subject areas

  • Pediatrics, Perinatology, and Child Health

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