Software reproducibility of myocardial blood flow and flow reserve quantification in ischemic heart disease: A 13N-ammonia PET study View Full Text


Ontology type: schema:ScholarlyArticle     


Article Info

DATE

2019-03-22

AUTHORS

Andrea G. Monroy-Gonzalez, Luis Eduardo Juarez-Orozco, Chunlei Han, Issi R. Vedder, David Vállez García, Ronald Borra, Piotr J. Slomka, Sergey V. Nesterov, Juhani Knuuti, Riemer H. J. A. Slart, Erick Alexanderson-Rosas

ABSTRACT

BACKGROUND: We explored agreement in the quantification of myocardial perfusion by cross-comparison of implemented software packages (SPs) in three distinguishable patient profile populations. METHODS: We studied 91 scans of patients divided into 3 subgroups based on their semi-quantitative perfusion findings: patients with normal perfusion, with reversible perfusion defects, and with fixed perfusion defects. Rest myocardial blood flow (MBF), stress MBF, and myocardial flow reserve (MFR) were obtained with QPET, SyngoMBF, and Carimas. Agreement between SPs was considered adequate when a pairwise standardized difference was found to be < 0.20 and its corresponding intraclass correlation coefficient was ≥ 0.75. RESULTS: In patients with normal perfusion, two out of three comparisons of global stress MBF quantifications were outside the limits of agreement. In ischemic patients, all comparisons of global stress MBF and MFR were outside the limits of established agreement. In patients with fixed perfusion defects, all SP comparisons of perfusion quantifications were within the limit of agreement. Regionally, agreement of these perfusion estimates was mostly found for the left anterior descending artery vascular territory. CONCLUSION: Reversible defects demonstrated the worst agreement in global stress MBF and MFR and discrepancies showed to be regional dependent. Reproducibility between SPs should not be assumed. More... »

PAGES

1-9

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/s12350-019-01620-3

DOI

http://dx.doi.org/10.1007/s12350-019-01620-3

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1112941830

PUBMED

https://www.ncbi.nlm.nih.gov/pubmed/30903608


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