Prognostically safe stress-only single-photon emission computed tomography myocardial perfusion imaging guided by machine learning: report from REFINE SPECT

• Published in: European heart journal cardiovascular imaging 2021-05, Vol.22 (6), p.705-714
• Main Authors: Hu, Lien-Hsin, Miller, Robert J H, Sharir, Tali, Commandeur, Frederic, Rios, Richard, Einstein, Andrew J, Fish, Mathews B, Ruddy, Terrence D, Kaufmann, Philipp A, Sinusas, Albert J, Miller, Edward J, Bateman, Timothy M, Dorbala, Sharmila, Di Carli, Marcelo, Liang, Joanna X, Eisenberg, Evann, Dey, Damini, Berman, Daniel S, Slomka, Piotr J
• Format: Article
• Language: English
• ISSN: 2047-2404; 2047-2412
• DOI: 10.1093/ehjci/jeaa134

Abstract Aims Single-photon emission computed tomography (SPECT) myocardial perfusion imaging (MPI) stress-only protocols reduce radiation exposure and cost but require clinicians to make immediate decisions regarding rest scan cancellation. We developed a machine learning (ML) approach for automatic rest scan cancellation and evaluated its prognostic safety. Methods and results  In total, 20 414 patients from a solid-state SPECT MPI international multicentre registry with clinical data and follow-up for major adverse cardiac events (MACE) were used to train ML for MACE prediction as a continuous probability (ML score), using 10-fold repeated hold-out testing to separate test from training data. Three ML score thresholds (ML1, ML2, and ML3) were derived by matching the cancellation rates achieved by physician interpretation and two clinical selection rules. Annual MACE rates were compared in patients selected for rest scan cancellation between approaches. Patients selected for rest scan cancellation with ML had lower annualized MACE rates than those selected by physician interpretation or clinical selection rules (ML1 vs. physician interpretation: 1.4 ± 0.1% vs. 2.1 ± 0.1%; ML2 vs. clinical selection: 1.5 ± 0.1% vs. 2.0 ± 0.1%; ML3 vs. stringent clinical selection: 0.6 ± 0.1% vs. 1.7 ± 0.1%, all P