Yuka Otaki1, Serge D Van Kriekinge1, Chih-Chun Wei1, Paul Kavanagh1, Ananya Singh1, Tejas Parekh1, Marcelo Di Carli2, Jamshid Maddahi3, Arkadiusz Sitek4, Christopher Buckley5, Daniel S Berman1, Piotr J Slomka6. 1. Department of Medicine (Division of Artificial Intelligence)- Imaging- and Biomedical Sciences- Cedars-Sinai Medical Center, 8700 Beverly Boulevard, Ste. Metro 203, Los Angeles, CA, 90048, USA. 2. Cardiovascular Imaging Program, Departments of Medicine and Radiology and Division of Nuclear Medicine and Molecular Imaging, Department of Radiology, Brigham and Women's Hospital, Boston, MA, USA. 3. Division of Nuclear Medicine, Department of Molecular and Medical Pharmacology and Division of Cardiology, Department of Medicine, David Geffen School of Medicine, UCLA, Los Angeles, CA, USA. 4. Sano Centre for Computational Medicine, Cracow, Malopolskie, Poland. 5. GE Healthcare, Pharmaceutical Diagnostics, Buckinghamshire, UK. 6. Department of Medicine (Division of Artificial Intelligence)- Imaging- and Biomedical Sciences- Cedars-Sinai Medical Center, 8700 Beverly Boulevard, Ste. Metro 203, Los Angeles, CA, 90048, USA. Piotr.Slomka@cshs.org.
Abstract
PURPOSE: We sought to evaluate the diagnostic performance for coronary artery disease (CAD) of myocardial blood flow (MBF) quantification with 18F-flurpiridaz PET using motion correction (MC) and residual activity correction (RAC). METHODS: In total, 231 patients undergoing same-day pharmacologic rest and stress 18F-flurpiridaz PET from Phase III Flurpiridaz trial (NCT01347710) were studied. Frame-by-frame MC was performed and RAC was accomplished by subtracting the rest residual counts from the dynamic stress polar maps. MBF and myocardial flow reserve (MFR) were derived with a two-compartment early kinetic model for the entire left ventricle (global), each coronary territory, and 17-segment. Global and minimal values of three territorial (minimal vessel) and segmental estimation (minimal segment) of stress MBF and MFR were evaluated in the prediction of CAD. MBF and MFR were evaluated with and without MC and RAC (1: no MC/no RAC, 2: no MC/RAC, 3: MC/RAC). RESULTS: The area-under the receiver operating characteristics curve (AUC [95% confidence interval]) of stress MBF with MC/RAC was higher for minimal segment (0.89 [0.85-0.94]) than for minimal vessel (0.86 [0.81-0.92], p = 0.03) or global estimation (0.81 [0.75-0.87], p < 0.0001). The AUC of MFR with MC/RAC was higher for minimal segment (0.87 [0.81-0.93]) than for minimal vessel (0.83 [0.76-0.90], p = 0.014) or global estimation (0.77 [0.69-0.84], p < 0.0001). The AUCs of minimal segment stress MBF and MFR with MC/RAC were higher compared to those with no MC/RAC (p < 0.001 for both) or no MC/no RAC (p < 0.0001 for both). CONCLUSIONS: Minimal segment MBF or MFR estimation with MC and RAC improves the diagnostic performance for obstructive CAD compared to global assessment.
PURPOSE: We sought to evaluate the diagnostic performance for coronary artery disease (CAD) of myocardial blood flow (MBF) quantification with 18F-flurpiridaz PET using motion correction (MC) and residual activity correction (RAC). METHODS: In total, 231 patients undergoing same-day pharmacologic rest and stress 18F-flurpiridaz PET from Phase III Flurpiridaz trial (NCT01347710) were studied. Frame-by-frame MC was performed and RAC was accomplished by subtracting the rest residual counts from the dynamic stress polar maps. MBF and myocardial flow reserve (MFR) were derived with a two-compartment early kinetic model for the entire left ventricle (global), each coronary territory, and 17-segment. Global and minimal values of three territorial (minimal vessel) and segmental estimation (minimal segment) of stress MBF and MFR were evaluated in the prediction of CAD. MBF and MFR were evaluated with and without MC and RAC (1: no MC/no RAC, 2: no MC/RAC, 3: MC/RAC). RESULTS: The area-under the receiver operating characteristics curve (AUC [95% confidence interval]) of stress MBF with MC/RAC was higher for minimal segment (0.89 [0.85-0.94]) than for minimal vessel (0.86 [0.81-0.92], p = 0.03) or global estimation (0.81 [0.75-0.87], p < 0.0001). The AUC of MFR with MC/RAC was higher for minimal segment (0.87 [0.81-0.93]) than for minimal vessel (0.83 [0.76-0.90], p = 0.014) or global estimation (0.77 [0.69-0.84], p < 0.0001). The AUCs of minimal segment stress MBF and MFR with MC/RAC were higher compared to those with no MC/RAC (p < 0.001 for both) or no MC/no RAC (p < 0.0001 for both). CONCLUSIONS: Minimal segment MBF or MFR estimation with MC and RAC improves the diagnostic performance for obstructive CAD compared to global assessment.
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