The Prognostic Significance of Quantitative Myocardial Perfusion: An Artificial Intelligence-Based Approach Using Perfusion Mapping

Abstract

Background: Myocardial perfusion reflects the macro- and microvascular coronary circulation. Recent quantitation developments using cardiovascular magnetic resonance perfusion permit automated measurement clinically. We explored the prognostic significance of stress myocardial blood flow (MBF) and myocardial perfusion reserve (MPR, the ratio of stress to rest MBF).

Methods: A 2-center study of patients with both suspected and known coronary artery disease referred clinically for perfusion assessment. Image analysis was performed automatically using a novel artificial intelligence approach deriving global and regional stress and rest MBF and MPR. Cox proportional hazard models adjusting for comorbidities and cardiovascular magnetic resonance parameters sought associations of stress MBF and MPR with death and major adverse cardiovascular events (MACE), including myocardial infarction, stroke, heart failure hospitalization, late (>90 day) revascularization, and death.

Results: A total of 1049 patients were included with a median follow-up of 605 (interquartile range, 464-814) days. There were 42 (4.0%) deaths and 188 MACE in 174 (16.6%) patients. Stress MBF and MPR were independently associated with both death and MACE. For each 1 mL·g-1·min-1 decrease in stress MBF, the adjusted hazard ratios for death and MACE were 1.93 (95% CI, 1.08-3.48, P=0.028) and 2.14 (95% CI, 1.58-2.90, P<0.0001), respectively, even after adjusting for age and comorbidity. For each 1 U decrease in MPR, the adjusted hazard ratios for death and MACE were 2.45 (95% CI, 1.42-4.24, P=0.001) and 1.74 (95% CI, 1.36-2.22, P<0.0001), respectively. In patients without regional perfusion defects on clinical read and no known macrovascular coronary artery disease (n=783), MPR remained independently associated with death and MACE, with stress MBF remaining associated with MACE only.

Conclusions: In patients with known or suspected coronary artery disease, reduced MBF and MPR measured automatically inline using artificial intelligence quantification of cardiovascular magnetic resonance perfusion mapping provides a strong, independent predictor of adverse cardiovascular outcomes.

Keywords: cardiovascular magnetic resonance; cardiovascular outcomes; inline perfusion quantification; myocardial perfusion.

Figures

Figure 1.

Automatic segmentation of the stress perfusion maps performed by machine learning with no user input. Base, mid, and apical left ventricle short axis slices (left to right) for a 76-year-old man with dyslipidemia and no death or major adverse cardiovascular events (A) and a 64-year-old woman with hypertension and atrial fibrillation who died within 24 months of the scan (B). Mean stress myocardial blood flow was 2.25 mL·g-1·min-1 in (A) and 1.52 mL·g-1·min-1 in (B).

Figure 2.

Study flow chart. A total of 1049 patients were included in the final analysis. A total of 143 patients met the exclusion criteria, there were reconstruction errors in perfusion maps in 15 cases, and there were 45 cases of inadequate stress (no splenic switch off). A total of 104 patients were lost to follow-up. There were 188 events in total (major adverse cardiovascular events [MACE]) in 174 patients, including 42 deaths.

Figure 3.

Kaplan-Meier survival estimate curves for stress myocardial blood flow (MBF) and myocardial perfusion reserve (MPR). Stress MBF (A and B) and MPR (C and D). The red lines demonstrate the survival curves for the highest 50th percentile, and the blue lines demonstrate the lowest 50th percentile of patients. B and D, Magnified to highlight the separation of the curves. Rates of death are higher with impaired perfusion. Compared with patients in the highest 50th percentile, the patients in the lowest 50th percentile of MBF and MPR had higher rates of death (P=0.032 and P=0.01, respectively).

Figure 4.

Kaplan-Meier survival estimate curves for stress myocardial blood flow (MBF) and myocardial perfusion reserve (MPR). The Kaplan Meier survival estimate curves demonstrate major adverse cardiovascular events over time for stress MBF (A) and MPR (B). The red lines demonstrate the survival curves for the highest 50th percentile, and the blue lines demonstrate the lowest 50th percentile of patients. Compared with patients in the highest 50th percentile, the patients in the lowest 50th percentile of MBF and MPR had higher rates of death (P<0.001 for both).