Key result
Abnormal stress phase entropy linked to ~44% higher mortality risk beyond standard PET-MPI variables.
Why the study?
The independent prognostic value of phase variables over PET myocardial perfusion imaging variables including myocardial flow reserve has not been studied.
Does stress phase entropy assessment improve prediction of all-cause mortality over standard PET-MPI variables in patients undergoing Rb PET?
Cohort (n=3,963)
No
Does stress phase entropy assessment improve prediction of all-cause mortality over standard PET-MPI variables in patients undergoing Rb PET?
Hazard Ratio: 1.44 (95% CI 1.18–1.75)
p-value: p=<0.001
Stress phase entropy provides independent and incremental prognostic value for all-cause mortality beyond standard PET-MPI variables including myocardial flow reserve.
Phase variables may refine mortality risk prediction on Rb-PET; leaves open incremental value beyond MFR for clinical decisions.
PURPOSE: Phase analysis can assess left ventricular dyssynchrony. The independent prognostic value of phase variables over positron emission tomography myocardial perfusion imaging (PET-MPI) variables including myocardial flow reserve (MFR) has not been studied. The aim of this study was to explore the prognostic value of phase variables for predicting mortality over standard PET-MPI variables. METHODS: Rb PET study were enrolled. All PET-MPI variables including phase variables (phase entropy, phase bandwidth, and phase standard deviation) were automatically obtained by QPET software (Cedars-Sinai, Los Angeles, CA). Cox proportional hazard analyses were used to assess associations with all-cause mortality (ACM). RESULTS: In a total of 3963 patients (median age 71 years; 57% male), 923 patients (23%) died during a median follow-up of 5 years. Annualized mortality rates increased with stress phase entropy, with a 4.6-fold difference between the lowest and highest decile groups of entropy (2.6 vs. 12.0%/year). Abnormal stress phase entropy (optimal cutoff value, 43.8%) stratified ACM risk in patients with normal and impaired MFR (both p < 0.001). Among three phase variables, only stress phase entropy was significantly associated with ACM after the adjustment of standard clinical and PET-MPI variables including MFR and stress-rest change of phase variables, whether modeled as binary variables (adjusted hazard ratio, 1.44 for abnormal entropy [> 43.8%]; 95%CI, 1.18-1.75; p < 0.001) or continuous variables (adjusted hazard ratio, 1.05 per 5% increase; 95%CI, 1.01-1.10; p = 0.030). The addition of stress phase entropy to the standard PET-MPI variables significantly improved the discriminatory power for ACM prediction (p < 0.001), but the other phase variables did not (p > 0.1). CONCLUSION: Stress phase entropy is independently and incrementally associated with ACM beyond standard PET-MPI variables including MFR. Phase entropy can be obtained automatically and included in clinical reporting of PET-MPI studies to improve patient risk prediction.
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Kuronuma et al. (2023) conducted a cohort in Suspected or known coronary artery disease referred for PET-MPI (n=3,963). Abnormal stress phase entropy (> 43.8%) vs. Normal stress phase entropy (≤ 43.8%) was evaluated on All-cause mortality (adjusted HR 1.44, 95% CI 1.18-1.75, p=<0.001). Abnormal stress phase entropy (> 43.8%) was independently associated with an increased risk of all-cause mortality (adjusted HR 1.44) beyond standard PET-MPI variables including myocardial flow reserve.
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