AI Article Synopsis

  • Obese patients pose challenges in SPECT myocardial perfusion imaging (MPI) due to increased soft tissue affecting results, prompting a study on whether automated quantitative analysis can better assess their cardiac risk based on obesity levels.
  • The study classified participants by body mass index (BMI) and found that higher total perfusion deficit (TPD) was linked to an increased risk of major adverse cardiac events (MACE), particularly in those with lower BMI categories and significant thresholds of TPD.
  • Automated quantitative methods showed superior prognostic accuracy compared to visual analysis, especially for patients with higher obesity levels, suggesting that combining different metrics can enhance risk stratification in this population.

Article Abstract

Background: Obese patients constitute a substantial proportion of patients referred for SPECT myocardial perfusion imaging (MPI), presenting a challenge of increased soft tissue attenuation. We investigated whether automated quantitative perfusion analysis can stratify risk among different obesity categories and whether two-view acquisition adds to prognostic assessment.

Methods: Participants were categorized according to body mass index (BMI). SPECT MPI was assessed visually and quantified automatically; combined total perfusion deficit (TPD) was evaluated. Kaplan-Meier and Cox proportional hazard analyses were used to assess major adverse cardiac event (MACE) risk. Prognostic accuracy for MACE was also compared.

Results: Patients were classified according to BMI: BMI < 30, 30 ≤ BMI < 35, BMI ≥ 35. In adjusted analysis, each category of increasing stress TPD was associated with increased MACE risk, except for 1% ≤ TPD < 5% and 5% ≤ TPD < 10% in patients with BMI ≥ 35. Compared to visual analysis, single-position stress TPD had higher prognostic accuracy in patients with BMI < 30 (AUC .652 vs .631, P < .001) and 30 ≤ BMI < 35 (AUC .660 vs .636, P = .027). Combined TPD had better discrimination than visual analysis in patients with BMI ≥ 35 (AUC .662 vs .615, P = .003).

Conclusions: Automated quantitative methods for SPECT MPI interpretation provide robust risk stratification in the obese population. Combined stress TPD provides additional prognostic accuracy in patients with more significant obesity.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8497048PMC
http://dx.doi.org/10.1007/s12350-020-02334-7DOI Listing

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