Department of Imaging, Medicine, and Biomedical Sciences, Cedars-Sinai Medical Center, 8700 Beverly Boulevard, Ste. A047N, Los Angeles, CA, 90048, USA.
Department of Cardiac Sciences, University of Calgary, Calgary, AB, Canada.
J Nucl Cardiol. 2022 Apr;29(2):727-736. doi: 10.1007/s12350-020-02334-7. Epub 2020 Sep 14.
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.
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.
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).
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.
肥胖患者在接受单光子发射计算机断层扫描(SPECT)心肌灌注成像(MPI)检查的患者中占很大比例,这给软组织衰减增加带来了挑战。我们研究了自动定量灌注分析是否可以对不同肥胖类别进行分层风险评估,以及两视图采集是否可以增加预后评估。
根据体重指数(BMI)对参与者进行分类。评估 SPECT MPI 视觉和自动定量;评估联合总灌注缺损(TPD)。使用 Kaplan-Meier 和 Cox 比例风险分析评估主要不良心脏事件(MACE)风险。还比较了 MACE 的预测准确性。
根据 BMI 将患者分类:BMI<30、30≤BMI<35、BMI≥35。在调整分析中,除 BMI≥35 的患者中 1%≤TPD<5%和 5%≤TPD<10%外,每个递增应激 TPD 类别与增加的 MACE 风险相关。与视觉分析相比,在 BMI<30(AUC.652 与.631,P<.001)和 30≤BMI<35(AUC.660 与.636,P=.027)的患者中,单部位应激 TPD 的预后准确性更高。在 BMI≥35 的患者中,联合 TPD 的区分度优于视觉分析(AUC.662 与.615,P=.003)。
SPECT MPI 解释的自动定量方法为肥胖人群提供了可靠的风险分层。在肥胖程度更显著的患者中,联合应激 TPD 可提供额外的预后准确性。