Influence of Body Mass Index on Radiation Exposure Across Imaging Modalities in the Evaluation of Chest Pain

Abstract

Background Essential to a patient‐centered approach to imaging individuals with chest pain is knowledge of differences in radiation effective dose across imaging modalities. Body mass index (BMI) is an important and underappreciated predictor of effective dose. This study evaluated the impact of BMI on estimated radiation exposure across imaging modalities. Methods and Results This was a retrospective analysis of patients with concern for cardiac ischemia undergoing positron emission tomography (PET)/computed tomography (CT), cadmium zinc telluride single‐photon emission CT (SPECT) myocardial perfusion imaging, or coronary CT angiography (CCTA) using state‐of‐the‐art imaging modalities and optimal radiation‐sparing protocols. Radiation exposure was calculated across BMI categories based on established cardiac imaging–specific conversion factors. Among 9046 patients (mean±SD age, 64.3±13.1 years; 55% men; mean±SD BMI, 30.6±6.9 kg/m 2 ), 4787 were imaged with PET/CT, 3092 were imaged with SPECT/CT, and 1167 were imaged with CCTA. Median (interquartile range) radiation effective doses were 4.4 (3.9–4.9) mSv for PET/CT, 4.9 (4.0–6.3) mSv for SPECT/CT, and 6.9 (4.0–11.2) mSv for CCTA. Patients at a BMI <20 kg/m 2 had similar radiation effective dose with all 3 imaging modalities, whereas those with BMI ≥20 kg/m 2 had the lowest effective dose with PET/CT. Radiation effective dose and variability increased dramatically with CCTA as BMI increased, and was 10 times higher in patients with BMI >45 kg/m 2 compared with <20 kg/m 2 (median, 26.9 versus 2.6 mSv). After multivariable adjustment, PET/CT offered the lowest effective dose, followed by SPECT/CT, and then CCTA ( P <0.001). Conclusions Although median radiation exposure is modest across state‐of‐the‐art PET/CT, SPECT/CT, and CCTA systems using optimal radiation‐sparing protocols, there are significant variations across modalities based on BMI. These data are important for making patient‐centered decisions for ischemic testing.