Evaluation of ultralow‐dose computed tomography on detection of pulmonary nodules in overweight or obese adult patients

Abstract

Purpose To evaluate the accuracy of pulmonary nodule (PN) detection in overweight or obese adult patients using ultralow‐dose computed tomography (ULDCT) with tin filtration at 100 kV and advanced model‐based iterative reconstruction (ADMIRE). Methods Eighty‐one patients with body mass indices of ≥25 kg/m2 were enrolled. All patients underwent low‐dose chest CT (LDCT), followed by ULDCT. Two radiologists experienced in LDCT established the standard of reference (SOR) for PNs. The number, type, size, and location of PNs were identified in the SOR. Effective dose, objective image quality (IQ), and subjective IQ based on two radiologists’ scores were compared between ULDCT and LDCT. The detection performances of radiologists based on ULDCT were calculated according to the nodule analyses. Logistic regression was used to test for independent predictors of PN detection sensitivity. Results Both the effective dose and objective IQ were lower for ULDCT than for LDCT (both p < 0.001). Both radiologists rated the subjective IQ of the overall IQ on ULDCT to be diagnostically sufficient. In total, 234 nodules (mean diameter, 3.4 ± 1.9 mm) were classified into 32 subsolid, 149 solid, and 53 calcified nodules according to the SOR. The overall sensitivity of ULDCT for nodule detection was 93.6%. Based on multivariate analyses, the nodule types (p = 0.015) and sizes (p = 0.013) were independent predictors of nodule detection. Conclusions Compared with LDCT, ULDCT with tin filtration at 100 kV and ADMIRE could significantly reduce the radiation dose in overweight or obese patients while maintaining good sensitivity for nodule detection.

Detection and size quantification of pulmonary nodules in ultralow-dose versus regular-dose CT: a comparative study in COPD patients

“…The readers were blinded from nodule information, and the RDCT and ULDCT scans were randomized and alternatively presented to reduce recall bias. More recently, Guo et al reported 93.6% sensitivity in nodule detection for ULDCT with ADMIRE level 3 in overweight or obese patients (BMI≥25 kg/m 2 ), at 85% reduced radiation dose, 29 which is similar compared to the sensitivity (95.5%) and radiation dose reduction (83%) in ULDCT in our study. This provides further evidence that ULDCT can be potentially used in a screening setting without being limited by screenee characteristics.…”

Prospective evaluation of deep learning image reconstruction for Lung-RADS and automatic nodule volumetry on ultralow-dose chest CT

“…Lastly, we included non-obese patients to consistently maintain the CT parameters and the CTDIvol of 0.1 mGy for a ULDCT scan as much as possible. Obese patients occupied 28% of the NLST screening population [ 31 ] and required a three to five times higher CT exposure than our protocol for a ULDCT scan [ 32 , 33 ]. Up-to-date studies evaluating a ULDCT with DLIR included non-obese patients [ 13 , 14 ] and future study is warranted for the applicability of ULDCT with DLIR for obese patients.…”