DIAGNOSTIC ACCURACY OF ULTRA-LOW-DOSE CT VS. STANDARD-DOSE CT FOR PULMONARY NODULE DETECTION: A SYSTEMATIC REVIEW AND META-ANALYSIS

Background: Standard dose computed tomography (CT) is a primary modality for detecting pulmonary nodules (PNs), but the health risk from cumulative radiation exposure has prompted the emergence of ultra-low-dose CT (ULDCT) as an alternative to reduce this dose, because its diagnostic accuracy remains variable, this systematic review and meta-analysis aims to synthesize the existing evidence to determine the diagnostic accuracy and effective radiation dose of ULDCT for pulmonary nodule detection. Methods: Following PRISMA guidelines, a systematic search was conducted in PubMed, Cochrane Library, and Ovid MEDLINE for original research published between 2015 and 2025 that evaluated the diagnostic accuracy of ULDCT for PN detection, for which a meta-analysis using random-effects models was performed to calculate the pooled sensitivity for nodule detection and the pooled mean effective radiation dose, with a subgroup analysis conducted to assess the impact of different reconstruction algorithms. Results: Forty-two studies comprising 15,792 patients were included, from which a meta-analysis of 11 studies demonstrated a pooled sensitivity of 91.9% (95% CI: 84.6%–97.1%) for PN detection with heterogeneity (I²=93.0%), and a pooled mean effective dose from 12 studies of 0.22 mSv (95% CI: 0.11–0.33 mSv), a level comparable to standard chest radiography, while subgroup analysis revealed a trend towards higher sensitivity with advanced reconstruction algorithms (96.7%) compared to standard iterative reconstruction (87.9%) that was not statistically significant (p=0.091), and a narrative synthesis confirmed ULDCT's accuracy for solid nodules but identified reduced sensitivity for subsolid, ground-glass, and small (