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Objectives  The aim of this phantom study was to minimize the radiation dose by finding the best combination of low tube current and low voltage that would result in accurate volume measurements when compared to standard CT imaging without significantly decreasing the sensitivity of detecting lung nodules both with and without the assistance of CAD.    Methods  An anthropomorphic chest phantom containing artificial solid and ground glass nodules (GGNs, 5–12 mm) was examined with a 64-row multi-detector CT scanner with three tube currents of 100, 50 and 25 mAs in combination with three tube voltages of 120, 100 and 80 kVp. This resulted in eight different protocols that were then compared to standard CT sensitivity (100 mAs/120 kVp). For each protocol, at least 127 different nodules were scanned in 21–25 phantoms. The nodules were analyzed in two separate sessions by three independent, blinded radiologists and computer-aided detection (CAD) software.    Results  The mean sensitivity of the radiologists for identifying solid lung nodules on a standard CT was 89.7%±4.9%. The sensitivity was not significantly impaired when the tube and current voltage were lowered at the same time, except at the lowest exposure level of 25 mAs/80 kVp [80.6%±4.3% (p = 0.031)]. Compared to the standard CT, the sensitivity for detecting GGNs was significantly lower at all dose levels when the voltage was 80 kVp; this result was independent of the tube current. The CAD significantly increased the radiologists’ sensitivity for detecting solid nodules at all dose levels (5–11%). No significant volume measurement errors (VMEs) were documented for the radiologists or the CAD software at any dose level.    Conclusions  Our results suggest a CT protocol with 25 mAs and 100 kVp is optimal for detecting solid and ground glass nodules in lung cancer screening. The use of CAD software is highly recommended at all dose levels.

plos one

Optimal Dose Levels in Screening Chest CT for Unimpaired Detection and Volumetry of Lung Nodules, with and without Computer Assisted Detection at Minimal Patient Radiation