OBJECTIVES: To evaluate the influence of exposure parameters and raw-data based iterative reconstruction (IR) on the performance of computer-aided detection (CAD) of pulmonary nodules on chest multidetector computed tomography (MDCT). MATERIAL AND METHODS: Seven porcine lung explants were inflated in a dedicated ex vivo phantom shell and prepared with n=162 artificial nodules of a clinically relevant volume and maximum diameter (46-1063mul, and 6.2-21.5mm). n=118 nodules were solid and n=44 part-solid. MDCT was performed with different combinations of 120 and 80kV with 120, 60, 30 and 12mA*s, and reconstructed with both filtered back projection (FBP) and IR. Subsequently, 16 datasets per lung were subjected to dedicated CAD software. The rate of true positive, false negative and false positive CAD marks was measured for each reconstruction. RESULTS: The rate of true positive findings ranged between 88.9-91.4% for FBP and 88.3-90.1% for IR (n.s.) with most exposure settings, but was significantly lower with the combination of 80kV and 12mA*s (80.9% and 81.5%, respectively, p〈0.05). False positive findings ranged between 2.3 - 8.1 annotations per lung. For nodule volumes 〈200mul the rate of true positives was significantly lower than for 〉300mul (p〈0.05). Similarly, it was significantly lower for diameters 〈12mm compared to 〉/=12mm (p〈0.05). The rate of true positives for solid and part-solid nodules was similar. CONCLUSIONS: Nodule CAD on chest MDCT is robust over a wide range of exposure settings. Noise reduction by IR is not detrimental for CAD, and may be used to improve image quality in the setting of low-dose MDCT for lung cancer screening.
Type of Publication:
Journal article published