Ultra-low-dose MDCT of the chest: influence on automated lung nodule detection.
OBJECTIVE
To evaluate the relationship between CT dose and the performance of a computer-aided diagnosis (CAD) system, and to determine how best to minimize patient exposure to ionizing radiation while maintaining sufficient image quality for automated lung nodule detection, by the use of lung cancer screening CT.


METHODS
Twenty-five asymptomatic volunteers participated in the study. Each volunteer underwent a low-dose CT scan without contrast enhancement (multidetector CT with 16 detector rows, 1.25 mm section thickness, 120 kVp, beam pitch 1.35, 0.6 second rotation time, with 1.25 mm thickness reconstruction at 1.25 mm intervals) using four different amperages 32, 16, 8, and 4 mAs. All series were analyzed using a commercially available CAD system for automatic lung nodule detection and the results were reviewed by a consensus reading by two radiologists. The McNemar test and Kappa analysis were used to compare differences in terms of the abilities to detect pulmonary nodules.


RESULTS
A total of 78 non-calcified true nodules were visualized in the 25 study subjects. The sensitivities for nodule detection were as follows: 72% at 32 mAs, 64% at 16 mAs, 59% at 8 mAs, and 40% at 4 mAs. Although the overall nodule-detecting performance was best at 32 mAs, no significant difference in nodule detectability was observed between scans at 16 mAs or 8 mAs versus 32 mAs. However, scans performed at 4 mAs were significantly inferior to those performed at 32 mAs (p < 0.001).


CONCLUSIONS
Reducing the radiation dose (i.e. reducing the amperage) lowers lung nodule detectability by CAD. However, relatively low dose scans were found to be acceptable and to cause no significant reduction in nodule detectability versus usual low-dose CT.
Lee
Ji Young
JY
Department of Radiology and Center for Imaging Science, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea.
Chung
Myung Jin
MJ
Yi
Chin A
CA
Lee
Kyung Soo
KS
D000328:Adult; D000368:Aged; D015992:Body Mass Index; D017076:Computer-Aided Design; D005260:Female; D006801:Humans; D008168:Lung / Q000000981:diagnostic imaging; D008175:Lung Neoplasms / Q000000981:diagnostic imaging*; D008297:Male; D008875:Middle Aged; D011446:Prospective Studies; D011829:Radiation Dosage; D014057:Tomography, X-Ray Computed