Purpose: Automatic tube current modulation (automA) represents a novel technique that alters CT tube current to maintain a constant pre-selected image quality. The purpose of this study was to compare image quality and diagnostic acceptability of CT examinations of abdomen and pelvis acquired with automA and fixed tube current technique.
Methods and Materials: 75 subjects (age = 19-84 years, mean age= 60 years, M:F= 42:33) underwent a follow-up CT examination of abdomen and pelvis with multidetector row CT scanner (GE Lightspeed 4.X, Waukesha, WI) with 16 channels, using automA technique (noise index= 10.5-11.5, mA range= 10-380, 140 kVp, 5mm slice thickness). These examinations were compared with previous CT scans performed with fixed tube current (200-300 mA, 140 kVp, 5mm slice thickness). Two subspecialty radiologist graded the studies for image noise, diagnostic acceptability and presence of any artifacts at superior aspect of liver, porta hepatis, right kidney hilum, iliac crest and acetabulum using a 5-point scale (1=unacceptable; 3=acceptable; 5=excellent). In addition, readers were asked to record the abnormality seen on each study. Statistical analysis of the data was performed using Wilcoxon signed rank test and kappa test of inter-observer agreement.
Results: 77 lesions were detected in the study cohort comprising of 21 liver masses, 14 with renal calculi, 12 adrenal masses, 12 uterine adnexal masses, 11 bowel masses and 7 gallstones. CT images acquired with automA technique did not miss any lesion. Although, scores for image noise and diagnostic acceptability were marginally lower for automA than fixed tube current at each level, these changes were not statistically significant. Compared to fixed tube current technique, both readers reported increased frequency and severity of beam hardening artifacts at the level of superior aspect of liver with automA.
Conclusion: Despite an increased frequency of beam hardening artifacts with automA technique compared to the fixed tube current technique, CT examinations of abdomen and chest acquired using automA provides images with equal image noise, diagnostic acceptability and lesion detection. (M.J. is an employee of GE Medical Systems.)
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