Michael Lally Steigner MD, Abstract Co-Author: Nothing to Disclose

Frank John Rybicki MD, PhD, Abstract Co-Author: Research grant, Toshiba Corporation Technical Advisor, Toshiba Corporation Research grant, Bracco Group Technical Advisor, Bracco Group Advisory Board, Vital Images, Inc

Amanda Gray Whitmore BA, Abstract Co-Author: Nothing to Disclose

Bernice E Hoppel PhD, Abstract Co-Author: Employee, Toshiba Corporation

Richard T. Mather PhD, Presenter: Employee, Toshiba Corporation

Dimitris Mitsouras PhD, Abstract Co-Author: Nothing to Disclose

Kanako Kunishima Kumamaru MD, Abstract Co-Author: Nothing to Disclose

Lowering patient radiation is important to expand the clinical role of coronary CTA. AIDR is an iterative processing algorithm that adaptively identifies and preserves image structure in conjunction with local denoising. The final image is a weighted summation of data with and without this processing. The purpose of this study is to introduce this algorithm and apply it to clinical coronary CTA images.

Images from seven consecutive coronary CTA patients were processed with standard reconstruction versus AIDR, and the following objective data was obtained. Image noise was evaluated as the Hounsfield Unit (HU) standard deviation (SD) within regions-of-interest (ROI) in the lung, ascending aorta, subcutaneous fat, and muscle. Overall image noise improvement was measured via the mean ratio of AIDR noise to that of standard reconstruction. Improved contrast-to-noise ratio (CNR) between aorta and muscle was similarly compared as the ratio with and without AIDR. A one-tailed t-test was used to test the hypothesis that noise and CNR ratios were not different than 1 (i.e. no improvement). Subjective data was obtained from an expert reader who evaluated overall diagnostic quality on a 4-point scale in the three major arteries (LAD, LCx, RCA). The Wilcoxon signed-rank test was used to assess differences in image quality between AIDR and standard reconstruction.

Mean AIDR image noise was 2.06 ± 0.22 times lower than standard reconstruction (p < 0.0001), and was consistent across anatomy (aorta: 2.12 ± .12; muscle: 1.98 ± 0.30; fat: 2.0 ± .29; air: 2.13 ± .12). The contrast to noise ratio in AIDR images was 2.11 ± 0.12 times higher than corresponding images without AIDR (p < 0.0001). Diagnostic quality was significantly higher using AIDR (3.33 ± 0.83 vs 2.67 ± 0.48, p < 0.0001).

An adaptive iterative dose reduction image processing method enables up to 2-fold noise reduction and 2-fold CNR increase in clinical cardiac CT images. Subjectively, images have improved quality. Future work can trade these technical advantages for potential radiation dose reductions.

Iterative image processing algorithms will likely play an important role in clinical dose reduction, including applications for coronary CTA patients.

Steigner, M, Rybicki, F, Whitmore, A, Hoppel, B, Mather, R, Mitsouras, D, Kumamaru, K, Improved Image Quality in Coronary CTA Using an Adaptive Iterative Dose Reduction (AIDR) Algorithm.  Radiological Society of North America 2010 Scientific Assembly and Annual Meeting, November 28 - December 3, 2010 ,Chicago IL. http://archive.rsna.org/2010/9014549.html