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Journal of Medical Imaging • Open Access

Evaluation of an iterative model–based reconstruction algorithm for low-tube-voltage (80 kVp) computed tomography angiography
Author(s): Peter B. Noël; Thomas Köhler; Alexander A. Fingerle; Kevin M. Brown; Stanislav Zabic; Daniela Münzel; Bernhard Haller; Thomas H. Baum; Martin Henninger; Reinhard Meier; Ernst J. Rummeny; Martin Dobritz

Paper Abstract

The objective of this study was to investigate the improvement in diagnostic quality of an iterative model–based reconstruction (IMBR) algorithm for low-tube-voltage (80-kVp) and low-tube-current in abdominal computed tomography angiography (CTA). A total of 11 patients were imaged on a 256-slice multidetector computed tomography for visualization of the aorta. For all patients, three different reconstructions from the low-tube-voltage data are generated: filtered backprojection (FBP), IMBR, and a mixture of both IMBR+FBP. To determine the diagnostic value of IMBR-based reconstructions, the image quality was assessed. With IMBR-based reconstructions, image noise could be significantly reduced, which was confirmed by a highly improved contrast-to-noise ratio. In the image quality assessment, radiologists were able to reliably detect more third-order and higher aortic branches in the IMBR reconstructions compared to FBP reconstructions. The effective dose level was, on average, 3.0 mSv for 80-kVp acquisitions. Low-tube-voltage CTAs significantly improve vascular contrast as presented by others; however, this effect in combination with IMBR enabled yet another substantial improvement of diagnostic quality. For IMBR, a significant improvement of image quality and a decreased radiation dose at low-tube-voltage can be reported.

Paper Details

Date Published: 9 October 2014
PDF: 7 pages
J. Med. Img. 1(3) 033501 doi: 10.1117/1.JMI.1.3.033501
Published in: Journal of Medical Imaging Volume 1, Issue 3
Show Author Affiliations
Peter B. Noël, Technische Univ. München (Germany)
Thomas Köhler, Philips Research (Germany)
Alexander A. Fingerle, Technische Univ. München (Germany)
Kevin M. Brown, Philips Healthcare (United States)
Stanislav Zabic, Philips Healthcare (United States)
Daniela Münzel, Technische Univ. München (Germany)
Bernhard Haller, Technische Univ. München (Germany)
Thomas H. Baum, Technische Univ. München (Germany)
Martin Henninger, Technische Univ. München (Germany)
Reinhard Meier, Technische Univ. München (Germany)
Ernst J. Rummeny, Technische Univ. München (Germany)
Martin Dobritz, Technische Univ. München (Germany)


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