Please use this identifier to cite or link to this item: https://ahro.austin.org.au/austinjspui/handle/1/16473
Title: Multidetector (64+) computed tomography angiography of the lower limb in symptomatic peripheral arterial disease: assessment of image quality and accuracy in a tertiary care setting
Austin Authors: Lim, Jeremy C;Ranatunga, Dinesh;Owen, Andrew R;Spelman, Timothy D;Galea, Michael ;Chuen, Jason ;Lim, Ruth P 
Affiliation: Austin Health, Heidelberg, Victoria, Australia
Centre for Population Health, Burnet Institute, Melbourne, Victoria, Australia
Department of Surgery, The University of Melbourne, Melbourne, Victoria, Australia
Department of Radiology, The University of Melbourne, Melbourne, Victoria, Australia
Issue Date: 7-Oct-2016
Date: 2016-10-07
Publication information: Journal of Computer Assisted Tomography 2016; online first: 7 October
Abstract: The aim of this study was to evaluate image quality and accuracy of 64+ detector multidetector computed tomography angiography (MDCTA) for hemodynamically significant (≥50%) stenosis in patients with symptomatic peripheral arterial disease (PAD) using digital subtraction angiography as the reference standard. METHODS: This is a retrospective study of 29 patients with PAD (19 men, 10 women) who underwent lower limb MDCTA (64- or 80-detector) and digital subtraction angiography. Image quality and accuracy of MDCTA for hemodynamically significant stenosis were assessed in the infrarenal aorta and 15 lower extremity segments. RESULTS: Four hundred fifty-three segments were adequately visualized at both modalities. Multidetector CTA had 84.8% sensitivity, 87.7% specificity, and 86.3% accuracy for significant stenosis. Accuracy was decreased in the calf when compromising arterial wall calcifications were present versus absent (55.9% vs 82.4%, P < 0.0001). CONCLUSIONS: 64+ MDCTA is accurate in patients with symptomatic PAD. However, diagnostic accuracy in below-knee vessels remains relatively poorer. Alternative imaging modalities should be considered where below-knee disease is suspected.
URI: https://ahro.austin.org.au/austinjspui/handle/1/16473
DOI: 10.1097/RCT.0000000000000494
Journal: Journal of Computer Assisted Tomography
PubMed URL: https://pubmed.ncbi.nlm.nih.gov/27753721
Type: Journal Article
Appears in Collections:Journal articles

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