Evaluation of various image reconstruction parameters in lower extremity stents using multidetector-row CT angiography: initial findings View Full Text


Ontology type: schema:ScholarlyArticle     


Article Info

DATE

2006-05-30

AUTHORS

Martin Heuschmid, Benjamin Wiesinger, Gunnar Tepe, Oliver Luz, Andreas F. Kopp, Claus D. Claussen, Stephan H. Duda

ABSTRACT

Image quality, visible lumen and patency of lower limb stents was assessed by multidetector-row computed tomography (MDCT) angiography using various reconstruction parameters and the results compared with conventional angiography. Fourteen patients (25 stents) were evaluated. From MDCT datasets, axial and coronal oblique reformations were reconstructed using differing reconstruction parameters (slice thickness, kernel, views). Artifacts and image quality were assessed using a five-degree scale (1=excellent, 5=poor). Visible stent diameter was measured. Stenosis severity was compared with calibrated catheter angiography. The image quality of medium and sharp image kernels were good/fair (1.9–2.4), while smooth kernel provided only acceptable/poor image quality (3.9–4.4). Coronal oblique images were rated superior to assess in-stent lumen rather than axial. Using medium and sharp kernels, the visible stent lumen was significantly greater than using smooth kernel (P<0.001). thirteen out of fourteen patients (24/25 stents) were correctly classified as patent. In one patient, in-stent stenosis (≥50%) was falsely diagnosed using CT angiography (CTA) with smooth kernel and was, therefore, rated as false positive. Coronal oblique views, as well as medium and sharp kernels, have shown the best results regarding image quality to assess stent patency in the lower limb. Therefore, MDCT could be a valuable non-invasive modality for stent imaging in the peripheral vasculature. More... »

PAGES

265-271

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/s00330-006-0315-1

DOI

http://dx.doi.org/10.1007/s00330-006-0315-1

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1001420029

PUBMED

https://www.ncbi.nlm.nih.gov/pubmed/16733677


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