Impact of contrast injection and stent-graft implantation on reproducibility of volume measurements in semiautomated segmentation of abdominal aortic aneurysm on computed tomography
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To assess the impact of contrast injection and stent-graft implantation on feasibility, accuracy, and reproducibility of abdominal aortic aneurysm (AAA) volume and maximal diameter (D-max) measurements using segmentation software.
Materials and methods
CT images of 80 subjects presenting AAA were divided into four equal groups: with or without contrast enhancement, and with or without stent-graft implantation. Semiautomated software was used to segment the aortic wall, once by an expert and twice by three readers. Volume and D-max reproducibility was estimated by intraclass correlation coefficients (ICC), and accuracy was estimated between the expert and the readers by mean relative errors.
All segmentations were technically successful. The mean AAA volume was 167.0 ± 82.8 mL and the mean D-max 55.0 ± 10.6 mm. Inter- and intraobserver ICCs for volume and D-max measurements were greater than 0.99. Mean relative errors between readers varied between −1.8 ± 4.6 and 0.0 ± 3.6 mL. Mean relative errors in volume and D-max measurements between readers showed no significant difference between the four groups (P ≥ 0.2).
The feasibility, accuracy, and reproducibility of AAA volume and D-max measurements using segmentation software were not affected by the absence of contrast injection or the presence of stent-graft.
• AAA volumetry by semiautomated segmentation is accurate on CT following endovascular repair.
• AAA volumetry by semiautomated segmentation is accurate on unenhanced CT.
• Standardization of the segmentation technique maximizes the reproducibility of volume measurements.
KeywordsAortic aneurysm Computed tomography Contrast media Stents Image processing Computer-assisted
The scientific guarantor of this publication is Gilles Soulez MD MSc. This study was partly funded by Siemens Medical and Object Research Systems and Nicolas Piché is an employee of Object Research Systems. This study has received funding from a clinical research scholarship (to GS and AT) from Fonds de la recherche en santé du Québec (FRSQ), an operating grant from the Ministère du développement économique, de l’innovation et de l’exportation du Québec (MDEIE) (2008-PSVT3-12792) and an operating grant from the CIHR (CIHR/SME Research Program - Operating Grants, 200809). Gilles Soulez and Claude Kauffmann are co-authors of a research patent on the segmentation software reported in this study. Sandra Larrivée and Marie-Pierre Sylvestre (CRCHUM) kindly provided statistical advice for this manuscript. This study was approved by the institutional review board but since it was retrospective written informed consent was waived by the institutional review board. Methodology: retrospective, software validation study, performed at one institution.
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