ArticleThe international journal of cardiovascular imaging2015
CT evaluation prior to transapical aortic valve replacement: semi-automatic versus manual image segmentation.
Article in The international journal of cardiovascular imaging, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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Who cites it
9 citing papers in PubMed.
- [Anythink for CT-based aorta root measurements before transcatheter aortic valve replacement: measurement consistency with 3mensio and impact on short-term prognosis].Nan fang yi ke da xue xue bao = Journal of Southern Medical University · 2022Article
- Fully automated measurement of aortic root anatomy using Philips HeartNavigator computed tomography software: fast, accurate, or both?European heart journal supplements : journal of the European Society of Cardiology · 2022Article
- Multi-Slice Computed Tomography Analysis in Patients Undergoing Transcatheter Aortic Valve Replacement - Impact of Workflows on Measurement of Virtual Aortic Annulus and Valve Size.Frontiers in cardiovascular medicine · 2022Article
- Potential impact of dynamic automated CT aortic annular measurements on outcomes for transcatheter aortic valve replacement sizing.The international journal of cardiovascular imaging · 2020Article
- Performance of Dynamic Automated CT Annular Measurements Compared to Standard Manual Measurements for Transcatheter Aortic Valve Replacement Sizing.Radiology. Cardiothoracic imaging · 2019Article
- Semi-automatic CT-angiography based evaluation of the aortic annulus in patients prior to TAVR: interchangeability with manual measurements.The international journal of cardiovascular imaging · 2018Article
- Inter- and intra-observer repeatability of aortic annulus measurements on screening CT for transcatheter aortic valve replacement (TAVR): Implications for appropriate device sizing.European journal of radiology · 2018Article
- Cardiovascular imaging 2015 in the International Journal of Cardiovascular Imaging.The international journal of cardiovascular imaging · 2016Review
- Vascular Imaging Before Transcatheter Aortic Valve Replacement (TAVR): Why and How?Current cardiology reports · 2016Review
Corrections and comments
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Authors and funding
11 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
To compare the performance of semi-automatic versus manual segmentation for ECG-triggered cardiovascular computed tomography (CT) examinations prior to transcatheter aortic valve replacement (TAVR), with focus on the speed and precision of experienced versus inexperienced observers. The preoperative ECG-triggered CT data of 30 consecutive patients who were scheduled for TAVR were included. All datasets were separately evaluated by two radiologists with 1 and 5 years of experience (novice and expert, respectively) in cardiovascular CT using an evaluation software program with or without a semi-automatic TAVR workflow. The time expended for data loading and all segmentation steps required for the implantation planning were assessed. Inter-software as well as inter-observer reliability analysis was performed. The CT datasets were successfully evaluated, with mean duration between 520.4 ± 117.6 s and 693.2 ± 159.5 s. The three most time-consuming steps were the 3D volume rendering, the measurement of aorta diameter and the sizing of the aortic annulus. Using semi-automatic segmentation, a novice could evaluate CT data approximately 12.3% faster than with manual segmentation, and an expert could evaluate CT data approximately 10.3% faster [mean differences of 85.4 ± 83.8 s (p < 0.001) and 59.8 ± 101 s (p < 0.001), respectively]. The inter-software reliability for a novice was slightly lower than for an expert; however, the reliability for a novice and expert was excellent (ICC 0.92, 95% CI 0.75-0.97/ICC 0.96, 95% CI 0.91-0.98). Automatic aortic annulus detection failed in two patients (6.7%). The study revealed excellent inter-software and inter-observer reliability, with a mean ICC of 0.95. TAVR evaluation can be accomplished significantly faster with semi-automatic rather than with manual segmentation, with comparable exactness, showing a benefit for experienced and inexperienced observers.
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