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Improved Registration of 3D CT Angiography with X-ray Fluoroscopy for Image Fusion During Transcatheter Aortic Valve Implantation
Published on: June 3, 2018
Automatic detection of aorto-femoral vessel trajectory from whole-body computed tomography angiography data sets
Xinpei Gao1, Pieter H Kitslaar2,3, Ricardo P J Budde4
1Division of Image Processing, Department of Radiology, Leiden University Medical Center, 9600, 2300 RC, Leiden, The Netherlands.
Insights
A new automated method accurately extracts the aorto-femoral artery trajectory from CT angiography (CTA) scans. This technique supports pre-procedural planning for trans-catheter aortic valve replacement (TAVR).
Area of Science:
- Medical Imaging
- Cardiovascular Interventions
- Computational Anatomy
Background:
- Accurate segmentation of the aorto-femoral artery is crucial for planning trans-catheter aortic valve replacement (TAVR).
- Current methods often require manual or semi-automated segmentation, which can be time-consuming and subject to inter-observer variability.
- Developing an automated approach can streamline the workflow and improve consistency in pre-procedural assessments.
Purpose of the Study:
- To develop and validate a fully automated technique for extracting the entire arterial access route from the femoral artery to the aortic root using computed tomography angiography (CTA) data.
- To compare the accuracy and reliability of the automated method against semi-automated results from experienced observers.
Main Methods:
- An automatic vessel tracking algorithm was employed to identify the centerline connecting femoral access points to the aortic root.
- A deformable 3D-model fitting method was utilized to delineate the lumen boundary of the vascular trajectory.
- The framework was validated on whole-body CTA datasets from 36 patients, comparing automated segmentations with those from two observers.
Main Results:
- The automated method achieved high Dice similarity indexes (0.950-0.982) compared to observers, demonstrating strong agreement.
- Inter-observer variability was comparable to the agreement between the automated method and observers.
- The automated method showed a slight, statistically significant overestimation of minimal luminal diameter (MLD) in the ilio-femoral artery and aorta compared to manual measurements.
Conclusions:
- The proposed fully automated segmentation approach provides reliable measurements of the aorto-femoral arterial access route.
- This technique has the potential to significantly support and enhance the image-guided work-up for TAVR procedures.
- This represents the first fully automatic segmentation method for the entire aorto-femoral vessel trajectory in CTA images.
Abstract:
Extraction of the aorto-femoral vessel trajectory is important to utilize computed tomography angiography (CTA) in an integrated workflow of the image-guided work-up prior to trans-catheter aortic valve replacement (TAVR). The aim of this study was to develop a new, fully-automated technique for the extraction of the entire arterial access route from the femoral artery to the aortic root. An automatic vessel tracking algorithm was first used to find the centerline that connected the femoral accessing points and the aortic root. Subsequently, a deformable 3D-model fitting method was used to delineate the lumen boundary of the vascular trajectory in the whole-body CTA dataset. A validation was carried out by comparing the automatically obtained results with semi-automatically obtained results from two experienced observers. The whole framework was validated on whole body CTA datasets of 36 patients. The average Dice similarity indexes between the segmentations of the automatic method and observer 1 for the left ilio-femoral artery, the right ilio-femoral artery and the aorta were 0.977 ± 0.030, 0.980 ± 0.019, 0.982 ± 0.016; the average Dice similarity indexes between the segmentations of the automatic method and observer 2 were 0.950 ± 0.040, 0.954 ± 0.031 and 0.965 ± 0.019, respectively. The inter-observer variability resulted in a Dice similarity index of 0.954 ± 0.038, 0.952 ± 0.031 and 0.969 ± 0.018 for the left ilio-femoral artery, the right ilio-femoral artery and the aorta. The average minimal luminal diameters (MLDs) of the ilio-femoral artery were 6.03 ± 1.48, 5.70 ± 1.43 and 5.52 ± 1.32 mm for the automatic method, observer 1 and observer 2 respectively. The MLDs of the aorta were 13.43 ± 2.54, 12.40 ± 2.93 and 12.08 ± 2.40 mm for the automatic method, observer 1 and observer 2 respectively. The automatic measurement overestimated the MLD slightly in the ilio-femoral artery at the average by 0.323 mm (SD = 0.49 mm, p < 0.001) compared to observer 1 and by 0.51 mm (SD = 0.71 mm, p < 0.001) compared to observer 2. The proposed segmentation approach can automatically provide reliable measurements of the entire arterial accessing route that can be used to support TAVR procedures. To the best of our knowledges, this approach is the first fully automatic segmentation method of the whole aorto-femoral vessel trajectory in CTA images.
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