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Editor's Choice - Fully Automatic Volume Segmentation Using Deep Learning Approaches to Assess the Thoracic Aorta,
Anna-Louise Pouncey1, Edmund Charles1, Colin Bicknell1
1Department of Vascular Surgery, Imperial College London, London, UK.
Insights
Fully automatic volume segmentation (FAVS) using AI accurately segments thoracic and visceral aortas, matching physician performance. This AI technology can improve workflows for complex aortic aneurysm treatment planning and monitoring.
Area of Science:
- Medical Imaging
- Artificial Intelligence
- Vascular Surgery
Background:
- Computed tomography angiography (CTA) is crucial for analyzing complex aortic aneurysms but is labor-intensive and variable.
- Current AI-driven segmentation is validated for infrarenal aorta but needs testing for thoracic and visceral segments.
Purpose of the Study:
- To assess the accuracy of fully automatic volume segmentation (FAVS) against physician-controlled manual segmentation (PCMS).
- To evaluate FAVS performance in the descending thoracic aorta, visceral abdominal aorta, and visceral vasculature.
Main Methods:
- Retrospective, multicenter observational cohort study of 50 pre-operative CTAs.
- Comparison of FAVS and PCMS using sensitivity, specificity, Dice similarity coefficient (DSC), and Jaccard index (JI).
- Analysis of visceral vessel identification and proximal visceral diameter measurements.
Main Results:
- FAVS showed comparable volumetric segmentation performance to PCMS (median DSC 0.93, JI 0.87).
- FAVS correctly identified 99.5% of visceral vessels with branchpoint coordinates within CTA spatial resolution limits.
- Diameter measurements by FAVS agreed well with PCMS and interphysician variability.
Conclusions:
- FAVS offers accurate and efficient segmentation of thoracic and visceral aortas, comparable to expert physicians.
- This AI technology has the potential to enhance clinical workflows for managing complex aortic aneurysms.
Objective:
Computed tomography angiography (CTA) imaging is essential to evaluate and analyse complex abdominal and thoraco-abdominal aortic aneurysms. However, CTA analyses are labour intensive, time consuming, and prone to interphysician variability. Fully automatic volume segmentation (FAVS) using artificial intelligence with deep learning has been validated for infrarenal aorta imaging but requires further testing for thoracic and visceral aorta segmentation. This study assessed FAVS accuracy against physician controlled manual segmentation (PCMS) in the descending thoracic aorta, visceral abdominal aorta, and visceral vasculature.
Methods:
This was a retrospective, multicentre, observational cohort study. Fifty pre-operative CTAs of patients with abdominal aortic aneurysm were randomly selected. Comparisons between FAVS and PCMS and assessment of inter- and intra-observer reliability of PCMS were performed. Volumetric segmentation performance was evaluated using sensitivity, specificity, Dice similarity coefficient (DSC), and Jaccard index (JI). Visceral vessel identification was compared by analysing branchpoint coordinates. Bland-Altman limits of agreement (BA-LoA) were calculated for proximal visceral diameters (excluding duplicate renals).
Results:
FAVS demonstrated performance comparable with PCMS for volumetric segmentation, with a median DSC of 0.93 (interquartile range [IQR] 0.91, 0.94), JI of 0.87 (IQR 0.84, 0.89), sensitivity of 0.99 (IQR 0.98, 0.99), and specificity of 1.00 (IQR 1.00, 1.00). These metrics are similar to interphysician comparisons: median DSC 0.93 (IQR 0.86, 0.93), JI 0.87 (IQR 0.76, 0.88), sensitivity 0.90 (IQR 0.86, 0.94), and specificity 1.00 (IQR 1.00, 1.00). FAVS correctly identified 99.5% (183/184) of visceral vessels. Branchpoint coordinates for FAVS and PCMS were within the limits of CTA spatial resolution (Δx -0.33 [IQR -1.70, 1.12], Δy 0.61 [IQR -1.25, 3.60], Δz 2.10 [IQR 0.37, 5.06] mm). BA-LoA for proximal visceral diameter measurements showed reasonable agreement: FAVS vs. PCMS mean difference -0.11 ± 5.23 mm compared with interphysician variability of 0.03 ± 5.27 mm.
Conclusion:
FAVS provides accurate, efficient segmentation of the thoracic and visceral aorta, delivering performance comparable to manual segmentation by expert physicians. This technology may enhance clinical workflows for monitoring and planning treatments for complex abdominal and thoraco-abdominal aortic aneurysms.
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