ArticleJournal of medical imaging (Bellingham, Wash.)2023
Fully automated pipeline for measurement of the thoracic aorta using joint segmentation and localization neural network.
Article in Journal of medical imaging (Bellingham, Wash.), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
9 citing papers in PubMed.
- From Bits to Bedside: From Data to Knowledge in Vascular Surgery.Journal of clinical medicine · 2026Review
- Automated Aortic Quantification Based on Artificial Intelligence: Validation Using Contrast-Enhanced and Non-Contrast CT Scans from the Same Session.Bioengineering (Basel, Switzerland) · 2026Article
- Growth Trajectories in Ascending Thoracic Aortic Dilation: Classification and Implications for the Effectiveness of Real-World Imaging Surveillance.Journal of the American Heart Association · 2026Article
- Refining cardiac segmentation from MRI volumes with CT labels for fine anatomy of the ascending aorta.Radiological physics and technology · 2025Article
- Distal anastomotic new entry tears predict long-term outcomes after hemi-arch repair for DeBakey I aortic dissection†.European journal of cardio-thoracic surgery : official journal of the European Association for Cardio-thoracic Surgery · 2025Article
- Growth Rate Assessed by Vascular Deformation Mapping Predicts Type B Aortic Dissection in Marfan Syndrome.Journal of the American Heart Association · 2025Article
- Three-dimensional characterization of ascending aortic strain, motion and growth in patients undergoing thoracic endovascular aortic repair.JVS-vascular science · 2025Article
- Baseline Diameter Does Not Predict Growth Rate in a Presurgical Ascending Thoracic Aortic Aneurysm Population.Journal of the American Heart Association · 2024Article
- Growth Rate Assessed by Vascular Deformation Mapping predicts Type B Aortic Dissection in Marfan Syndrome.medRxiv : the preprint server for health sciences · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
Abstract
Purpose: Diagnosis and surveillance of thoracic aortic aneurysm (TAA) involves measuring the aortic diameter at various locations along the length of the aorta, often using computed tomography angiography (CTA). Currently, measurements are performed by human raters using specialized software for three-dimensional analysis, a time-consuming process, requiring 15 to 45 min of focused effort. Thus, we aimed to develop a convolutional neural network (CNN)-based algorithm for fully automated and accurate aortic measurements. Approach: Using 212 CTA scans, we trained a CNN to perform segmentation and localization of key landmarks jointly. Segmentation mask and landmarks are subsequently used to obtain the centerline and cross-sectional diameters of the aorta. Subsequently, a cubic spline is fit to the aortic boundary at the sinuses of Valsalva to avoid errors related inclusions of coronary artery origins. Performance was evaluated on a test set of 60 scans with automated measurements compared against expert manual raters. Result: Compared to training separate networks for each task, joint training yielded higher accuracy for segmentation, especially at the boundary ( Conclusion: Fully automated aortic diameter measurements in TAA are feasible using a CNN-based algorithm. Automated measurements demonstrated low errors that are comparable in magnitude to those with manual raters; however, measurement error was highest in the aortic root and arch.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.