ArticleThe international journal of cardiovascular imaging2019
VASIM: an automated tool for the quantification of carotid atherosclerosis by computed tomography angiography.
Article in The international journal of cardiovascular imaging, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed, 11 citations in OpenAlex.
- The application value of deep learning-based reconstruction combined with segmented contrast injection in "one-stop" cardio-cerebrovascular computed tomography angiography.Quantitative imaging in medicine and surgery · 2025Article
- Quantifying Carotid Stenosis: History, Current Applications, Limitations, and Potential: How Imaging Is Changing the Scenario.Life (Basel, Switzerland) · 2024Review
- Computer Science meets Vascular Surgery: Keeping a pulse on artificial intelligence.Seminars in vascular surgery · 2023Review
- Artificial Intelligence Evidence-Based Current Status and Potential for Lower Limb Vascular Management.Journal of personalized medicine · 2021Review
- Carotid Plaque Composition Assessed by CT Predicts Subsequent Cardiovascular Events among Subjects with Carotid Stenosis.AJNR. American journal of neuroradiology · 2021Article
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Authors and funding
6 authors at 4 institutions in 2 countries.
Funding
Abstract
The diagnostic imaging techniques currently used to evaluate the arterial atherosclerosis hinge on the manual marking and calculation of the stenosis degree. However, the manual assessment is highly dependent on the operator and characterized by low replicability. The study aimed to develop a fully-automated tool for the segmentation and analysis of atherosclerosis in the extracranial carotid arteries. The dataset consisted of 59 randomly-chosen individuals who had undergone head-and-neck computed tomography angiography (CTA), at the Tampere University Hospital, Tampere, Finland. The analysis algorithm was mainly based on the detection of carotid arteries, delineation of the vascular wall, and extraction of the atherosclerotic plaque. To improve the vascular detection rate, the model-based and volume-wide analytical approaches were deployed. A new fully-automated vascular imaging (VASIM) software tool was developed. For stenosis over 50%, the success rate was 83% for the detection and segmentation. Specificity and sensitivity of the algorithm were 25% and 83%, respectively. The overall accuracy was 71%. The VASIM tool is the first published approach for the fully-automated analysis of atherosclerosis in extracranial carotid arteries. The tool provides new outputs, which may help with the quantitative and qualitative, clinical evaluation of the atherosclerosis burden and evolution. The findings from this study provide a basis for the further development of automated atherosclerosis diagnosis and plaque analysis with CTA.
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Registered trials
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