Machine learning models for predicting transstenotic pressure gradient based on computed tomography angiography features
The developed machine learning model shows promising potential for the noninvasive prediction of transverse sinus TPG based on CTA-derived features.
Authors
- Binbin Sui (ORCID: https://orcid.org/0000-0002-1052-6992)
- Han Xu (ORCID: https://orcid.org/0000-0001-5493-6857)
- Xiaoyu Qiu (ORCID: https://orcid.org/0000-0003-1888-2964)
- Chihang Dai
- Zhiyuan An (ORCID: https://orcid.org/0000-0003-3573-5456)
- Guopeng Wang (ORCID: https://orcid.org/0000-0002-5947-3131)
- Shusheng Gong (ORCID: https://orcid.org/0000-0001-6847-3195)
- Zhenghan Yang (ORCID: https://orcid.org/0000-0003-3986-1732)
- Yan Huang (ORCID: https://orcid.org/0009-0001-2298-3971)
- Long Jin (ORCID: https://orcid.org/0000-0002-5329-5098)
- Xue Zhang (ORCID: https://orcid.org/0000-0002-0892-3665)
- Lijun Cai (ORCID: https://orcid.org/0000-0002-9665-592X)
- Heyu Ding (ORCID: https://orcid.org/0000-0003-1519-6141)
- Pengfei Zhao (ORCID: https://orcid.org/0009-0000-4640-9248)
- Zhenchang Wang (ORCID: https://orcid.org/0000-0001-8190-6469)
- Hui Zhang (ORCID: https://orcid.org/0000-0001-6300-9334)
Institutions
- Shanxi University (CN)
- Capital Medical University (CN)
- Beijing Tian Tan Hospital (CN)
- Beijing Friendship Hospital (CN)
- Beihang University (CN)
Publication Details
- Journal
- Quantitative Imaging in Medicine and Surgery
- Published
- 2025-09-24
- DOI
- https://doi.org/10.21037/qims-2025-157
- Primary Topic
- Cerebrovascular and Carotid Artery Diseases
- Type
- article
- Field-Weighted Citation Impact
- 0.00