Journal article
Regional Stiffness and Hardening Indices: New Indicators Derived from Multidimensional Dynamic CTA for Aneurysm Risk Assessment
Advanced science, Vol.11(47), 2400653
12/18/2024
DOI: 10.1002/advs.202400653
PMCID: PMC11653626
PMID: 39449669
Appears in UI Libraries Support Open Access
Abstract
Two indices, indicating the regional average stiffness and the pace of strain hardening respectively, are derived from the nonlinear stress–strain behavior obtained from biomechanical analysis of aneurysm. A comprehensive method based on electrocardiographic‐gated multidimensional dynamic computed tomography angiography (MD CTA) is developed for extracting these mechanical characteristics in vivo. The proposed indices are evaluated by 26 cases including 9 healthy, one aortosclerosis, and 16 abdominal aortic aneurysm cases. The difference of SSI and dSSI value between aneurysmal and healthy groups is up to orders in magnitude. Significant correlation of these indices with the clinical indicator of aneurysm diameter is found. Logistic models based on these indices are capable to sharply discriminate the healthy and the aneurysmal arteries with AUC>0.98. This work introduces new tools and new indices for aortic mechanical assessment which may shed light on understanding the mechanical condition, pathological state and eventually benefit clinical decision‐making.
Details
- Title: Subtitle
- Regional Stiffness and Hardening Indices: New Indicators Derived from Multidimensional Dynamic CTA for Aneurysm Risk Assessment
- Creators
- Tianming Huang - Department of Technology Boea Wisdom (Hangzhou) Network Technology Co., Ltd. Hangzhou 310000 ChinaXiaoyu Qi - Huazhong University of Science and TechnologyLan Cao - Department of Technology Boea Wisdom (Hangzhou) Network Technology Co., Ltd. Hangzhou 310000 ChinaMing Yang - Union HospitalHuan Luo - Department of Technology Boea Wisdom (Hangzhou) Network Technology Co., Ltd. Hangzhou 310000 ChinaQin Li - Union HospitalPeidong Qian - Department of Technology Boea Wisdom (Hangzhou) Network Technology Co., Ltd. Hangzhou 310000 ChinaJia Lu - University of IowaZiqiao Lei - Union HospitalYuanming Luo - University of IowaChao Yang - Huazhong University of Science and Technology
- Resource Type
- Journal article
- Publication Details
- Advanced science, Vol.11(47), 2400653
- DOI
- 10.1002/advs.202400653
- PMID
- 39449669
- PMCID
- PMC11653626
- NLM abbreviation
- Adv Sci (Weinh)
- ISSN
- 2198-3844
- eISSN
- 2198-3844
- Publisher
- Wiley
- Grant note
- Key Research and Development Program of Hubei ProvinceNational Natural Science Foundation of China: 82270520
X.Q., M.Y., P.Q., Q.L., Z.Q., and C.Y. are supported by the Key Research and Development Program of Hubei Province through Grant No. 2022BCA024, and Q.L. and C. Y. are supported by the National Natural Science Foundation of China through Grant No. 82270520. The authors thank Hao Lu, Haonan Zhang, Xiao Yang, Yeyuan Zheng and Ze Wu, Yanqiong Li from Boea Wisdom for the assistance in medical image processing, and Ying Liu, Linlin Guo, Gezhen Chen and Dianxi Chen from the Union Hospital for the assistance in patient information and CTA image collecting.
- Language
- English
- Electronic publication date
- 10/25/2024
- Date published
- 12/18/2024
- Academic Unit
- Iowa Technology Institute; Mechanical Engineering
- Record Identifier
- 9984740855902771
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