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Understanding Atherosclerosis Through an Osteoarthritis Data Set
- Source :
- Arteriosclerosis, Thrombosis, and Vascular Biology. 39:1018-1025
- Publication Year :
- 2019
- Publisher :
- Ovid Technologies (Wolters Kluwer Health), 2019.
-
Abstract
- Atherosclerotic cardiovascular disease remains a worldwide epidemic and one of the leading causes of death nowadays. Vessel wall imaging can be used to understand the development and progression of atherosclerosis, but it is rarely done because of the high cost. We recently identified the Osteoarthritis Initiative, a large prospective cohort study of knee osteoarthritis, which might serve as a valuable source for atherosclerosis research with its serial knee magnetic resonance imaging data. We have found that these images are suitable for vessel wall image analysis of the lower extremity arteries. Here, we will introduce the Osteoarthritis Initiative data set and explain why it could be used for cardiovascular research purposes. Also, we will briefly comment on peripheral artery atherosclerosis as it is covered in the Osteoarthritis Initiative image data set and review the use of vessel wall imaging for studying atherosclerosis. We think data mining of imaging studies, not originally designed on cardiovascular research, can not only maximize the value of the imaging data set but also boost our understanding of atherosclerosis.
- Subjects :
- 030203 arthritis & rheumatology
medicine.medical_specialty
medicine.diagnostic_test
business.industry
Arterial disease
Atherosclerotic cardiovascular disease
Cardiovascular research
Magnetic resonance imaging
Osteoarthritis
030204 cardiovascular system & hematology
medicine.disease
Imaging data
Data set
03 medical and health sciences
0302 clinical medicine
medicine
Cardiology and Cardiovascular Medicine
Intensive care medicine
Prospective cohort study
business
Subjects
Details
- ISSN :
- 15244636 and 10795642
- Volume :
- 39
- Database :
- OpenAIRE
- Journal :
- Arteriosclerosis, Thrombosis, and Vascular Biology
- Accession number :
- edsair.doi...........56dfb15fdf1b20369b0fd1c9fda1e0b6