We have located links that may give you full text access.
Development of a shape-based algorithm for identification of asymptomatic vertebral compression fractures: A proof-of-principle study.
Osteoporosis and Sarcopenia 2024 March
OBJECTIVES: Vertebral fracture is both common and serious among adults, yet it often goes undiagnosed. This study aimed to develop a shape-based algorithm (SBA) for the automatic identification of vertebral fractures.
METHODS: The study included 144 participants (50 individuals with a fracture and 94 without a fracture) whose plain thoracolumbar spine X-rays were taken. Clinical diagnosis of vertebral fracture (grade 0 to 3) was made by rheumatologists using Genant's semiquantitative method. The SBA algorithm was developed to determine the ratio of vertebral body height loss. Based on the ratio, SBA classifies a vertebra into 4 classes: 0 = normal, 1 = mild fracture, 2 = moderate fracture, 3 = severe fracture). The concordance between clinical diagnosis and SBA-based classification was assessed at both person and vertebra levels.
RESULTS: At the person level, the SBA achieved a sensitivity of 100% and specificity of 62% (95% CI, 51%-72%). At the vertebra level, the SBA achieved a sensitivity of 84% (95% CI, 72%-93%), and a specificity of 88% (95% CI, 85%-90%). On average, the SBA took 0.3 s to assess each X-ray.
CONCLUSIONS: The SBA developed here is a fast and efficient tool that can be used to systematically screen for asymptomatic vertebral fractures and reduce the workload of healthcare professionals.
METHODS: The study included 144 participants (50 individuals with a fracture and 94 without a fracture) whose plain thoracolumbar spine X-rays were taken. Clinical diagnosis of vertebral fracture (grade 0 to 3) was made by rheumatologists using Genant's semiquantitative method. The SBA algorithm was developed to determine the ratio of vertebral body height loss. Based on the ratio, SBA classifies a vertebra into 4 classes: 0 = normal, 1 = mild fracture, 2 = moderate fracture, 3 = severe fracture). The concordance between clinical diagnosis and SBA-based classification was assessed at both person and vertebra levels.
RESULTS: At the person level, the SBA achieved a sensitivity of 100% and specificity of 62% (95% CI, 51%-72%). At the vertebra level, the SBA achieved a sensitivity of 84% (95% CI, 72%-93%), and a specificity of 88% (95% CI, 85%-90%). On average, the SBA took 0.3 s to assess each X-ray.
CONCLUSIONS: The SBA developed here is a fast and efficient tool that can be used to systematically screen for asymptomatic vertebral fractures and reduce the workload of healthcare professionals.
Full text links
Related Resources
Trending Papers
Haemodynamic monitoring during noncardiac surgery: past, present, and future.Journal of Clinical Monitoring and Computing 2024 April 31
Obesity pharmacotherapy in older adults: a narrative review of evidence.International Journal of Obesity 2024 May 7
2024 AHA/ACC/AMSSM/HRS/PACES/SCMR Guideline for the Management of Hypertrophic Cardiomyopathy: A Report of the American Heart Association/American College of Cardiology Joint Committee on Clinical Practice Guidelines.Circulation 2024 May 9
Get seemless 1-tap access through your institution/university
For the best experience, use the Read mobile app
All material on this website is protected by copyright, Copyright © 1994-2024 by WebMD LLC.
This website also contains material copyrighted by 3rd parties.
By using this service, you agree to our terms of use and privacy policy.
Your Privacy Choices
You can now claim free CME credits for this literature searchClaim now
Get seemless 1-tap access through your institution/university
For the best experience, use the Read mobile app