Advanced 2D image processing technique to predict hip fracture risk in an older population based on single DXA scans
- PDF / 529,924 Bytes
- 9 Pages / 595.276 x 790.866 pts Page_size
- 71 Downloads / 159 Views
ORIGINAL ARTICLE
Advanced 2D image processing technique to predict hip fracture risk in an older population based on single DXA scans F. Jazinizadeh 1 & J.D. Adachi 2 & C.E. Quenneville 1,3 Received: 4 March 2020 / Accepted: 29 April 2020 # International Osteoporosis Foundation and National Osteoporosis Foundation 2020
Abstract Summary A new technique to enhance hip fracture risk prediction in older adults was presented and assessed. The new method dramatically improved prediction at high specificity levels using only a standard clinical diagnostic scan. This has the potential to be implemented in clinical practice to enhance patient fragility diagnosis. Introduction Diagnosis of osteoporosis is based on the measurement of bone mineral density (BMD) using dual-energy X-ray absorptiometry (DXA) scans. However, studies have shown this to be insufficient to accurately predict hip fractures. Therefore, complementary methods are needed to enhance hip fracture risk prediction to identify vulnerable patients. Methods Hip DXA scans were obtained for 192 subjects from the Canadian Multicenter Osteoporosis Study (CaMos), 50 of whom had experienced a hip fracture within 5 years of the scan. 2D statistical shape and appearance modeling was performed to account for the effect of the femur’s geometry and BMD distribution on hip fracture risk. Statistical shape modeling (SSM), and statistical appearance modeling (SAM) were also used separately to predict the fracture risk based solely on the femur’s geometry and BMD distribution, respectively. Combined with BMD, age, and body mass index (BMI), logistic regression was performed to estimate the fracture risk over the 5-year period. Results Using the new technique, hip fractures were correctly predicted in 78% of cases compared with 36% when using the Tscore. The accuracy of the prediction was not greatly reduced when using SSM and SAM (78% and 74% correct, respectively). Various geometric and BMD distribution traits were identified in the fractured and non-fractured groups. Conclusion 2D SSAM can dramatically improve hip fracture prediction at high specificity levels and estimate the year of the impending fracture using standard clinical images. This has the potential to be implemented in clinical practice to estimate hip fracture risk. Keywords DXA scan . Hip fracture risk . Image processing . Statistical shape and appearance modeling
Introduction Osteoporosis is a disease in older adults that is characterized by a reduction in bone density and is associated with fragility fractures [1]. With the aging population, the occurrence of
* C.E. Quenneville [email protected] 1
Department of Mechanical Engineering, McMaster University, ABB-C308, 1280 Main St. West, Hamilton, Ontario L8S 4L8, Canada
2
Department of Medicine, McMaster University, Hamilton, Ontario, Canada
3
School of Biomedical Engineering, McMaster University, Hamilton, Ontario, Canada
osteoporotic fractures is growing. A previous study has shown that osteoporotic fractures occur more frequently than heart atta
Data Loading...
