Opportunistic screening for osteoporosis using hands radiographs
Poster Area
Lecturer: Farid Gharehmohammadi
Track: MIE: Posters
I am pleased to confirm my availability to present the poster from 10 am to 12 pm during the initial two days of the conference schedule.
This is a retrospective study of 812 patients aged 50 years or older who had dual-energy X-ray absorptiometry (DXA) and radiographs of the hands within 12 months of each other. This dataset was randomly split into training/validation (n=533) and test (n=136) datasets. A deep learning (DL) framework was used to predict osteoporosis/osteopenia. Correlations between the textural analysis of the bones and DXA measurements were obtained. We found that the DL model had an accuracy of 82.00%, sensitivity of 87.03%, specificity of 61.00% and an area under the curve (AUC) of 74.00% to detect osteoporosis/osteopenia. Our findings show that radiographs of the hand can be used to screen for osteoporosis/osteopenia and identify patients who should get formal DXA evaluation.
Language
English
Seminar type
On site only
Level of knowledge
Advanced
Conference
MIE
Authors
Farid Gharehmohammadi
Lecturers
Farid Gharehmohammadi Lecturer
Postdoctoral research fellow
Mayo Clinic
I am pleased to confirm my availability to present the poster from 10 am to 12 pm during the initial two days of the conference schedule.