Researchers explored the use of image-based phenotyping based on dual-energy X-ray absorptiometry (DXA) scans.
By Dr. Chinta SidharthanAug 28 2023Reviewed by Lily Ramsey, LLM In a recent study published in the NPJ Digital Medicine Journal, researchers explored the use of image-based phenotyping based on dual-energy X-ray absorptiometry scans of knees to train a deep-learning model to diagnose knee osteoarthritis cases.
Given the large volumes of clinical image data present in population biobanks, an automated phenotyping approach can potentially be used to ascertain disease status and severity. Chest X-ray images have been previously used to accurately diagnose severe acute respiratory syndrome coronavirus 2 infections and pneumonia.
Related StoriesThe researchers also generated a polygenic risk score specific for each phenotype to determine whether, in a dataset of 300,000 cases, improvements in predicted ICD-10 records of knee osteoarthritis were associated with a higher statistical power in finding novel loci. The image segmentation algorithm was trained and validated using 63 images derived from DXA scans of knees, in which the positions of the tibia, fibula, and femur were marked at the pixel level, and validated by trained clinicians.
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