A novel deep learning method for large-scale analysis of bone marrow adiposity using UK Biobank Dixon MRI data

• Published in: Computational and structural biotechnology journal Vol. 24; pp. 89 - 104
• Main Authors: Morris, David M., Wang, Chengjia, Papanastasiou, Giorgos, Gray, Calum D., Xu, Wei, Sjöström, Samuel, Badr, Sammy, Paccou, Julien, Semple, Scott IK, MacGillivray, Tom, Cawthorn, William P.
• Format: Journal Article
• Language: English
• Published: Netherlands Elsevier B.V 01.12.2024; Elsevier; Research Network of Computational and Structural Biotechnology
• Subjects: Ageing; Biomarkers; Bone; Bone marrow adipose tissue; Bone marrow adiposity; Bone marrow fat fraction; Deep learning; Life Sciences; Magnetic resonance imaging; Osteoporosis; Predictive analytics; Sex differences; UK Biobank; Deep learning; Osteoporosis; Magnetic resonance imaging; Bone marrow adiposity; Ageing; Biomarkers; Bone marrow adipose tissue; Sex differences; Bone; Bone marrow fat fraction; Predictive analytics; UK Biobank

Bone marrow adipose tissue (BMAT) represents > 10% fat mass in healthy humans and can be measured by magnetic resonance imaging (MRI) as the bone marrow fat fraction (BMFF). Human MRI studies have identified several diseases associated with BMFF but have been relatively small scale. Population-sc...