Deep Learning-Based Skeleton Segmentation for Analysis of Bone Marrow and Cortical Bone in Water-Fat Magnetic Resonance Imaging

Abstract: A major health concern for subjects with diabetes is weaker bones and increased fracture risk. Current clinical assessment of the bone strength is performed by measuring Bone Mineral Density (BMD), where low BMD-values are associated with an increased risk of fracture. However, subjects with Type 2 Diabetes (T2D) have been shown to have normal or higher BMD-levels compared to healthy controls, which does not reflect the recognized bone fragility among diabetics. Thus, there is need for more research about diabetes-related bone fragility to find other factors of impaired bone health. One potential biomarker that has recently been studied is Bone Marrow Fat (BMF). The data in this project consisted of whole-body water-fat Magnetic Resonance Imaging (MRI) volumes from the UK Biobank Imaging study (UKBB). Each subject in this data has a water volume and a fat volume, allowing for a quantitative assessment of water and fat content in the body. To analyze and perform quantitative measurements of the bones specifically, a Deep Learning (DL) model was trained, validated, and tested for performing fully automated and objective skeleton segmentation, where six different bones were segmented: spine, femur, pelvis, scapula, clavicle and humerus. The model was trained and validated on 120 subjects with 6-fold cross-validation and tested on eight subjects. All ground-truth segmentations of the training and test data were generated using two semi-automatic pipelines. The model was evaluated for each bone separately as well as the overall skeleton segmentation and achieved varying accuracy, performing better on larger bones than on smaller ones. The final trained model was applied on a larger dataset of 9562 subjects (16% type 2 diabetics) and the BMF, as well as bone marrow volume (BMV) and cortical bone volume (CBV), were measured in the segmented bones of each subject. The results of the quantified biomarkers were compared between T2D and healthy subjects. The comparison revealed possible differences between healthy and diabetic subjects, suggesting a potential for new findings related to diabetes and associated bone fragility.