Large-scale inference of liver fat with neural networks on UK Biobank body MRI

The UK Biobank Imaging Study has acquired medical scans of more than 40,000 volunteer participants. The resulting wealth of anatomical information has been made available for research, together with extensive metadata including measurements of liver fat. These values play an important role in metabolic disease, but are only available for a minority of imaged subjects as their collection requires the careful work of image analysts on dedicated liver MRI. Another UK Biobank protocol is neck-to-knee body MRI for analysis of body composition. The resulting volumes can also quantify fat fractions, even though they were reconstructed with a two- instead of a three-point Dixon technique. In this work, a novel framework for automated inference of liver fat from UK Biobank neck-to-knee body MRI is proposed. A ResNet50 was trained for regression on two-dimensional slices from these scans and the reference values as target, without any need for ground truth segmentations. Once trained, it performs fast, objective, and fully automated predictions that require no manual intervention. On the given data, it closely emulates the reference method, reaching a level of agreement comparable to different gold standard techniques. The network learned to rectify non-linearities in the fat fraction values and identified several outliers in the reference. It outperformed a multi-atlas segmentation baseline and inferred new estimates for all imaged subjects lacking reference values, expanding the total number of liver fat measurements by factor six

Osteoclast Activated FoxP3+ CD8+ T-Cells Suppress Bone Resorption in vitro

BACKGROUND: Osteoclasts are the body's sole bone resorbing cells. Cytokines produced by pro-inflammatory effector T-cells (T(EFF)) increase bone resorption by osteoclasts. Prolonged exposure to the T(EFF) produced cytokines leads to bone erosion diseases such as osteoporosis and rheumatoid arthritis. The crosstalk between T-cells and osteoclasts has been termed osteoimmunology. We have previously shown that under non-inflammatory conditions, murine osteoclasts can recruit naïve CD8 T-cells and activate these T-cells to induce CD25 and FoxP3 (Tc(REG)). The activation of CD8 T-cells by osteoclasts also induced the cytokines IL-2, IL-6, IL-10 and IFN-γ. Individually, these cytokines can activate or suppress osteoclast resorption. PRINCIPAL FINDINGS: To determine the net effect of Tc(REG) on osteoclast activity we used a number of in vitro assays. We found that Tc(REG) can potently and directly suppress bone resorption by osteoclasts. Tc(REG) could suppress osteoclast differentiation and resorption by mature osteoclasts, but did not affect their survival. Additionally, we showed that Tc(REG) suppress cytoskeletal reorganization in mature osteoclasts. Whereas induction of Tc(REG) by osteoclasts is antigen-dependent, suppression of osteoclasts by Tc(REG) does not require antigen or re-stimulation. We demonstrated that antibody blockade of IL-6, IL-10 or IFN-γ relieved suppression. The suppression did not require direct contact between the Tc(REG) and osteoclasts. SIGNIFICANCE: We have determined that osteoclast-induced Tc(REG) can suppress osteoclast activity, forming a negative feedback system. As the CD8 T-cells are activated in the absence of inflammatory signals, these observations suggest that this regulatory loop may play a role in regulating skeletal homeostasis. Our results provide the first documentation of suppression of osteoclast activity by CD8 regulatory T-cells and thus, extend the purview of osteoimmunology