The Human Phenotype Ontology (HPO, https://hpo.jax.org) was launched in 2008 to provide a comprehensive logical standard to describe and computationally analyze phenotypic abnormalities found in human disease. The HPO is now a worldwide standard for phenotype exchange. The HPO has grown steadily since its inception due to considerable contributions from clinical experts and researchers from a diverse range of disciplines. Here, we present recent major extensions of the HPO for neurology, nephrology, immunology, pulmonology, newborn screening, and other areas. For example, the seizure subontology now reflects the International League Against Epilepsy (ILAE) guidelines and these enhancements have already shown clinical validity. We present new efforts to harmonize computational definitions of phenotypic abnormalities across the HPO and multiple phenotype ontologies used for animal models of disease. These efforts will benefit software such as Exomiser by improving the accuracy and scope of cross-species phenotype matching. The computational modeling strategy used by the HPO to define disease entities and phenotypic features and distinguish between them is explained in detail.We also report on recent efforts to translate the HPO into indigenous languages. Finally, we summarize recent advances in the use of HPO in electronic health record systems.

The spinal cord is frequently affected by atrophy and/or lesions in multiple sclerosis (MS) patients. Segmentation of the spinal cord and lesions from MRI data provides measures of damage, which are key criteria for the diagnosis, prognosis, and longitudinal monitoring in MS. Automating this operation eliminates inter-rater variability and increases the efficiency of large-throughput analysis pipelines. Robust and reliable segmentation across multi-site spinal cord data is challenging because of the large variability related to acquisition parameters and image artifacts. In particular, a precise delineation of lesions is hindered by a broad heterogeneity of lesion contrast, size, location, and shape. The goal of this study was to develop a fully-automatic framework — robust to variability in both image parameters and clinical condition — for segmentation of the spinal cord and intramedullary MS lesions from conventional MRI data of MS and non-MS cases. Scans of 1,042 subjects (459 healthy controls, 471 MS patients, and 112 with other spinal pathologies) were included in this multi-site study (n=30). Data spanned three contrasts (T1-, T2-, and T2*-weighted) for a total of 1,943 volumes and featured large heterogeneity in terms of resolution, orientation, coverage, and clinical conditions. The proposed cord and lesion automatic segmentation approach is based on a sequence of two Convolutional Neural Networks (CNNs). To deal with the very small proportion of spinal cord and/or lesion voxels compared to the rest of the volume, a first CNN with 2D dilated convolutions detects the spinal cord centerline, followed by a second CNN with 3D convolutions that segments the spinal cord and/or lesions. CNNs were trained independently with the Dice loss. When compared against manual segmentation, our CNN-based approach showed a median Dice of 95% vs. 88% for PropSeg (p≤0.05), a state-of-the-art spinal cord segmentation method. Regarding lesion segmentation on MS data, our framework provided a Dice of 60%, a relative volume difference of −15%, and a lesion-wise detection sensitivity and precision of 83% and 77%, respectively. In this study, we introduce a robust method to segment the spinal cord and intramedullary MS lesions on a variety of MRI contrasts. The proposed framework is open-source and readily available in the Spinal Cord Toolbox.

Multiple sclerosis (MS) is an inflammatory disorder of the CNS that affects both the brain and the spinal cord. MRI studies in MS focus more often on the brain than on the spinal cord, owing to the technical challenges in imaging this smaller, mobile structure. However, spinal cord abnormalities at disease onset have important implications for diagnosis and prognosis. Furthermore, later in the disease course, in progressive MS, myelopathy becomes the primary characteristic of the clinical presentation, and extensive spinal cord pathology--including atrophy, diffuse abnormalities and numerous focal lesions--is common. Recent spinal cord imaging studies have employed increasingly sophisticated techniques to improve detection and quantification of spinal cord lesions, and to elucidate their relationship with physical disability. Quantitative MRI measures of cord size and tissue integrity could be more sensitive to the axonal loss and other pathological processes in the spinal cord than is conventional MRI, putting quantitative MRI in a key role to elucidate the association between disability and spinal cord abnormalities seen in people with MS. In this Review, we summarize the most recent MS spinal cord imaging studies and discuss the new insights they have provided into the mechanisms of neurological impairment. Finally, we suggest directions for further and future research.

Aim: The aims of this study were to determine the reliability, responsiveness and minimally important change score of the Multiple Sclerosis Impact Scale (MSIS)-29 physical using the Expanded Disability Status Scale (EDSS) as an anchor measure. Methods: 214 patients with multiple sclerosis (MS) (EDSS 0-8.5) had concurrent MSIS-29 and EDSS assessments at baseline and at up to 4 years of follow-up. Results: 116 patients had unchanged EDSS scores. Stability of the MSIS-29 physical (mean change 0.1 points) was better in the 85 patients with EDSS 0-5.0 than in the 31 patients with EDSS 5.5-8.5 in whom the MSIS-29 physical score fell by 8 points, a response shift phenomenon. A floor effect for the MSIS-29 was observed in 5% of stable patients at both time points. 98 patients experienced EDSS change with moderately strong statistically significant correlations between change scores in the EDSS and the MSIS-29 physical (r = 0.523, p,0.0001). Effect sizes for MSIS-29 physical change were moderate to large. Using receiver operating characteristic curves, the MSIS-29 change score which produced a combination of optimal sensitivity and specificity was chosen for both EDSS ranges. For EDSS range 5.5-8, a change score of 8 had a sensitivity of 87% and specificity of 67%. For EDSS 0-5.0, a change score of 7 had a sensitivity of 78% and a specificity of 51%. Conclusions: The MSIS-29 physical performs well over time, and is suitable for use in trials; a minimal change score of 8 points in the MSIS-29 is clinically significant.

Background:Understanding long-term disability in multiple sclerosis (MS) is a key goal of research; it is relevant to how we monitor and treat the disease.Objectives:The Magnetic Imaging in MS (MAGNIMS) collaborative group sought to determine the relationship of brain lesion load, and brain and spinal cord atrophy, with physical disability in patients with long-established MS.Methods:Patients had a magnetic resonance imaging (MRI) scan of their brain and spinal cord, from which we determined brain grey (GMF) and white matter (WMF) fractional volumes, upper cervical spinal cord cross-sectional area (UCCA) and brain T2-lesion volume (T2LV). We assessed patient disability using the Expanded Disability Status Scale (EDSS). We analysed associations between EDSS and MRI measures, using two regression models (dividing cohort by EDSS into two and four sub-groups).Results:In the binary model, UCCA (p < 0.01) and T2LV (p = 0.02) were independently associated with the requirement of a walking aid. In the four-category model UCCA (p < 0.01), T2LV (p = 0.02) and GMF (p = 0.04) were independently associated with disability.Conclusions:Long-term physical disability was independently linked with atrophy of the spinal cord and brain T2 lesion load, and less consistently, with brain grey matter atrophy. Combinations of spinal cord and brain MRI measures may be required to capture clinically-relevant information in people with MS of long disease duration.