Natural history of a cohort of ABCD1 variant female carriers.

BACKGROUND AND PURPOSE: The therapeutic scenario of X-linked adrenoleukodystrophy (X-ALD) is rapidly changing. Whereas the disease is well characterized in men, the condition remains to be fully clarified in women carrying ATP binding cassette subfamily D member 1 (ABCD1) variants. Specifically, data on clinical progression are needed, in order to recommend any appropriate management. The objective of this study was to outline the natural history of a cohort of untreated ABCD1 heterozygous female carriers. METHODS: Longitudinal data from a single-center population of 60 carriers were retrospectively reviewed. Demographics, anthropometrics, serum very long chain fatty acid (VLCFA) levels, clinical parameters and the Adult ALD Clinical Score (AACS) were collected from every recorded visit in a 7-year period and analyzed to define the phenotype modifications, to determine factors associated with clinical features, and to estimate the annual progression rate and the subsequent sample size for interventional trials. RESULTS: Thirty-two patients were eligible for the study, and 59.4% were symptomatic at baseline. Clinical severity worsens with age which increases risk of symptom onset, the cut-off of 41 years being crucial for phenoconversion. VLCFA levels were not predictive and did not change over time. Symptomatic carriers were followed up for 3.45 ± 2.1 years. The AACS increased at an annual rate of 0.24 points. The estimated sample size for 30% reduction in annual progression at 80% power was 272. CONCLUSIONS: This study provides data on the natural disease progression of untreated ABCD1 heterozygous female carriers, demonstrating the relevance of aging. The estimated annual increase of the AACS will be useful for future interventional studies.

Validation of low-cost system for gait assessment in children with ataxia.

BACKGROUND: Ataxic syndromes include several rare, inherited and acquired conditions. One of the main issues is the absence of specific, and sensitive automatic evaluation tools and digital outcome measures to obtain a continuous monitoring of subjects' motor ability. OBJECTIVES: This study aims to test the usability of the Kinect system for assessing ataxia severity, exploring the potentiality of clustering algorithms and validating this system with a standard motion capture system. METHODS: Gait evaluation was performed by standardized gait analysis and by Kinect v2 during the same day in a cohort of young patient (mean age of 13.8±7.2). We analyzed the gait spatio-temporal parameters and we looked at the differences between the two systems through correlation and agreement tests. As well, we tested for possible correlations with the SARA scale as well. Finally, standard classification algorithm and principal components analysis were used to discern disease severity and groups. RESULTS: We found biases and linear relationships between all the parameters. Significant correlations emerged between the SARA and the Speed, the Stride Length and the Step Length. PCA results, highlighting that a machine learning approach combined with Kinect-based evaluation shows great potential to automatically assess disease severity and diagnosis. CONCLUSIONS: The spatio-temporal parameters measured by Kinect cannot be used interchangeably with those parameters acquired with standard motion capture system in clinical practice but can still provide fundamental information. Specifically, these results might bring to the development of a novel system to perform easy and quick evaluation of gait in young patients with ataxia, useful for patients stratification in terms of clinical severity and diagnosis.

Spatio-temporal parameters of ataxia gait dataset obtained with the Kinect.

Ataxic syndromes include several rare, inherited and acquired conditions. One of the main issues is the absence of specific, and sensitive automatic evaluation tools and digital outcome measures to obtain a continuous monitoring of subjects' motor ability. Gait evaluation was performed by Kinect v2 in a cohort of young participant affected by ataxia syndrome. The dataset is composed of the spatio-temporal parameters calculated by the skeleton acquired by the Kinect sensor, by the diagnosis of each participant, and by the total score of the clinical scale SARA. These parameters have been previously validated and corrected as requested by the Bland-Altman test.

Generating a minimal set of templates for the hippocampal region in MR neuroimages.

OBJECTIVES: We detail a procedure for generating a set of templates for the hippocampal region in magnetic resonance (MR) images, representative of the clinical conditions of the population under investigation. METHODS: The first step is robust standardization of the intensity scale of brain MR images, belonging to patients with different degrees of neuropathology (Alzheimer's disease). So similar tissues have similar intensities, even across images coming from different sources. After the automatic extraction of the hippocampal region from a large dataset of images, we address template generation, choosing by clusterization methods a small number of the extracted regions. RESULTS: We assess that template generation is largely independent on the clusterization method and on the number and the clinical condition of the patients. The templates are chosen as the most representative images in a population. The estimation of the "minimum" number of templates for the hippocampal region can be proposed, using a metric based on the geometrical position of the extracted regions. CONCLUSIONS: This study describes a simple and easily reproducible procedure to generate templates for the hippocampal region. It can be generalized and applied to other brain regions, which may be relevant for neuroimaging studies.