Brain structural damage in Friedreich's ataxia.

ABSTRACT Objective: Neuropathological descriptions of the brain in Friedreich’s ataxia (FRDA) were obtained before avail- ability of the current molecular genetic tests for this disease. Voxel-based morphometry (VBM) enables an unbiased whole-brain quantitative analysis of differences in gray matter (GM) and white matter (WM) volume. Methods: Using VBM, we assessed the brain structural damage in 22 patients with genetically confirmed FRDA and 25 healthy controls. The results were correlated with the disease duration and the severity of the patients’ clinical deficits—evaluated using the International Cerebellar Ataxia Rating Scale and Inherited Ataxia Clinical Rating Scale. Results: In patients with FRDA, VBM showed a symmetrical volume loss in dorsal medulla, infero-medial portions of the cerebellar hemispheres, the rostral vermis and in the dentate region. No volume loss in cerebral hemispheres was observed. The atrophy of the cerebel- lum and medulla correlated with the severity of the clinical deficit and disease duration. Conclusions: In patients with FRDA, significant GM and WM loss was observed only in the cerebellum and dorsal medulla. These structural changes correlate with the severity of the clinical deficit and disease duration

G-CSF Prevents the Progression of Structural Disintegration of White Matter Tracts in Amyotrophic Lateral Sclerosis: A Pilot Trial

Background: The hematopoietic protein Granulocyte-colony stimulating factor (G-CSF) has neuroprotective and regenerative properties. The G-CSF receptor is expressed by motoneurons, and G-CSF protects cultured motoneuronal cells from apoptosis. It therefore appears as an attractive and feasible drug candidate for the treatment of amyotrophic lateral sclerosis (ALS). The current pilot study was performed to determine whether treatment with G-CSF in ALS patients is feasible.Methods: Ten patients with definite ALS were entered into a double-blind, placebo-controlled, randomized trial. Patients received either 10 mu g/kg BW G-CSF or placebo subcutaneously for the first 10 days and from day 20 to 25 of the study. Clinical outcome was assessed by changes in the ALS functional rating scale (ALSFRS), a comprehensive neuropsychological test battery, and by examining hand activities of daily living over the course of the study (100 days). The total number of adverse events (AE) and treatment-related AEs, discontinuation due to treatment-related AEs, laboratory parameters including leukocyte, erythrocyte, and platelet count, as well as vital signs were examined as safety endpoints. Furthermore, we explored potential effects of G-CSF on structural cerebral abnormalities on the basis of voxel-wise statistics of Diffusion Tensor Imaging (DTI), brain volumetry, and voxel-based morphometry.Results: Treatment was well-tolerated. No significant differences were found between groups in clinical tests and brain volumetry from baseline to day 100. However, DTI analysis revealed significant reductions of fractional anisotropy (FA) encompassing diffuse areas of the brain when patients were compared to controls. On longitudinal analysis, the placebo group showed significant greater and more widespread decline in FA than the ALS patients treated with G-CSF.Conclusions: Subcutaneous G-CSF treatment in ALS patients appears as feasible approach. Although exploratory analysis of clinical data showed no significant effect, DTI measurements suggest that the widespread and progressive microstructural neural damage in ALS can be modulated by G-CSF treatment. These findings may carry significant implications for further clinical trials on ALS using growth factors

Whole-brain histogram and voxel-based analyses of apparent diffusion coefficient and magnetization transfer ratio in celiac disease, epilepsy, and cerebral calcifications syndrome

BACKGROUND AND PURPOSE: Diffusion and magnetization transfer (MT) techniques have been applied to the investigation with MR of epilepsy and have revealed changes in patients with or without abnormalities on MR imaging. We hypothesized that also in the coeliac disease (CD), epilepsy and cerebral calcifications (CEC) syndrome diffusion and MT techniques could reveal brain abnormalities undetected by MR imaging and tentatively correlated to epilepsy. MATERIALS AND METHODS: Diffusion and MT weighted images were obtained in 10 patients with CEC, 8 patients with CD without epilepsy and 17 healthy volunteers. The whole brain apparent diffusion coefficient (ADC) and MT ratio (MTR) maps were analyzed with histograms and the Statistical Parametric Mapping 2 (SPM2) software. We employed the non-parametric Mann-Whitney U test to assess differences for ADC and MTR histogram metrics. Voxel by voxel comparison of the ADC and MTR maps was performed with 2 tails t-test corrected for multiple comparison. RESULTS: A significantly higher whole brain ADC value as compared to healthy controls was observed in CEC (P = 0.006) and CD (P = 0.01) patients. SPM2 showed bilateral areas of significantly decreased MTR in the parietal and temporal subcortical white matter (WM) in the CEC patients. CONCLUSION: Our study indicates that diffusion and MT techniques are also capable of revealing abnormalities undetected by MR imaging. In particular patients with CEC syndrome show an increase of the whole brain ADC histogram which is more pronounced than in patients with gluten intolerance. IN CEC patients, voxel-based analysis demonstrates a localized decrease of the MTR in the parieto-temporal subcortical WM

Value of prominent flow voids without cord edema in the detection of spinal arteriovenous fistulae

Purpose: To determine the prevalence of spinal dural arteriovenous fistulae (SDAVF) in patients presenting with prominent vascular flow voids on imaging without other imaging findings suggestive of SDAVF. Methods: We retrospectively identified patients from January 1, 2005 to March 1, 2012 who underwent spinal angiography for suspected SDAVF with prominent vascular flow voids on prior imaging. We excluded patients with other major spinal pathology or other imaging findings of SDAVF including cord hyperintensity, enhancement, or expansion. We calculated the proportion of patients with positive findings for SDAVF on angiography and evaluated the prevalence of SDAVF for this finding alone and in correlation with clinical findings. Results: 18 patients underwent spinal angiography for prominent flow voids on imaging without other spinal pathology or imaging findings of SDAVF. Three had a SDAVF detected on angiography. The prevalence of SDAVF in this population was low, only 17% (95% CI 6-39%). All of the patients with positive angiography findings had myelopathy, increasing the prevalence to 100% if the additional clinical finding of myelopathy was present. Conclusions: Prominent flow voids without other imaging findings suggestive of SDAVF is poorly predictive of the presence of a SDAVF, unless myelopathy is present clinically. © 2014 Alhilali et al

The Pivotal Role of Baseline LDCT for Lung Cancer Screening in the Era of Artificial Intelligence

In this narrative review, we address the ongoing challenges of lung cancer (LC) screening using chest low-dose computerized tomography (LDCT) and explore the contributions of artificial intelligence (AI), in overcoming them. We focus on evaluating the initial (baseline) LDCT examination, which provides a wealth of information relevant to the screening participant's health. This includes the detection of large-size prevalent LC and small-size malignant nodules that are typically diagnosed as LCs upon growth in subsequent annual LDCT scans. Additionally, the baseline LDCT examination provides valuable information about smoking-related comorbidities, including cardiovascular disease, chronic obstructive pulmonary disease, and interstitial lung disease (ILD), by identifying relevant markers. Notably, these comorbidities, despite the slow progression of their markers, collectively exceed LC as ultimate causes of death at follow-up in LC screening participants. Computer-assisted diagnosis tools currently improve the reproducibility of radiologic readings and reduce the false negative rate of LDCT. Deep learning (DL) tools that analyze the radiomic features of lung nodules are being developed to distinguish between benign and malignant nodules. Furthermore, AI tools can predict the risk of LC in the years following a baseline LDCT. AI tools that analyze baseline LDCT examinations can also compute the risk of cardiovascular disease or death, paving the way for personalized screening interventions. Additionally, DL tools are available for assessing osteoporosis and ILD, which helps refine the individual's current and future health profile. The primary obstacles to AI integration into the LDCT screening pathway are the generalizability of performance and the explainability

Fractal Analysis of MRI Data at 7 T: How Much Complex Is the Cerebral Cortex?

The human brain is a highly complex structure, which can be only partially described by conventional metrics derived from magnetic resonance imaging (MRI), such as volume, cortical thickness, and gyrification index. In the last years, the fractal dimension (FD) - a useful quantitative index of fractal geometry - has proven to well express the morphological complexity of the cerebral cortex. However, this complexity is likely higher than that we can observe using MRI scanners with 1.5 T or 3 T field strength. Ultrahigh-field MRI (UHF-MRI) improves imaging of smaller anatomical brain structures by exploring down to a submillimetric spatial resolution with higher signal-to-noise and contrast-to-noise ratios. Accordingly, we hypothesized that UHF-MRI might reveal a higher level of the structural complexity of the cerebral cortex. In this study, using an improved box-counting algorithm, we estimated the FD of the cerebral cortex in six public or private T1-weighted MRI datasets of young healthy subjects (for a total of 87 subjects), acquired at different field strengths (1.5 T, 3 T, and 7 T). Our results showed, for the first time, that MRI-derived FD values of the cerebral cortex imaged at 7 T were significantly higher than those observed at lower field strengths. UHF-MRI provides an anatomical definition not achievable at lower field strengths and can improve unveiling the real structural complexity of the human brain

Alcohol Induces Sensitization to Gluten in Genetically Susceptible Individuals: A Case Control Study

Background: The mechanisms of cerebellar degeneration attributed to prolonged and excessive alcohol intake remain unclear. Additional or even alternative causes of cerebellar degeneration are often overlooked in suspected cases of alcohol-related ataxia. The objectives of this study were two fold: (1) to investigate the prevalence of gluten-related serological markers in patients with alcohol-related ataxia and; (2) to compare the pattern of brain involvement on magnetic resonance imaging between patients with alcohol and gluten ataxias. Materials & Methods: Patients diagnosed with alcohol and gluten ataxias were identified from a retrospective review of patients attending a tertiary clinic. HLA genotype and serological markers of gluten-related disorders were recorded. Cerebellar volumetry, MR spectroscopy and voxel-based morphometric analyses were performed on patients and compared with matched control data. Results: Of 904 registered patients, 104 had alcohol ataxia and 159 had gluten ataxia. 61% of the alcohol ataxia group and 70% of the gluten ataxia group had HLA DQ2/DQ8 genotype compared to 30% in healthy local blood donors. 44% of patients with alcohol ataxia had antigliadin antibodies compared to 12% in the healthy local population and 10% in patients with genetically confirmed ataxias. None of the patients with alcohol ataxia and antigliadin antibodies had celiac disease compared to 40% in patients with gluten ataxia. The pattern of structural brain abnormality in patients with alcohol ataxia who had antigliadin antibodies differed from gluten ataxia and was identical to that of alcohol ataxia. Conclusions: Alcohol related cerebellar degeneration may, in genetically susceptible individuals, induce sensitization to gluten. Such sensitization may result from a primary cerebellar insult, but a more systemic effect is also possible. The duration and amount of exposure to alcohol may not be the only factors responsible for the cerebellar insult

Efficacy of MRI data harmonization in the age of machine learning: a multicenter study across 36 datasets

Pooling publicly-available MRI data from multiple sites allows to assemble extensive groups of subjects, increase statistical power, and promote data reuse with machine learning techniques. The harmonization of multicenter data is necessary to reduce the confounding effect associated with non-biological sources of variability in the data. However, when applied to the entire dataset before machine learning, the harmonization leads to data leakage, because information outside the training set may affect model building, and potentially falsely overestimate performance. We propose a 1) measurement of the efficacy of data harmonization; 2) harmonizer transformer, i.e., an implementation of the ComBat harmonization allowing its encapsulation among the preprocessing steps of a machine learning pipeline, avoiding data leakage by design. We tested these tools using brain T1-weighted MRI data from 1740 healthy subjects acquired at 36 sites. After harmonization, the site effect was removed or reduced, and we showed the data leakage effect in predicting individual age from MRI data, highlighting that introducing the harmonizer transformer into a machine learning pipeline allows for avoiding data leakage by design