Abnormal Development of the Corpus Callosum in Autism Spectrum Disorder: An MRI Study.

BACKGROUND: Altered size in the corpus callosum (CC) has been reported in individuals with autism spectrum disorder (ASD), but few studies have investigated younger children. Moreover, knowledge about the age-related changes in CC size in individuals with ASD is limited. OBJECTIVES: Our objective was to investigate the age-related size of the CC and compare them with age-matched healthy controls between the ages of 2 and 18 years. METHODS: Structural-weighted images were acquired in 97 male patients diagnosed with ASD; published data were used for the control group. The CC was segmented into 7 distinct subregions (rostrum, genu, rostral body, anterior midbody, posterior midbody, isthmus, and splenium) as per Witelson's technique using ITK-SNAP software. We calculated both the total length and volume of the CC as well as the length and height of its 7 subregions. The length of the CC measures was studied as both continuous and categorical forms. For the continuous form, Pearson's correlation was used, while categorical forms were based on age ranges reflecting brain expansion during early postnatal years. Differences in CC measures between adjacent age groups in individuals with ASD were assessed using a Student t-test. Mean and standard deviation scores were compared between ASD and control groups using the Welch t-test. RESULTS: Age showed a moderate positive association with the total length of the CC (r = 0.43; Padj = 0.003) among individuals with ASD. Among the subregions, a positive association was observed only in the anterior midbody of the CC (r = 0.41; Padj = 0.01). No association was found between the age and the height of individual subregions or with the total volume of the CC. In comparison with healthy controls, individuals with ASD exhibited shorter lengths and heights of the genu and splenium of the CC across wide age ranges. CONCLUSION: Overall, our results highlight a distinct abnormal developmental trajectory of CC in ASD, particularly in the genu and splenium structures, potentially reflecting underlying pathophysiological mechanisms that warrant further investigation.

Severity of muscle impairment and its progression assessed using musculoskeletal magnetic resonance imaging and diffusion tension imaging in 78 boys with Duchenne muscular dystrophy: a retrospective study.

Purpose: Duchenne muscular dystrophy (DMD) is the most common and severe form of muscular dystrophy. Current diagnostic tests like genetic testing, needle electromyography, and muscle biopsy are either not easily available or invasive, and they are impractical for assessing disease progression and treatment outcomes. Therefore, there is a need for a non-invasive and accurate investigative modality for DMD. In recent years, musculoskeletal magnetic resonance imaging (MRI-MSK) along with fractional anisotropy (FA) and diffusion tensor imaging (DTI) have become major non-invasive tools. Material and methods: T1-weighted MRI-MSK and FA measures of DTI of 78 DMD patients were retrospectively studied to identify the distinct pattern of muscle involvement and fatty infiltration as age and/or disease progresses. Correlation analysis was performed between MRI-MSK grade score vs. age, muscle strength, and Vignos scale. Spearman's rank correlation coefficient was used. Results: As age increased, the MRI grade score and Vignos score increased. There was a statistically significant high positive correlation between MRI-MSK grade score and age, and low positive correlation with Vignos scores. With increasing age, the muscle strength on manual muscle testing (MMT) and FA value decreased. There was high negative correlation with muscle strength on MMT and low positive correlation between FA values and MMT score. Conclusions: On T1-weighted MRI, a distinct pattern, extent, and distribution of lower limb muscle involvement can be seen. MRI-MSK grade score worsens with progressing age, reducing strength, and increasing functional impairment. FA alone may not be an accurate marker in assessing progression of DMD. MRI-MSK and other DTI measures should be further explored as diagnostic and prognostic tools for DMD.

Machine-Learning-Based Radiomics for Classifying Glioma Grade from Magnetic Resonance Images of the Brain.

Grading of gliomas is a piece of critical information related to prognosis and survival. Classifying glioma grade by semantic radiological features is subjective, requires multiple MRI sequences, is quite complex and clinically demanding, and can very often result in erroneous radiological diagnosis. We used a radiomics approach with machine learning classifiers to determine the grade of gliomas. Eighty-three patients with histopathologically proven gliomas underwent MRI of the brain. Whenever available, immunohistochemistry was additionally used to augment the histopathological diagnosis. Segmentation was performed manually on the T2W MR sequence using the TexRad texture analysis softwareTM, Version 3.10. Forty-two radiomics features, which included first-order features and shape features, were derived and compared between high-grade and low-grade gliomas. Features were selected by recursive feature elimination using a random forest algorithm method. The classification performance of the models was measured using accuracy, precision, recall, f1 score, and area under the curve (AUC) of the receiver operating characteristic curve. A 10-fold cross-validation was adopted to separate the training and the test data. The selected features were used to build five classifier models: support vector machine, random forest, gradient boost, naive Bayes, and AdaBoost classifiers. The random forest model performed the best, achieving an AUC of 0.81, an accuracy of 0.83, f1 score of 0.88, a recall of 0.93, and a precision of 0.85 for the test cohort. The results suggest that machine-learning-based radiomics features extracted from multiparametric MRI images can provide a non-invasive method for predicting glioma grades preoperatively. In the present study, we extracted the radiomics features from a single cross-sectional image of the T2W MRI sequence and utilized these features to build a fairly robust model to classify low-grade gliomas from high-grade gliomas (grade 4 gliomas).

Plasticity of the Primary Motor Cortex in Patients with Primary Brain Tumors.

There are two neuron-level mechanisms proposed to underlie neural plasticity: recruiting neurons nearby to support the lost function (ipsilesional plasticity) and uncovering latent pathways that can assume the function that was lost (contralesional plasticity). While both patterns have been demonstrated in patient groups following injury, the specific mechanisms underlying each mode of plasticity are poorly understood. In a retrospective case series of 13 patients, we utilize a novel paradigm that analyzes serial fMRI scans in patients harboring intrinsic brain tumors that vary in location and growth kinetics to better understand the mechanisms underlying these two modes of plasticity in the human primary motor cortex. Twelve patients in our series had some degree of primary motor cortex plasticity, an area previously thought to have limited plasticity. Patients harboring smaller lesions with slower growth kinetics and increasing distance from the primary motor region demonstrated recruitment of ipsilateral motor regions. Conversely, larger, faster-growing lesions in close proximity to the primary motor region were associated with activation of the contralesional primary motor cortex, along with increased activation of the supplementary motor area. These data increase our understanding of the adaptive abilities of the brain and may lead to improved treatment strategies for those suffering from motor loss secondary to brain injuries.

Neuroprotective effects of vitamin E in cold induced cerebral injury in guinea pigs.

Significant reduction in hemorrhage (10 v/s 13), necrosis (2 v/s 4), cavitations (7 v/s 13), neuronal degeneration, perivascular and parenchymal inflammatory infiltrate (7 v/s 11) were observed in Vitamin E treated cold induced head injury in guinea pigs, evaluated post injury using the modified Benderson's scale. The results suggest that Vitamin E is highly effective in promoting clinical and histopathological recovery in cold induced head injury in guinea pigs.