Negative Associations between Corpus Callosum Midsagittal Area and IQ in a Representative Sample of Healthy Children and Adolescents

Documented associations between corpus callosum size and cognitive ability have heretofore been inconsistent potentially owing to differences in sample characteristics, differing methodologies in measuring CC size, or the use of absolute versus relative measures. We investigated the relationship between CC size and intelligence quotient (IQ) in the NIH MRI Study of Normal Brain Development sample, a large cohort of healthy children and adolescents (aged six to 18, n = 198) recruited to be representative of the US population. CC midsagittal area was measured using an automated system that partitioned the CC into 25 subregions. IQ was measured using the Wechsler Abbreviated Scale of Intelligence (WASI). After correcting for total brain volume and age, a significant negative correlation was found between total CC midsagittal area and IQ (r = −0.147; p = 0.040). Post hoc analyses revealed a significant negative correlation in children (age<12) (r = −0.279; p = 0.004) but not in adolescents (age $\geq$ 12) (r = −0.005; p = 0.962). Partitioning the subjects by gender revealed a negative correlation in males (r = −0.231; p = 0.034) but not in females (r = 0.083; p = 0.389). Results suggest that the association between CC and intelligence is mostly driven by male children. In children, a significant gender difference was observed for FSIQ and PIQ, and in males, a significant age-group difference was observed for FSIQ and PIQ. These findings suggest that the correlation between CC midsagittal area and IQ may be related to age and gender

Negative associations between corpus callosum midsagittal area and IQ in a representative sample of healthy children and adolescents.

Documented associations between corpus callosum size and cognitive ability have heretofore been inconsistent potentially owing to differences in sample characteristics, differing methodologies in measuring CC size, or the use of absolute versus relative measures. We investigated the relationship between CC size and intelligence quotient (IQ) in the NIH MRI Study of Normal Brain Development sample, a large cohort of healthy children and adolescents (aged six to 18, n = 198) recruited to be representative of the US population. CC midsagittal area was measured using an automated system that partitioned the CC into 25 subregions. IQ was measured using the Wechsler Abbreviated Scale of Intelligence (WASI). After correcting for total brain volume and age, a significant negative correlation was found between total CC midsagittal area and IQ (r = -0.147; p = 0.040). Post hoc analyses revealed a significant negative correlation in children (ag

The Features of Blood Supply of Corpus Callosum and the Structure of Its Hemomicrocirculatory Channel

Today we know the location of the sources of arterial blood delivery to the corpus callosum and we can approximately say, where are situated the venous vessels that the blood outflows from it to, but it is absolutely unknown, what is the intermediate link – the blood microcirculatory channel.Aim of research. The aim of our research is in identification of the ways of venous outflow from corpus callosum and in clarification of the principle of structural organization of its hemomicrocirculatory channel.Materials and methods. In the work are used the median total preparations of the corpus callosum (together with septum pellucidum and cerebral fornix formations) of 10 men 36–60 years old. Histological paraffin sections, colored by hematoxylin and eosin and according to Van-gieson were made of these preparations, and the methods of plastination of the corpus callosum tissues in epoxy resin with further creation of polished sections of different width and serial fine sections of blocs, for which coloration served the 1 % solution of blue methene for 1% borax solution, were also used.Results. It was established, that the arterial microvessels, starting from vascular plexus that covers the upper surface of corpus callosum, penetrate it as arterioles along interfunicular connective tissue septs that divide its commissural funicles between them. The arterioles are prolonged directly in venous microvessels that can be related to gathering venules. These direct microvascular communications, coming through the thickness of corpus callosum, can be named perforating arteriolovenular anastomoses. The aforesaid collector venules, localized in the lowest sections of interfunicular interlayers, are the direct inflows of venous channel of septum pellucidum. In general system of blood supply of corpus callosum the main arteries on the one side and the veins of septum pellucidum – on the other, are not accompanied by the vessels of opposite type.Conclusions. The blood microcirculatory channel of corpus callosum is the complexly branched in its thickness net of resistive, metabolic and capacitive microvessels, placed on the running way between arterial channel of soft cerebral tunic that covers the upper surface of corpus callosum and collector veins of septum pellucidum, situated below it. The direct shunting tracts between them are perforating arteriolovenular anastomoses

Brain Extraction comparing Segment Anything Model (SAM) and FSL Brain Extraction Tool

Brain extraction is a critical preprocessing step in almost every neuroimaging study, enabling accurate segmentation and analysis of Magnetic Resonance Imaging (MRI) data. FSL's Brain Extraction Tool (BET), although considered the current gold standard, presents limitations such as over-extraction, which can be particularly problematic in brains with lesions affecting the outer regions, inaccurate differentiation between brain tissue and surrounding meninges, and susceptibility to image quality issues. Recent advances in computer vision research have led to the development of the Segment Anything Model (SAM) by Meta AI, which has demonstrated remarkable potential across a wide range of applications. In this paper, we present a comparative analysis of brain extraction techniques using BET and SAM on a variety of brain scans with varying image qualities, MRI sequences, and brain lesions affecting different brain regions. We find that SAM outperforms BET based on several metrics, particularly in cases where image quality is compromised by signal inhomogeneities, non-isotropic voxel resolutions, or the presence of brain lesions that are located near or involve the outer regions of the brain and the meninges. These results suggest that SAM has the potential to emerge as a more accurate and precise tool for a broad range of brain extraction applications.Comment: 9 pages, 4 figures, 2 tables, SI in the given ur

THE FEATURES OF BLOOD SUPPLY OF CORPUS CALLOSUM AND THE STRUCTURE OF ITS HEMOMICROCIRCULATORY CHANNEL

Today we know the location of the sources of arterial blood delivery to the corpus callosum and we can approximately say, where are situated the venous vessels that the blood outflows from it to, but it is absolutely unknown, what is the intermediate link – the blood microcirculatory channel. Aim of research.&nbsp;The aim of our research is in identification of the ways of venous outflow from corpus callosum and in clarification of the principle of structural organization of its hemomicrocirculatory channel. Materials and methods.&nbsp;In the&nbsp;work are used the median total preparations of the corpus callosum (together with septum pellucidum and cerebral fornix formations) of 10 men 36–60 years old. Histological paraffin sections, colored by hematoxylin and eosin and according to Van-gieson were made of these preparations, and the methods of plastination of the corpus callosum tissues in epoxy resin with further creation of polished sections of different width and serial fine sections of blocs, for which coloration served the 1 % solution of blue methene for 1% borax solution, were also used. Results.&nbsp;It was established, that the arterial microvessels, starting from vascular plexus that covers the upper surface of corpus callosum, penetrate it as arterioles along interfunicular connective tissue septs that divide its commissural funicles between them. The arterioles are prolonged directly in venous microvessels that can be related to gathering venules. These direct microvascular communications, coming through the thickness of corpus callosum, can be named perforating arteriolovenular anastomoses. The aforesaid collector venules, localized in the lowest sections of interfunicular interlayers, are the direct inflows of venous channel of septum pellucidum. In general system of blood supply of corpus callosum the main arteries on the one side and the veins of septum pellucidum – on the other, are not accompanied by the vessels of opposite type. Conclusions.&nbsp;The blood microcirculatory channel of corpus callosum is the complexly branched in its thickness net of resistive, metabolic and capacitive microvessels, placed on the running way between arterial channel of soft cerebral tunic that covers the upper surface of corpus callosum and collector veins of septum pellucidum, situated below it. The direct shunting tracts between them are perforating arteriolovenular anastomoses

Corpus callosum index and long-term disability in multiple sclerosis patients

Prediction of long-term disability in patients with multiple sclerosis (MS) is essential. Magnetic resonance imaging (MRI) measurement of brain volume may be of predictive value but sophisticated MRI techniques are often inaccessible in clinical practice. The corpus callosum index (CCI) is a normalized measurement that reflects changes of brain volume. We investigated medical records and 533 MRI scans at diagnosis and during clinical follow-up of 169 MS patients (mean age 42±11years, 86% relapsing-remitting MS, time since first relapse 11±9years). CCI at diagnosis was 0.345±0.04 and correlated with duration of disease (p=0.002; r=−0.234) and expanded disability status scale (EDSS) score at diagnosis (r=−0.428; p<0.001). Linear regression analyses identified age, duration of disease, relapse rate and EDSS at diagnosis as independent predictors for disability after mean of 7.1years (Nagelkerkes' R:0.56). Annual CCI decrease was 0.01±0.02 (annual tissue loss: 1.3%). In secondary progressive MS patients, CCI decrease was double compared to that in relapsing-remitting MS patients (p=0.04). There was a trend of greater CCI decrease in untreated patients compared to those who received disease modifying drugs (p=0.2). CCI is an easy to use MRI marker for estimating brain atrophy in patients with MS. Brain atrophy as measured with CCI was associated with disability progression but it was not an independent predictor of long-term disabilit

Mid-sagittal plane detection for advanced physiological measurements in brain scans

Objective: The process of diagnosing many neurodegenerative diseases, such as Parkinson's and progressive supranuclear palsy, involves the study of brain magnetic resonance imaging (MRI) scans in order to identify and locate morphological markers that can highlight the health status of the subject. A fundamental step in the pre-processing and analysis of MRI scans is the identification of the mid-sagittal plane, which corresponds to the mid-brain and allows a coordinate reference system for the whole MRI scan set. Approach: To improve the identification of the mid-sagittal plane we have developed an algorithm in Matlab® based on the k-means clustering function. The results have been compared with the evaluation of four experts who manually identified the mid-sagittal plane and whose performances have been combined with a cognitive decisional algorithm in order to define a gold standard. Main results: The comparison provided a mean percentage error of 1.84%. To further refine the automatic procedure we trained a machine learning system using the results from the proposed algorithm and the gold standard. We tested this machine learning system and obtained results comparable to medical raters with a mean absolute error of 1.86 slices. Significance: The system is promising and could be directly incorporated into broader diagnostic support systems

A CAD system for early diagnosis of autism using different imaging modalities.

The term “autism spectrum disorder” (ASD) refers to a collection of neuro-developmental disorders that affect linguistic, behavioral, and social skills. Autism has many symptoms, most prominently, social impairment and repetitive behaviors. It is crucial to diagnose autism at an early stage for better assessment and investigation of this complex syndrome. There have been a lot of efforts to diagnose ASD using different techniques, such as imaging modalities, genetic techniques, and behavior reports. Imaging modalities have been extensively exploited for ASD diagnosis, and one of the most successful ones is Magnetic resonance imaging(MRI),where it has shown promise for the early diagnosis of the ASD related abnormalities in particular. Magnetic resonance imaging (MRI) modalities have emerged as powerful means that facilitate non-invasive clinical diagnostics of various diseases and abnormalities since their inception in the 1980s. After the advent in the nineteen eighties, MRI soon became one of the most promising non- invasive modalities for visualization and diagnostics of ASD-related abnormalities. Along with its main advantage of no exposure to radiation, high contrast, and spatial resolution, the recent advances to MRI modalities have notably increased diagnostic certainty. Multiple MRI modalities, such as different types of structural MRI (sMRI) that examines anatomical changes, and functional MRI (fMRI) that examines brain activity by monitoring blood flow changes,have been employed to investigate facets of ASD in order to better understand this complex syndrome. This work aims at developing a new computer-aided diagnostic (CAD) system for autism diagnosis using different imaging modalities. It mainly relies on making use of structural magnetic resonance images for extracting notable shape features from parts of the brainthat proved to correlate with ASD from previous neuropathological studies. Shape features from both the cerebral cortex (Cx) and cerebral white matter(CWM)are extracted. Fusion of features from these two structures is conducted based on the recent findings suggesting that Cx changes in autism are related to CWM abnormalities. Also, when fusing features from more than one structure, this would increase the robustness of the CAD system. Moreover, fMRI experiments are done and analyzed to find areas of activation in the brains of autistic and typically developing individuals that are related to a specific task. All sMRI findings are fused with those of fMRI to better understand ASD in terms of both anatomy and functionality,and thus better classify the two groups. This is one aspect of the novelty of this CAD system, where sMRI and fMRI studies are both applied on subjects from different ages to diagnose ASD. In order to build such a CAD system, three main blocks are required. First, 3D brain segmentation is applied using a novel hybrid model that combines shape, intensity, and spatial information. Second, shape features from both Cx and CWM are extracted and anf MRI reward experiment is conducted from which areas of activation that are related to the task of this experiment are identified. Those features were extracted from local areas of the brain to provide an accurate analysis of ASD and correlate it with certain anatomical areas. Third and last, fusion of all the extracted features is done using a deep-fusion classification network to perform classification and obtain the diagnosis report. Fusing features from all modalities achieved a classification accuracy of 94.7%, which emphasizes the significance of combining structures/modalities for ASD diagnosis. To conclude, this work could pave the pathway for better understanding of the autism spectrum by finding local areas that correlate to the disease. The idea of personalized medicine is emphasized in this work, where the proposed CAD system holds the promise to resolve autism endophenotypes and help clinicians deliver personalized treatment to individuals affected with this complex syndrome

Development and Validation of Automated Magnetic Resonance Parkinsonism Index 2.0 to Distinguish Progressive Supranuclear Palsy-Parkinsonism From Parkinson's Disease

Background: Differentiating progressive supranuclear palsy-parkinsonism (PSP-P) from Parkinson's disease (PD) is clinically challenging. Objective: This study aimed to develop an automated Magnetic Resonance Parkinsonism Index 2.0 (MRPI 2.0) algorithm to distinguish PSP-P from PD and to validate its diagnostic performance in two large independent cohorts. Methods: We enrolled 676 participants: a training cohort (n&nbsp;=&nbsp;346; 43 PSP-P, 194 PD, and 109 control subjects) from our center and an independent testing cohort (n&nbsp;=&nbsp;330; 62 PSP-P, 171 PD, and 97 control subjects) from an international research group. We developed a new in-house algorithm for MRPI 2.0 calculation and assessed its performance in distinguishing PSP-P from PD and control subjects in both cohorts using receiver operating characteristic curves. Results: The automated MRPI 2.0 showed excellent performance in differentiating patients with PSP-P from patients with PD and control subjects both in the training cohort (area under the receiver operating characteristic curve [AUC]&nbsp;=&nbsp;0.93 [95% confidence interval, 0.89–0.98] and AUC&nbsp;=&nbsp;0.97 [0.93–1.00], respectively) and in the international testing cohort (PSP-P versus PD, AUC&nbsp;=&nbsp;0.92 [0.87–0.97]; PSP-P versus controls, AUC&nbsp;=&nbsp;0.94 [0.90–0.98]), suggesting the generalizability of the results. The automated MRPI 2.0 also accurately distinguished between PSP-P and PD in the early stage of the diseases (AUC&nbsp;=&nbsp;0.91 [0.84–0.97]). A strong correlation (r&nbsp;=&nbsp;0.91, P &lt; 0.001) was found between automated and manual MRPI 2.0 values. Conclusions: Our study provides an automated, validated, and generalizable magnetic resonance biomarker to distinguish PSP-P from PD. The use of the automated MRPI 2.0 algorithm rather than manual measurements could be important to standardize measures in patients with PSP-P across centers, with a positive impact on multicenter studies and clinical trials involving patients from different geographic regions. © 2022 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society