Keywords: Other Neurodegeneration, Nervous system, Autism spectrum disorder,Synthetic MR

Motivation: To comprehend the brain microstructure of ASD patients, with or without Mental Retardation, and differentiate between them.

Goal(s): This article aims to evaluate the differences of T1 and T2 relaxometry in disease related brain regions for children with ASD-MR , ASD group, and HC group, by using Synthetic MRI. 

Approach: MAGiC data were processed in SyMRI to create T1 and T2 relaxometry maps. Two pediatric radiologists outlined regions of interest on these maps using ITK-SNAP.

Results: The T1 in left thalamus could be sensitive to reflect the microstructural change in patient groups and could be helpful indicator to differentiate the ASD and ASD-MR.

Impact: T1 relaxometry derived from Synthetic MRI is potential for differentiation of Autism Spectrum Disorder and Autism Spectrum Disorder with Mental retardation.

Keywords: White Matter, White Matter, Autism Spectrum Disorder; eXtreme Gradient Boosting; Tract-Based Spatial Statistics

Motivation: The diagnosis of Autism Spectrum Disorder (ASD) poses a substantial challenge, primarily due to the lack of a definitive biomarker.

Goal(s): Our primary objective is to uncover white matter irregularities prevalent in pediatric autism.

Approach: Our study leveraged Tract-Based Spatial Statistics (TBSS) analysis to scrutinize deviations in the white matter microstructure in ASD, and we implemented an eXtreme Gradient Boosting (XGBoost) model to effectively differentiate between individuals with ASD and healthy controls.

Results: Through the TBSS analysis, we identified notable disparities between groups. Moreover, the XGBoost model demonstrated exceptional proficiency in accurately classifying individuals with ASD and healthy controls.

Impact: This study delved into the white matter microstructural alterations in individuals with ASD by examining DKI data and its associated white matter tract integrity (WMTI) metrics. Additionally, our machine learning findings offered fresh perspectives toward objectively diagnosing ASD.

Keywords: Epilepsy, Arterial spin labelling, Automatic Subregion Segmentation

Motivation: Evaluating the hippocampal volume and perfusion level is important in the diagnosis of hippocampal sclerosis (HS). However, further observation at the subregion level is difficult. 

Goal(s): To investigate the alterations in hippocampal subregion volume and blood flow in HS patients with an automatic segmentation procedure. 

Approach: T1-MPRAGE and 3D-pCASL images were automatically segmented to quantify the hippocampal subregion volume and blood flow. The diagnostic performance of these subregion quantitative metrics in HS were statistically analyzed.

Results:  The volume (V_CA1) and blood flow (CBF_CA1) of CA1 region are independent factors in diagnosing HS. The combination of V_CA1 and CBF_CA1 has the highest diagnostic performance. 

Impact:  The combination of automatic segmentation and arterial spin labeling offers a quantitative imaging foundation for diagnosing hippocampal sclerosis at the subregion level. This scheme can also be applied to other MR techniques to improve the diagnostic effectiveness in hippocampal research.

Keywords: Epilepsy, Epilepsy, ptx, UHF

Motivation: In one third of patients diagnosed with drug-resistant focal epilepsy 3T MRI cannot identify the causative lesion. Single transmit (1Tx) 7T MRI is more sensitive, but signal dropouts obscure temporal lobes where lesions often occur.

Goal(s): Show feasibility of parallel transmit (pTx) 7T MRI to identify epileptogenic lesions and compare with circularly polarized (CP) 7T MRI.

Approach: 10 patients with drug-resistant focal epilepsy and normal 3T were scanned with pTx and CP 7T MRI.

Results: : pTx images were more uniform than CP. In three cases epileptogenic lesions (focal cortical dysplasia and encephalocele) that had not been visible at 3T were revealed.

Impact: Parallel transmit (pTx) 7T MRI improves lesion detection in drug-resistant focal epilepsy patients. With further validation, this could contribute to surgical decision making, potentially without requiring invasive depth electrodes tests. This would widen access to curative epilepsy surgery.

Keywords: Epilepsy, Epilepsy, MRS, Neurometabolites, Neurotransmission

Motivation: TLE is a common epileptic syndrome. Potential dysregulation in GABAergic and glutamatergic mechanisms in epilepsy include neuronal, glial, and/or neuronal-glial interaction dysfunction, leading to increased seizure risks.

Goal(s): The study aimed to explore the utility of MEGA-PRESS MRS in patients with drug-resistant temporal lobe epilepsy for seizure lateralization.

Approach: In-vivo MRS to assess GABA and Glu levels and video-EEG in drug-resistant unilateral TLE patients for seizure localization.

Results: Concordance between neurometabolites with video-EEG for lateralization demonstrates that the correct classification percentage for GABA was 86.7%, indicating an 86.7% chance that GABA will be able to lateralize the unaffected side as detected by VEEG.

Impact: Clinical utility of MEGA-PRES as a presurgical tool for assessing in-vivo neurometabolic profiles and adding knowledge of the role of GABA and Glu in epilepsy and its interplay

Keywords: Epilepsy, fMRI (resting state), Sleep-related hypermotor epilepsy, graph theory analysis, functional brain network.

Motivation: To investigate the topological properties of brain functional connectomes in patients with sleep-related hypermotor epilepsy (SHE). 

Goal(s): Little is known about the topological organization changes of brain functional networks in SHE patients.

Approach: 57 SHE patients and 54 healthy controls underwent resting-state functional MRI examination. Topological properties of brain networks were identified using graph-based theoretical analysis.

Results: Compared to controls,  SHE patients showed longer characteristic path length (Lp) and lower global efficiency (Eglob), decreased nodal centralities in several regions, and connectivity aberrations. Lp and normalized Lp had positive correlations while Eglob and nodal centralities of thalamus had negative correlations with epilepsy duration.

Impact: The aberrant topological properties in brain functional networks of SHE may provide insights into the pathophysiology of epileptogenesis. The identification and characterization of network changes may contribute to clinical treatment through the disruption or inhibition of these epileptogenic networks.

Keywords: Psychiatric Disorders, fMRI (resting state)

Motivation: The abnormal brain areas in autism spectrum disorder (ASD) patients detected by resting-state functional MRI (RS-fMRI) and 3D-T1 MRI alone are not completely consistent.

Goal(s): To explore the structural and functional coupling change in ASD patients.

Approach: Correlation analyses were conducted between structural and functional measures of the abnormal brain area in ASD and compared with healthy controls.

Results: ASD patients not only had abnormal function in the thalamus and superior frontal gyrus, but also showed the reverse trend of correlation between the gray matter volume and functional indicators compared with healthy controls.

Impact: The abnormal function and reverse trend of correlation between the gray matter volume and functional indicators in the thalamus and superior frontal gyrus compared with healthy controls might provide new perspective for deeply understanding neural mechanisms in autism spectrum disorder.

Keywords: Epilepsy, Epilepsy, Microscopic anisotropy, Hippocampus

Motivation: Surgical outcomes for patients with temporal lobe epilepsy (TLE) are limited by the lack of imaging biomarkers that are sensitive to abnormalities.

Goal(s): Our goal was to assess the sensitivity of diffusion MRI metrics to hippocampal abnormalities in patients with TLE.

Approach: We measured mean diffusivity and microscopic fractional anisotropy in a specific hippocampal subfield in TLE patients and healthy volunteers, then used logistic regression to classify cohorts.

Results: The diffusion model was better at distinguishing between patients and volunteers than typical measurements of hippocampal volume, assessed using receiver operating characteristic curves (area under curve 0.87 vs. 0.71-0.76).

Impact: Advanced diffusion MRI metrics are sensitive to hippocampal abnormalities in temporal lobe epilepsy and may be able to improve surgical outcomes by helping clinicians locate the seizure focus for surgical excision.  

Keywords: Epilepsy, fMRI (resting state), drug-resistant，structural, functional, networks

Motivation: _{Epilepsy is widely regarded as a brain network disorder. However, few studies have investigated the interaction between brain structural networks and functional networks in epilepsy.} 

Goal(s): To investigate the topological alterations of brain networks in children and adolescents with drug-resistant epilepsy.

Approach: Global graph theoretic network measures of global properties, nodal properties and rich club organizational properties were computed.

Results: Aberrant topological attributes and connectivity patterns have been found in DRE. Rich-club connectivity was lower in patients with DRE than that in controls.

Impact: Altered Dc in the left pallidum may provide a new theoretical basis for clinical treatment of DRE. The present findings enhanced our understanding of the neurophysiologic mechanisms associated with DRE.

Keywords: Epilepsy, Brain Connectivity, Spasms, Infantile; Magnetic Resonance Imaging; Imaging; Three-Dimensional; Cerebral Cortex

Motivation: Whether there is micro-structural alteration in the temporal lobe of Infantile epileptic spasms syndrome (IESS) patients is yet to be clarified, of which resulting in severe language function impairment.

Goal(s): To explore the potential mechanism of neurological impairment in children with IESS.

Approach: We conducted a study with BSID-II for clinical evaluation, meanwhile voxel-based morphometry (VBM) for MRI data analysis.

Results: In IESS group, the most significant volume loss of gray matter in right fusiform (Broadman area 21) and middle temporal gyrus (Wernicke's area) were key node for voice recognition, language processing, semantic retrieval, memory, and understanding network.

Impact: The findings of this study light up an anatomical basis for language impairment in children with IESS.

Keywords: Epilepsy, Gray Matter

Motivation: The relationship of grey-matter atrophy in structural epilepsy across various etiologies remains poorly understood. 

Goal(s): To perform volumetric brain MRI analysis in the presence of structural epileptogenic brain lesions. 

Approach: 68 subjects with structural epilepsy were longitudinally imaged, grey-matter volume estimates were derived from SynthSeg segmentations and corrected for structural lesions with manual segmentation. Grey-matter volume change was assessed over five structural etiological groups and related to the Seizure Frequency Score.

Results: Our data show significant correlation between grey-matter volume loss and the Seizure Frequency Score. We could find no clear trend across etiological groups in our primary analysis. 

Impact: Our analysis of grey-matter volume loss in structural epilepsy shows a correlation with the Seizure Frequency Score, supporting the concept of epilepsy-associated neurodegeneration and highlighting the importance of early diagnosis and treatment. 

Keywords: Epilepsy, Diffusion/other diffusion imaging techniques

Motivation: To explore the microstructural changes of hippocampal subregions in temporal lobe epilepsy(TLE) patients.

Goal(s): The microstructure of hippocampal subregion in TLE patients was significantly changed, which would provide imaging basis for the diagnosis of MRI negative TLE patients.

Approach: Using neurite orientation dispersion and density imaging (NODDI) combined with automatic segmentation technology to explore TLE changes in microstructure and volume of hippocampal subregion in patients.

Results: This study demonstrated the ability of NODDI technique to detect the changes of hippocampal microstructure in TLE patients. NDI may be more able to highlight neuronal damage and fiber recombination in TLE patients.

Impact: This study demonstrated the ability of NODDI technique to detect the changes of hippocampal microstructure in TLE patients. NDI may be more able to highlight neuronal damage and fiber recombination in TLE patients.

Keywords: Epilepsy, Epilepsy

Motivation: This study is motivated by the need for better predictive indexs for postoperative outcomes in MRI-negative refractory temporal lobe epilepsy (TLE) patients.

Goal(s): To ascertain whether machine learning models using dynamic regional homogeneity (dReHo) can predict surgical success in these patients.

Approach: The approach involved analyzing resting-state fMRI data from TLE patients and healthy controls, calculating ReHo and dReHo values, and applying these as features in a support vector machine classifier.

Results: The classifier using dReHo achieved 73.3% accuracy in predicting postoperative outcomes, significantly outperforming the ReHo-based model.

Impact: The ability to predict postoperative outcomes using dReHo could guide clinical decision-making and patient counseling, potentially leading to improved management of TLE.

Keywords: White Matter, Pediatric, autism spectrum disorders;Tract-Based Spatial Statistics

Motivation: Many children with autism spectrum disorders(ASD) do not exhibit typical clinical manifestations in their early years, making early diagnosis challenging. 

Goal(s): This study aimed to characterize changes in the brain microstructure of children with ASD through the use of white matter tract integrity (WMTI) metrics.

Approach: Whole-brain and ROI-based methods were applied to analyze differences in DKI-based WMTI metrics between children with ASD and healthy children.

Results: The results revealed that axonal water fraction (AWF) was significantly elevated in the bilateral cerebral hemispheres of children with ASD. Quantitative analysis of the corpus callosum demonstrated its ability to distinguish between ASD and healthy children. 

Impact: New WMTI metrics enhance our understanding of the underlying pathomechanisms of ASD and could serve as early biomarkers for microstructural changes in the brain of ASD.

Keywords: White Matter, White Matter, Autism spectrum disorder; Diffusion kurtosis imaging; White matter tract integrity; Corpus callosum; Machine learning.

Motivation: With the rising incidence of autism spectrum disorder (ASD) and the absence of clear diagnostic biomarkers, there's an urgent need to facilitate early diagnosis and intervention for affected children.

Goal(s): We aimed to investigate microstructural disparities within the corpus callosum of ASD.

Approach: We extracted diffusion parameters in the corpus callosum's genu, body, and splenium. Logistic Regression and Linear Discriminant Analysis models were constructed to assess the diagnostic potential of each parameter.

Results: Significant distinctions in diffusion and white matter tract integrity metrics were observed, and machine learning models revealed the effectiveness of metrics in ASD diagnosis.

Impact: DKI data can be used to evaluate the abnormalities in the microstructure of the corpus callosum in children with ASD and provide objective measurements to diagnose children with ASD.

Keywords: Epilepsy, Perfusion, ASL Perfusion MRI, Lateralization of TLE, Blood Teritorry

Motivation: To enhance lateralization of drug-resistant mesial temporal lobe epilepsy (mTLE) for improved surgery decisions. Using arterial spin labeling (ASL) MRI, this study explores vascular territories to differentiate left and right mTLE.

Goal(s): To assess ASL MRI's potential in distinguishing between mTLE types by studying cerebral blood flow changes. 

Approach: It involves comparing mTLE groups to controls using ASL MRI and vascular territory analysis, identifying specific brain regions affecting lateralization. 

Results: They highlight vascular territory changes crucial in distinguishing mTLE types, emphasizing the clinical significance of ASL MRI. 

Impact: This research may significantly impact treatment decisions, benefitting individuals with challenging mTLE and guiding future epilepsy research.