INTRODUCTION: Interpretation and analysis of magnetic resonance imaging (MRI) scans in clinical settings comprise time-consuming visual ratings and complex neuroimage processing that require trained professionals. To combat these challenges, artificial intelligence (AI) techniques can aid clinicians in interpreting brain MRI for accurate diagnosis of neurodegenerative diseases but they require extensive validation. Thus, the aim of this study was to validate the use of AI-based AQUA (Neurophet Inc., Seoul, Republic of Korea) segmentation software in a Southeast Asian community-based cohort with normal cognition, mild cognitive impairment (MCI) and dementia. METHOD: Study participants belonged to the community-based Biomarker and Cognition Study in Singapore. Participants aged between 30 and 95 years, having cognitive concerns, with no diagnosis of major psychiatric, neurological or systemic disorders who were recruited consecutively between April 2022 and July 2023 were included. Participants underwent neuropsychological assessments and structural MRI, and were classified as cognitively normal, with MCI or with dementia. MRI pre-processing using automated pipelines, along with human-based visual ratings, were compared against AI-based automated AQUA output. Default mode network grey matter (GM) volumes were compared between cognitively normal, MCI and dementia groups. RESULTS: A total of 90 participants (mean age at visit was 63.32±10.96 years) were included in the study (30 cognitively normal, 40 MCI and 20 dementia). Non-parametric Spearman correlation analysis indicated that AQUA-based and human-based visual ratings were correlated with total (ρ=0.66; P<0.0001), periventricular (ρ=0.50; P<0.0001) and deep (ρ=0.57; P<0.0001) white matter hyperintensities (WMH). Additionally, volumetric WMH obtained from AQUA and automated pipelines was also strongly correlated (ρ=0.84; P<0.0001) and these correlations remained after controlling for age at visit, sex and diagnosis. Linear regression analyses illustrated significantly different AQUA-derived default mode network GM volumes between cognitively normal, MCI and dementia groups. Dementia participants had significant atrophy in the posterior cingulate cortex compared to cognitively normal participants (P=0.021; 95% confidence interval [CI] -1.25 to -0.08) and in the hippocampus compared to cognitively normal (P=0.0049; 95% CI -1.05 to -0.16) and MCI participants (P=0.0036; 95% CI -1.02 to -0.17). CONCLUSION Our findings demonstrate high concordance between human-based visual ratings and AQUA-based ratings of WMH. Additionally, the AQUA GM segmentation pipeline showed good differentiation in key regions between cognitively normal, MCI and dementia participants. Based on these findings, the automated AQUA software could aid clinicians in examining MRI scans of patients with cognitive impairment.
Humans ; Cognitive Dysfunction/pathology* ; Magnetic Resonance Imaging/methods* ; Male ; Middle Aged ; Female ; Aged ; Artificial Intelligence ; Software ; Dementia/diagnostic imaging* ; Aged, 80 and over ; Adult ; Singapore ; Neuropsychological Tests ; Brain/pathology* ; Cohort Studies ; Gray Matter/pathology* ; Southeast Asian People

In different stages of schizophrenia (SZ), alterations in gray matter volume (GMV) of patients are normally regulated by various pathological mechanisms. Instead of analyzing stage-specific changes, this study employed a multivariate structural covariance model and sliding-window approach to investigate the illness duration-related developmental trajectory of GMV in SZ. The trajectory is defined as a sequence of brain regions activated by illness duration, represented as a sparsely directed matrix. By applying this approach to structural magnetic resonance imaging data from 145 patients with SZ, we observed a continuous developmental trajectory of GMV from cortical to subcortical regions, with an average change occurring every 0.208 years, covering a time window of 20.176 years. The starting points were widely distributed across all networks, except for the ventral attention network. These findings provide insights into the neuropathological mechanism of SZ with a neuroprogressive model and facilitate the development of process for aided diagnosis and intervention with the starting points.
Humans ; Schizophrenia/pathology* ; Gray Matter/pathology* ; Magnetic Resonance Imaging ; Disease Progression ; Male ; Female ; Brain/pathology* ; Cerebral Cortex/pathology* ; Adult

Gray Matter/diagnostic imaging* ; Cerebral Cortex ; Brain ; Magnetic Resonance Imaging

OBJECTIVES: Prediabetes is associated with an increased risk of cognitive impairment and neurodegenerative diseases. However, the exact mechanism of prediabetes-related brain diseases has not been fully elucidated. The brain structure of patients with prediabetes has been damaged to varying degrees, and these changes may affect the topological characteristics of large-scale brain networks. The structural covariance of connected gray matter has been demonstrated valuable in inferring large-scale structural brain networks. The alterations of gray matter structural covariance networks in prediabetes remain unclear. This study aims to examine the topological features and robustness of gray matter structural covariance networks in prediabetes. METHODS: A total of 48 subjects were enrolled in this study, including 23 patients with prediabetes (the PD group) and 25 age-and sex-matched healthy controls (the Ctr group). All subjects' high-resolution 3D T₁ images of the brain were collected by a 3.0 Tesla MR machine. Mini-mental state examination was used to evaluate the cognitive status of each subject. We calculated the gray matter volume of 116 brain regions with automated anatomical labeling (AAL) template, and constructed gray matter structural covariance networks by thresholding interregional structural correlation matrices as well as graph theoretical analysis. The area under the curve (AUC) in conjunction with permutation testing was employed for testing the differences in network measures, which included small world parameter (Sigma), normalized clustering coefficient (Gamma), normalized path length (Lambda), global efficiency, characteristic path length, local efficiency, mean clustering coefficient, and network robustness parameters. RESULTS: The network in both groups followed small-world characteristics, showing that Sigma was greater than 1, the Lambda was much higher than 1, and Gamma was close to 1. Compared with the Ctr group, the network of the PD group showed increased Sigma, Lambda, and Gamma across a range of network sparsity. The Gamma of the PD group was significantly higher than that in the Ctr group in the network sparsity range of 0.12-0.16, but there was no difference between the 2 groups (all P>0.05). The grey matter network showed an increased characteristic path length and a decreased global efficiency in the PD group, but AUC analysis showed that there was no significant difference between groups (all P>0.05). For the network separation measures, the local efficiency and mean clustering coefficient of the gray matter network in the PD group were significantly increased and AUC analysis also confirmed it (P=0.001 and P=0.004, respectively). In addition, network robustness analysis showed that the grey matter network of the PD group was more vulnerable to random damage (P=0.001). CONCLUSIONS The prediabetic gray matter network shows an increased average clustering coefficient and local efficiency, and is more vulnerable to random damage than the healthy control, suggesting that the topological characteristics of the prediabetes grey matter covariant network have changed (network separation enhanced and network robustness reduced), which may provide new insights into the brain damage relevant to the disease.
Humans ; Gray Matter/diagnostic imaging* ; Prediabetic State ; Magnetic Resonance Imaging ; Cerebral Cortex ; Brain

Objective: To analyze the morphological changes of gray matter in clefts lip and palate (CLP) children using voxel-based morphometric (VBM) and surface-based morphometric (SBM) methods. So as to provide a reference for the neural mechanism of cleft palate speech disorder (CPSD) in CLP population. Methods: A total of 29 CLP children with CPSD who were admitted to Department of Oral & Maxillofacial Plastic & Tramuma Surgery, Capital Medical University School of Stomatology from January 2017 to January 2022 were selected (CLP group), including 9 males and 20 females, aged (9.6±3.2) years (5-17 years old). During the same period, 33 healthy children (healthy control group) were recruited in Beijing Children's Hospital, including 9 males and 24 females, aged (9.6±2.4) years (5-16 years). Results: There were no significant differences in age and gender between the healthy control group and the CLP group (t=-0.07, P=0.944; χ²=0.11, P=0.745). Compared with the healthy control group, the left inferior temporal gyrus, right inferior parietal angular gyrus, and left upper cerebellar gray matter volume in the CLP group were significantly decreased (P<0.05), and the volume of the right medial superior frontal gyrus was significantly increased (P<0.05). The left inferior frontal gyrus insula and the right insula cortical thickness of the subjects in the CLP group were significantly thinner [family-wise error rate (FWER) correction, P=0.035]. The right hemisphere cingulate gyrus isthmus sulcus index increased in the CLP group (FWER correction, P=0.040). Conclusions: CLP children with speech disorder have multiple language-related brain regions with reduced gray matter (GM) volume, decreased cortical thickness, and increased gyrificaition index. The abnormal changes in GM morphology in these brain regions may be related to the characteristics of cleft palate speech disorder in the CLP population.
Adolescent ; Brain ; Child ; Child, Preschool ; Cleft Palate ; Female ; Gray Matter/diagnostic imaging* ; Humans ; Magnetic Resonance Imaging/methods* ; Male ; Speech

Major depressive disorder (MDD) is a main type of mood disorder, characterized by significant and lasting depressed mood. Until now, the pathogenesis of MDD is not clear, but it is certain that biological, psychological, and social factors are involved. Childhood trauma is considered to be an important factor in the development of this disease. Previous studies have found that nearly half of the patients with MDD have experienced childhood trauma, and different types of childhood trauma, gender, and age show different effects on this disease. In addition, the clinical characteristics of MDD patients with childhood trauma are also different, which often have more severe depressive symptoms, higher risk of suicide, and more severe cognitive impairment. The response to antidepressants is also worse. In terms of biological mechanisms and marker characteristics, the serotonin transporter gene and the FKBP prolyl isomerase 5 have been shown to play an important role in MDD and childhood trauma. Moreover, some brain imaging and biomarkers showed specific features, such as changes in gray matter in the dorsal lateral prefrontal cortex, and abnormal changes in hypothalamic-pituitary-adrenal axis function.
Child ; Depressive Disorder, Major ; Gray Matter ; Humans ; Hypothalamo-Hypophyseal System ; Pituitary-Adrenal System ; Suicide

OBJECTIVE: To investigate the intra- and inter-scanner reproducibility of quantitative susceptibility mapping (QSM) of cerebral subcortical nuclei in healthy adults. METHODS: QSM was performed in 21 healthy adults on two different 3.0T MR scanners, and the region of interest (ROI) method was used to measure the magnetic susceptibility value of the left subcortical nuclei (the head of the caudate, putamen, globus pallidus, thalamus, substantia nigra and red nucleus). The intraclass correlation coefficient (ICC) and Bland-Altman method were used to evaluate the inter-scanner and intra-scanner reliability. RESULTS: The ICCs of the susceptibility value ranged from 0.90 to 0.99 for all the subcortical gray nuclei except for the head of the caudate nucleus measured on the same MR scanner by the same observer. Bland-Altman analysis revealed that the points with susceptibility differences for all the subcortical gray nuclei except for substantia nigra located in the 95% CI of limits of agreement for the same MR scanner. The ICCs of the susceptibility value for the inter-scanner was 0.49 (0.08-0.75) for the head of the caudate nuleus, 0.80 (0.57-0.91) for the putamen, 0.77 (0.51-0.90) for the globus pallidus, 0.78 (0.54-0.91) for the thalamus, 0.80 (0.56-0.91) for the substantia nigra and 0.93 (0.83-0.97) for the red nucleus. The points with susceptibility difference (95.2%, 20/21) located in the 95% CI of limits of agreement for the putamen and the thalamus measured on two different MR scanners. CONCLUSIONS The intra-scanner reproducibility of QSM of the subcortical gray nuclei is superior to the inter-scanner reproducibility in healthy adults.
Adult ; Brain/diagnostic imaging* ; Gray Matter ; Humans ; Iron ; Magnetic Resonance Imaging ; Reproducibility of Results ; Substantia Nigra/diagnostic imaging*

OBJECTIVE: Alternate ascending/descending directional navigation (ALADDIN) is a novel arterial spin labeling technique that does not require a separate spin preparation pulse. We sought to compare the normalized cerebral blood flow (nCBF) values obtained by ALADDIN and dynamic susceptibility contrast (DSC) perfusion magnetic resonance imaging (MRI) in patients with primary brain tumors. MATERIALS AND METHODS: Sixteen patients with primary brain tumors underwent MRI scans including contrast-enhanced T1-weighted imaging, DSC perfusion MRI, and ALADDIN. The nCBF values of normal gray matter (GM) and tumor areas were measured by both DSC perfusion MRI and ALADDIN, which were compared by the Wilcoxon signed rank test. Subgroup analyses according to pathology were performed with the Wilcoxon signed rank test. RESULTS: Higher mean nCBF values of GM regions in the bilateral frontal lobe, temporal lobe, and caudate were detected by ALADDIN than by DSC perfusion MRI (p <0.05). In terms of the mean or median nCBF values and the mean of the top 10% nCBF values from tumors, DSC perfusion MRI and ALADDIN did not statistically significantly differ either overall or in each tumor group. CONCLUSION: ALADDIN tended to detect higher nCBF values in normal GM, as well as higher perfusion portions of primary brain tumors, than did DSC perfusion MRI. We believe that the high perfusion signal on ALADDIN can be beneficial in lesion detection and characterization.
Brain Neoplasms ; Cerebrovascular Circulation ; Frontal Lobe ; Glioma ; Gray Matter ; Humans ; Magnetic Resonance Angiography ; Magnetic Resonance Imaging ; Pathology ; Perfusion ; Temporal Lobe

A 65-year-old male patient underwent C-arm fluoroscopy-guided bilateral celiac plexus neurolysis to relieve peritoneal seeding-related pain associated with pancreatic cancer. Following confirmation of spreading, and no intravascular injection of contrast media, 7.5 ml of 0.25% chirocaine was injected in each side. The pain subsided after the block, with no motor or sensory deficits. Subsequently, celiac plexus neurolysis with 99.8% alcohol was performed using a posterolateral approach under fluoroscopic guidance. The patient was instructed to maintain a prone position for 2 hours while the procedure was performed. Approximately 4 hours later, the patient experienced paralysis of both lower extremities and hypoesthesia. Emergent magnetic resonance imaging of the thoracic and lumbar spine revealed gray matter signal change in the cord and conus medullaris at the T10-L1 level, and decreased perfusion at the T11-T12 vertebral bodies, suggesting spinal cord infarction. The patient remained paraplegic until his death 24 days later.
Aged ; Celiac Plexus* ; Contrast Media ; Gray Matter ; Humans ; Hypesthesia ; Infarction ; Lower Extremity ; Magnetic Resonance Imaging ; Male ; Pancreatic Neoplasms* ; Paralysis ; Paraplegia* ; Perfusion ; Prone Position ; Spinal Cord ; Spine

OBJECTIVE: To compare apparent diffusion coefficients (ADCs) of brain segments by using two diffusion-weighted imaging acquisition modes, single-shot echo-planar imaging (ss-EPI) and read-out-segmented echo-planar imaging (rs-EPI), and to assess their correlation and agreement in healthy controls. MATERIALS AND METHODS: T2-weighted (T2W) images, rs-EPI, and ss-EPI of 30 healthy subjects were acquired using a 3T magnetic resonance scanner. The T2W images were co-registered to the rs-EPI and ss-EPI, which were then segmented into the gray matter (GM), white matter (WM), and cerebrospinal fluid (CSF) to generate masking templates. ADC maps of rs-EPI and ss-EPI were also segmented into the GM, WM, and CSF by using the generated templates. ADCs of rs-EPI and ss-EPI were compared using Student's t tests and correlated using Pearson's correlation coefficients. Bland-Altman plots were used to assess the agreement between acquisitions.
Brain ; Cerebrospinal Fluid ; Diffusion ; Echo-Planar Imaging ; Gray Matter ; Healthy Volunteers ; Magnetic Resonance Imaging ; Masks ; White Matter