Neuroanatomical subtypes of schizophrenia and relationship with illness duration and deficit status.

BACKGROUND: The heterogeneity of schizophrenia (SCZ) regarding psychopathology, illness trajectory and their inter-relationships with underlying neural substrates remain incompletely understood. In a bid to reduce illness heterogeneity using neural substrates, our study aimed to replicate the findings of an earlier study by Chand et al. (2020). We employed brain structural measures for subtyping SCZ patients, and evaluate each subtype's relationship with clinical features such as illness duration, psychotic psychopathology, and additionally deficit status. METHODS: Overall, 240 subjects (160 SCZ patients, 80 healthy controls) were recruited for this study. The participants underwent brain structural magnetic resonance imaging scans and clinical rating using the Positive and Negative Syndrome Scale. Neuroanatomical subtypes of SCZ were identified using "Heterogeneity through discriminative analysis" (HYDRA), a clustering technique which accounted for relevant covariates and the inter-group normalized percentage changes in brain volume were also calculated. RESULTS: As replicated, two neuroanatomical subtypes (SG-1 and SG-2) were found amongst our patients with SCZ. The subtype SG-1 was associated with enlargements in the third and lateral ventricles, volume increase in the basal ganglia (putamen, caudate, pallidum), longer illness duration, and deficit status. The subtype SG-2 was associated with reductions of cortical and subcortical structures (hippocampus, thalamus, basal ganglia). CONCLUSIONS: These replicated findings have clinical implications in the early intervention, response monitoring, and prognostication of SCZ. Future studies may adopt a multi-modal neuroimaging approach to enhance insights into the neurobiological composition of relevant subtypes.

Presence of enlarged perivascular spaces is associated with reduced processing speed in asymptomatic, working-aged adults.

BACKGROUND: Enlarged perivascular spaces (ePVS) and white matter hyperintensities (WMHs) are recognised neuroimaging lesions for symptomatic and/or occult cerebral small vessel disease (CSVD) that are linked with the predisposition to cardiocerebrovascular risk and neurocognitive impairment. This study aimed to determine the interrelation between the WMHs and ePVS, neurocognition, and cardiocerebrovascular risk profiles in asymptomatic working-aged adults at a single-center population-based cohort. METHODS: Fifty-four asymptomatic subjects (mean age: 39.6 ± 11.6 years) with low-to-moderate cardiocerebrovascular risk measured by QRISK3 prediction score were recruited and underwent neurocognitive evaluation and 3T MRI brain scan. Contour plot with multiple logistic and linear regression were utilized to study the interrelation between the variables. RESULTS: The presence of WMHs and ePVS was associated with hypertension, systolic blood pressure, QRISK3 score, and age, whereby asymptomatic older subjects had higher prevalence for WHMs and ePVS (mean age: WMHs [46.6 ± 12.2 years]; ePVS [43.12 ± 12.2 years]). Higher ePVS load and reduced hippocampal volume among ePVS subjects was associated with reduced processing speed (odd ratio, 1.06; 95% confidence interval: 1.00 to 1.13) and reduced working memory performance (standardized ß coefficients, -0.46 [95% CI: 0.46 to 12.1], p < 0.05), respectively. CONCLUSIONS: Albeit from a single center in the suburban east coast peninsular Malaysia, this study is to first from the region to highlight the subtle impacts of occult CSVD manifestations (WMHs and ePVS) on some aspects of neurocognition in an otherwise asymptomatic, relatively young working-aged adults with low-to-moderate cardiocerebrovascular risk scores.

Machine learning classification of schizophrenia patients and healthy controls using diverse neuroanatomical markers and Ensemble methods.

Schizophrenia is a major psychiatric disorder that imposes enormous clinical burden on patients and their caregivers. Determining classification biomarkers can complement clinical measures and improve understanding of the neural basis underlying schizophrenia. Using neuroanatomical features, several machine learning based investigations have attempted to classify schizophrenia from healthy controls but the range of neuroanatomical measures employed have been limited in range to date. In this study, we sought to classify schizophrenia and healthy control cohorts using a diverse set of neuroanatomical measures (cortical and subcortical volumes, cortical areas and thickness, cortical mean curvature) and adopted Ensemble methods for better performance. Additionally, we correlated such neuroanatomical features with Quality of Life (QoL) assessment scores within the schizophrenia cohort. With Ensemble methods and diverse neuroanatomical measures, we achieved classification accuracies ranging from 83 to 87%, sensitivities and specificities varying between 90-98% and 65-70% respectively. In addition to lower QoL scores within schizophrenia cohort, significant correlations were found between specific neuroanatomical measures and psychological health, social relationship subscale domains of QoL. Our results suggest the utility of inclusion of subcortical and cortical measures and Ensemble methods to achieve better classification performance and their potential impact of parsing out neurobiological correlates of quality of life in schizophrenia.

Aberrant Neurogliovascular Unit Dynamics in Cerebral Small Vessel Disease: A Rheological Clue to Vascular Parkinsonism.

The distinctive anatomical assemble and functionally discrete multicellular cerebrovasculature dynamics confer varying rheological and blood-brain barrier permeabilities to preserve the integrity of cerebral white matter and its neural microenvironment. This homeostasis intricately involves the glymphatic system that manages the flow of interstitial solutes, metabolic waste, and clearance through the venous circulation. As a physiologically integrated neurogliovascular unit (NGVU) serving a particularly vulnerable cerebral white matter (from hypoxia, metabolic insults, infection, and inflammation), a likely insidious process over a lifetime could inflict microenvironment damages that may lead to pathological conditions. Two such conditions, cerebral small vessel disease (CSVD) and vascular parkinsonism (VaP), with poorly understood pathomechanisms, are frequently linked to this brain-wide NGVU. VaP is widely regarded as an atypical parkinsonism, described by cardinal motor manifestations and the presence of cerebrovascular disease, particularly white matter hyperintensities (WMHs) in the basal ganglia and subcortical region. WMHs, in turn, are a recognised imaging spectrum of CSVD manifestations, and in relation to disrupted NGVU, also include enlarged perivascular spaces. Here, in this narrative review, we present and discuss on recent findings that argue for plausible clues between CSVD and VaP by focusing on aberrant multicellular dynamics of a unique integrated NGVU-a crossroad of the immune-vascular-nervous system-which may also extend fresher insights into the elusive interplay between cerebral microvasculature and neurodegeneration, and the potential therapeutic targets.

Deformable Registration-Based Super-resolution for Isotropic Reconstruction of 4-D MRI Volumes.

Multi-plane super-resolution (SR) has been widely employed for resolution improvement of MR images. However, this has mostly been limited to MRI acquisitions with rigid motion. In cases of non-rigid motion, volumes are usually pre-registered using deformable registration methods before SR reconstruction. The pre-registered images are then used as input for the SR reconstruction. Since deformable registration involves smoothening of the inputs, using pre-registered inputs could lead to loss in information in SR reconstructions. Additionally, any registration errors present in pre-registered inputs could propagate throughout SR reconstructions leading to error accumulation. To address these limitations, in this study, we propose a deformable registration-based super-resolution reconstruction (DIRSR) reconstruction, which handles deformable registration as part of super-resolution. This approach has been demonstrated using 12 synthetic 4-D MRI lung datasets created using single plane (coronal) datasets of six patients and multi-plane (coronal and axial) 4-D lung MRI dataset of one patient. From our evaluation, DIRSR reconstructions are sharper and well aligned compared to reconstructions using SR of pre-registered inputs and rigid-registration SR. MSE, SNR and SSIM evaluations also indicate better reconstruction quality from DIRSR compared to reconstructions from SR of pre-registered inputs (p-value less than 0.0001). In conclusion, we found superior isotropic reconstructions of 4-D MR datasets from DIRSR reconstructions, which could benefit volumetric MR analyses.

A preclinical evaluation of an autologous living hyaline-like cartilaginous graft for articular cartilage repair: a pilot study.

In this pilot study, an autologous synthetic scaffold-free construct with hyaline quality, termed living hyaline cartilaginous graft (LhCG), was applied for treating cartilage lesions. Implantation of autologous LhCG was done at load-bearing regions of the knees in skeletally mature mini-pigs for 6 months. Over the course of this study, significant radiographical improvement in LhCG treated sites was observed via magnetic resonance imaging. Furthermore, macroscopic repair was effected by LhCG at endpoint. Microscopic inspection revealed that LhCG engraftment restored cartilage thickness, promoted integration with surrounding native cartilage, produced abundant cartilage-specific matrix molecules, and re-established an intact superficial tangential zone. Importantly, the repair efficacy of LhCG was quantitatively shown to be comparable to native, unaffected cartilage in terms of biochemical composition and biomechanical properties. There were no complications related to the donor site of cartilage biopsy. Collectively, these results imply that LhCG engraftment may be a viable approach for articular cartilage repair.

Diffusion weighted magnetic resonance imaging and its recent trend-a survey.

Since its inception in 1985, diffusion weighted magnetic resonance imaging has been evolving and is becoming instrumental in diagnosis and investigation of tissue functions in various organs including brain, cartilage, and liver. Even though brain related pathology and/or investigation remains as the main application, diffusion weighted magnetic resonance imaging (DWI) is becoming a standard in oncology and in several other applications. This review article provides a brief introduction of diffusion weighted magnetic resonance imaging, challenges involved and recent advancements.