Neuroanatomical markers of familial risk in adolescents with Conduct Disorder and their unaffected relatives

Background: Previous studies have reported brain structure abnormalities in conduct disorder (CD), but it is unclear whether these neuroanatomical alterations mediate the effects of familial (genetic and environmental) risk for CD. We investigated brain structure in adolescents with CD and their unaffected relatives (URs) to identify neuroanatomical markers of familial risk for CD. Methods: Forty-one adolescents with CD, 24 URs of CD probands, and 38 healthy controls (aged 12-18), underwent structural magnetic resonance imaging. We performed surface-based morphometry analyses, testing for group differences in cortical volume, thickness, surface area, and folding. We also assessed the volume of key subcortical structures. Results: The CD and UR groups both displayed structural alterations (lower surface area and folding) in left inferior parietal cortex compared with controls. In contrast, CD participants showed lower insula and pars opercularis volume than controls, and lower surface area and folding in these regions than controls and URs. The URs showed greater folding in rostral anterior cingulate and inferior temporal cortex than controls and greater medial orbitofrontal folding than CD participants. The surface area and volume differences were not significant when controlling for attention-deficit/hyperactivity disorder comorbidity. There were no group differences in subcortical volumes. Conclusions: These findings suggest that alterations in inferior parietal cortical structure partly mediate the effects of familial risk for CD. These structural changes merit investigation as candidate endophenotypes for CD. Neuroanatomical changes in medial orbitofrontal and anterior cingulate cortex differentiated between URs and the other groups, potentially reflecting neural mechanisms of resilience to CD.</p

Reduced Default Mode Connectivity in Adolescents With Conduct Disorder

Objective: conduct disorder (CD) is characterized by impulsive, aggressive, and antisocial behaviors that may be related to deficits in empathy and moral reasoning. The brain’s default mode network (DMN) has been implicated in self-referential cognitive processes of this kind.Method: we examined connectivity between key nodes of the DMN in 29 male adolescents with CD and 29 age- and sex-matched typically-developing adolescents. We ensured that group differences in DMN connectivity were not explained by comorbidity with other disorders by systematically controlling for the effects of substance use disorders (SUDs), attention-deficit/hyperactivity disorder (ADHD) symptoms, psychopathic traits, and other common mental health problems.Results: only after adjusting for co-occurring ADHD symptoms, the group with CD showed hypo-connectivity between core DMN regions relative to typically-developing controls. ADHD symptoms themselves were associated with DMN hyperconnectivity. There was no effect of psychopathic traits on DMN connectivity in the group with CD, and the key results were unchanged when controlling for SUDs and other common mental health problems.Conclusion: future research should directly investigate the possibility that the aberrant DMN connectivity observed in the current study contributes to CD-related deficits in empathy and moral reasoning, and examine self-referential cognitive processes in CD more generall

The BOLD MRI response of the brain to alterations in arterial blood pressure

The impact of blood pressure changes on cerebral blood flow is an important area of investigation. The cerebral autoregulation mechanism acts to maintain blood supply to the brain, despite changes in blood pressure. Blood flow alterations are closely linked to neuronal activation, and this activity can be visualised using blood oxygenation level dependent magnetic resonance imaging (BOLD MRI) – functional MRI. The aim of this project is to investigate the effect of dynamic blood pressure stimuli on the BOLD MRI signal in the brain. Two blood pressure stimuli were employed; thigh cuff deflation and the Valsalva manoeuvre. BOLD MRI signal changes were measured throughout both challenges. Arterial and venous blood pressure and tympanic membrane displacement (TMD) measurements were also made during these challenges. Blood pressure data was used to drive two linked models. The first model represented cerebral vascular physiology (Ursino) and this fed into a second model (Buxton), which predicted the resulting BOLD signal changes. This allowed comparison with experimental BOLD data. TMD data was also compared to intracranial pressure changes predicted by the Ursino model. The experimental BOLD data was found to agree reasonably well with the BOLD signal changes predicted by the modelling. BOLD signal changes are most influenced by deoxyhaemoglobin changes, predominantly as a result of blood flow alterations during the blood pressure challenges, which are not immediately compensated for by the autoregulation mechanism. TMD changes did not reflect intracranial pressure changes predicted by the modelling. In conclusion, if such blood pressure changes do occur during a functional MRI experiment, they may cause changes in the BOLD signal that are not due to neuronal activation. These signal changes may be employed to investigate the cerebral autoregulation mechanism across the brain, or to correct for inaccuracies in functional MRI data in patients with impaired cerebral autoregulatio

Automatic veins analysis of susceptibility weighted image in hypoxic-ischaemic encephalopathy

Background and objective: the purpose of this study is to evaluate venous vascular structure and distribution as prognostic indicators of developmental outcomes for infants with neonatal hypoxic-ischaemic encephalopathy (HIE) by detecting and analysing ridges representing vessels on susceptibility-weighted magnetic resonance images (SWIs). Methods: forty-two infants with neonatal HIE underwent SWI in the neonatal period and neurodevelopmental assessment at age 2 years. Normalised histograms of the width, intensity, length and Hessian eigenvalues extracted from the ridge analysis of each patient's SWI are applied as feature vectors to feed into supervised classifiers such as the kNN and random forest (RF) classifiers to predict their neurodevelopmental outcomes. Here we also propose a supervised classifier for automatic prognosis of automated detection of SWI signs of HIE. Our classifier proposed in this paper demonstrates a superior performance in HIE prognosis for the datasets associated with cognitive and motor outcomes and it also enables to determination of brain regions which have been affected by hypoxia-ischaemia by extracting appropriate features from SWI images. Results: the feature vectors containing width, intensity, length, and eigenvalue show a promising classification accuracy of 78.67% ± 2.58Linear regression, polynomial regression, and support vector regression (SVR) models predicted outcomes and the lower mean relative errors (MRE) for motor and cognitive outcomes are 0.088 ± 0.073 and 0.101 ± 0.11 respectively. Conclusion: the features derived from the vascular ridges improve the prognostic value of SWI in HIE. Our findings suggest that it is possible to predict neurological, motor, and cognitive outcomes by numerical analysis of neonatal SW images and to identify brain regions on SWI affected by hypoxia-ischaemia.</p

Neuroanatomical markers of familial risk in adolescents with Conduct Disorder and their unaffected relatives

Background: Previous studies have reported brain structure abnormalities in conduct disorder (CD), but it is unclear whether these neuroanatomical alterations mediate the effects of familial (genetic and environmental) risk for CD. We investigated brain structure in adolescents with CD and their unaffected relatives (URs) to identify neuroanatomical markers of familial risk for CD. Methods: Forty-one adolescents with CD, 24 URs of CD probands, and 38 healthy controls (aged 12-18), underwent structural magnetic resonance imaging. We performed surface-based morphometry analyses, testing for group differences in cortical volume, thickness, surface area, and folding. We also assessed the volume of key subcortical structures. Results: The CD and UR groups both displayed structural alterations (lower surface area and folding) in left inferior parietal cortex compared with controls. In contrast, CD participants showed lower insula and pars opercularis volume than controls, and lower surface area and folding in these regions than controls and URs. The URs showed greater folding in rostral anterior cingulate and inferior temporal cortex than controls and greater medial orbitofrontal folding than CD participants. The surface area and volume differences were not significant when controlling for attention-deficit/hyperactivity disorder comorbidity. There were no group differences in subcortical volumes. Conclusions: These findings suggest that alterations in inferior parietal cortical structure partly mediate the effects of familial risk for CD. These structural changes merit investigation as candidate endophenotypes for CD. Neuroanatomical changes in medial orbitofrontal and anterior cingulate cortex differentiated between URs and the other groups, potentially reflecting neural mechanisms of resilience to CD.</p

Hypoxic-ischaemic encephalopathy prognosis using susceptibility weighted image analysis based on histogram orientation gradient

The aim of this study is to analyse the susceptibility-weighted magnetic resonance images (SWI) by using Histogram of Oriented Gradients (HOG) as a global feature to identify areas of the neonatal brain affected by Hypoxic-ischaemic encephalopathy (HIE). 42 infants with neonatal HIE have undergone under SW imaging in the neonatal period and have been investigated through neurodevelopmental assessment at 24 months of age. HOG features are used to represent the whole brain SW images and the region of interest separated from the brain image registration algorithm. We use k-nearest neighbours (kNN) and random forest to classify the SWI images into normal and abnormal groups, and then we compare our results to our previous work. The result shows an effective classification, which achieved an accuracy of 76.25±10.9. Our research suggests that automated analysis of neonatal SWI images can identify brain regions affected by HIE on SWI images and predict motor and cognitive outcomes

A case-control study of the locus coeruleus degeneration in Alzheimer’s disease

The locus coeruleus (LC) is the major source of noradrenaline, which plays a key role in cognition. We aimed to detect the extent of the LC signal attenuation in Alzheimer's disease (AD) patients using a neuromelanin (NM)-sensitive MRI and how it may correlate with inflammatory and autonomic measures. An individually matched case-control study design was employed. 24 patients with AD and 24 age and gender matched controls with no cognitive impairment were recruited. The primary outcome measure was the LC signal intensity indicated by the LC contrast ratio (CR) and measured by the NM-sensitive MRI. Secondary outcome measures included neuropsychometric tests of cognitive state, peripheral inflammatory and autonomic measures. Conditional logistic regression analysis revealed a significant 22% LC-CR reduction in the AD group compared with the control group. However, there was no statistical significance from inflammatory or autonomic measures. This is the largest individually-matched case-control study to visualise the LC degeneration in AD patients. The study revealed significant LC degeneration which holds promise to stratify patients who may benefit from treatment targeting noradrenergic dysfunction.</p

Synovial folds of the lateral atlantoaxial joints:in vivo quantitative assessment using magnetic resonance imaging in healthy volunteers

Study design: analysis of magnetic resonance (MR) images of healthy volunteers.Objective: to develop and validate an imaging protocol and measurement technique to describe the morphology and quantify the dimensions of the synovial folds of the lateral atlantoaxial joints in vivo.Summary of background date: the synovial folds of the lateral atlantoaxial joints are considered to be a potential source of neck pain and headache, especially following whiplash injury. Until recently, it has not been possible to image the synovial folds in vivo and consequently their normal morphology is not fully understood.Methods: MR images of the cervical spine of 17 volunteers (4 male and 13 female) were acquired using a 1.5-tesla scanner. The morphology of the synovial folds at the lateral atlantoaxial joints was described and their presence determined. The volume and cross-sectional area of the ventral and dorsal synovial folds of the right and left lateral atlantoaxial joints were measured and compared. The relationship between the dimensions of the synovial folds and subject age was examined. Twenty synovial folds were measured twice by one observer and once by a second observer for the determination of measurement reliability.Results: there was a significant difference in volume (chi [3] = 17.54, P = 0.000) and cross-sectional area (chi [3] = 18.95, P = 0.000) between the ventral and dorsal synovial folds of the left and right lateral atlantoaxial joints. There was no correlation between synovial fold dimensions and age. The reliability of the measurements ranged from intraclass correlation coefficient 0.95 to 0.99 (intraobserver reliability) and intraclass correlation coefficients 0.75 to 0.82 (interobserver reliability).Conclusion: MR imaging was successfully implemented as a noninvasive method for visualizing the synovial folds of the lateral atlantoaxial joints and quantifying their dimensions in healthy volunteers. The results of this study provide a basis for future studies investigating synovial fold pathology in patients with neck pain and headache

Data supporting the University of Southampton Doctoral thesis &quot;Neuropathology of the Locus Coeruleus in Alzheimer&rsquo;s Disease&quot; focusing on Locus Coeruleus in Alzheimer&rsquo;s disease MRI study data ARUK

Dataset relating to Chapter 3 of PhD thesis &quot;Neuropathology of the Locus Coeruleus in Alzheimer&rsquo;s Disease&quot;. Data presented in SPSS. Data collected from AD and control participants consented and recruited at the Memory Assessment &amp; Research Centre, Southern Health NHSFT. This data contains: Demographic details, medical history, current medications, cognitive and functional assessment scores, blood pressure readings following various tasks designed to elicit autonomic nervous system responses. MR Images obtained at University Hospital Southampton NHSFT and analysed using ImageJ to give Locus coeruleus signal data. Pupil light response measures obtained at Department of Psychology, UoS. SPSS required to view the data. </span

Rule-based deep learning method for prognosis of neonatal hypoxic-ischaemic encephalopathy by using susceptibility weighted image analysis

Susceptibility weighted imaging (SWI) of neonatal hypoxic-ischaemic brain injury can provide assistance in the prognosis of neonatal hypoxic-ischaemic encephalopathy (HIE). We propose a convolutional neural network model to classify SWI images with HIE. Due to the lack of a large dataset, transfer learning method with fine-tuning a pre-trained ResNet 50 is introduced. We randomly select 11 datasets from patients with normal neurology outcomes (n = 31) and patients with abnormal neurology outcomes (n = 11) at 24 months of age to avoid bias in classification due to any imbalance in the data. Then we develop a rule-based system to improve the classification performance, with an accuracy of 0.93 ± 0.09. We also compute heatmaps produced by the Grad-CAM technique to analyze which areas of SWI images contributed more to the classification patients with abnormal neurology outcome, such regions can interpret the relationship between the brain regions affected by hypoxic-ischaemic and neurodevelopmental outcomes of infants with HIE at the age of 2 years