Can we accurately classify schizophrenia patients from healthy controls using magnetic resonance imaging and machine learning?:A multi-method and multi-dataset study

Machine learning is a powerful tool that has previously been used to classify schizophrenia (SZ) patients from healthy controls (HC) using magnetic resonance images. Each study, however, uses different datasets, classification algorithms, and validation techniques. Here, we perform a critical appraisal of the accuracy of machine learning methodologies used in SZ/HC classifications studies by comparing three machine learning algorithms (logistic regression [LR], support vector machines [SVMs], and linear discriminant analysis [LDA]) on three independent datasets (435 subjects total) using two tissue density estimates and cortical thickness (CT). Performance is assessed using 10-fold cross-validation, as well as a held-out validation set. Classification using CT outperformed tissue densities, but there was no clear effect of dataset. LR, SVMs, and LDA each yielded the highest accuracies for a different feature set and validation paradigm, but most accuracies were between 55 and 70%, well below previously reported values. The highest accuracy achieved was 73.5% using CT data and an SVM. Taken together, these results illustrate some of the obstacles to constructing effective disease classifiers, and suggest that tissue densities and CT may not be sufficiently sensitive for SZ/HC classification given current available methodologies and sample sizes

Placenta Imaging Workshop 2018 report:Multiscale and multimodal approaches

The Centre for Medical Image Computing (CMIC) at University College London (UCL) hosted a two-day workshop on placenta imaging on April 12th and 13th 2018. The workshop consisted of 10 invited talks, 3 contributed talks, a poster session, a public interaction session and a panel discussion about the future direction of placental imaging. With approximately 50 placental researchers in attendance, the workshop was a platform for engineers, clinicians and medical experts in the field to network and exchange ideas. Attendees had the chance to explore over 20 posters with subjects ranging from the movement of blood within the placenta to the efficient segmentation of fetal MRI using deep learning tools. UCL public engagement specialists also presented a poster, encouraging attendees to learn more about how to engage patients and the public with their research, creating spaces for mutual learning and dialogue

Variability and magnitude of brain glutamate levels in schizophrenia: a meta and mega-analysis

Glutamatergic dysfunction is implicated in schizophrenia pathoaetiology, but this may vary in extent between patients. It is unclear whether inter-individual variability in glutamate is greater in schizophrenia than the general population. We conducted meta-analyses to assess (1) variability of glutamate measures in patients relative to controls (log coefficient of variation ratio: CVR); (2) standardised mean differences (SMD) using Hedges g; (3) modal distribution of individual-level glutamate data (Hartigan’s unimodality dip test). MEDLINE and EMBASE databases were searched from inception to September 2022 for proton magnetic resonance spectroscopy (1H-MRS) studies reporting glutamate, glutamine or Glx in schizophrenia. 123 studies reporting on 8256 patients and 7532 controls were included. Compared with controls, patients demonstrated greater variability in glutamatergic metabolites in the medial frontal cortex (MFC, glutamate: CVR = 0.15, p < 0.001; glutamine: CVR = 0.15, p = 0.003; Glx: CVR = 0.11, p = 0.002), dorsolateral prefrontal cortex (glutamine: CVR = 0.14, p = 0.05; Glx: CVR = 0.25, p < 0.001) and thalamus (glutamate: CVR = 0.16, p = 0.008; Glx: CVR = 0.19, p = 0.008). Studies in younger, more symptomatic patients were associated with greater variability in the basal ganglia (BG glutamate with age: z = −0.03, p = 0.003, symptoms: z = 0.007, p = 0.02) and temporal lobe (glutamate with age: z = −0.03, p = 0.02), while studies with older, more symptomatic patients associated with greater variability in MFC (glutamate with age: z = 0.01, p = 0.02, glutamine with symptoms: z = 0.01, p = 0.02). For individual patient data, most studies showed a unimodal distribution of glutamatergic metabolites. Meta-analysis of mean differences found lower MFC glutamate (g = −0.15, p = 0.03), higher thalamic glutamine (g = 0.53, p < 0.001) and higher BG Glx in patients relative to controls (g = 0.28, p < 0.001). Proportion of males was negatively associated with MFC glutamate (z = −0.02, p < 0.001) and frontal white matter Glx (z = −0.03, p = 0.02) in patients relative to controls. Patient PANSS total score was positively associated with glutamate SMD in BG (z = 0.01, p = 0.01) and temporal lobe (z = 0.05, p = 0.008). Further research into the mechanisms underlying greater glutamatergic metabolite variability in schizophrenia and their clinical consequences may inform the identification of patient subgroups for future treatment strategies

Using Magnetic Resonance Imaging to Study Neurometabolic and Neuroanatomical Alterations in Patients with Schizophrenia

Schizophrenia is a debilitating mental illness that places a large burden on patients, their families, and society-at-large. The glutamate hypothesis of schizophrenia puts forth a compelling mechanism to characterize features of the illness. To this end, we explored the neurometabolic and neuroanatomical profiles of patients with schizophrenia using magnetic resonance imaging, with a particular focus on the glutamatergic system. First, we explored associative striatum neurometabolite levels using proton magnetic resonance spectroscopy (1H-MRS) within a sample composed of antipsychotic-naïve patients experiencing their first-episode of psychosis (FEP) and age- and sex-matched healthy controls. The FEP group had elevated myo-inositol, choline, and glutamate levels compared to the healthy control group. Second, again within a sample of antipsychotic-naïve patients with FEP and age- and sex-matched healthy controls, we investigated whether elevated levels of glutamatergic neurometabolites within the precommissural dorsal caudate (PDC), as assessed by 1H-MRS, were related to measures of brain structure. In addition to widespread cortical thinning and suggestions of possible precommissural caudate volume (PCV) deficits within the patient group, a negative association between PDC glutamate+glutamine levels and PCV was found in the FEP group. Third, striatal neurometabolite levels were examined using 1H-MRS within a sample of patients with schizophrenia who had undergone long-term antipsychotic treatment and healthy controls. No group differences in neurometabolite levels were identified. Multiple study visits permitted a 1H-MRS reliability assessment. Taken together, the results from this body of work suggest elevated levels of striatal glutamatergic neurometabolites within the early, antipsychotic-naïve stages of schizophrenia, which are contrastingly shown to be comparable to those of healthy controls in the later, medicated stages of illness. Findings also provide evidence for glial activation that may resultantly disrupt glutamatergic tone, as well as a striatal excitotoxic mechanism that may account for some of the vast structural compromise that exists in patients with schizophrenia.Ph.D

Trait impulsivity is not related to post-commissural putamen volumes : A replication study in healthy men

High levels of trait impulsivity are considered a risk factor for substance abuse and drug addiction. We recently found that non-planning trait impulsivity was negatively correlated with post-commissural putamen volumes in men, but not women, using the Karolinska Scales of Personality (KSP). Here, we attempted to replicate this finding in an independent sample using an updated version of the KSP: the Swedish Universities Scales of Personality (SSP). Data from 88 healthy male participants (Mean Age: 28.16 +/- 3.34), who provided structural T1-weighted magnetic resonance images (MRIs) and self-reported SSP impulsivity scores, were analyzed. Striatal sub-region volumes were acquired using the Multiple Automatically Generated Templates (MAGeT-Brain) algorithm. Contrary to our previous findings trait impulsivity measured using SSP was not a significant predictor of post-commissural putamen volumes (beta = .14, df = 84, p = .94). A replication Bayes Factors analysis strongly supported this null result. Consistent with our previous findings, secondary exploratory analyses found no relationship between ventral striatum volumes and SSP trait impulsivity (beta = -.05, df = 84, p = .28). An exploratory analysis of the other striatal compartments showed that there were no significant associations with trait impulsivity. While we could not replicate our previous findings in the current sample, we believe this work will aide future studies aimed at establishing meaningful brain biomarkers for addiction vulnerability in healthy humans

Cortical Amyloid β Deposition and Current Depressive Symptoms in Alzheimer Disease and Mild Cognitive Impairment.

Depressive symptoms are frequently seen in patients with dementia and mild cognitive impairment (MCI). Evidence suggests that there may be a link between current depressive symptoms and Alzheimer disease (AD)-associated pathological changes, such as an increase in cortical amyloid-β (Aβ). However, limited in vivo studies have explored the relationship between current depressive symptoms and cortical Aβ in patients with MCI and AD. Our study, using a large sample of 455 patients with MCI and 153 patients with AD from the Alzheimer's disease Neuroimaging Initiatives, investigated whether current depressive symptoms are related to cortical Aβ deposition. Depressive symptoms were assessed using the Geriatric Depression Scale and Neuropsychiatric Inventory-depression/dysphoria. Cortical Aβ was quantified using positron emission tomography with the Aβ probe(18)F-florbetapir (AV-45).(18)F-florbetapir standardized uptake value ratio (AV-45 SUVR) from the frontal, cingulate, parietal, and temporal regions was estimated. A global AV-45 SUVR, defined as the average of frontal, cingulate, precuneus, and parietal cortex, was also used. We observed that current depressive symptoms were not related to cortical Aβ, after controlling for potential confounds, including history of major depression. We also observed that there was no difference in cortical Aβ between matched participants with high and low depressive symptoms, as well as no difference between matched participants with the presence and absence of depressive symptoms. The association between depression and cortical Aβ deposition does not exist, but the relationship is highly influenced by stressful events in the past, such as previous depressive episodes, and complex interactions of different pathways underlying both depression and dementia

Cortical Amyloid β Deposition and Current Depressive Symptoms in Alzheimer Disease and Mild Cognitive Impairment.

Depressive symptoms are frequently seen in patients with dementia and mild cognitive impairment (MCI). Evidence suggests that there may be a link between current depressive symptoms and Alzheimer disease (AD)-associated pathological changes, such as an increase in cortical amyloid-β (Aβ). However, limited in vivo studies have explored the relationship between current depressive symptoms and cortical Aβ in patients with MCI and AD. Our study, using a large sample of 455 patients with MCI and 153 patients with AD from the Alzheimer's disease Neuroimaging Initiatives, investigated whether current depressive symptoms are related to cortical Aβ deposition. Depressive symptoms were assessed using the Geriatric Depression Scale and Neuropsychiatric Inventory-depression/dysphoria. Cortical Aβ was quantified using positron emission tomography with the Aβ probe(18)F-florbetapir (AV-45).(18)F-florbetapir standardized uptake value ratio (AV-45 SUVR) from the frontal, cingulate, parietal, and temporal regions was estimated. A global AV-45 SUVR, defined as the average of frontal, cingulate, precuneus, and parietal cortex, was also used. We observed that current depressive symptoms were not related to cortical Aβ, after controlling for potential confounds, including history of major depression. We also observed that there was no difference in cortical Aβ between matched participants with high and low depressive symptoms, as well as no difference between matched participants with the presence and absence of depressive symptoms. The association between depression and cortical Aβ deposition does not exist, but the relationship is highly influenced by stressful events in the past, such as previous depressive episodes, and complex interactions of different pathways underlying both depression and dementia

The impact of the Siemens Tim Trio to Prisma upgrade and the addition of volumetric navigators on cortical thickness, structure volume, and 1H-MRS indices: An MRI reliability study with implications for longitudinal study designs

Many magnetic resonance imaging (MRI) measures are being studied longitudinally to explore topics such as biomarker detection and clinical staging. A pertinent concern to longitudinal work is MRI scanner upgrades. When upgrades occur during the course of a longitudinal MRI neuroimaging investigation, there may be an impact on the compatibility of pre- and post-upgrade measures. Similarly, subject motion is another issue that may be detrimental to MRI work and embedding volumetric navigators (vNavs) within acquisition sequences has emerged as a technique that allows for prospective motion correction. Our research group recently underwent an upgrade from a Siemens MAGNETOM 3T Tim Trio system to a Siemens MAGNETOM 3T Prisma Fit system. The goals of the current work were to: 1) investigate the impact of this upgrade on commonly used structural imaging measures and proton magnetic resonance spectroscopy indices (“Prisma Upgrade protocol”) and 2) examine structural imaging measures in a sequence with vNavs alongside a standard acquisition sequence (“vNav protocol”). While high reliability was observed for most of the investigated MRI outputs, suboptimal reliability was observed for certain indices. Across the scanner upgrade, increases in frontal, temporal, and cingulate cortical thickness (CT) and thalamus volume, along with decreases in parietal CT and amygdala, globus pallidus, hippocampus, and striatum volumes, were observed. No significant impact of the upgrade was found in 1H-MRS analyses. Further, CT estimates were found to be larger in MPRAGE acquisitions compared to vNav-MPRAGE acquisitions mainly within temporal areas, while the opposite was found mostly in parietal brain regions. The results from this work should be considered in longitudinal study designs and comparable prospective motion correction investigations are warranted in cases of marked head movement