Clinical Utility of Machine-Learning Approaches in Schizophrenia: Improving Diagnostic Confidence for Translational Neuroimaging

Machine-learning approaches are becoming commonplace in the neuroimaging literature as potential diagnostic and prognostic tools for the study of clinical populations. However, very few studies provide clinically informative measures to aid in decision-making and resource allocation. Head-to-head comparison of neuroimaging-based multivariate classifiers is an essential first step to promote translation of these tools to clinical practice. We systematically evaluated the classifier performance using back-to-back structural MRI in two field strengths (3- and 7-T) to discriminate patients with schizophrenia (n = 19) from healthy controls (n = 20). Gray matter (GM) and white matter images were used as inputs into a support vector machine to classify patients and control subjects. Seven Tesla classifiers outperformed the 3-T classifiers with accuracy reaching as high as 77% for the 7-T GM classifier compared to 66.6% for the 3-T GM classifier. Furthermore, diagnostic odds ratio (a measure that is not affected by variations in sample characteristics) and number needed to predict (a measure based on Bayesian certainty of a test result) indicated superior performance of the 7-T classifiers, whereby for each correct diagnosis made, the number of patients that need to be examined using the 7-T GM classifier was one less than the number that need to be examined if a different classifier was used. Using a hypothetical example, we highlight how these findings could have significant implications for clinical decision-making. We encourage the reporting of measures proposed here in future studies utilizing machine-learning approaches. This will not only promote the search for an optimum diagnostic tool but also aid in the translation of neuroimaging to clinical use

Cortical folding and the potential for prognostic neuroimaging in schizophrenia

In 41 patients with schizophrenia, we used neuroanatomical information derived from structural imaging to identify patients with more severe illness, characterised by high symptom burden, low processing speed, high degree of illness persistence and lower social and occupational functional capacity. Cortical folding, but not thickness or volume, showed a high discriminatory ability in correctly identifying patients with more severe illness

Altered connectivity of the right anterior insula drives the pain connectome changes in chronic knee osteoarthritis

Resting-state functional connectivity (FC) has proven a powerful approach to understand the neural underpinnings of chronic pain, reporting altered connectivity in three main networks: the default mode (DMN), central executive (CEN), and the salience network (SN). The interrelation and possible mechanisms of these changes are less well understood in chronic pain. Based on emerging evidence of its role to drive switches between network states, the right anterior insula (rAI, an SN hub) may play a dominant role in network connectivity changes underpinning chronic pain. To test this hypothesis, we used seed-based resting-state FC analysis including dynamic and effective connectivity metrics in 25 people with chronic osteoarthritis (OA) pain and 19 matched healthy volunteers. Compared to controls, participants with painful knee OA presented with increased anticorrelation between the right anterior insula (SN) and DMN regions. Also, the left dorsal prefrontal cortex (CEN hub) showed more negative FC with the right temporal gyrus. Granger causality analysis revealed increased negative influence of the right anterior insula on the posterior cingulate (DMN) in OA patients in line with the observed enhanced anticorrelation. Moreover, dynamic FC was lower in the DMN of patients and thus more similar to temporal dynamics of the SN. Together, these findings evidence a widespread network disruption in patients with persistent osteoarthritis pain, and point toward a driving role of the rAI

Structural covariance and cortical reorganization in schizophrenia: a MRI-based morphometric study

Background: In patients with schizophrenia, distributed abnormalities are observed in grey matter volume. A recent hypothesis posits that these distributed changes are indicative of a plastic reorganization process occurring in response to a functional defect in neuronal information transmission. We investigated the structural covariance across various brain regions in early-stage schizophrenia to determine if indeed the observed patterns of volumetric loss conform to a coordinated pattern of structural reorganization. Methods: Structural MRI scans were obtained from 40 healthy adults and 41 age, gender and parental socioeconomic status matched patients with schizophrenia. Volumes of grey matter tissue was estimated at regional level across 90 atlas-based parcellations. Group level structural covariance was studied using a graph theoretical framework. Results: Patients had distributed reduction in grey matter volume, with high degree of localized covariance (clustering) compared to controls. Patients with schizophrenia had reduced centrality of anterior cingulate and insula but increased centrality of the fusiform cortex, compared to controls. Simulating targeted removal of highly central nodes resulted in significant loss of the overall covariance patterns in patients compared to controls. Conclusion: Regional volumetric deficits in schizophrenia are not a result of random, mutually independent processes. Our observations support the occurrence of a spatially interconnected reorganization with systematic de-escalation of conventional ‘hub’ regions. This raises the question of whether the morphological architecture in schizophrenia is primed for compensatory functions, albeit with a high risk of inefficiency

Manganese-enhanced magnetic resonance imaging depicts brain activity in models of acute and chronic pain: a new window to study experimental spontaneous pain?

Application of functional imaging techniques to animal models is vital to understand pain mechanisms, but is often confounded by the need to limit movement artefacts with anaesthesia, and a focus on evoked responses rather than clinically relevant spontaneous pain and related hyperalgesia. The aim of the present study was to investigate the potential of manganese-enhanced magnetic resonance imaging (MEMRI) to measure neural responses during on-going pain that underpins hyperalgesia in pre-clinical models of nociception. As a proof of concept that MEMRI is sensitive to the neural activity of spontaneous, intermittent behaviour, we studied a separate positive control group undergoing a voluntary running wheel experiment. In the pain models, pain behaviour (weight bearing asymmetry and hindpaw withdrawal thresholds (PWTs)) was measured at baseline and following either intra-articular injection of nerve growth factor (NGF, 10 µg/50 µl; acute pain model, n=4 rats per group), or the chondrocyte toxin monosodium iodoacetate (MIA, 1 mg/50 µl; chronic model, n=8 rats per group), or control injection. Separate groups of rats underwent a voluntary wheel running protocol (n=8 rats per group). Rats were administered with paramagnetic ion Mn2+ as soluble MnCl2 over seven days (subcutaneous osmotic pump) to allow cumulative activity-dependent neural accumulation in the models of pain, or over a period of running. T1-weighted MR imaging at 7 T was performed under isoflurane anaesthesia using a receive-only rat head coil in combination with a 72 mm volume coil for excitation. The pain models resulted in weight bearing asymmetry (NGF: 20.0 ± 5.2%, MIA: 15 ± 3%), and a reduction in PWT in the MIA model (8.3 ± 1.5 g) on the final day of assessment before undergoing MR imaging. Voxel-wise and region-based analysis of MEMRI data did not identify group differences in T1 signal. However, MnCl2 accumulation in the VTA, right Ce amygdala, and left cingulate was negatively correlated with pain responses (greater differences in weight bearing), similarly MnCl2 accumulation was reduced in the VTA in line with hyperalgesia (lower PWTs), which suggests reduced regional activation as a result of the intensity and duration of pain experienced during the 7 days of MnCl2 exposure. Motor cortex T1-weighted signal increase was associated with the distance ran in the wheel running study, while no between group difference was seen. Our data suggest that on-going pain related signal changes identified using MEMRI offers a new window to study the neural underpinnings of spontaneous pain in rats

Brain perfusion patterns are altered in chronic knee pain:a spatial covariance analysis of arterial spin labelling MRI

Chronic musculoskeletal pain is a common problem globally. Current evidence suggests that maladapted central pain pathways are associated with pain chronicity, for example, in postoperative pain after knee replacement. Other factors such as low mood, anxiety, and tendency to catastrophize are also important contributors. We aimed to investigate brain imaging features that underpin pain chronicity based on multivariate pattern analysis of cerebral blood flow (CBF), as a marker of maladaptive brain changes. This was achieved by identifying CBF patterns that discriminate chronic pain from pain-free conditions and by exploring their explanatory power for factors thought to drive pain chronification. In 44 chronic knee pain and 29 pain-free participants, we acquired both CBF and T1-weighted data. Participants completed questionnaires related to affective processes and pressure and cuff algometry to assess pain sensitization. Two factor scores were extracted from these scores representing negative affect and pain sensitization. A spatial covariance principal component analysis of CBF identified 5 components that significantly discriminated chronic pain participants from controls, with the unified network achieving 0.83 discriminatory accuracy (area under the curve). In chronic knee pain, significant patterns of relative hypoperfusion were evident in anterior default-mode and salience network hubs, while hyperperfusion was seen in posterior default mode, thalamus, and sensory regions. One component correlated positively with the pain sensitization score (r = 0.43, P = 0.006), suggesting that this CBF pattern reflects neural activity changes encoding pain sensitization. Here, we report a distinct chronic knee pain-related representation of CBF, pointing toward a brain signature underpinning central aspects of pain sensitization

Medio‐dorsal thalamic dysconnectivity in chronic knee pain: A possible mechanism for negative affect and pain comorbidity

The reciprocal interaction between pain and negative affect is acknowledged but pain-related alterations in brain circuits involved in this interaction, such as the mediodorsal thalamus (MDThal), still require a better understanding. We sought to investigate the relationship between MDThal circuitry, negative affect and pain severity in chronic musculoskeletal pain. For these analyses, participants with chronic knee pain (CKP, n = 74) and without (n = 36) completed magnetic resonance imaging scans and questionnaires. Seed-based MDThal functional connectivity (FC) was compared between groups. Within CKP group, we assessed the interdependence of MDThal FC with negative affect. Finally, post hoc moderation analysis explored whether burden of pain influences affect-related MDThal FC. The CKP group showed altered MDThal FC to hippocampus, ventromedial prefrontal cortex and subgenual anterior cingulate. Furthermore, in CKP group, MDThal connectivity correlated significantly with negative affect in several brain regions, most notably the medial prefrontal cortex, and this association was stronger with increasing pain burden and absent in pain-free controls. In conclusion, we demonstrate mediodorsal thalamo-cortical dysconnectivity in chronic pain with areas linked to mood disorders and associations of MDThal FC with negative affect. Moreover, burden of pain seems to enhance affect sensitivity of MDThal FC. These findings suggest mediodorsal thalamic network changes as possible drivers of the detrimental interplay between chronic pain and negative affect

Connectivity-Guided Theta Burst Transcranial Magnetic Stimulation Versus Repetitive Transcranial Magnetic Stimulation for Treatment-Resistant Moderate to Severe Depression: Magnetic Resonance Imaging Protocol and SARS-CoV-2–Induced Changes for a Randomized Double-blind Controlled Trial

Background:Depression is a significant health and economic burden. In approximately one third of patients, depression is resistant to first line treatments and therefore it is essential that alternative treatments are found. Transcranial magnetic stimulation (TMS) is a neuromodulatory treatment involving the application of magnetic pulses to the brain that is approved in the UK and the US in treatment resistant depression. This trial aims to compare the clinical effectiveness, cost-effectiveness and mechanism of action between standard treatment repetitive TMS (rTMS) targeted at the F3 EEG site, with a newer treatment – a type of TMS called theta-burst stimulation (TBS) targeted based on measures of functional brain connectivity. This protocol outlines the brain imaging acquisition and analysis for the BRIGhTMIND trial that is used to create personalised TMS targets and answer the proposed mechanistic hypotheses.Objective:The objectives of the imaging arm of the BRIGhTMIND study are to identify functional and neurochemical brain signatures indexing the treatment mechanisms of rTMS and cgiTBS and to identify imaging-based markers predicting response to treatment.Methods:The study is a randomised double-blind controlled trial with 1:1 allocation to either 20 sessions of a) TBS or b) standard rTMS. Multimodal magnetic resonance imaging (MRI) is acquired per participant at baseline (prior to TMS treatment) with T1-weighted and task-free functional MRI during rest (rsfMRI) utilised to estimate TMS targets. For participants enrolled in the mechanistic substudy additional diffusion-weighted, sequences are acquired at baseline and at post-treatment follow-up 16 weeks after treatment randomisation. Core datasets of T1-weighted and task-free functional MRI during rest (rsfMRI) are acquired for all participants and utilised to estimate TMS targets. Additional sequences of arterial spin labelling, magnetic resonance spectroscopy and diffusion-weighted images are acquired dependent on recruitment site for mechanistic evaluation. Standard rTMS treatment is targeted at the F3 electrode site over the left dorsolateral prefrontal cortex whilst TBS treatment is guided using the coordinate of peak effective connectivity from the right anterior insula to the left dorsolateral prefrontal cortex. Both treatment targets benefit from a level of MRI-guidance but only TBS is provided with precision targeting based on functional brain connectivity.Results:Recruitment began January 2019 and is ongoing. Data collection is expected to continue until January 2023.Conclusions:This trial will determine the impact of precision MRI guidance on rTMS treatment, and furthermore, assess the neural mechanisms underlying this treatment in treatment resistant depressed patients. Clinical Trial: International Standard Randomized Controlled Trial Number (ISRCTN) 19674644; https://www.isrctn.com/ISRCTN19674644. Registered 2nd October 2018

Connectivity guided theta burst transcranial magnetic stimulation versus repetitive transcranial magnetic stimulation for treatment-resistant moderate to severe depression: study protocol for a randomised double-blind controlled trial (BRIGhTMIND)

Introduction The BRIGhTMIND study aims to determine the clinical effectiveness, cost effectiveness and mechanism of action of connectivity guided intermittent Theta Burst Stimulation (cgiTBS) versus standard repetitive Transcranial Magnetic Stimulation (rTMS) in adults with moderate to severe treatment resistant depression. Methods and analysis The study is a randomised double-blind controlled trial with 1:1 allocation to either 20 sessions of (a) cgiTBS or (b) neuronavigated rTMS not using connectivity guidance. A total of 368 eligible participants with a diagnosis of current unipolar major depressive disorder that is both treatment resistant (defined as scoring 2 or more on the Massachusetts General Hospital (MGH) Staging Score) and moderate to severe (scoring >16 on the 17-item Hamilton Depression Rating Scale (HDRS-17)), will be recruited from primary and secondary care settings at four treatment centres in the United Kingdom. The primary outcome is depression response at 16 weeks (50% or greater reduction in HDRS-17 score from baseline). Secondary outcomes include assessments of self-rated depression, anxiety, psychosocial functioning, cognition and quality of life at 8, 16 and 26 weeks post randomisation. Cost effectiveness, patient acceptability, safety, mechanism of action and predictors of response will also be examined

Structural connectivity of the salience-executive loop in schizophrenia

Previously, differences have been shown in effective connectivity of the salience network between healthy controls and patients with schizophrenia. Specifically, the right anterior insula (rAI) fails to modulate the dorsolateral prefrontal cortex (DLPFC). In 35 controls and 31 patients with schizophrenia, we extended these findings by investigating the white matter connectivity of this pathway using tractography, and its relationship with the disrupted effective connectivity. We showed increased fractional anisotropy in the pathway connecting the rAI with the DLPFC, which related to reduced effective connectivity. This may be due to either secondary changes in white matter or a primary defect in structural integrity resulting from deficient axonal pruning. This novel finding warrants further investigation of white matter connectivity in schizophrenia and the mechanisms underlying this pathophysiology