A pilot cross-sectional investigation of symptom clusters and associations with patient-reported outcomes in Myalgic Encephalomyelitis/Chronic Fatigue Syndrome and Post COVID-19 Condition.

BACKGROUND: Myalgic Encephalomyelitis/Chronic Fatigue Syndrome (ME/CFS) is associated with long-term disability and poor quality of life (QoL). Cardinal ME/CFS symptoms (including post-exertional malaise, cognitive dysfunction and sleep disturbances) have been observed in Post COVID-19 Condition (PCC). To gain further insight into the potential role of ME/CFS as a post-COVID-19 sequela, this study investigates associations between symptoms and patient-reported outcomes, as well as symptom clusters. METHODS: Participants included Australian residents aged between 18 and 65 years formally diagnosed with ME/CFS fulfilling the Canadian or International Consensus Criteria or PCC meeting the World Health Organization case definition. Validated, self-administered questionnaires collected participants' sociodemographic and illness characteristics, symptoms, QoL and functional capacity. Associations between symptoms and patient-reported outcomes were investigated with multivariate linear regression models. Hierarchical cluster analysis was performed to identify symptom clusters. RESULTS: Most people with ME/CFS (pwME/CFS) and people with PCC (pwPCC) were female (n = 48/60, 80.0% and n = 19/30, 63.3%, respectively; p = 0.12). PwME/CFS were significantly younger (x̄=41.75, s = 12.91 years) than pwPCC (x̄=48.13, s =10.05 years; p =0.017). Autonomic symptoms (notably dyspnoea) were associated with poorer scores in most patient-reported outcome domains for both cohorts. None of the four symptom clusters identified were unique to ME/CFS or PCC. Clusters were largely delineated by the presence of gastrointestinal and neurosensory symptoms, illness duration, ME/CFS criteria met and total symptoms. CONCLUSIONS: Illness duration may explain differences in symptom burden between pwME/CFS and pwPCC. PCC diagnostic criteria must be refined to distinguish pwPCC at risk of long-term ME/CFS-like illness and subsequently deliver necessary care and support.

Post COVID-19 Condition (PCC), or Long COVID, refers to the ongoing symptoms experienced after acute COVID-19 illness. The symptoms reported by people with PCC (pwPCC) resemble Myalgic Encephalomyelitis/Chronic Fatigue Syndrome (ME/CFS). However, existing diagnostic criteria for PCC are broad and cannot discern PCC subtypes (such as pwPCC experiencing ME/CFS-like illness), which may require different approaches to care. This study contributes to improving PCC case criteria and approaches to care for both ME/CFS and PCC by investigating the relationships between symptoms and patient-reported outcomes among pwPCC and people with ME/CFS (pwME/CFS).For both cohorts, symptoms had a negative relationship with all aspects of health. Autonomic symptoms, notably breathing issues, returned the most negative associations. Pain, flu-like symptoms and lack of temperature control appeared more burdensome among pwPCC. These symptoms may signify the early stages of ME/CFS. Symptom clusters were also identified for the first time among a combined cohort of pwME/CFS and pwPCC in this study. Importantly, none of the symptom clusters were specific to ME/CFS or PCC. Instead, symptom clusters were defined by the prevalence of gastrointestinal and neurosensory symptoms, illness duration, ME/CFS criteria met and the total number of symptoms.This study suggests that the few differences between ME/CFS and PCC may be explained by illness duration. These findings further implicate ME/CFS as a potential post-COVID-19 outcome. As ME/CFS is associated with profound reductions in quality of life and functioning, identifying pwPCC experiencing ME/CFS-like illness through refined diagnostic criteria must be prioritised to ensure the delivery of necessary care.

Illness presentation and quality of life in myalgic encephalomyelitis/chronic fatigue syndrome and post COVID-19 condition: a pilot Australian cross-sectional study.

PURPOSE: Post COVID-19 Condition (PCC), being persistent COVID-19 symptoms, is reminiscent of Myalgic Encephalomyelitis/Chronic Fatigue Syndrome (ME/CFS)-a chronic multi-systemic illness characterised by neurocognitive, autonomic, endocrinological and immunological disturbances. This novel cross-sectional investigation aims to: (1) compare symptoms among people with ME/CFS (pwME/CFS) and people with PCC (pwPCC) to inform developing PCC diagnostic criteria; and (2) compare health outcomes between patients and people without acute or chronic illness (controls) to highlight the illness burdens of ME/CFS and PCC. METHODS: Sociodemographic and health outcome data were collected from n = 61 pwME/CFS, n = 31 pwPCC and n = 54 controls via validated, self-administered questionnaires, including the 36-Item Short-Form Health Survey version 2 (SF-36v2) and World Health Organization Disability Assessment Schedule version 2.0 (WHODAS 2.0). PwME/CFS and pwPCC also provided self-reported severity and frequency of symptoms derived from the Canadian and International Consensus Criteria for ME/CFS and the World Health Organization case definition for PCC. RESULTS: Both illness cohorts similarly experienced key ME/CFS symptoms. Few differences in symptoms were observed, with memory disturbances, muscle weakness, lymphadenopathy and nausea more prevalent, light-headedness more severe, unrefreshed sleep more frequent, and heart palpitations less frequent among pwME/CFS (all p < 0.05). The ME/CFS and PCC participants' SF-36v2 or WHODAS 2.0 scores were comparable (all p > 0.05); however, both cohorts returned significantly lower scores in all SF-36v2 and WHODAS 2.0 domains when compared with controls (all p < 0.001). CONCLUSION: This Australian-first investigation demonstrates the congruent and debilitating nature of ME/CFS and PCC, thereby emphasising the need for multidisciplinary care to maximise patient health outcomes.

Imbalanced Brain Neurochemicals in Long COVID and ME/CFS: A Preliminary Study Using MRI.

PURPOSE: Long COVID and myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) patients experience multiple complex symptoms, potentially linked to imbalances in brain neurochemicals. This study aims to measure brain neurochemical levels in long COVID and ME/CFS patients as well as healthy controls to investigate associations with severity measures. METHODS: Magnetic resonance spectroscopy data were acquired with a 3T Prisma magnetic resonance imaging scanner (Siemens Healthcare, Erlangen, Germany). We measured absolute levels of brain neurochemicals in the posterior cingulate cortex in long COVID (n = 17), ME/CFS (n = 17), and healthy controls (n = 10) using Osprey software. The statistical analyses were performed using SPSS version 29 (IBM, Armonk, NY). Age and sex were included as nuisance covariates. RESULTS: Glutamate levels were significantly higher in patients with long COVID (P = .02) and ME/CFS (P = .017) than in healthy controls. No significant difference was found between the 2 patient cohorts. Additionally, N-acetyl-aspartate levels were significantly higher in long COVID patients (P = .012). Importantly, brain neurochemical levels were associated with self-reported severity measures in long COVID and ME/CFS. CONCLUSION: Our study identified significantly elevated glutamate and N-acetyl-aspartate levels in long COVID and ME/CFS patients compared with healthy controls. No significant differences in brain neurochemicals were observed between the 2 patient cohorts, suggesting a potential overlap in their underlying pathology. These findings suggest that imbalanced neurochemicals contribute to the complex symptoms experienced by long COVID and ME/CFS patients.

Altered brain connectivity in Long Covid during cognitive exertion: a pilot study.

Introduction: Debilitating Long-Covid symptoms occur frequently after SARS-COVID-19 infection. Methods: Functional MRI was acquired in 10 Long Covid (LCov) and 13 healthy controls (HC) with a 7 Tesla scanner during a cognitive (Stroop color-word) task. BOLD time series were computed for 7 salience and 4 default-mode network hubs, 2 hippocampus and 7 brainstem regions (ROIs). Connectivity was characterized by the correlation coefficient between each pair of ROI BOLD time series. We tested for HC versus LCov differences in connectivity between each pair of the 20 regions (ROI-to-ROI) and between each ROI and the rest of the brain (ROI-to-voxel). For LCov, we also performed regressions of ROI-to-ROI connectivity with clinical scores. Results: Two ROI-to-ROI connectivities differed between HC and LCov. Both involved the brainstem rostral medulla, one connection to the midbrain, another to a DM network hub. Both were stronger in LCov than HC. ROI-to-voxel analysis detected multiple other regions where LCov connectivity differed from HC located in all major lobes. Most, but not all connections, were weaker in LCov than HC. LCov, but not HC connectivity, was correlated with clinical scores for disability and autonomic function and involved brainstem ROI. Discussion: Multiple connectivity differences and clinical correlations involved brainstem ROIs. Stronger connectivity in LCov between the medulla and midbrain may reflect a compensatory response. This brainstem circuit regulates cortical arousal, autonomic function and the sleep-wake cycle. In contrast, this circuit exhibited weaker connectivity in ME/CFS. LCov connectivity regressions with disability and autonomic scores were consistent with altered brainstem connectivity in LCov.

Biomarkers for myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS): a systematic review.

BACKGROUND: Myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) is a multifaceted condition that affects most body systems. There is currently no known diagnostic biomarker; instead, diagnosis is dependent on application of symptom-based case criteria following exclusion of any other potential medical conditions. While there are some studies that report potential biomarkers for ME/CFS, their efficacy has not been validated. The aim of this systematic review is to collate and appraise literature pertaining to a potential biomarker(s) which may effectively differentiate ME/CFS patients from healthy controls. METHODS: This systematic review was conducted according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses and Cochrane review guidelines. PubMed, Embase and Scopus were systematically searched for articles containing "biomarker" and "ME/CFS" keywords in the abstract or title and if they included the following criteria: (1) were observational studies published between December 1994 and April 2022; (2) involved adult human participants; (3) full text is available in English (4) original research; (5) diagnosis of ME/CFS patients made according to the Fukuda criteria (1994), Canadian Consensus Criteria (2003), International Consensus Criteria (2011) or Institute of Medicine Criteria (2015); (6) study investigated potential biomarkers of ME/CFS compared to healthy controls. Quality and Bias were assessed using the Joanna Briggs Institute Critical Appraisal Checklist for Case Control Studies. RESULTS: A total of 101 publications were included in this systematic review. Potential biomarkers ranged from genetic/epigenetic (19.8%), immunological (29.7%), metabolomics/mitochondrial/microbiome (14.85%), endovascular/circulatory (17.82%), neurological (7.92%), ion channel (8.91%) and physical dysfunction biomarkers (8.91%). Most of the potential biomarkers reported were blood-based (79.2%). Use of lymphocytes as a model to investigate ME/CFS pathology was prominent among immune-based biomarkers. Most biomarkers had secondary (43.56%) or tertiary (54.47%) selectivity, which is the ability for the biomarker to identify a disease-causing agent, and a moderate (59.40%) to complex (39.60%) ease-of-detection, including the requirement of specialised equipment. CONCLUSIONS: All potential ME/CFS biomarkers differed in efficiency, quality, and translatability as a diagnostic marker. Reproducibility of findings between the included publications were limited, however, several studies validated the involvement of immune dysfunction in the pathology of ME/CFS and the use of lymphocytes as a model to investigate the pathomechanism of illness. The heterogeneity shown across many of the included studies highlights the need for multidisciplinary research and uniform protocols in ME/CFS biomarker research.

Brainstem volume changes in myalgic encephalomyelitis/chronic fatigue syndrome and long COVID patients.

Myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) and long COVID patients have overlapping neurological, autonomic, pain, and post-exertional symptoms. We compared volumes of brainstem regions for 10 ME/CFS (CCC or ICC criteria), 8 long COVID (WHO Delphi consensus), and 10 healthy control (HC) subjects on 3D, T1-weighted MRI images acquired using sub-millimeter isotropic resolution using an ultra-high field strength of 7 Tesla. Group comparisons with HC detected significantly larger volumes in ME/CFS for pons (p = 0.004) and whole brainstem (p = 0.01), and in long COVID for pons (p = 0.003), superior cerebellar peduncle (p = 0.009), and whole brainstem (p = 0.005). No significant differences were found between ME/CFS and long COVID volumes. In ME/CFS, we detected positive correlations between the pons and whole brainstem volumes with "pain" and negative correlations between the midbrain and whole brainstem volumes with "breathing difficulty." In long COVID patients a strong negative relationship was detected between midbrain volume and "breathing difficulty." Our study demonstrated an abnormal brainstem volume in both ME/CFS and long COVID consistent with the overlapping symptoms.

Connectivity Between Salience and Default Mode Networks and Subcortical Nodes Distinguishes Between Two Classes of Myalgic Encephalomyelitis/Chronic Fatigue Syndrome.

Background: Myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) is a debilitating disease with unknown pathophysiology. Functional magnetic resonance imaging (fMRI) studies in ME/CFS have reported disparate connectivities for the brain salience (SA) network and default mode network (DMN). Materials and Methods: In this study, we acquired resting-state and task fMRI with an advanced scanner for improved subject numbers: 24 healthy controls (HC) and 42 ME/CFS patients, 18 meeting the International Consensus Criteria (ICC) and 24 meeting the Fukuda criteria. We evaluated mean functional connectivity between the SA network and DMN hubs and subcortical regions known to be involved in ME/CFS. We tested the hypothesis that ME/CFS connectivity differed from HC and the ICC and Fukuda classes are distinguished by different connectivities with HC for different pairs of SA network, DMN, or subcortical hubs. Results: During resting-state fMRI, only two connections differed from HC, both for Fukuda ME/CFS and both with an SA network hub. During task fMRI, 10 ME/CFS connections differed from HC, 5 for ICC, and 5 for Fukuda. None was common to both classes. Eight of the 10 different connections involved an SA network hub, six of the 10 were weaker in ME/CFS, and 4 were stronger. SA network connections to the hippocampus and brainstem reticular activation system (RAS) differed from and were stronger than HC. Conclusions: The SA network mediates the relative activity of the DMN and executive networks and an imbalance will have functional consequences. The RAS and hippocampus modulate cortical activation. Different regulatory connections are consistent with the impaired cognitive performance and sleep-wake cycle of ME/CFS. Different neuropathologies are involved in ICC and Fukuda classes. Impact statement Criteria for the diagnosis of the debilitating myalgic encephalitis/chronic fatigue syndrome (ME/CFS) condition have evolved over two decades. Physicians are now instructed that the recent, more stringent (ICC) questionnaire criteria define a disease that is distinct from those remaining subjects defined by the previous Fukuda criteria. This work reports the remarkable finding that functional magnetic resonance imaging connectivity can differentiate between these two classes of ME/CFS. This is the first objective medical evidence that the questionnaire-based diagnosis does indeed differentiate between two different disease states. This facilitates a clearer understanding of ME/CFS and can better direct research and therapy development.

Subcortical and default mode network connectivity is impaired in myalgic encephalomyelitis/chronic fatigue syndrome.

Myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) is a complex chronic condition with core symptoms of fatigue and cognitive dysfunction, suggesting a key role for the central nervous system in the pathophysiology of this disease. Several studies have reported altered functional connectivity (FC) related to motor and cognitive deficits in ME/CFS patients. In this study, we compared functional connectivity differences between 31 ME/CFS and 15 healthy controls (HCs) using 7 Tesla MRI. Functional scans were acquired during a cognitive Stroop color-word task, and blood oxygen level-dependent (BOLD) time series were computed for 27 regions of interest (ROIs) in the cerebellum, brainstem, and salience and default mode networks. A region-based comparison detected reduced FC between the pontine nucleus and cerebellum vermis IX (p = 0.027) for ME/CFS patients compared to HCs. Our ROI-to-voxel analysis found significant impairment of FC within the ponto-cerebellar regions in ME/CFS. Correlation analyses of connectivity with clinical scores in ME/CFS patients detected associations between FC and 'duration of illness' and 'memory scores' in salience network hubs and cerebellum vermis and between FC and 'respiratory rate' within the medulla and the default mode network FC. This novel investigation is the first to report the extensive involvement of aberrant ponto-cerebellar connections consistent with ME/CFS symptomatology. This highlights the involvement of the brainstem and the cerebellum in the pathomechanism of ME/CFS.

Anti-Correlated Myelin-Sensitive MRI Levels in Humans Consistent with a Subcortical to Sensorimotor Regulatory Process-Multi-Cohort Multi-Modal Evidence.

Differential axonal myelination synchronises signalling over different axon lengths. The consequences of myelination processes described at the cellular level for the regulation of myelination at the macroscopic level are unknown. We analysed multiple cohorts of myelin-sensitive brain MRI. Our aim was to (i) confirm a previous report of anti-correlation between myelination in subcortical and sensorimotor areas in healthy subjects, (ii) and thereby test our hypothesis for a regulatory interaction between them. We analysed nine image-sets across three different human cohorts using six MRI modalities. Each image-set contained healthy controls (HC) and ME/CFS subjects. Subcortical and Sensorimotor regions of interest (ROI) were optimised for the detection of anti-correlations and the same ROIs were used to test the HC in all image-sets. For each cohort, median MRI values were computed in both regions for each subject and their correlation across the cohort was computed. We confirmed negative correlations in healthy controls between subcortical and sensorimotor regions in six image-sets: three T1wSE (p = 5 × 10-8, 5 × 10-7, 0.002), T2wSE (p =2 × 10-6), MTC (p = 0.01), and WM volume (p = 0.02). T1/T2 was the exception with a positive correlation (p = 0.01). This myelin regulation study is novel in several aspects: human subjects, cross-sectional design, ROI optimization, spin-echo MRI and reproducible across multiple independent image-sets. In multiple independent image-sets we confirmed an anti-correlation between subcortical and sensorimotor myelination which supports a previously unreported regulatory interaction. The subcortical region contained the brain's primary regulatory nuclei. We suggest a mechanism has evolved whereby relatively low subcortical myelination in an individual is compensated by upregulated sensorimotor myelination to maintain adequate sensorimotor performance.

Identification of transient receptor potential melastatin 3 proteotypic peptides employing an efficient membrane protein extraction method for natural killer cells.

Introduction: Mutations and misfolding of membrane proteins are associated with various disorders, hence they make suitable targets in proteomic studies. However, extraction of membrane proteins is challenging due to their low abundance, stability, and susceptibility to protease degradation. Given the limitations in existing protocols for membrane protein extraction, the aim of this investigation was to develop a protocol for a high yield of membrane proteins for isolated Natural Killer (NK) cells. This will facilitate genetic analysis of membrane proteins known as transient receptor potential melastatin 3 (TRPM3) ion channels in myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) research. Methods: Two protocols, internally identified as Protocol 1 and 2, were adapted and optimized for high yield protein extraction. Protocol 1 utilized ultrasonic and salt precipitation, while Protocol 2 implemented a detergent and chloroform/methanol approach. Protein concentrations were determined by the Pierce Bicinchoninic Acid (BCA) and the Bio-Rad DC (detergent compatible) protein assays according to manufacturer's recommendation. Using Protocol 2, protein samples were extracted from NK cells of n = 6 healthy controls (HC) and n = 4 ME/CFS patients. In silico tryptic digest and enhanced signature peptide (ESP) predictor were used to predict high-responding TRPM3 tryptic peptides. Trypsin in-gel digestion was performed on protein samples loaded on SDS-PAGE gels (excised at 150-200 kDa). A liquid chromatography-multiple reaction monitoring (LC-MRM) method was optimized and used to evaluate the detectability of TRPM3 n = 5 proteotypic peptides in extracted protein samples. Results: The detergent-based protocol protein yield was significantly higher (p < 0.05) compared with the ultrasonic-based protocol. The Pierce BCA protein assay showed more reproducibility and compatibility compared to the Bio-Rad DC protein assay. Two high-responding tryptic peptides (GANASAPDQLSLALAWNR and QAILFPNEEPSWK) for TRPM3 were detectable in n = 10 extracted protein samples from NK cells isolated from HC and ME/CFS patients. Conclusion: A method was optimized for high yield protein extraction from human NK cells and for the first time TRPM3 proteotypic peptides were detected using LC-MRM. This new method provides for future research to assess membrane protein structural and functional relationships, particularly to facilitate proteomic investigation of TRPM3 ion channel isoforms in NK cells in both health and disease states, such as ME/CFS.

Alteration of Cortical Volume and Thickness in Myalgic Encephalomyelitis/Chronic Fatigue Syndrome.

Myalgic Encephalomyelitis/Chronic fatigue syndrome (ME/CFS) patients suffer from neurocognitive impairment. In this study, we investigated cortical volumetric and thickness changes in ME/CFS patients and healthy controls (HC). We estimated mean surface-based cortical volume and thickness from 18 ME/CFS patients who met International Consensus Criteria (ICC) and 26 HC using FreeSurfer. Vertex-wise analysis showed significant reductions in the caudal middle frontal gyrus (p = 0.0016) and precuneus (p = 0.013) thickness in ME/CFS patients compared with HC. Region based analysis of sub-cortical volumes found that amygdala volume (p = 0.002) was significantly higher in ME/CFS patients compared with HC. We also performed interaction-with-group regressions with clinical measures to test for cortical volume and thickness correlations in ME/CFS with opposite slopes to HC (abnormal). ME/CFS cortical volume and thickness regressions with fatigue, heart-rate variability, heart rate, sleep disturbance score, respiratory rate, and cognitive performance were abnormal. Our study demonstrated different cortical volume and thickness in ME/CFS patients and showed abnormal cortical volume and thickness regressions with key symptoms of ME/CFS patients.

Volumetric differences in hippocampal subfields and associations with clinical measures in myalgic encephalomyelitis/chronic fatigue syndrome.

Myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) patients suffer from a cognitive and memory dysfunction. Because the hippocampus plays a key role in both cognition and memory, we tested for volumetric differences in the subfields of the hippocampus in ME/CFS. We estimated hippocampal subfield volumes for 25 ME/CFS patients who met Fukuda criteria only (ME/CFSFukuda ), 18 ME/CFS patients who met the stricter ICC criteria (ME/CFSICC ), and 25 healthy controls (HC). Group comparisons with HC detected extensive differences in subfield volumes in ME/CFSICC but not in ME/CFSFukuda . ME/CFSICC patients had significantly larger volume in the left subiculum head (p < 0.001), left presubiculum head (p = 0.0020), and left fimbria (p = 0.004). Correlations of hippocampus subfield volumes with clinical measures were stronger in ME/CFSICC than in ME/CFSFukuda patients. In ME/CFSFukuda patients, we detected positive correlations between fatigue and hippocampus subfield volumes and a negative correlation between sleep disturbance score and the right CA1 body volume. In ME/CFSICC patients, we detected a strong negative relationship between fatigue and left hippocampus tail volume. Strong negative relationships were also detected between pain and SF36 physical scores and two hippocampal subfield volumes (left: GC-ML-DG head and CA4 head). Our study demonstrated that volumetric differences in hippocampal subfields have strong statistical inference for patients meeting the ME/CFSICC case definition and confirms hippocampal involvement in the cognitive and memory problems of ME/CFSICC patients.

Diffusion tensor imaging reveals neuronal microstructural changes in myalgic encephalomyelitis/chronic fatigue syndrome.

Myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) patients suffer from a variety of physical and neurological complaints indicating the central nervous system plays a role in ME/CFS pathophysiology. Diffusion tensor imaging (DTI) has been used to study microstructural changes in neurodegenerative diseases. In this study, we evaluated DTI parameters to investigate microstructural abnormalities in ME/CFS patients. We estimated DTI parameters in 25 ME/CFS patients who met Fukuda criteria (ME/CFSFukuda ), 18 ME/CFS patients who met International Consensus Criteria (ICC) (ME/CFSICC ) only and 26 healthy control (HC) subjects. In addition to voxel-based DTI-parameter group comparisons, we performed voxel-based DTI-parameter interaction-with-group regressions with clinical and autonomic measures to test for abnormal regressions. Group comparisons between ME/CFSICC and HC detected significant clusters (a) with decreased axial diffusivity (p = .001) and mean diffusivity (p = .01) in the descending cortico-cerebellar tract in the midbrain and pons and (b) with increased transverse diffusivity in the medulla. The mode of anisotropy was significantly decreased (p = .001) in a cluster in the superior longitudinal fasciculus region. Voxel-based group comparisons between ME/CFSFukuda and HC did not detect significant clusters. For ME/CFSICC and HC, DTI parameter interaction-with-group regressions were abnormal for the clinical measures of information processing score, SF36 physical, sleep disturbance score and respiration rate in both grey and white matter regions. Our study demonstrated that DTI parameters are sensitive to microstructural changes in ME/CFSICC and could potentially act as an imaging biomarker of abnormal pathophysiology in ME/CFS. The study also shows that strict case definitions are essential in investigation of the pathophysiology of ME/CFS.

Mapping of pathological change in chronic fatigue syndrome using the ratio of T1- and T2-weighted MRI scans.

Myalgic Encephalomyelitis or Chronic Fatigue Syndrome (ME/CFS) subjects suffer from a variety of cognitive complaints indicating that the central nervous system plays a role in its pathophysiology. Recently, the ratio T1w/T2w has been used to study changes in tissue myelin and/or iron levels in neurodegenerative diseases such as multiple sclerosis and schizophrenia. In this study, we applied the T1w/T2w method to detect changes in tissue microstructure in ME/CFS patients relative to healthy controls. We mapped the T1w/T2w signal intensity values in the whole brain for forty-five ME/CFS patients who met Fukuda criteria and twenty-seven healthy controls and applied both region- and voxel-based quantification. We also performed interaction-with-group regressions with clinical measures to test for T1w/T2w relationships that are abnormal in ME/CFS at the population level. Region-based analysis showed significantly elevated T1w/T2w values (increased myelin and/or iron) in ME/CFS in both white matter (WM) and subcortical grey matter. The voxel-based group comparison with sub-millimetre resolution voxels detected very significant clusters with increased T1w/T2w in ME/CFS, mostly in subcortical grey matter, but also in brainstem and projection WM tracts. No areas with decreased T1w/T2w were found in either analysis. ME/CFS T1w/T2w regressions with heart-rate variability, cognitive performance, respiration rate and physical well-being were abnormal in both gray and white matter foci. Our study demonstrates that the T1w/T2w approach is very sensitive and shows increases in myelin and/or iron in WM and basal ganglia in ME/CFS.

A systematic review of neurological impairments in myalgic encephalomyelitis/ chronic fatigue syndrome using neuroimaging techniques.

BACKGROUND: Myalgic encephalomyelitis/ Chronic Fatigue Syndrome (ME/CFS) is a multi-system illness characterised by a diverse range of debilitating symptoms including autonomic and cognitive dysfunction. The pathomechanism remains elusive, however, neurological and cognitive aberrations are consistently described. This systematic review is the first to collect and appraise the literature related to the structural and functional neurological changes in ME/CFS patients as measured by neuroimaging techniques and to investigate how these changes may influence onset, symptom presentation and severity of the illness. METHODS: A systematic search of databases Pubmed, Embase, MEDLINE (via EBSCOhost) and Web of Science (via Clarivate Analytics) was performed for articles dating between December 1994 and August 2019. Included publications report on neurological differences in ME/CFS patients compared with healthy controls identified using neuroimaging techniques such as magnetic resonance imaging, positron emission tomography and electroencephalography. Article selection was further refined based on specific inclusion and exclusion criteria. A quality assessment of included publications was completed using the Joanna Briggs Institute checklist. RESULTS: A total of 55 studies were included in this review. All papers assessed neurological or cognitive differences in adult ME/CFS patients compared with healthy controls using neuroimaging techniques. The outcomes from the articles include changes in gray and white matter volumes, cerebral blood flow, brain structure, sleep, EEG activity, functional connectivity and cognitive function. Secondary measures including symptom severity were also reported in most studies. CONCLUSIONS: The results suggest widespread disruption of the autonomic nervous system network including morphological changes, white matter abnormalities and aberrations in functional connectivity. However, these findings are not consistent across studies and the origins of these anomalies remain unknown. Future studies are required confirm the potential neurological contribution to the pathology of ME/CFS.

Influence of 7T GRE-MRI Signal Compartment Model Choice on Tissue Parameters.

Quantitative assessment of tissue microstructure is important in studying human brain diseases and disorders. Ultra-high field magnetic resonance imaging (MRI) data obtained using a multi-echo gradient echo sequence have been shown to contain information on myelin, axonal, and extracellular compartments in tissue. Quantitative assessment of water fraction, relaxation time (T2*), and frequency shift using multi-compartment models has been shown to be useful in studying white matter properties via specific tissue parameters. It remains unclear how tissue parameters vary with model selection based on 7T multiple echo time gradient-recalled echo (GRE) MRI data. We applied existing signal compartment models to the corpus callosum and investigated whether a three-compartment model can be reduced to two compartments and still resolve white matter parameters [i.e., myelin water fraction (MWF) and g-ratio]. We show that MWF should be computed using a three-compartment model in the corpus callosum, and the g-ratios obtained using three compartment models are consistent with previous reports. We provide results for other parameters, such as signal compartment frequency shifts.

7T GRE-MRI signal compartments are sensitive to dysplastic tissue in focal epilepsy.

Ultra-high field magnetic resonance imaging data obtained using a multi-echo gradient echo sequence has been shown to contain information on tissue microstructure. Quantitative assessment of water fraction, relaxation time and frequency shift using multi-compartment signal modelling may help improve our understanding of diseases and disorders affecting the human brain. In this study, we explored tissue microstructure information by analysing voxel compartment water fraction and frequency shifts derived from 7 T multi-echo gradient recalled echo MRI data. We aimed to test whether the parameters of a three compartment model could distinguish the normal cortex from the cortex affected by focal cortical dysplasia. We compartmentalised normal and dysplastic cortical regions in patients diagnosed with focal cortical dysplasia. We found the frequency shift parameter of the shortest T2⁎ signal compartment to be sensitive to regions of dysplastic tissue. We conclude that mathematical modelling of echo time dependent gradient recalled echo MRI signals in patients with focal cortical dysplasia can potentially delineate cortical areas that have undergone microstructural changes in comparison to normal tissue.

Assessment of microstructural signal compartments across the corpus callosum using multi-echo gradient recalled echo at 7 T.

Quantitative assessment of tissue microstructure is important in studying human brain diseases and disorders in which white matter is implicated, as it has been linked to demyelination, re-myelination, and axonal damage in clinical conditions. Ultra-high field magnetic resonance imaging data obtained using a multi-echo gradient echo sequence has been shown to contain information on myelin, axonal and extracellular compartments in white matter. In this study, we aimed to assess the sensitivity of a three-compartment model to estimate the variation of corresponding compartment parameters (water fraction, relaxation time and frequency shift) of the corpus callosum sub-regions, which are known to have different tissue structure. Additionally, we computed the g-ratio using myelin and axonal water fractions and performed a voxel-by-voxel analysis in the corpus callosum. Based on data acquired for ten participants, we show that the myelin compartment water fraction and T2∗ is consistent across the corpus callosum sub-regions, whilst myelin frequency shift varies. The results show that the variation in water fraction, T2∗ and frequency shift for the myelin signal compartment across the corpus callosum is smaller than for the axonal and extracellular signal compartments. The computed g-ratio was comparable to previously published studies in the corpus callosum. Our study suggests that a multi-echo GRE approach in vivo combined with a complex three-compartment model is sensitive to microstructural parameter variations across the human corpus callosum.

Level set method with automatic selective local statistics for brain tumor segmentation in MR images.

The level set approach is a powerful tool for segmenting images. This paper proposes a method for segmenting brain tumor images from MR images. A new signed pressure function (SPF) that can efficiently stop the contours at weak or blurred edges is introduced. The local statistics of the different objects present in the MR images were calculated. Using local statistics, the tumor objects were identified among different objects. In this level set method, the calculation of the parameters is a challenging task. The calculations of different parameters for different types of images were automatic. The basic thresholding value was updated and adjusted automatically for different MR images. This thresholding value was used to calculate the different parameters in the proposed algorithm. The proposed algorithm was tested on the magnetic resonance images of the brain for tumor segmentation and its performance was evaluated visually and quantitatively. Numerical experiments on some brain tumor images highlighted the efficiency and robustness of this method.