Quantitative MRI in leukodystrophies

Leukodystrophies constitute a large and heterogeneous group of genetic diseases primarily affecting the white matter of the central nervous system. Different disorders target different white matter structural components. Leukodystrophies are most often progressive and fatal. In recent years, novel therapies are emerging and for an increasing number of leukodystrophies trials are being developed. Objective and quantitative metrics are needed to serve as outcome measures in trials. Quantitative MRI yields information on microstructural properties, such as myelin or axonal content and condition, and on the chemical composition of white matter, in a noninvasive fashion. By providing information on white matter microstructural involvement, quantitative MRI may contribute to the evaluation and monitoring of leukodystrophies. Many distinct MR techniques are available at different stages of development. While some are already clinically applicable, others are less far developed and have only or mainly been applied in healthy subjects. In this review, we explore the background, current status, potential and challenges of available quantitative MR techniques in the context of leukodystrophies

Applicability of multiple quantitative magnetic resonance methods in genetic brain white matter disorders

Background and purpose: Magnetic resonance imaging (MRI) measures of tissue microstructure are important for monitoring brain white matter (WM) disorders like leukodystrophies and multiple sclerosis. They should be sensitive to underlying pathological changes. Three whole-brain isotropic quantitative methods were applied and compared within a cohort of controls and leukodystrophy patients: two novel myelin water imaging (MWI) techniques (multi-compartment relaxometry diffusion-informed MWI: MCR-DIMWI, and multi-echo T2 relaxation imaging with compressed sensing: METRICS) and neurite orientation dispersion and density imaging (NODDI).// Methods: For 9 patients with different leukodystrophies (age range 0.4-62.4 years) and 15 control subjects (2.3-61.3 years), T1-weighted MRI, fluid-attenuated inversion recovery, multi-echo gradient echo with variable flip angles, METRICS, and multi-shell diffusion-weighted imaging were acquired on 3 Tesla. MCR-DIMWI, METRICS, NODDI, and quality control measures were extracted to evaluate differences between patients and controls in WM and deep gray matter (GM) regions of interest (ROIs). Pearson correlations, effect size calculations, and multi-level analyses were performed.// Results: MCR-DIMWI and METRICS-derived myelin water fractions (MWFs) were lower and relaxation times were higher in patients than in controls. Effect sizes of MWF values and relaxation times were large for both techniques. Differences between patients and controls were more pronounced in WM ROIs than in deep GM. MCR-DIMWI-MWFs were more homogeneous within ROIs and more bilaterally symmetrical than METRICS-MWFs. The neurite density index was more sensitive in detecting differences between patients and controls than fractional anisotropy. Most measures obtained from MCR-DIMWI, METRICS, NODDI, and diffusion tensor imaging correlated strongly with each other.// Conclusion: This proof-of-concept study shows that MCR-DIMWI, METRICS, and NODDI are sensitive techniques to detect changes in tissue microstructure in WM disorders

Proton Magnetic Resonance Spectroscopy in 22q11 Deletion Syndrome

OBJECTIVE: People with velo-cardio-facial syndrome or 22q11 deletion syndrome (22q11DS) have behavioral, cognitive and psychiatric problems. Approximately 30% of affected individuals develop schizophrenia-like psychosis. Glutamate dysfunction is thought to play a crucial role in schizophrenia. However, it is unknown if and how the glutamate system is altered in 22q11DS. People with 22q11DS are vulnerable for haploinsufficiency of PRODH, a gene that codes for an enzyme converting proline into glutamate. Therefore, it can be hypothesized that glutamatergic abnormalities may be present in 22q11DS. METHOD: We employed proton magnetic resonance spectroscopy ((1)H-MRS) to quantify glutamate and other neurometabolites in the dorsolateral prefrontal cortex (DLPFC) and hippocampus of 22 adults with 22q11DS (22q11DS SCZ+) and without (22q11DS SCZ-) schizophrenia and 23 age-matched healthy controls. Also, plasma proline levels were determined in the 22q11DS group. RESULTS: We found significantly increased concentrations of glutamate and myo-inositol in the hippocampal region of 22q11DS SCZ+ compared to 22q11DS SCZ-. There were no significant differences in levels of plasma proline between 22q11DS SCZ+ and 22q11DS SCZ-. There was no relationship between plasma proline and cerebral glutamate in 22q11DS. CONCLUSION: This is the first in vivo(1)H-MRS study in 22q11DS. Our results suggest vulnerability of the hippocampus in the psychopathology of 22q11DS SCZ+. Altered hippocampal glutamate and myo-inositol metabolism may partially explain the psychotic symptoms and cognitive impairments seen in this group of patients

Metabolites predict lesion formation and severity in relapsing-remitting multiple sclerosis

BACKGROUND: Multiple sclerosis is characterized by white matter lesions, which are visualized with conventional T2-weighted magnetic resonance imaging (MRI). Little is known about local metabolic processes preceding the appearance and during the pathological development of new lesions. OBJECTIVE: To identify metabolite changes preceding white matter (WM) lesions and pathological severity of lesions over time. METHODS: A total of 59 relapsing-remitting multiple sclerosis (MS) patients were scanned four times, with 6-month intervals. Imaging included short-TE magnetic resonance spectroscopic imaging (MRSI) and diffusion tensor imaging (DTI). RESULTS: A total of 16 new lesions appeared within the MRSI slab in 12 patients. Glutamate increased (+1.0 mM (+19%), p = 0.039) 12 and 6 months before new lesions appeared. In these areas, the increase in creatine and choline 6 months before until lesion appearance was negatively correlated with radial diffusivity (ρ = -0.73, p = 0.002 and ρ = -0.72, p = 0.002). Increase in creatine also correlated with the increase of axial diffusivity in the same period (ρ = -0.53, p = 0.034). When splitting the lesions into "mild" and "severe" based on radial diffusivity, only mild lesions showed an increase in creatine and choline during lesion formation ( p = 0.039 and p = 0.008, respectively). CONCLUSION: Increased glutamate heralded the appearance of new T2-visible WM lesions. In pathologically "mild" lesions, an increase in creatine and choline was found during lesion formation

Relationship Between White Matter Lesions and Gray Matter Atrophy in Multiple Sclerosis: A Systematic Review

BACKGROUND: There is currently no consensus about the extent of gray matter (GM) atrophy that can be attributed to secondary changes following white matter (WM) lesions, or the temporal and spatial relationships between the two phenomena. Elucidating this interplay will broaden the understanding of the combined inflammatory and neurodegenerative pathophysiology of multiple sclerosis (MS), and separating atrophic changes due to primary and secondary neurodegenerative mechanisms will then be pivotal to properly evaluate treatment effects, especially if these treatments target the different processes individually. OBJECTIVE: To untangle these complex pathological mechanisms, this systematic review provides an essential first step: an objective and comprehensive overview of the existing in vivo knowledge of the relationship between brain WM lesions and GM atrophy, in patients diagnosed with MS. The overall aim was to clarify the extent to which WM lesions associate with both global and regional GM atrophy, and how this may differ in the different disease subtypes. METHODS: We searched MEDLINE (through PubMed) and Embase for reports containing direct associations between brain GM and WM lesion measures obtained by conventional MRI sequences in patients with clinically isolated syndrome (CIS) and MS. No restriction was applied for publication date. The quality and risk of bias in included studies was evaluated using the Quality Assessment Tool for observational cohort and cross-sectional studies (NIH, Bethesda, MA). Qualitative and descriptive analyses were performed. RESULTS: A total of 90 articles were included. WM lesion volumes were mostly related to global, cortical and deep GM volumes, and those significant associations were almost without exception negative, indicating that higher WM lesion volumes were associated with lower GM volumes or lower cortical thicknesses. The most consistent relation between WM lesions and GM atrophy was seen in early (relapsing) disease, and less so in progressive MS. CONCLUSION: The findings suggest that GM neurodegeneration is mostly secondary to damage in the WM during early disease stages, while becoming more detached and dominated by other, possibly primary neurodegenerative disease mechanisms, in progressive MS

Correction to: Relevance of neuroimaging for neurocognitive and behavioral outcome after pediatric traumatic brain injury (Brain Imaging and Behavior, (2018), 12, 1, (29-43), 10.1007/s11682-017-9673-3)

JC Goslings is the correct name of the sixth author of this article

Fronto-limbic disconnection in patients with multiple sclerosis and depression

BACKGROUND: The biological mechanism of depression in multiple sclerosis (MS) is not well understood. Based on work in major depressive disorder, fronto-limbic disconnection might be important. OBJECTIVE: To investigate structural and functional fronto-limbic changes in depressed MS (DMS) and non-depressed MS (nDMS) patients. METHODS: In this retrospective study, 22 moderate-to-severe DMS patients (disease duration 8.2 ± 7.7 years), 21 nDMS patients (disease duration 15.3 ± 8.3 years), and 12 healthy controls underwent neuropsychological testing and magnetic resonance imaging (MRI; 1.5 T). Brain volumes (white matter (WM), gray matter, amygdala, hippocampus, thalamus), lesion load, fractional anisotropy (FA) of fronto-limbic tracts, and resting-state functional connectivity (FC) between limbic and frontal areas were measured and compared between groups. Regression analysis was performed to relate MRI measures to the severity of depression. RESULTS: Compared to nDMS patients, DMS patients (shorter disease duration) had lower WM volume ( p < 0.01), decreased FA of the uncinate fasciculus ( p < 0.05), and lower FC between the amygdala and frontal regions ( p < 0.05). Disease duration, FA of the uncinate fasciculus, and FC of the amygdala could explain 48% of variance in the severity of depression. No differences in cognition were found. CONCLUSION: DMS patients showed more pronounced (MS) damage, that is, structural and functional changes in temporo-frontal regions, compared to nDMS patients, suggestive of fronto-limbic disconnection

Diagnostic accuracy of neuroimaging to delineate diffuse gliomas within the brain: A meta-Analysis

BACKGROUND: Brain imaging in diffuse glioma is used for diagnosis, treatment planning, and follow-up. PURPOSE: In this meta-Analysis, we address the diagnostic accuracy of imaging to delineate diffuse glioma. DATA SOURCES: We systematically searched studies of adults with diffuse gliomas and correlation of imaging with histopathology. STUDY SELECTION: Study inclusion was based on quality criteria. Individual patient data were used, if available. DATA ANALYSIS: A hierarchic summary receiver operating characteristic method was applied. Low-And high-grade gliomas were analyzed in subgroups. DATA SYNTHESIS: Sixty-one studies described 3532 samples in 1309 patients. The mean Standard for Reporting of Diagnostic Accuracy score (13/25) indicated suboptimal reporting quality. For diffuse gliomas as a whole, the diagnostic accuracy was best with T2-weighted imaging, measured as area under the curve, false-positive rate, true-positive rate, and diagnostic odds ratio of 95.6%, 3.3%, 82%, and 152. For low-grade gliomas, the diagnostic accuracy of T2-weighted imaging as a reference was 89.0%, 0.4%, 44.7%, and 205; and for high-grade gliomas, with T1-weighted gadolinium-enhanced MR imaging as a reference, it was 80.7%, 16.8%, 73.3%, and 14.8. In high-grade gliomas, MR spectroscopy (85.7%, 35.0%, 85.7%, and 12.4) and 11C methionine-PET (85.1%, 38.7%, 93.7%, and 26.6) performed better than the reference imaging. LIMITATIONS: True-negative samples were underrepresented in these data, so false-positive rates are probably less reliable than truepositive rates. Multimodality imaging data were unavailable. CONCLUSIONS: The diagnostic accuracy of commonly used imaging is better for delineation of low-grade gliomas than high-grade gliomas on the basis of limited evidence. Improvement is indicated from advanced techniques, such as MR spectroscopy and PET.SCOPUS: ar.jinfo:eu-repo/semantics/publishe