In the new WHO 2021 Classification of CNS Tumors the chapter "Circumscribed astrocytic gliomas, glioneuronal and neuronal tumors" encompasses several different rare tumor entities, which occur more ...frequently in children, adolescents, and young adults. The Task Force has reviewed the evidence of diagnostic and therapeutic interventions, which is low particularly for adult patients, and draw recommendations accordingly. Tumor diagnosis, based on WHO 2021, is primarily performed using conventional histological techniques; however, a molecular workup is important for differential diagnosis, in particular, DNA methylation profiling for the definitive classification of histologically unresolved cases. Molecular factors are increasing of prognostic and predictive importance. MRI finding are non-specific, but for some tumors are characteristic and suggestive. Gross total resection, when feasible, is the most important treatment in terms of prolonging survival and achieving long-term seizure control. Conformal radiotherapy should be considered in grade 3 and incompletely resected grade 2 tumors. In recurrent tumors reoperation and radiotherapy, including stereotactic radiotherapy, can be useful. Targeted therapies may be used in selected patients: BRAF and MEK inhibitors in pilocytic astrocytomas, pleomorphic xanthoastrocytomas, and gangliogliomas when BRAF altered, and mTOR inhibitor everolimus in subependymal giant cells astrocytomas. Sequencing to identify molecular targets is advocated for diagnostic clarification and to direct potential targeted therapies.
ABSTRACT
BACKGROUND
Demyelination is a core pathological feature of multiple sclerosis (MS) and spontaneous remyelination appears to be an important mechanism for repair in the disease. Magnetization ...transfer ratio imaging (MTR) has been used extensively to evaluate demyelination, although limitations to its specificity are recognized. MT saturation imaging (MTsat) removes some of the T1 dependence of MTR. We have performed a comparative evaluation of MTR and MTsat imaging in a mixed group of subjects with active MS, to explore their relative sensitivity to pathology relevant to explaining clinical outcomes.
METHODS
A total of 134 subjects underwent MRI of their brain and cervical spinal cord. Isotropic 3‐dimensional pre‐ and postcontrast T1‐weighted and T2‐weighted fluid‐attenuated inversion recovery (FLAIR) volumes were segmented into brain normal appearing white matter (NAWM), brain WM lesions (WML), normal appearing spinal cord (NASC), and spinal cord lesions. Volumes and metrics for MTR and MTsat histograms were calculated for each region.
RESULTS
Significant Spearman correlations were found with the Expanded Disability Status Scale and timed 25‐foot walk for the whole brain and WML MTR, but not in that from the NAWM or any cervical spinal cord region. By contrast, the MTsat was correlated with both disability metrics in all these regions in both the brain and spine.
CONCLUSIONS
This study extends prior work relating atrophy and lesion load with disability, by characterization of MTsat parameters. MTsat is practical in routine clinical applications and may be more sensitive to tissue damage than MTR for both brain and cervical spinal cord.
This commentary discusses the implications of disease-modifying treatments for Alzheimer's disease which seem likely to appear in the next few years and results from a meeting of British experts in ...neurodegenerative diseases in Edinburgh. The availability of such treatments would help change public and professional attitudes and accelerate engagement with the prodromal and preclinical populations who might benefit from them. However, this would require an updated understanding of Alzheimer's disease, namely the important distinction between Alzheimer's disease and Alzheimer's dementia.
Since treatments are likely to be most effective in the early stages, identification of clinically relevant brain changes (for example, amyloid burden using imaging or cerebrospinal fluid biomarkers) will be crucial. While current biomarkers could be useful in identifying eligibility for new therapies, trial data are not available to aid decisions about stopping or continuing treatment in clinical practice. Therefore, effective monitoring of safety and effectiveness when these treatments are introduced into clinical practice will be necessary to inform wide-scale use. Equity of access is key but there is a tension between universal access for everyone with a diagnosis of Alzheimer's disease and specifying an eligible population most likely to respond. We propose the resources necessary for an optimal care pathway as well as the necessary education and training for primary and secondary care.
The majority of current services in the UK and elsewhere would not be able to accommodate the specialist investigations required to select patients and prescribe these therapies. Therefore, a stepped approach would be necessary: from innovating sentinel clinical-academic centres that already have capacity to deliver the necessary phase IV trials, through early adoption in a hub and spoke model, to nationwide adoption for true equity of access. The optimism generated by recent and anticipated developments in the understanding and treatment of Alzheimer's disease presents a great opportunity to innovate and adapt our services to incorporate the next exciting development in the field of dementia.
To prospectively perform longitudinal magnetic resonance (MR) perfusion imaging of conservatively treated low-grade gliomas to determine whether relative cerebral blood volume (rCBV) changes precede ...malignant transformation as defined by conventional MR imaging and clinical criteria.
All patients gave written informed consent for this institutional ethics committee-approved study. Thirteen patients (seven men, six women; age range, 29-69 years) with biopsy-proved low-grade glioma treated only with antiepileptic drugs were examined longitudinally with susceptibility-weighted perfusion, T2-weighted, fluid-attenuated inversion recovery, and high-dose contrast material-enhanced T1-weighted MR imaging at 6-month intervals to date or until malignant transformation was diagnosed. Student t tests were used to determine differences in rCBV values between "transformers" and "nontransformers" at defined time points throughout study follow-up.
Seven patients showed progression to high-grade tumors between 6 and 36 months (mean, 22.3 months), and disease in six patients remained stable over a period of 12-36 months (mean, 23 months). Transformers had a slightly (but not statistically significantly) higher group mean rCBV than nontransformers at the point of study entry (1.93 vs 1.31). In nontransformers, the rCBV remained relatively stable and increased to only 1.52 over a mean follow-up of 23 months. In contrast, transformers showed a continuous increase in rCBV up to the point of transformation, when contrast enhancement became apparent on T1-weighted images. The group mean rCBV was 5.36 at transformation but also showed a significant increase from the initial study at 12 months (3.14, P = .022) and at 6 months (3.65, P = .049) before transformation. Rates of rCBV change between two successive time points were also significantly higher in transformers than in nontransformers.
In transforming low-grade glioma, susceptibility-weighted MR perfusion imaging can demonstrate significant increases in rCBV up to 12 months before contrast enhancement is apparent on T1-weighted MR images.
IntroductionGliomas are the most common primary tumour of the central nervous system (CNS), with an estimated annual incidence of 6.6 per 100 000 individuals in the USA and around 14 deaths per day ...from brain tumours in the UK. The genomic and biological landscape of brain tumours has been increasingly defined and, since 2016, the WHO classification of tumours of the CNS incorporates molecular data, along with morphology, to define tumour subtypes more accurately. The Tessa Jowell BRAIN MATRIX Platform (TJBM) study aims to create a transformative clinical research infrastructure that leverages UK National Health Service resources to support research that is patient centric and attractive to both academic and commercial investors.Methods and analysisThe TJBM study is a programme of work with the principal purpose to improve the knowledge of glioma and treatment for patients with glioma. The programme includes a platform study and subsequent interventional clinical trials (as separate protocols). The platform study described here is the backbone data-repository of disease, treatment and outcome data from clinical, imaging and pathology data being collected in patients with glioma from secondary care hospitals. The primary outcome measure of the platform is time from biopsy to integrated histological–molecular diagnosis using whole-genome sequencing and epigenomic classification. Secondary outcome measures include those that are process centred, patient centred and framework based. Target recruitment for the study is 1000 patients with interim analyses at 100 and 500 patients.Ethics and disseminationThe study will be performed in accordance with the recommendations guiding physicians in biomedical research involving human subjects, adopted by the 18th World Medical Association General Assembly, Helsinki, Finland and stated in the respective participating countries’ laws governing human research, and Good Clinical Practice. The protocol was initially approved on 18 February 2020 by West Midlands – Edgbaston Research Ethics Committee; the current protocol (v3.0) was approved on 15 June 2022. Participants will be required to provide written informed consent. A meeting will be held after the end of the study to allow discussion of the main results among the collaborators prior to publication. The results of this study will be disseminated through national and international presentations and peer-reviewed publications. Manuscripts will be prepared by the Study Management Group and authorship will be determined by mutual agreement.Trial registration numberNCT04274283, 18-Feb-2020; ISRCTN14218060, 03-Feb-2020.
The objectives of this study were to define the range of apparent diffusion coefficients (ADCs) from whole-body DWI in normal abdominal organs and bone marrow, to identify ADC differences between ...sexes and changes occurring with age, and to evaluate the effect of the fat fraction (FF) on the ADC of normal liver parenchyma and bone marrow.
Fifty-one healthy volunteers (mean age = 38 years; age range = 23-68 years) underwent whole-body DWI using single-shot echo-planar imaging (b = 0, 150, 400, 750, and 1000 s/mm(2)). A two-point Dixon technique was used to evaluate the FF. Perfusion-sensitive ADCs, which we refer to as "ADCALL," and perfusion-insensitive ADCs, which we refer to as "ADCHIGH," of the liver and renal parenchyma, spleen, pancreatic tail, and red and yellow bone marrow were calculated. The relationships between ADC and sex, age, and FF were examined.
ADCALL and ADCHIGH were significantly higher in female volunteers for the pancreatic tail (p = 0.046 and 0.008, respectively), red bone marrow (p = 0.029 and 0.001), and yellow bone marrow (p < 0.001 for both) but with considerable overlap. There were significant negative correlations between ADCALL and ADCHIGH and age in the liver parenchyma (p = 0.008 and 0.01, respectively) and in the yellow bone marrow (p = 0.013 and 0.039) for all subjects. ADCALL and ADCHIGH were also negatively correlated with FF in the liver parenchyma (p = 0.006 and 0.008, respectively) and in yellow bone marrow (p < 0.001 and p = 0.001) in all subjects.
The ADCs of normal liver parenchyma and bone marrow change significantly with age. The ADCs of bone marrow in women are significantly higher than those of men and correlate strongly with FF. These effects may have an impact on image interpretation when using whole-body DWI to assess disease burden and treatment response.
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•Microstructural MRI shows early change in multiple sclerosis not evident as atrophy.•Magnetization transfer saturation, but not ratio, may detect subtle myelin loss.•MRI g-ratio also ...detects longitudinal change in normal-appearing white matter.•Interpretation of MRI g-ratio change is complex due to axonal volume dependence.•Technique test-retest agreement limits sensitivity to change in individual patients.
Quantitative microstructural MRI, such as myelin-sensitive magnetisation transfer ratio (MTR) or saturation (MTsat), axon-sensitive water diffusion Neurite Orientation Dispersion and Density Imaging (NODDI), and the aggregate g-ratio, may provide more specific markers of white matter integrity than conventional MRI for early patient stratification in relapsing-remitting multiple sclerosis (RRMS). The aim of this study was to determine the sensitivity of such markers to longitudinal pathological change within cerebral white matter lesions (WML) and normal-appearing white matter (NAWM) in recently diagnosed RRMS.
Seventy-nine people with recently diagnosed RRMS, from the FutureMS longitudinal cohort, were recruited to an extended MRI protocol at baseline and one year later. Twelve healthy volunteers received the same MRI protocol, repeated within two weeks. Ethics approval and written informed consent were obtained.
3T MRI included magnetisation transfer, and multi-shell diffusion-weighted imaging. NAWM and whole brain were segmented from 3D T1-weighted MPRAGE, and WML from T2-weighted FLAIR. MTR, MTsat, NODDI isotropic (ISOVF) and intracellular (ICVF) volume fractions, and g-ratio (calculated from MTsat and NODDI data) were measured within WML and NAWM. Brain parenchymal fraction (BPF) was also calculated.
Longitudinal change in BPF and microstructural metrics was assessed with paired t-tests (α = 0.05) and linear mixed models, adjusted for confounding factors with False Discovery Rate (FDR) correction for multiple comparisons. Longitudinal changes were compared with test-retest Bland-Altman limits of agreement from healthy control white matter. The influence of longitudinal change on g-ratio was explored through post-hoc analysis in silico by computing g-ratio with realistic simulated MTsat and NODDI values.
In NAWM, g-ratio and ICVF increased, and MTsat decreased over one year (adjusted mean difference = 0.007, 0.005, and −0.057 respectively, all FDR-corrected p < 0.05). There was no significant change in MTR, ISOVF, or BPF. In WML, MTsat, NODDI ICVF and ISOVF increased over time (adjusted mean difference = 0.083, 0.024 and 0.016, respectively, all FDR-corrected p < 0.05). Group-level longitudinal changes exceeded test-retest limits of agreement for NODDI ISOVF and ICVF in WML only. In silico analysis showed g-ratio may increase due to a decrease in MTsat or ISOVF, or an increase in ICVF.
G-ratio and MTsat changes in NAWM over one year may indicate subtle myelin loss in early RRMS, which were not apparent with BPF or NAWM MTR. Increases in NAWM and WML NODDI ICVF were not anticipated, and raise the possibility of axonal swelling or morphological change. Increases in WML MTsat may reflect myelin repair. Changes in NODDI ISOVF are more likely to reflect alterations in water content. Competing MTsat and ICVF changes may account for the absence of g-ratio change in WML. Longitudinal changes in microstructural measures are significant at a group level, however detection in individual patients in early RRMS is limited by technique reproducibility.
MTsat and g-ratio are more sensitive than MTR to early pathological changes in RRMS, but complex dependence of g-ratio on NODDI parameters limit the interpretation of aggregate measures in isolation. Improvements in technique reproducibility and validation of MRI biophysical models across a range of pathological tissue states are needed.
Management of symptoms and prevention of life-threatening hemorrhage in immune thrombocytopenia (ITP) must be balanced against adverse effects of therapies. Because current treatment guidelines based ...on platelet count are confounded by variable bleeding phenotypes, there is a need to identify new objective markers of disease severity for treatment stratification. In this cross-sectional prospective study of 49 patients with ITP and nadir platelet counts <30 × 109/L and 18 aged-matched healthy controls, we used susceptibility-weighted magnetic resonance imaging to detect cerebral microbleeds (CMBs) as a marker of occult hemorrhage. CMBs were detected using a semiautomated method and correlated with clinical metadata using multivariate regression analysis. No CMBs were detected in health controls. In contrast, lobar CMBs were identified in 43% (21 of 49) of patients with ITP; prevalence increased with decreasing nadir platelet count (0/4, ≥15 × 109/L; 2/9, 10-14 × 109/L; 4/11, 5-9 × 109/L; 15/25 <5 × 109/L) and was associated with longer disease duration (P = 7 × 10−6), lower nadir platelet count (P = .005), lower platelet count at time of neuroimaging (P = .029), and higher organ bleeding scores (P = .028). Mucosal and skin bleeding scores, number of previous treatments, age, and sex were not associated with CMBs. Occult cerebral microhemorrhage is common in patients with moderate to severe ITP. Strong associations with ITP duration may reflect CMB accrual over time or more refractory disease. Further longitudinal studies in children and adults will allow greater understanding of the natural history and clinical and prognostic significance of CMBs.
•Brain SWI demonstrates occult cerebral microbleeds in almost 50% of patients with ITP and platelet counts less than 30 × 109/L.•CMBs are associated with longer disease duration and lower nadir platelet count and may be a useful noninvasive marker of hemorrhagic risk.
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Automated whole brain segmentation from magnetic resonance images is of great interest for the development of clinically relevant volumetric markers for various neurological diseases. Although deep ...learning methods have demonstrated remarkable potential in this area, they may perform poorly in nonoptimal conditions, such as limited training data availability. Manual whole brain segmentation is an incredibly tedious process, so minimizing the data set size required for training segmentation algorithms may be of wide interest. The purpose of this study was to compare the performance of the prototypical deep learning segmentation architecture (U-Net) with a previously published atlas-free traditional machine learning method, Classification using Derivative-based Features (C-DEF) for whole brain segmentation, in the setting of limited training data.
C-DEF and U-Net models were evaluated after training on manually curated data from 5, 10, and 15 participants in 2 research cohorts: (1) people living with clinically diagnosed HIV infection and (2) relapsing-remitting multiple sclerosis, each acquired at separate institutions, and between 5 and 295 participants' data using a large, publicly available, and annotated data set of glioblastoma and lower grade glioma (brain tumor segmentation). Statistics was performed on the Dice similarity coefficient using repeated-measures analysis of variance and Dunnett-Hsu pairwise comparison.
C-DEF produced better segmentation than U-Net in lesion (29.2%-38.9%) and cerebrospinal fluid (5.3%-11.9%) classes when trained with data from 15 or fewer participants. Unlike C-DEF, U-Net showed significant improvement when increasing the size of the training data (24%-30% higher than baseline). In the brain tumor segmentation data set, C-DEF produced equivalent or better segmentations than U-Net for enhancing tumor and peritumoral edema regions across all training data sizes explored. However, U-Net was more effective than C-DEF for segmentation of necrotic/non-enhancing tumor when trained on 10 or more participants, probably because of the inconsistent signal intensity of the tissue class.
These results demonstrate that classical machine learning methods can produce more accurate brain segmentation than the far more complex deep learning methods when only small or moderate amounts of training data are available (n ≤ 15). The magnitude of this advantage varies by tissue and cohort, while U-Net may be preferable for deep gray matter and necrotic/non-enhancing tumor segmentation, particularly with larger training data sets (n ≥ 20). Given that segmentation models often need to be retrained for application to novel imaging protocols or pathology, the bottleneck associated with large-scale manual annotation could be avoided with classical machine learning algorithms, such as C-DEF.
Purpose
The purpose of this study is to investigate the robustness of pharmacokinetic modelling of DCE-MRI brain tumour data and to ascertain reliable perfusion parameters through a model selection ...process and a stability test.
Methods
DCE-MRI data of 14 patients with primary brain tumours were analysed using the Tofts model (TM), the extended Tofts model (ETM), the shutter speed model (SSM) and the extended shutter speed model (ESSM). A no-effect model (NEM) was implemented to assess overfitting of data by the other models. For each lesion, the Akaike Information Criteria (AIC) was used to build a 3D model selection map. The variability of each pharmacokinetic parameter extracted from this map was assessed with a noise propagation procedure, resulting in voxel-wise distributions of the coefficient of variation (CV).
Results
The model selection map over all patients showed NEM had the best fit in 35.5% of voxels, followed by ETM (32%), TM (28.2%), SSM (4.3%) and ESSM (< 0.1%). In analysing the reliability of
K
trans
, when considering regions with a CV < 20%, ≈ 25% of voxels were found to be stable across all patients. The remaining 75% of voxels were considered unreliable.
Conclusions
The majority of studies quantifying DCE-MRI data in brain tumours only consider a single model and whole tumour statistics for the output parameters. Appropriate model selection, considering tissue biology and its effects on blood brain barrier permeability and exchange conditions, together with an analysis on the reliability and stability of the calculated parameters, is critical in processing robust brain tumour DCE-MRI data.
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