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The fifth edition of the World Health Organization Classification of Tumours of the Central Nervous System (WHO CNS5) published in 2021 builds on the 2016 edition and incorporates output from the Consortium to Inform Molecular and Practical Approaches to CNS Tumour Taxonomy (cIMPACT-NOW). WHO CNS5 introduces fundamental changes to brain tumour classification through the introduction of new tumour families and types, especially in the paediatric population, and a revision of diagnostic criteria for some of the existing neoplasms. Neuroradiologists are central to brain tumour diagnostics, and it is therefore essential that they become familiar with the key updates. This review aims to summarise the most relevant updates for the neuroradiologist and, where available, discuss the known radiophenotypes of various new tumour types to allow for increased accuracy of language and diagnosis. Of particular importance, WHO CNS5 places greater emphasis on organising tumours by molecular type to reflect biology, as well as to allow for better planning of treatment. The principal updates in adult tumours concern the molecular definition of glioblastoma, restructuring of diffuse gliomas, and the introduction of several new tumour types. The updates to the paediatric classification are protean, ranging from the introduction of new types to establishing separate tumour families for paediatric-type gliomas. This review summarises the most significant revisions and captures the rationale and radiological implications for the major updates.

Relapsed or refractory primary central nervous system lymphoma (rrPCNSL) confers a poor prognosis with no accepted standard of care. Very few prospective studies have been conducted in this patient group. This study was a multicenter phase 1/2 study that investigated thiotepa in combination with ifosfamide, etoposide, and rituximab (TIER) for the treatment of PCNSL relapsed or refractory to high-dose methotrexate-based chemotherapy. A 3 + 3 design investigated the recommended phase 2 dose of thiotepa for a single-stage phase 2 cohort by assessing the activity of 2 cycles of TIER against rrPCNSL. The primary outcome was overall response rate. The dose-finding study demonstrated that 50 mg/m2 of thiotepa could be safely delivered within the TIER regimen. No dose-limiting toxicities were encountered in phase 1, and TIER was well-tolerated by the 27 patients treated in phase 2. The most common grade 3 to 4 toxicities were neutropenia (56% of patients) and thrombocytopenia (39%). An overall response was confirmed in 14 patients (52%), which met the prespecified threshold for clinically relevant activity. The median progression-free survival was 3 months (95% confidence interval [CI], 2 to 6 months) and overall survival 5 months (95% CI, 3 to 9 months). Exploratory analyses suggest a greater benefit for thiotepa-naïve patients. Six patients successfully completed autologous stem cell transplantation (ASCT) consolidation, with 4 experiencing durable remissions after a median follow-up of 50 months. The TIER regimen can be delivered safely and is active against rrPCNSL. When it is followed by ASCT, it can provide durable remission and long-term survival. However, for the majority of patients, prognosis remains poor, and novel treatment strategies are urgently needed. This trial was registered at https://www.clinicaltrialsregister.eu/ctr-search/search as EudraCT 2014-000227-24 and ISRCTN 12857473.

Molecular parameters have become integral to glioma diagnosis. Much of radiogenomics research has focused on the use of advanced MRI techniques, but conventional MRI sequences remain the mainstay of clinical assessments. The aim of this research was to synthesize the current published data on the accuracy of standard clinical MRI for diffuse glioma genotyping, specifically targeting IDH and 1p19q status. A systematic search was performed in September 2019 using PubMed and the Cochrane Library, identifying studies on the diagnostic value of T1 pre-/post-contrast, T2, FLAIR, T2*/SWI and/or 3-directional diffusion-weighted imaging sequences for the prediction of IDH and/or 1p19q status in WHO grade II-IV diffuse astrocytic and oligodendroglial tumours as defined in the WHO 2016 Classification of CNS Tumours. Forty-four studies including a total of 5286 patients fulfilled the inclusion criteria. Correlations between key glioma molecular markers, namely IDH and 1p19q, and distinctive MRI findings have been established, including tumour location, signal composition (including the T2-FLAIR mismatch sign) and apparent diffusion coefficient values. Consistent trends have emerged indicating that conventional MRI is valuable for glioma genotyping, particularly in presumed lower grade glioma. However, due to limited interobserver testing, the reproducibility of qualitatively assessed visual features remains an area of uncertainty.

Background A readily implemented MRI biomarker for glioma genotyping is currently lacking. Purpose To evaluate clinically available MRI parameters for predicting isocitrate dehydrogenase (IDH) status in patients with glioma. Materials and Methods In this retrospective study of patients studied from July 2008 to February 2019, untreated World Health Organization (WHO) grade II/III gliomas were analyzed by three neuroradiologists blinded to tissue results. Apparent diffusion coefficient (ADC) minimum (ADCmin) and mean (ADCmean) regions of interest were defined in tumor and normal appearing white matter (ADCNAWM). A visual rating of anatomic features (T1 weighted, T1 weighted with contrast enhancement, T2 weighted, and fluid-attenuated inversion recovery) was performed. Interobserver comparison (intraclass correlation coefficient and Cohen κ) was followed by nonparametric (Kruskal-Wallis analysis of variance) testing of associations between ADC metrics and glioma genotypes, including Bonferroni correction for multiple testing. Descriptors with sufficient concordance (intraclass correlation coefficient, >0.8; κ > 0.6) underwent univariable analysis. Predictive variables (P < .05) were entered into a multivariable logistic regression and tested in an additional test sample of patients with glioma. Results The study included 290 patients (median age, 40 years; interquartile range, 33-52 years; 169 male patients) with 82 IDH wild-type, 107 IDH mutant/1p19q intact, and 101 IDH mutant/1p19q codeleted gliomas. Two predictive models incorporating ADCmean-to-ADCNAWM ratio, age, and morphologic characteristics, with model A mandating calcification result and model B recording cyst formation, classified tumor type with areas under the receiver operating characteristic curve of 0.94 (95% confidence interval [CI]: 0.91, 0.97) and 0.96 (95% CI: 0.93, 0.98), respectively. In the test sample of 49 gliomas (nine IDH wild type, 21 IDH mutant/1p19q intact, and 19 IDH mutant/1p19q codeleted), the classification accuracy was 40 of 49 gliomas (82%; 95% CI: 71%, 92%) for model A and 42 of 49 gliomas (86%; 95% CI: 76%, 96%) for model B. Conclusion Two algorithms that incorporated apparent diffusion coefficient values, age, and tumor morphologic characteristics predicted isocitrate dehydrogenase status in World Health Organization grade II/III gliomas on the basis of standard clinical MRI sequences alone. © RSNA, 2020 Online supplemental material is available for this article.

We highlight an unusual case of multifocal glioblastoma in an adolescent patient, manifesting as four discrete brain lesions, each distinct in appearance. Familiarity with the diverse imaging features of glioblastoma can reduce misdiagnosis and avoid treatment delays.

Introduction: Gliomatosis cerebri describes a rare growth pattern of diffusely infiltrating glioma. The treatment options are limited and clinical outcomes remain poor. To characterise this population of patients, we examined referrals to a specialist brain tumour centre. Methods: We analysed demographic data, presenting symptoms, imaging, histology and genetics, and survival in individuals referred to a multidisciplinary team meeting over a 10-year period. Results: In total, 29 patients fulfilled the inclusion criteria with a median age of 64 years. The most common presenting symptoms were neuropsychiatric (31%), seizure (24%) or headache (21%). Of 20 patients with molecular data, 15 had IDH wild-type glioblastoma, with an IDH1 mutation most common in the remainder (5/20). The median length of survival from MDT referral to death was 48 weeks (IQR 23 to 70 weeks). Contrast enhancement patterns varied between and within tumours. In eight patients who had DSC perfusion studies, five (63%) had a measurable region of increased tumour perfusion with rCBV values ranging from 2.8 to 5.7. A minority of patients underwent MR spectroscopy with 2/3 (66.6%) false-negative results. Conclusions: Gliomatosis imaging, histological and genetic findings are heterogeneous. Advanced imaging, including MR perfusion, could identify biopsy targets. Negative MR spectroscopy does not exclude the diagnosis of glioma.

Background T1‐weighted dynamic contrast‐enhanced (DCE) perfusion magnetic resonance imaging (MRI) has been broadly utilized in the evaluation of brain tumors. We aimed at assessing the diagnostic accuracy of DCE‐MRI in discriminating between low‐grade gliomas (LGGs) and high‐grade gliomas (HGGs), between tumor recurrence and treatment‐related changes, and between primary central nervous system lymphomas (PCNSLs) and HGGs. Methods We performed this study based on the Preferred Reporting Items for Systematic Reviews and Meta‐Analysis of Diagnostic Test Accuracy Studies criteria. We systematically surveyed studies evaluating the diagnostic accuracy of DCE‐MRI for the aforementioned entities. Meta‐analysis was conducted with the use of a random effects model. Results Twenty‐seven studies were included after screening of 2945 possible entries. We categorized the eligible studies into three groups: those utilizing DCE‐MRI to differentiate between HGGs and LGGs (14 studies, 546 patients), between recurrence and treatment‐related changes (9 studies, 298 patients) and between PCNSLs and HGGs (5 studies, 224 patients). The pooled sensitivity, specificity, and area under the curve for differentiating HGGs from LGGs were 0.93, 0.90, and 0.96, for differentiating tumor relapse from treatment‐related changes were 0.88, 0.86, and 0.89, and for differentiating PCNSLs from HGGs were 0.78, 0.81, and 0.86, respectively. Conclusions Dynamic contrast‐enhanced‐Magnetic resonance imaging is a promising noninvasive imaging method that has moderate or high accuracy in stratifying gliomas. DCE‐MRI shows high diagnostic accuracy in discriminating between HGGs and their low‐grade counterparts, and moderate diagnostic accuracy in discriminating recurrent lesions and treatment‐related changes as well as PCNSLs and HGGs., Dynamic contrast‐enhanced‐Magnetic resonance imaging has high diagnostic accuracy in grading gliomas and moderate accuracy in surveillance of high‐grade gliomas and differentiation from primary central nervous system lymphomas. DCE‐MRI is a promising noninvasive imaging technique in diagnosing different types of brain tumors.

Background: To determine if filtration-histogram based texture analysis (MRTA) of clinical MR imaging can non-invasively identify molecular subtypes of untreated gliomas. Methods: Post Gadolinium T1-weighted (T1+Gad) images, T2-weighted (T2) images and apparent diffusion coefficient (ADC) maps of 97 gliomas (54 = WHO II, 20 = WHO III, 23 = WHO IV) between 2010 and 2016 were studied. Whole-tumor segmentations were performed on a proprietary texture analysis research platform (TexRAD, Cambridge, UK) using the software’s freehand drawing tool. MRTA commences with a filtration step, followed by quantification of texture using histogram texture parameters. Results were correlated using non-parametric statistics with a logistic regression model generated. Results: T1+Gad performed best for IDH typing of glioblastoma (sensitivity 91.9%, specificity 100%, AUC 0.945) and ADC for non-Gadolinium-enhancing gliomas (sensitivity 85.7%, specificity 78.4%, AUC 0.877). T2 was moderately precise (sensitivity 83.1%, specificity 78.9%, AUC 0.821). Excellent results for IDH typing were achieved from a combination of the three sequences (sensitivity 90.5%, specificity 94.5%, AUC = 0.98). For discriminating 1p19q genotypes, ADC produced the best results using unfiltered textures (sensitivity 80.6%, specificity 89.3%, AUC 0.811). Conclusion: Preoperative glioma genotyping with MRTA appears valuable with potential for clinical translation. The optimal choice of texture parameters is influenced by sequence choice, tumour morphology and segmentation method.

Primary central nervous system lymphoma (PCNSL) has variable imaging appearances, which overlap with those of glioblastoma (GBM), thereby necessitating invasive tissue diagnosis. We aimed to investigate whether a rapid filtration histogram analysis of clinical MRI data supports the distinction of PCNSL from GBM. Ninety tumours (PCNSL n = 48, GBM n = 42) were analysed using pre-treatment MRI sequences (T1-weighted contrast-enhanced (T1CE), T2-weighted (T2), and apparent diffusion coefficient maps (ADC)). The segmentations were completed with proprietary texture analysis software (TexRAD version 3.3). Filtered (five filter sizes SSF = 2–6 mm) and unfiltered (SSF = 0) histogram parameters were compared using Mann-Whitney U non-parametric testing, with receiver operating characteristic (ROC) derived area under the curve (AUC) analysis for significant results. Across all (n = 90) tumours, the optimal algorithm performance was achieved using an unfiltered ADC mean and the mean of positive pixels (MPP), with a sensitivity of 83.8%, specificity of 8.9%, and AUC of 0.88. For subgroup analysis with &gt, 1/3 necrosis masses, ADC permitted the identification of PCNSL with a sensitivity of 96.9% and specificity of 100%. For T1CE-derived regions, the distinction was less accurate, with a sensitivity of 71.4%, specificity of 77.1%, and AUC of 0.779. A role may exist for cross-sectional texture analysis without complex machine learning models to differentiate PCNSL from GBM. ADC appears the most suitable sequence, especially for necrotic lesion distinction.

BACKGROUND: To assess anatomical and quantitative diffusion-weighted MR imaging features in a recently classified lethal neoplasm, H3 K27M histone-mutant diffuse midline glioma [World Health Organization (WHO) IV]. METHODS: Fifteen untreated gliomas in teenagers and adults (median age 19, range, 14–64) with confirmed H3 K27M histone-mutant genotype were analysed at a national referral centre. Morphological characteristics including tumour epicentre(s), T2/FLAIR and Gadolinium enhancement patterns, calcification, haemorrhage and cyst formation were recorded. Multiple apparent diffusion coefficient (ADC(min), ADC(mean)) regions of interest were sited in solid tumour and normal appearing white matter (ADC(NAWM)) using post-processing software (Olea Sphere v2.3, Olea Medical). ADC histogram data (2(nd), 5(th), 10(th) percentile, median, mean, kurtosis, skewness) were calculated from volumetric tumour segmentations and tested against the regions of interest (ROI) data (Wilcoxon signed rank test). RESULTS: The median interval from imaging to tissue diagnosis was 9 (range, 0–74) days. The structural MR imaging findings varied between individuals and within tumours, often featuring signal heterogeneity on all MR sequences. All gliomas demonstrated contact with the brain midline, and 67% exhibited rim-enhancing necrosis. The mean ROI ADC(min) value was 0.84 (±0.15 standard deviation, SD) ×10(−3) mm(2)/s. In the largest tumour cross-section (excluding necrosis), an average ADC(mean) value of 1.12 (±0.25)×10(−3) mm(2)/s was observed. The mean ADC(min/NAWM) ratio was 1.097 (±0.149), and the mean ADC(mean/NAWM) ratio measured 1.466 (±0.299). With the exception of the 2(nd) centile, no statistical difference was observed between the regional and histogram derived ADC results. CONCLUSIONS: H3 K27M-mutant gliomas demonstrate variable morphology and diffusivity, commonly featuring moderately low ADC values in solid tumour. Regional ADC measurements appeared representative of volumetric histogram data in this study.

BACKGROUND AND PURPOSE: Studies consistently report lower ADC values in isocitrate dehydrogenase (IDH) wild-type gliomas than in IDH mutant tumors, but their methods and thresholds vary. This research aimed to compare volumetric and regional ADC measurement techniques for glioma genotyping, with a focus on IDH status prediction. MATERIALS AND METHODS: Treatment-naive World Health Organization grade II and III gliomas were analyzed by 3 neuroradiologist readers blinded to tissue results. ADC minimum and mean ROIs were defined in tumor and in normal-appearing white matter to calculate normalized values. T2-weighted tumor VOIs were registered to ADC maps with histogram parameters (mean, 2nd and 5th percentiles) extracted. Nonparametric testing (eta2 and ANOVA) was performed to identify associations between ADC metrics and glioma genotypes. Logistic regression was used to probe the ability of VOI and ROI metrics to predict IDH status. RESULTS: The study included 283 patients with 79 IDH wild-type and 204 IDH mutant gliomas. Across the study population, IDH status was most accurately predicted by ROI mean normalized ADC and VOI mean normalized ADC, with areas under the curve of 0.83 and 0.82, respectively. The results for ROI-based genotyping of nonenhancing and solid-patchy enhancing gliomas were comparable with volumetric parameters (area under the curve = 0.81–0.84). In rim-enhancing, centrally necrotic tumors (n = 23), only volumetric measurements were predictive (0.90). CONCLUSIONS: Regional normalized mean ADC measurements are noninferior to volumetric segmentation for defining solid glioma IDH status. Partially necrotic, rim-enhancing tumors are unsuitable for ROI assessment and may benefit from volumetric ADC quantification.

PET holds potential to provide additional information about tumour metabolic processes, which could aid brain tumour differential diagnosis, grading, molecular subtyping and/or the distinction of therapy effects from disease recurrence. This review discusses PET techniques currently in use for untreated and treated glioma characterization and aims to critically assess the evidence for different tracers ([F]Fluorodeoxyglucose, choline and amino acid tracers) in this context.

This review describes the definition, incidence, clinical implications, and magnetic resonance imaging (MRI) findings of pseudoprogression of brain tumors, in particular, but not limited to, high‐grade glioma. Pseudoprogression is an important clinical problem after brain tumor treatment, interfering not only with day‐to‐day patient care but also the execution and interpretation of clinical trials. Radiologically, pseudoprogression is defined as a new or enlarging area(s) of contrast agent enhancement, in the absence of true tumor growth, which subsides or stabilizes without a change in therapy. The clinical definitions of pseudoprogression have been quite variable, which may explain some of the differences in reported incidences, which range from 9–30%. Conventional structural MRI is insufficient for distinguishing pseudoprogression from true progressive disease, and advanced imaging is needed to obtain higher levels of diagnostic certainty. Perfusion MRI is the most widely used imaging technique to diagnose pseudoprogression and has high reported diagnostic accuracy. Diagnostic performance of MR spectroscopy (MRS) appears to be somewhat higher, but MRS is less suitable for the routine and universal application in brain tumor follow‐up. The combination of MRS and diffusion‐weighted imaging and/or perfusion MRI seems to be particularly powerful, with diagnostic accuracy reaching up to or even greater than 90%. While diagnostic performance can be high with appropriate implementation and interpretation, even a combination of techniques, however, does not provide 100% accuracy. It should also be noted that most studies to date are small, heterogeneous, and retrospective in nature. Future improvements in diagnostic accuracy can be expected with harmonization of acquisition and postprocessing, quantitative MRI and computer‐aided diagnostic technology, and meticulous evaluation with clinical and pathological data. Level of Evidence: 3 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2018;48:571–589.

Objectives At a European Society of Neuroradiology (ESNR) Annual Meeting 2015 workshop, commonalities in practice, current controversies and technical hurdles in glioma MRI were discussed. We aimed to formulate guidance on MRI of glioma and determine its feasibility, by seeking information on glioma imaging practices from the European Neuroradiology community. Methods Invitations to a structured survey were emailed to ESNR members (n=1,662) and associates (n=6,400), European national radiologists’ societies and distributed via social media. Results Responses were received from 220 institutions (59% academic). Conventional imaging protocols generally include T2w, T2-FLAIR, DWI, and pre- and post-contrast T1w. Perfusion MRI is used widely (85.5%), while spectroscopy seems reserved for specific indications. Reasons for omitting advanced imaging modalities include lack of facility/software, time constraints and no requests. Early postoperative MRI is routinely carried out by 74% within 24–72 h, but only 17% report a percent measure of resection. For follow-up, most sites (60%) issue qualitative reports, while 27% report an assessment according to the RANO criteria. A minority of sites use a reporting template (23%). Conclusion Clinical best practice recommendations for glioma imaging assessment are proposed and the current role of advanced MRI modalities in routine use is addressed. Key Points • We recommend the EORTC-NBTS protocol as the clinical standard glioma protocol. • Perfusion MRI is recommended for diagnosis and follow-up of glioma. • Use of advanced imaging could be promoted with increased education activities. • Most response assessment is currently performed qualitatively. • Reporting templates are not widely used, and could facilitate standardisation. Electronic supplementary material The online version of this article (10.1007/s00330-018-5314-5) contains supplementary material, which is available to authorized users.

Rapidly progressive encephalopathy in an HIV-positive patient presents a major diagnostic and management challenge. CD8+ encephalitis is a severe but treatable form of HIV-related acute encephalopathy, characterised by diffuse perivascular and intraparenchymal CD8+ lymphocytic infiltration. It can occur in patients who are apparently stable on antiretroviral treatment and probably results from viral escape into the central nervous system. Treatment, including high-dose corticosteroids, can give an excellent neurological outcome, even in people with severe encephalopathy and a very poor initial neurological status. We report a woman with CD8+ encephalitis, with a normal CD4 count and undetectable serum viral load, who made a good recovery despite the severity of her presentation.

The skull base is a highly complex and difficult to access anatomical region, which constitutes a relatively common site for neoplasms. Imaging plays a central role in establishing the differential diagnosis, to determine the anatomic tumour spread and for operative planning. All skull base imaging should be performed using thin-section multiplanar imaging, whereby CT and MRI can be considered complimentary. An interdisciplinary team approach is central to improve the outcome of these challenging tumours.

Background: The aim of this study was to translate dynamic glucose enhancement (DGE) body magnetic resonance imaging (MRI) based on the glucose chemical exchange saturation transfer (glucoCEST) signal to a 3 T clinical field strength. Methods: An infusion protocol for intravenous (i.v.) glucose was optimised using a hyperglycaemic clamp to maximise the chances of detecting exchange-sensitive MRI signal. Numerical simulations were performed to define the optimum parameters for glucoCEST measurements with consideration to physiological conditions. DGE images were acquired for patients with lymphomas and prostate cancer injected i.v. with 20% glucose. Results: The optimised hyperglycaemic clamp infusion based on the DeFronzo method demonstrated higher efficiency and stability of glucose delivery as compared to manual determination of glucose infusion rates. DGE signal sensitivity was found to be dependent on T 2 , B 1 saturation power and integration range. Our results show that motion correction and B 0 field inhomogeneity correction are crucial to avoid mistaking signal changes for a glucose response while field drift is a substantial contributor. However, after B 0 field drift correction, no significant glucoCEST signal enhancement was observed in tumour regions of all patients in vivo . Conclusions: Based on our simulated and experimental results, we conclude that glucose-related signal remains elusive at 3 T in body regions, where physiological movements and strong effects of B 1 + and B 0 render the originally small glucoCEST signal difficult to detect.

Background and purpose There is increasing evidence that many IDH wildtype (IDHwt) astrocytomas have a poor prognosis and although MR features have been identified, there remains diagnostic uncertainty in the clinic. We have therefore conducted a comprehensive analysis of conventional MR features of IDHwt astrocytomas and performed a Bayesian logistic regression model to identify critical radiological and basic clinical features that can predict IDH mutation status. Materials and methods 146 patients comprising 52 IDHwt astrocytomas (19 WHO Grade II diffuse astrocytomas (A II) and 33 WHO Grade III anaplastic astrocytomas (A III)), 68 IDHmut astrocytomas (53 A II and 15 A III) and 26 GBM were studied. Age, sex, presenting symptoms and Overall Survival were recorded. Two neuroradiologists assessed 23 VASARI imaging descriptors of MRI features and the relation between IDH mutation status and MR and basic clinical features was modelled by Bayesian logistic regression, and survival by Kaplan-Meier plots. Results The features of greatest predictive power for IDH mutation status were, age at presentation (OR = 0.94 +/−0.03), tumour location within the thalamus (OR = 0.15 +/−0.25), involvement of speech receptive areas (OR = 0.21 +/−0.26), deep white matter invasion of the brainstem (OR = 0.10 +/−0.32), and T1/FLAIR signal ratio (OR = 1.63 +/−0.64). A logistic regression model based on these five features demonstrated excellent out-of-sample predictive performance (AUC = 0.92 +/−0.07; balanced accuracy 0.81 +/−0.09). Stepwise addition of further VASARI variables did not improve performance. Conclusion Five demographic and VASARI features enable excellent individual prediction ofIDH mutation status, opening the way to identifying patients with IDHwt astrocytomas for earlier tissue diagnosis and more aggressive management.

To investigate if quantitative apparent diffusion coefficient (ADC) measurements can predict genetic subtypes of non-gadolinium-enhancing gliomas, comparing whole tumour against single slice analysis. Volumetric T2-derived masks of 44 gliomas were co-registered to ADC maps with ADC mean (ADCmean) calculated. For the slice analysis, two observers placed regions of interest in the largest tumour cross-section. The ratio (ADCratio) between ADCmean in the tumour and normal appearing white matter was calculated for both methods. Isocitrate dehydrogenase (IDH) wild-type gliomas showed the lowest ADC values throughout (p < 0.001). ADCmean in the IDH-mutant 1p19q intact group was significantly higher than in the IDH-mutant 1p19q co-deleted group (p < 0.01). A volumetric ADCmean threshold of 1201 × 10−6 mm2/s identified IDH wild-type with a sensitivity of 83% and a specificity of 86%; a volumetric ADCratio cut-off value of 1.65 provided a sensitivity of 80% and a specificity of 92% (area under the curve (AUC) 0.9–0.94). A slice ADCratio threshold for observer 1 (observer 2) of 1.76 (1.83) provided a sensitivity of 80% (86%), specificity of 91% (100%) and AUC of 0.95 (0.96). The intraclass correlation coefficient was excellent (0.98). ADC measurements can support the distinction of glioma subtypes. Volumetric and two-dimensional measurements yielded similar results in this study. • Diffusion-weighted MRI aids the identification of non-gadolinium-enhancing malignant gliomas • ADC measurements may permit non-gadolinium-enhancing glioma molecular subtyping • IDH wild-type gliomas have lower ADC values than IDH-mutant tumours • Single cross-section and volumetric ADC measurements yielded comparable results in this study

PURPOSE: To generate a narrative synthesis of published data on the use of endogenous chemical exchange saturation transfer (CEST) MRI in brain tumors. MATERIALS AND METHODS: A systematic database search (PubMed, Ovid Embase, Cochrane Library) was used to collate eligible studies. Two researchers independently screened publications according to predefined exclusion and inclusion criteria, followed by comprehensive data extraction. All included studies were subjected to a bias risk assessment using the Quality Assessment of Diagnostic Accuracy Studies tool. RESULTS: The electronic database search identified 430 studies, of which 36 fulfilled the inclusion criteria. The final selection of included studies was categorized into five groups as follows: grading gliomas, 19 studies (area under the receiver operating characteristic curve [AUC], 0.500–1.000); predicting molecular subtypes of gliomas, five studies (AUC, 0.610–0.920); distinction of different brain tumor types, seven studies (AUC, 0.707–0.905); therapy response assessment, three studies (AUC not given); and differentiating recurrence from treatment-related changes, five studies (AUC, 0.880–0.980). A high bias risk was observed in a substantial proportion of studies. CONCLUSION: Endogenous CEST MRI offers valuable, potentially unique information in brain tumors, but its diagnostic accuracy remains incompletely known. Further research is required to assess the method’s role in support of molecular genetic diagnosis, to investigate its use in the posttreatment phase, and to compare techniques with a view to standardization. Keywords: Brain/Brain Stem, MR-Imaging, Neuro-Oncology Supplemental material is available for this article. © RSNA, 2020

Recently, mutations in the TUBB4A gene have been found to underlie hypomyelination with atrophy of the basal ganglia and cerebellum (H-ABC) syndrome, a rare neurodegenerative disorder of infancy and childhood. TUBB4A mutations also have been described as causative of DYT4 ("hereditary whispering dysphonia"). However, in DYT4, brain imaging has been reported to be normal and, therefore, H-ABC syndrome and DYT4 have been construed to be different disorders, despite some phenotypic overlap. Hence, the question of whether these disorders reflect variable expressivity or pleiotropy of TUBB4A mutations has been raised. We report four unrelated patients with imaging findings either partially or totally consistent with H-ABC syndrome, who were found to have TUBB4A mutations. All four subjects had a relatively homogenous phenotype characterized by severe generalized dystonia with superimposed pyramidal and cerebellar signs, and also bulbar involvement leading to complete aphonia and swallowing difficulties, even though one of the cases had an intermediate phenotype between H-ABC syndrome and DYT4. Genetic analysis of the TUBB4A gene showed one previously described and two novel mutations (c.941C>T; p.Ala314Val and c.900G>T; p.Met300Ile) in the exon 4 of the gene. While expanding the genetic spectrum of H-ABC syndrome, we confirm its radiological heterogeneity and demonstrate that phenotypic overlap with DYT4. Moreover, reappraisal of previously reported cases would also argue against pleiotropy of TUBB4A mutations. We therefore suggest that H-ABC and DYT4 belong to a continuous phenotypic spectrum associated with TUBB4A mutations.

Introduction Intensive postsurgical therapies have improved survival in children with primitive neuroectodermal tumour, but there is concern that the combination of chemotherapy and radiotherapy may result in a compound injury to normal brain. The purposes of this analysis were to characterise what types of imaging abnormalities occur, identify risk factors and explore how treatment-related changes may be distinguished from tumour. Method One hundred fifty-three MRI studies in 14 children treated with sequential chemotherapy, hyperfractionated accelerated radiotherapy and high-dose thiotepa were retrospectively analysed at a paediatric national referral centre. Results We observed 11 episodes of new focal enhancing lesions, 5 of which were transient and judged to be treatment related. In addition, 7/14 (50%) of children demonstrated moderate to severe brain volume loss featuring a leukodystrophy pattern. Conclusion Treatment-related brain MRI abnormalities occurred frequently in this series with a risk of misdiagnosis as tumour. A proportion of patients suffer generalised white matter injury, which has not been appreciated as a side effect of this particular therapy.

Sixty percent of vascular anomalies in children are found in the head and neck. These lesions can present throughout antenatal, perinatal and childhood development. They broadly fall into two categories: vascular tumours and vascular malformations. Their clinical and, often, psychological impact is determined by both pathological type and location: many lesions follow an uncomplicated natural course and other more complex, extensive or progressive lesions can present a threat to life from mass effect, haemorrhage or large volume arteriovenous shunting. Vascular tumours include infantile haemangioma (IH), congenital haemangioma (CH) and kaposiform hemangioendothelioma (KH); of which IH is the most common. Management options for vascular tumours include conservative approaches, oral medications and surgical intervention as determined by tumour type, location and associated complications. Vascular malformations can be categorised into low flow and high flow lesions. Low flow lesions include capillary, venous and lymphatic malformations (LMs). High flow lesions describe the arteriovenous malformations (AVMs), a highly heterogeneous group of lesions which can present in a variety of ways—the mainstay of treatment for these dynamic lesions is endovascular or surgical obliteration. We provide a practical framework for clinical classification of vascular anomalies of the head and neck in children. We also explore principles of their clinical and radiological assessment along with management, highlighting the importance of a multi-disciplinary approach.

At least 25% of individuals with sickle cell disease will have a neurological complication over their lifetime, often as early as in childhood. Neuroradiological findings in patients with sickle cell disease are common and include acute territorial infarction, silent ischaemia and intracranial haemorrhage. Imaging abnormalities are typically, but not always, manifestations of the underlying vasculopathy. Coexisting acute and chronic pathology may pose challenges to interpretation.