Early pseudoprogression and progression lesions in glioblastoma patients are both metabolically heterogeneous.

The standard treatment in glioblastoma includes maximal safe resection followed by concomitant radiotherapy plus chemotherapy and adjuvant temozolomide. The first follow-up study to evaluate treatment response is performed 1 month after concomitant treatment, when contrast-enhancing regions may appear that can correspond to true progression or pseudoprogression. We retrospectively evaluated 31 consecutive patients at the first follow-up after concomitant treatment to check whether the metabolic pattern assessed with multivoxel MRS was predictive of treatment response 2 months later. We extracted the underlying metabolic patterns of the contrast-enhancing regions with a blind-source separation method and mapped them over the reference images. Pattern heterogeneity was calculated using entropy, and association between patterns and outcomes was measured with Cramér's V. We identified three distinct metabolic patterns-proliferative, necrotic, and responsive, which were associated with status 2 months later. Individually, 70% of the patients showed metabolically heterogeneous patterns in the contrast-enhancing regions. Metabolic heterogeneity was not related to the regions' size and only stable patients were less heterogeneous than the rest. Contrast-enhancing regions are also metabolically heterogeneous 1 month after concomitant treatment. This could explain the reported difficulty in finding robust pseudoprogression biomarkers.

Proton MR spectroscopy shows improved performance to segregate high-grade astrocytoma subgroups when defined with the new 2021 World Health Organization classification of central nervous system tumors.

OBJECTIVES: The 2021 World Health Organization (WHO) classification of central nervous system (CNS) tumors prioritizes isocitrate dehydrogenase (IDH) mutation to define tumor types in diffuse gliomas, in contrast to the 2016 classification, which prioritized histological features. Our objective was to investigate the influence of this change in the performance of proton MR spectroscopy (1H-MRS) in segregating high-grade diffuse astrocytoma subgroups. METHODS: Patients with CNS WHO grade 3 and 4 diffuse astrocytoma, known IDH mutation status, and available 1H-MRS were retrospectively retrieved and divided into 4 groups based on IDH mutation status and histological grade. Differences in 1H-MRS between groups were analyzed with the Kruskal-Wallis test. The points on the spectrum that showed the greatest differences were chosen to evaluate the performance of 1H-MRS in discriminating between grades 3 and 4 tumors (WHO 2016 defined), and between IDH-mutant and IDH-wildtype tumors (WHO 2021). ROC curves were constructed with these points, and AUC values were calculated and compared. RESULTS: The study included 223 patients with high-grade diffuse astrocytoma. Discrimination between IDH-mutant and IDH-wildtype tumors showed higher AUC values (highest AUC short TE, 0.943; long TE, 0.864) and more noticeable visual differences than the discrimination between grade 3 and 4 tumors (short TE, 0.885; long TE, 0.838). CONCLUSION: Our findings suggest that 1H-MRS is more applicable to classify high-grade astrocytomas defined with the 2021 criteria. Improved metabolomic robustness and more homogeneous groups yielded better tumor type discrimination by 1H-MRS with the new criteria. CLINICAL RELEVANCE STATEMENT: The 2021 World Health Organization classification of brain tumors empowers molecular criteria to improve tumor characterization. This derives in greater segregation of high-grade diffuse astrocytoma subgroups by MR spectroscopy and warrants further development of brain tumor classification tools with spectroscopy. KEY POINTS: • The new 2021 updated World Health Organization classification of central nervous system tumors maximizes the role of molecular diagnosis in the classification of brain tumors. • Proton MR spectroscopy performs better to segregate high-grade astrocytoma subgroups when defined with the new criteria. • The study provides additional evidence of improved metabolic characterization of brain tumor subgroups with the new criteria.

Deeply 3D-T1-TFE hypointense voxels are characteristic of phase-rim lesions in multiple sclerosis.

OBJECTIVES: The development of new drugs for the treatment of progressive multiple sclerosis (MS) highlights the need for new prognostic biomarkers. Phase-rim lesions (PRLs) have been proposed as markers of progressive disease but are difficult to identify and quantify. Previous studies have identified T1-hypointensity in PRLs. The aim of this study was to compare the intensity profiles of PRLs and non-PRL white-matter lesions (nPR-WMLs) on three-dimensional T1-weighted turbo field echo (3DT1TFE) MRI. We then evaluated the performance of a derived metric as a surrogate for PRLs as potential markers for risk of disease progression. METHODS: This study enrolled a cohort of relapsing-remitting (n = 10) and secondary progressive MS (n = 10) patients for whom 3 T MRI was available. PRLs and nPR-WMLs were segmented, and voxel-wise normalized T1-intensity histograms were analyzed. The lesions were divided equally into training and test datasets, and the fifth-percentile (p5)-normalized T1-intensity of each lesion was compared between groups and used for classification prediction. RESULTS: Voxel-wise histogram analysis showed a unimodal histogram for nPR-WMLs and a bimodal histogram for PRLs with a large peak in the hypointense limit. Lesion-wise analysis included 1075 nPR-WMLs and 39 PRLs. The p5 intensity of PRLs was significantly lower than that of nPR-WMLs. The T1 intensity-based PRL classifier had a sensitivity of 0.526 and specificity of 0.959. CONCLUSIONS: Profound hypointensity on 3DT1TFE MRI is characteristic of PRLs and rare in other white-matter lesions. Given the widespread availability of T1-weighted imaging, this feature might serve as a surrogate biomarker for smoldering inflammation. CLINICAL RELEVANCE STATEMENT: Quantitative analysis of 3DT1TFE may detect deeply hypointense voxels in multiple sclerosis lesions, which are highly specific to PRLs. This could serve as a specific indicator of smoldering inflammation in MS, aiding in early detection of disease progression. KEY POINTS: • Phase-rim lesions (PRLs) in multiple sclerosis present a characteristic T1-hypointensity on 3DT1TFE MRI. • Intensity-normalized 3DT1TFE can be used to systematically identify and quantify these deeply hypointense foci. • Deep T1-hypointensity may act as an easily detectable, surrogate marker for PRLs.

Differentiating IDH-mutant astrocytomas and 1p19q-codeleted oligodendrogliomas using DSC-PWI: high performance through cerebral blood volume and percentage of signal recovery percentiles.

OBJECTIVE: Presurgical differentiation between astrocytomas and oligodendrogliomas remains an unresolved challenge in neuro-oncology. This research aims to provide a comprehensive understanding of each tumor's DSC-PWI signatures, evaluate the discriminative capacity of cerebral blood volume (CBV) and percentage of signal recovery (PSR) percentile values, and explore the synergy of CBV and PSR combination for pre-surgical differentiation. METHODS: Patients diagnosed with grade 2 and 3 IDH-mutant astrocytomas and IDH-mutant 1p19q-codeleted oligodendrogliomas were retrospectively retrieved (2010-2022). 3D segmentations of each tumor were conducted, and voxel-level CBV and PSR were extracted to compute mean, minimum, maximum, and percentile values. Statistical comparisons were performed using the Mann-Whitney U test and the area under the receiver operating characteristic curve (AUC-ROC). Lastly, the five most discriminative variables were combined for classification with internal cross-validation. RESULTS: The study enrolled 52 patients (mean age 45-year-old, 28 men): 28 astrocytomas and 24 oligodendrogliomas. Oligodendrogliomas exhibited higher CBV and lower PSR than astrocytomas across all metrics (e.g., mean CBV = 2.05 and 1.55, PSR = 0.68 and 0.81 respectively). The highest AUC-ROCs and the smallest p values originated from CBV and PSR percentiles (e.g., PSRp70 AUC-ROC = 0.84 and p value = 0.0005, CBVp75 AUC-ROC = 0.8 and p value = 0.0006). The mean, minimum, and maximum values yielded lower results. Combining the best five variables (PSRp65, CBVp70, PSRp60, CBVp75, and PSRp40) achieved a mean AUC-ROC of 0.87 for differentiation. CONCLUSIONS: Oligodendrogliomas exhibit higher CBV and lower PSR than astrocytomas, traits that are emphasized when considering percentiles rather than mean or extreme values. The combination of CBV and PSR percentiles results in promising classification outcomes. CLINICAL RELEVANCE STATEMENT: The combination of histogram-derived percentile values of cerebral blood volume and percentage of signal recovery from DSC-PWI enhances the presurgical differentiation between astrocytomas and oligodendrogliomas, suggesting that incorporating these metrics into clinical practice could be beneficial. KEY POINTS: • The unsupervised selection of percentile values for cerebral blood volume and percentage of signal recovery enhances presurgical differentiation of astrocytomas and oligodendrogliomas. • Oligodendrogliomas exhibit higher cerebral blood volume and lower percentage of signal recovery than astrocytomas. • Cerebral blood volume and percentage of signal recovery combined provide a broader perspective on tumor vasculature and yield promising results for this preoperative classification.

DSC-PWI presurgical differentiation of grade 4 astrocytoma and glioblastoma in young adults: rCBV percentile analysis across enhancing and non-enhancing regions.

PURPOSE: The presurgical discrimination of IDH-mutant astrocytoma grade 4 from IDH-wildtype glioblastoma is crucial for patient management, especially in younger adults, aiding in prognostic assessment, guiding molecular diagnostics and surgical planning, and identifying candidates for IDH-targeted trials. Despite its potential, the full capabilities of DSC-PWI remain underexplored. This research evaluates the differentiation ability of relative-cerebral-blood-volume (rCBV) percentile values for the enhancing and non-enhancing tumor regions compared to the more commonly used mean or maximum preselected rCBV values. METHODS: This retrospective study, spanning 2016-2023, included patients under 55 years (age threshold based on World Health Organization recommendations) with grade 4 astrocytic tumors and known IDH status, who underwent presurgical MR with DSC-PWI. Enhancing and non-enhancing regions were 3D-segmented to calculate voxel-level rCBV, deriving mean, maximum, and percentile values. Statistical analyses were conducted using the Mann-Whitney U test and AUC-ROC. RESULTS: The cohort consisted of 59 patients (mean age 46; 34 male): 11 astrocytoma-4 and 48 glioblastoma. While glioblastoma showed higher rCBV in enhancing regions, the differences were not significant. However, non-enhancing astrocytoma-4 regions displayed notably higher rCBV, particularly in lower percentiles. The 30th rCBV percentile for non-enhancing regions was 0.705 in astrocytoma-4, compared to 0.458 in glioblastoma (p = 0.001, AUC-ROC = 0.811), outperforming standard mean and maximum values. CONCLUSION: Employing an automated percentile-based approach for rCBV selection enhances differentiation capabilities, with non-enhancing regions providing more insightful data. Elevated rCBV in lower percentiles of non-enhancing astrocytoma-4 is the most distinguishable characteristic and may indicate lowly vascularized infiltrated edema, contrasting with glioblastoma's pure edema.

MR dynamic-susceptibility-contrast perfusion metrics in the presurgical discrimination of adult solitary intra-axial cerebellar tumors.

OBJECTIVES: Adult solitary intra-axial cerebellar tumors are uncommon. Their presurgical differentiation based on neuroimaging is crucial, since management differs substantially. Comprehensive full assessment of MR dynamic-susceptibility-contrast perfusion-weighted imaging (DSC-PWI) may reveal key differences between entities. This study aims to provide new insights on perfusion patterns of these tumors and to explore the potential of DSC-PWI in their presurgical discrimination. METHODS: Adult patients with a solitary cerebellar tumor on presurgical MR and confirmed histological diagnosis of metastasis, medulloblastoma, hemangioblastoma, or pilocytic astrocytoma were retrospectively retrieved (2008-2023). Volumetric segmentation of tumors and normal-appearing white matter (for normalization) was semi-automatically performed on CE-T1WI and coregistered with DSC-PWI. Mean normalized values per patient tumor-mask of relative cerebral blood volume (rCBV), percentage of signal recovery (PSR), peak height (PH), and normalized time-intensity curves (nTIC) were extracted. Statistical comparisons were done. Then, the dataset was split into training (75%) and test (25%) cohorts and a classifier was created considering nTIC, rCBV, PSR, and PH in the model. RESULTS: Sixty-eight patients (31 metastases, 13 medulloblastomas, 13 hemangioblastomas, and 11 pilocytic astrocytomas) were included. Relevant differences between tumor types' nTICs were demonstrated. Hemangioblastoma showed the highest rCBV and PH, pilocytic astrocytoma the highest PSR. All parameters showed significant differences on the Kruskal-Wallis tests (p < 0.001). The classifier yielded an accuracy of 98% (47/48) in the training and 85% (17/20) in the test sets. CONCLUSIONS: Intra-axial cerebellar tumors in adults have singular and significantly different DSC-PWI signatures. The combination of perfusion metrics through data-analysis rendered excellent accuracies in discriminating these entities. CLINICAL RELEVANCE STATEMENT: In this study, the authors constructed a classifier for the non-invasive imaging presurgical diagnosis of adult intra-axial cerebellar tumors. The resultant tool can be a support for decision-making in the clinical practice and enables optimal personalized patient management. KEY POINTS: • Adult intra-axial cerebellar tumors exhibit specific, singular, and statistically significant different MR dynamic-susceptibility-contrast perfusion-weighted imaging (DSC-PWI) signatures. • Data-analysis, applied to MR DSC-PWI, could provide added value in the presurgical diagnosis of solitary cerebellar metastasis, medulloblastoma, hemangioblastoma, and pilocytic astrocytoma. • A classifier based on DSC-PWI metrics yields excellent accuracy rates and could be used as a support tool for radiologic diagnosis with clinician-friendly displays.

Voxel-level analysis of normalized DSC-PWI time-intensity curves: a potential generalizable approach and its proof of concept in discriminating glioblastoma and metastasis.

OBJECTIVE: Standard DSC-PWI analyses are based on concrete parameters and values, but an approach that contemplates all points in the time-intensity curves and all voxels in the region-of-interest may provide improved information, and more generalizable models. Therefore, a method of DSC-PWI analysis by means of normalized time-intensity curves point-by-point and voxel-by-voxel is constructed, and its feasibility and performance are tested in presurgical discrimination of glioblastoma and metastasis. METHODS: In this retrospective study, patients with histologically confirmed glioblastoma or solitary-brain-metastases and presurgical-MR with DSC-PWI (August 2007-March 2020) were retrieved. The enhancing tumor and immediate peritumoral region were segmented on CE-T1wi and coregistered to DSC-PWI. Time-intensity curves of the segmentations were normalized to normal-appearing white matter. For each participant, average and all-voxel-matrix of normalized-curves were obtained. The 10 best discriminatory time-points between each type of tumor were selected. Then, an intensity-histogram analysis on each of these 10 time-points allowed the selection of the best discriminatory voxel-percentile for each. Separate classifier models were trained for enhancing tumor and peritumoral region using binary logistic regressions. RESULTS: A total of 428 patients (321 glioblastomas, 107 metastases) fulfilled the inclusion criteria (256 men; mean age, 60 years; range, 20-86 years). Satisfactory results were obtained to segregate glioblastoma and metastases in training and test sets with AUCs 0.71-0.83, independent accuracies 65-79%, and combined accuracies up to 81-88%. CONCLUSION: This proof-of-concept study presents a different perspective on brain MR DSC-PWI evaluation by the inclusion of all time-points of the curves and all voxels of segmentations to generate robust diagnostic models of special interest in heterogeneous diseases and populations. The method allows satisfactory presurgical segregation of glioblastoma and metastases. KEY POINTS: • An original approach to brain MR DSC-PWI analysis, based on a point-by-point and voxel-by-voxel assessment of normalized time-intensity curves, is presented. • The method intends to extract optimized information from MR DSC-PWI sequences by impeding the potential loss of information that may represent the standard evaluation of single concrete perfusion parameters (cerebral blood volume, percentage of signal recovery, or peak height) and values (mean, maximum, or minimum). • The presented approach may be of special interest in technically heterogeneous samples, and intrinsically heterogeneous diseases. Its application enables satisfactory presurgical differentiation of GB and metastases, a usual but difficult diagnostic challenge for neuroradiologist with vital implications in patient management.

Magnetic resonance spectroscopy in posterior fossa tumours: the tumour spectroscopic signature may improve discrimination in adults among haemangioblastoma, ependymal tumours, medulloblastoma, and metastasis.

OBJECTIVES: Assessing a posterior fossa tumour in an adult can be challenging. Metastasis, haemangioblastoma, ependymal tumours, and medulloblastoma are the most common diagnostic possibilities. Our aim was to evaluate the contribution of magnetic resonance spectroscopy (MRS) in the diagnosis of these entities. METHODS: We retrospectively evaluated 56 consecutive patients with a posterior fossa tumour and histological diagnosis of ependymal tumour, medulloblastoma, haemangioblastoma, and metastasis in which good-quality spectra at short (TE 30 ms) or/and intermediate (TE, 136 ms) TE were available. Spectra were compared using the Mann-Whitney U non-parametric test in order to select the spectral datapoints and the intensity ratios that showed significant differences between groups of lesions. Performance of these datapoints and their ratios were assessed with ROC curves. RESULTS: The most characteristic signatures on spectroscopy were high choline (Cho) in medulloblastoma (p < 0.001), high myoinositol (mIns) in ependymal tumours (p < 0.05), and high lipids (LIP) in haemangioblastoma (p < 0.01) and metastasis (p < 0.01). Selected ratios between normalised intensity signals of resonances provided accuracy values between 79 and 95% for pairwise comparisons. Intensity ratio NI3.21ppm/3.55ppm provided satisfactory discrimination between medulloblastoma and ependymal tumours (accuracy, 92%), ratio NI2.11ppm/1.10ppm discriminated ependymal tumours from haemangioblastoma (accuracy, 94%), ratio NI3.21ppm/1.13ppm discriminated haemangioblastoma from medulloblastoma (accuracy, 95%), and ratio NI1.28ppm/2.02pmm discriminated haemangioblastoma from metastasis (accuracy, 83%). CONCLUSIONS: MRS may improve the non-invasive diagnosis of posterior fossa tumours in adults. KEY POINTS: • High choline suggests a medulloblastoma in a posterior fossa tumour. • High myoinositol suggests an ependymal lesion in a posterior fossa tumour. • High lipids suggest a metastasis or a haemangioblastoma in a posterior fossa tumour.

Is a pretreatment radiological staging system feasible for suggesting the optimal extent of resection and predicting prognosis in glioblastoma? An observational study.

To assess the value of resection in glioblastoma based on pre-surgical tumor characteristics and a subsequent staging system. The lack of a staging system for glioblastoma hinders the analysis of treatment outcome. We classified 292 uniformly treated glioblastoma patients as stage I, II, or III based on tumor size, location, and eloquence and then analyzed the impact of the extent of resection. We classified 62% of patients as stage I, 25.3% as stage II, and 12.7% as stage III. Gross total resection (GTR) was performed mainly in stage I rather than stage II or III patients (79.2% vs. 14.6% vs. 6.3%; P < 0.001). Overall survival (OS) was 17.7, 14.6, and 10.8 months for stage I, II, and III patients, respectively (P = 0.005). Longer OS was significantly associated with greater extent of resection, younger age, KPS ≥ 70%, MGMT methylation, lower stage, and tumor ≤ 5 cm. In the subgroups of stage I (P = 0.04) and stage II (P < 0.001)-but not stage III-patients, GTR and partial resection (PR) were associated with longer OS. We constructed several multivariable models including different variables, and greater extent of resection, smaller tumor size, and MGMT methylation consistently emerged as independent markers of longer OS. This staging system provides a feasible tool for comparison of results. We confirmed the value of partial resection in stage I and II patients, in contrast to some reports suggesting that biopsy only is sufficient when gross total resection cannot be safely achieved.

Leukocyte adhesion molecule dynamics after Natalizumab withdrawal in Multiple Sclerosis.

Cell-adhesion molecules (CAMs) dynamics in Multiple Sclerosis (MS) patients have been widely studied after Natalizumab (NTZ) introduction. However, their temporal dynamics after NTZ withdrawal (NTZ-W) has not been described. We prospectively evaluate changes in the expression levels of CAMs (CD49d, CD29, L-Selectin and CD11a) involved in T cell migration of 22 MS patients after NTZ-W. CD49d, CD29 and CD11a expression experienced a continuous increase expression two months after NTZ-W and Cd49d expression at month six after NTZ-W correlated to NTZ treatment duration, both in CD45+CD4+ and CD45+CD8+. CD49d expression up to month three after NTZ-W was related to MS activity in CD45+CD8+ at the end of the study. Results from this study suggest that patients with a longer NTZ treatment are more susceptible to present a "molecular rebound" after NTZ-W. CD49d determination may be a useful tool to closely monitor MS activity in patients who interrupt NTZ.

Early post-operative magnetic resonance imaging in glioblastoma: correlation among radiological findings and overall survival in 60 patients.

OBJECTIVES: To evaluate early post-operative magnetic resonance (EPMR) as a prognostic tool after resection of glioblastoma. METHODS: Sixty EPMR examinations were evaluated for perioperative infarct, tumour growth between diagnosis and EPMR, contrast enhancement pattern, and extent of resection (EOR). The EOR was approached with the subjective evaluation of radiologists and by quantifying volumes. These parameters were tested as predictors of survival using the Kaplan-Meier method. RESULTS: Contrast enhancement was found in 59 patients (59/60; 98 %). Showing a thin-linear pattern of enhancement was the most favourable finding. Patients with this pattern survived longer than patients with thick-linear (median overall survival (OS) thin-linear=609 days; thick-linear=432 days; P = .023) or nodular (median OS = 318 days; P = .001) enhancements. The subjective evaluation of the EOR performed better than its quantification. Patients survived longer when resection was total (median OS total resection=609 days; subtotal=371 days; P = .001). When resection was subtotal, patients survived longer if it was superior to 95 % (median OS resection superior to 95 %=559 days; inferior to 95 %=256 days; P = .034). CONCLUSIONS: EPMR provides valuable prognostic information after surgical resection of glioblastomas. A thin-linear pattern of contrast enhancement is the most favourable finding. Further prognostic stratification may be obtained by assessing the EOR. KEY POINTS: • Some kind of contrast enhancement may be found in most EPMR examinations. • Thin-linear enhancements in the EPMR may be considered benign findings. • The EOR evaluated in the EPMR may stratify prognostic groups of patients. • The subjective evaluation of the EOR performs slightly better than its quantification.

Classification of brain tumours from MR spectra: the INTERPRET collaboration and its outcomes.

The INTERPRET project was a multicentre European collaboration, carried out from 2000 to 2002, which developed a decision-support system (DSS) for helping neuroradiologists with no experience of MRS to utilize spectroscopic data for the diagnosis and grading of human brain tumours. INTERPRET gathered a large collection of MR spectra of brain tumours and pseudo-tumoural lesions from seven centres. Consensus acquisition protocols, a standard processing pipeline and strict methods for quality control of the aquired data were put in place. Particular emphasis was placed on ensuring the diagnostic certainty of each case, for which all cases were evaluated by a clinical data validation committee. One outcome of the project is a database of 304 fully validated spectra from brain tumours, pseudotumoural lesions and normal brains, along with their associated images and clinical data, which remains available to the scientific and medical community. The second is the INTERPRET DSS, which has continued to be developed and clinically evaluated since the project ended. We also review here the results of the post-INTERPRET period. We evaluate the results of the studies with the INTERPRET database by other consortia or research groups. A summary of the clinical evaluations that have been performed on the post-INTERPRET DSS versions is also presented. Several have shown that diagnostic certainty can be improved for certain tumour types when the INTERPRET DSS is used in conjunction with conventional radiological image interpretation. About 30 papers concerned with the INTERPRET single-voxel dataset have so far been published. We discuss stengths and weaknesses of the DSS and the lessons learned. Finally we speculate on how the INTERPRET concept might be carried into the future.

Effectiveness of natalizumab in patients with highly active relapsing remitting multiple sclerosis.

INTRODUCTION: We evaluated the effectiveness of natalizumab in patients with highly active, relapsing-remitting multiple sclerosis (HA-RRMS) to identify baseline predictors associated with freedom from disease activity. METHODS: We analyzed 70 patients treated with natalizumab and followed for at least 1 year with progression of disability of ≥1 point on the EDSS before starting therapy. We recorded freedom from clinical activity, radiological activity, and disease activity (clinical and radiological). RESULTS: The median (IQR) follow-up was 2.3 (2.0-3.8) years. Of the 52 patients who completed 2 years of treatment, 25 were free of disease activity (48.1%). The ARR decreased from a mean ± SD of 2.49 ± 0.86 at baseline to 0.47 ± 0.83 at the end of the first year (p < 0.001) and 0.34 ± 0.69 at the end of the second year (p < 0.001). The percentage of patients with gadolinium-enhanced lesions decreased from 21 at baseline to 5.7 at the end of the first year (p < 0.001) and to 5.8 during the second year (p < 0.005). Baseline EDSS ≤3.0 was significantly associated with freedom from disease activity (OR, 2.49; 95% CI, 1.24-4.99; p = 0.010). CONCLUSIONS: Natalizumab is effective in patients with HA-RRMS. Baseline EDSS ≤3.0 increases the probability of remaining disease-free in HA-RRMS treated with natalizumab.

Multicentre evaluation of the INTERPRET decision support system 2.0 for brain tumour classification.

In a previous study, we have shown the added value of (1) H MRS for the neuroradiological characterisation of adult human brain tumours. In that study, several methods of MRS analysis were used, and a software program, the International Network for Pattern Recognition of Tumours Using Magnetic Resonance Decision Support System 1.0 (INTERPRET DSS 1.0), with a short-TE classifier, provided the best results. Since then, the DSS evolved into a version 2.0 that contains an additional long-TE classifier. This study has two objectives. First, to determine whether clinicians with no experience of spectroscopy are comparable with spectroscopists in the use of the system, when only minimum training in the use of the system was given. Second, to assess whether or not a version with another TE is better than the initial version. We undertook a second study with the same cases and nine evaluators to assess whether the diagnostic accuracy of DSS 2.0 was comparable with the values obtained with DSS 1.0. In the second study, the analysis protocol was flexible in comparison with the first one to mimic a clinical environment. In the present study, on average, each case required 5.4 min by neuroradiologists and 9 min by spectroscopists for evaluation. Most classes and superclasses of tumours gave the same results as with DSS 1.0, except for astrocytomas of World Health Organization (WHO) grade III, in which performance measured as the area under the curve (AUC) decreased: AUC = 0.87 (0.72-1.02) with DSS 1.0 and AUC = 0.62 (0.55-0.70) with DSS 2.0. When analysing the performance of radiologists and spectroscopists with respect to DSS 1.0, the results were the same for most classes. Having data with two TEs instead of one did not affect the results of the evaluation.

(1)H-MRS is useful to reinforce the suspicion of primary central nervous system lymphoma prior to surgery.

OBJECTIVES: To assess whether (1)H-MRS may be useful to reinforce the radiological suspicion of PCNSL. METHODS: In this retrospective study, we included 546 patients with untreated brain tumours in which single-voxel spectroscopy at TE 30 ms and 136 ms had been performed. The patients were split into two subgroups: "training set" and "test set." Differences between PCNSL and five other types of intracranial tumours were assessed in the test set of patients using the Mann-Whitney U nonparametric test and cut-off values for pair-wise comparisons defined by constructing receiver operating characteristic curves. These thresholds were used to construct classifiers for binary comparison between PCNSL and non-PCNSL. The performance of the obtained classifiers was assessed in the independent test set of patients. RESULTS: Significant differences were found between PCNSL and the other groups evaluated. All bilateral comparisons performed in the test set obtained accuracy values above 70 % (71-89 %). Lipids were found to be useful to discriminate between PCNSL and glioblastoma/metastasis at short TE. Myo-inositol resonance was found to be very consistent for discriminating between PCNSL and astrocytomas at short TE. CONCLUSIONS: (1)H-MRS is useful to reinforce diagnostic suspicion of PCNSL on MRI. KEY POINTS: • (1) H-MRS can be used to reinforce the diagnostic suspicion of PCNSL. • Lipids can be used to discriminate between PCNSL and GB/MET. • Myo-inositol resonance can be used to discriminate between PCNSL and astrocytomas.

The T1-dark-rim: A novel imaging sign for detecting smoldering inflammation in multiple sclerosis.

PURPOSE: Paramagnetic rim lesions (PRLs), usually identified in susceptibility-weighted imaging (SWI), are a promising prognostic biomarker of disability progression in multiple sclerosis (MS). However, SWI is not routinely performed in clinical practice. The objective of this study is to define a novel imaging sign, the T1-dark rim, identifiable in a standard 3DT1 gradient-echo inversion-recovery sequence, such as 3D T1 turbo field echo (3DT1FE) and explore its performance as a SWI surrogate to define PRLs. METHODS: This observational cross-sectional study analyzed MS patients who underwent 3T magnetic resonance imaging (MRI) including 3DT1TFE and SWI. Rim lesions were evaluated in 3DT1TFE, processed SWI, and SWI phase and categorized as true positive, false positive, or false negative based on the value of the T1-dark rim in predicting SWI phase PRLs. Sensitivity and positive predictive values of the T1-dark rim for detecting PRLs were calculated. RESULTS: Overall, 80 rim lesions were identified in 63 patients (60 in the SWI phase and 78 in 3DT1TFE; 58 true positives, 20 false positives, and two false negatives). The T1-dark rim demonstrated 97% sensitivity and 74% positive predictive value for detecting PRLs. More PRLs were detected in the SWI phase than in processed SWI (60 and 57, respectively). CONCLUSION: The T1-dark rim sign is a promising and accessible novel imaging marker to detect PRLs whose high sensitivity may enable earlier detection of chronic active lesions to guide MS treatment escalation. The relevance of T1-dark rim lesions that are negative on SWI opens up a new field for analysis.

Tumoral and normal brain tissue extraction protocol for wide-scope screening of organic pollutants.

Little is known about the presence of organic pollutants in human brain (and even less in brain tumors). In this regard, it is necessary to develop new analytical protocols capable of identifying a wide range of exogenous chemicals in this type of samples (by combining target, suspect and non-target strategies). These methodologies should be robust and simple. This is particularly challenging for solid samples, as reliable extraction and clean-up techniques should be combined to obtain an optimal result. Hence, the present study focuses on the development of an analytical methodology that allows the screening of a wide range of organic chemicals in brain and brain tumor samples. This protocol was based on a solid-liquid extraction based on bead beating, solid-phase extraction clean-up with multi-layer mixed-mode cartridges, reconstitution and LC-HRMS analysis. To evaluate the performance of the extraction methodology, a set of 66 chemicals (e.g., pharmaceuticals, biocides, or plasticizers, among others) with a wide range of physicochemical properties was employed. Quality control parameters (i.e., linear range, sensitivity, matrix effect (ME%), and recoveries (R%)) were calculated and satisfactory results were obtained for them (e.g., R% within 60-120% for 32 chemicals, or ME% higher than 50% (signal suppression) for 79% of the chemicals).

Prospective diagnostic performance evaluation of single-voxel 1H MRS for typing and grading of brain tumours.

The purpose of this study was to evaluate whether single-voxel (1)H MRS could add useful information to conventional MRI in the preoperative characterisation of the type and grade of brain tumours. MRI and MRS examinations from a prospective cohort of 40 consecutive patients were analysed double blind by radiologists and spectroscopists before the histological diagnosis was known. The spectroscopists had only the MR spectra, whereas the radiologists had both the MR images and basic clinical details (age, sex and presenting symptoms). Then, the radiologists and spectroscopists exchanged their predictions and re-evaluated their initial opinions, taking into account the new evidence. Spectroscopists used four different systems of analysis for (1)H MRS data, and the efficacy of each of these methods was also evaluated. Information extracted from (1)H MRS significantly improved the radiologists' MRI-based characterisation of grade IV tumours (glioblastomas, metastases, medulloblastomas and lymphomas) in the cohort [area under the curve (AUC) in the MRI re-evaluation 0.93 versus AUC in the MRI evaluation 0.85], and also of the less malignant glial tumours (AUC in the MRI re-evaluation 0.93 versus AUC in the MRI evaluation 0.81). One of the MRS analysis systems used, the INTERPRET (International Network for Pattern Recognition of Tumours Using Magnetic Resonance) decision support system, outperformed the others, as well as being better than the MRI evaluation for the characterisation of grade III astrocytomas. Thus, preoperative MRS data improve the radiologists' performance in diagnosing grade IV tumours and, for those of grade II-III, MRS data help them to recognise the glial lineage. Even in cases in which their diagnoses were not improved, the provision of MRS data to the radiologists had no negative influence on their predictions.

High Myoinositol on Proton MR Spectroscopy Could Be a Potential Signature of Papillary Tumors of the Pineal Region-Case Report of Two Patients.

Papillary tumor of the pineal region (PTPR) is an uncommon entity in which a presurgical suspicion may be crucial for patient management. Maximal safe neurosurgical resection is of choice when PTPR is suspected, whereas non-surgical approaches can be considered in other tumors of the pineal region, such as pineocytoma or concrete subtypes of germ-cell tumors. In general terms, imaging features of tumors of the pineal region have been reported to be unspecific. Nevertheless, in this report, we describe two pathology-confirmed PTPRs in which presurgical proton MR spectroscopy demonstrated extremely high myoinositol, a pattern which drastically differs from that of other pineal tumors. We hypothesize that this high myoinositol may be related to PTPR's known ependymal component, and that it could be used as a specific non-invasive diagnostic signature.