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Immune check point inhibitors (ICIs) are a group of anti-cancer pharmacological agents which modify T cell activity in order to potentiate an effective immune response against tumor cells. While these drugs prove extremely potent against several types of malignancies, they may be associated with significant autoimmune adverse events. We report a patient who developed a subacute cerebellar syndrome shortly after starting treatment with nivolumab, a PD-1 inhibitor, for renal clear cell carcinoma, with detectable paraneoplastic PCA-2 antibodies. The tumor specimen stained positively for MAP1B, the antigen of PCA-2. The patient responded well to treatment with glucocorticosteroids. This is the first case to our knowledge of PCA-2 paraneoplastic cerebellar degeneration associated with ICI use, which presents in a patient with a malignancy not typically associated with neurological paraneoplastic phenomena. Treatment with immune checkpoint inhibitors (ICIs) is extremely effective in potentiating an immune response against tumor cells, but bears a substantial risk for the development of autoimmune phenomena, including paraneoplastic neurological syndromes. Increasing use of ICIs is leading to increasing numbers of patients with new-onset neurological symptoms. Awareness of these novel entities will aid in early diagnosis and proper treatment.

Treatment response assessment in patients with high-grade gliomas (HGG) is heavily dependent on changes in lesion size on MRI. However, in conventional MRI, treatment-related changes can appear as enhancing tissue, with similar presentation to that of active tumor tissue. We propose a model-free data-driven method for differentiation between these tissues, based on dynamic contrast-enhanced (DCE) MRI.The study included a total of 66 scans of patients with glioblastoma. Of these, 48 were acquired from 1 MRI vendor and 18 scans were acquired from a different MRI vendor and used as test data. Of the 48, 24 scans had biopsy results. Analysis included semi-automatic arterial input function (AIF) extraction, direct DCE pharmacokinetic-like feature extraction, and unsupervised clustering of the two tissue types. Validation was performed via (a) comparison to biopsy result (b) correlation to literature-based DCE curves for each tissue type, and (c) comparison to clinical outcome.Consistency between the model prediction and biopsy results was found in 20/24 cases. An average correlation of 82% for active tumor and 90% for treatment-related changes was found between the predicted component and population-based templates. An agreement between the predicted results and radiologist's assessment, based on RANO criteria, was found in 11/12 cases.The proposed method could serve as a non-invasive method for differentiation between lesion tissue and treatment-related changes.

OBJECTIVEPreoperative localization of seizure onset zones (SOZs) is an evolving field in the treatment of refractory epilepsy. Both magnetic source imaging (MSI), and the more recent EEG-correlated functional MRI (EEG-fMRI), have shown applicability in assisting surgical planning. The purpose of this study was to evaluate the capability of each method and their combination in localizing the seizure onset lobe (SL).METHODSThe study included 14 patients who underwent both MSI and EEG-fMRI before undergoing implantation of intracranial EEG (icEEG) as part of the presurgical planning of the resection of an epileptogenic zone (EZ) during the years 2012–2018. The estimated location of the SL by each method was compared with the location determined by icEEG. Identification rates of the SL were compared between the different methods.RESULTSMSI and EEG-fMRI showed similar identification rates of SL locations in relation to icEEG results (88% ± 31% and 73% ± 42%, respectively; p = 0.281). The additive use of the coverage lobes of both methods correctly identified 100% of the SL, significantly higher than EEG-fMRI alone (p = 0.039) and nonsignificantly higher than MSI (p = 0.180). False-identification rates of the additive coverage lobes were significantly higher than MSI (p = 0.026) and EEG-fMRI (p = 0.027). The intersecting lobes of both methods showed the lowest false identification rate (13% ± 6%, p = 0.01).CONCLUSIONSBoth MSI and EEG-fMRI can assist in the presurgical evaluation of patients with refractory epilepsy. The additive use of both tests confers a high identification rate in finding the SL. This combination can help in focusing implantation of icEEG electrodes targeting the SOZ.

Background and ObjectivesTo explore the clinical characteristics and HLA associations of patients with anti–leucine-rich glioma-inactivated 1 encephalitis (LGI1E) from a large single center in Israel. Anti-LGI1E is the most commonly diagnosed antibody-associated encephalitic syndrome in adults. Recent studies of various populations reveal significant associations with specific HLA genes. We examined the clinical characteristics and HLA associations of a cohort of Israeli patients.MethodsSeventeen consecutive patients with anti-LGI1E diagnosed at Tel Aviv Medical Center between the years 2011 and 2018 were included. HLA typing was performed using next-generation sequencing at the tissue typing laboratory of Sheba Medical Center and compared with data from the Ezer Mizion Bone Marrow Donor Registry, containing over 1,000,000 samples.ResultsOur cohort displayed a male predominance and median age at onset in the 7th decade, as previously reported. The most common presenting symptom was seizures. Notably, paroxysmal dizziness spells were significantly more common than previously reported (35%), whereas faciobrachial dystonic seizures were found only in 23%. HLA analysis revealed overrepresentation of DRB1*07:01 (OR: 3.18, CI: 20.9p< 1.e-5) and DRB1*04:02 (OR: 3.8, CI: 20.1p< 1.e-5), as well as of the DQ allele DQB1*02:02 (OR: 2.8, CI: 14.2p< 0.0001) as previously reported. A novel overrepresentation observed among our patients was of the DQB1*03:02 allele (OR: 2.3, CI: 6.9p< 0.008). In addition, we found DR-DQ associations, among patients with anti-LGI1E, that showed complete or near-complete linkage disequilibrium (LD). By applying LD analysis to an unprecedentedly large control cohort, we were able to show that although in the general population, DQB*03:02 is not fully associated with DRB1*04:02, in the patient population, both alleles are always coupled, suggesting the DRB1*04:02 association to be primary to disease predisposition. In silico predictions performed for the overrepresented DQ alleles reveal them to be strong binders of LGI1-derived peptides, similarly to overrepresented DR alleles. These predictions suggest a possible correlation between peptide binding sites of paired DR-DQ alleles.DiscussionOur cohort presents distinct immune characteristics with substantially higher overrepresentation of DRB1*04:02 and slightly lower overrepresentation of DQB1*07:01 compared with previous reports implying differences between different populations. DQ-DR interactions found in our cohort may shed additional light on the complex role of immunogenetics in the pathogenesis of anti-LGI1E, implying a possible relevance of certain DQ alleles and DR-DQ interactions.

In recent years, several automatic methods have been proposed to differentiate between brain tumor recurrence and treatment-related changes following radiotherapy, based on conventional and advanced MRI methods. Vascular parameters extracted from dynamic contrast-enhanced (DCE) were suggested as potential markers for disease progression. Yet, most studies that proposed machine-learning methods or relayed on threshold values of DCE for classification, did not analyze separately Glioblastoma (GBM) and brain metastasis, and often offer the same method/threshold values, neglecting the different vascularity of these two tumor types. Understanding and quantifying the differences between tumors type can improve early diagnosis of recurrence and may improve the reliability of identifying treatment-related changes. The aim of this study was to quantify vascular parameters of tumor recurrence and to assess differences between GBM and brain metastasis, specifically metastasis of breast cancer. METHOD: 41 MRI scans were included: 24 from patients with GBM: 20 with recurrence and 4 with treatment-related changes, and 17 scans from patients with brain metastasis of breast cancer: 10 with recurrence and 7 with treatment-related changes (diagnosis were based on radiological follow-up/histopathology, when available). MRIs were performed on a 3.0 Tesla MRI scanner (Siemens MAGNETOM Prisma) and included T1, T1+contrast, and DCE images. DCE analysis was performed using DUSTER and Ktrans, Vp and Kep pharmacokinetic parameters were compared between groups. RESULTS: Patients with GBM often demonstrated both tumor recurrence and areas with treatment-related changes. Significantly differences were detected between tumor recurrence and treatment-related changes, and higher Vp and Ktrans were detected in recurrent GBM as compared to recurrent breast cancer metastasis. Cutoff for differentiation between tumor recurrence and treatment-related changes will be presented specifically for each tumor type. To conclude, when defining quantitative threshold values for clinical decision-making, the inherent differences between primary and metastatic brain tumors should be taken into account.

ObjectiveExploring the clinical characteristics and HLA associations of patients with anti-leucine–rich glioma-inactivated 1 encephalitis (LGI1E) from a large single center in IsraelBackgroundAnti-LGI1E is one of the most commonly diagnosed antibody-associated encephalitic syndromes in adults. Recent studies of various populations reveal significant associations with specific Human Leukocyte Antigen (HLA) genes. We examined the clinical characteristics and HLA associations of a cohort of Israeli patients.Design/MethodsSeventeen consecutive anti-LGI1E patients diagnosed at Tel Aviv Sourasky Medical Center between the years 2011-2018 were included. HLA typing was performed using NGS methodology at the tissue typing laboratory of Sheba Medical Center and compared to data from the "Ezer Mizion" Bone Marrow Donor Registry, containing over 1,000,000 samples.ResultsOur cohort displayed a male predominance and median age of onset in the 7th decade, as previously reported. All patients responded to immunotherapy, though residual damage was not uncommon (23% with MRS >1). HLA analysis revealed overexpression of DRB1*07:01 (OR 13, CI 0.6 p < 1.e-10) and DRB1*04:02 (OR 12, CI-0.6 p < 1.e-10), as previously reported, as well as of the DQ alleles DQB1*02:02 (OR 12, CI 0.6 p < 1.e-10), DQB1*03:03 (OR 27, CI 0.9 p < 1.e-10), previously attributed to linkage disequilibrium (LD) with the mentioned DR alleles. An additional allele overexpressed among our patients was the DQB1*03:02 allele (OR 12, CI 0.6 p < 1.e-10), which appeared in complete LD with DRB1*04:02. Linkage disequilibrium analysis performed on patients and controls suggests these DR-DQ associations are unique to anti-LGI1E patients. In silico predictions performed for the overexpressed DQ alleles reveal them to be strong binders of LGI1 derived peptides, and suggest a correlation between peptide binding sites of paired DR-DQ alleles.ConclusionsOur findings shed additional light on the complex role of immunogenetics in the pathogenesis of anti-LGI1E, implying the possible relevance of certain DQ alleles as well as DR-DQ interactions.

MR-guided laser interstitial thermal therapy (MRgLITT) is a minimally invasive technique for ablating brain lesions under real-time MRI feedback and control of the ablation process. The Medtronic Visualase system was recently approved for use in Europe and Israel. We report our initial technical experience using the system in the first 16 cases in which the system was used to ablate focal epileptogenic lesions. We included all consecutive patients with intractable epilepsy who underwent MRgLITT procedures between 2018 and 2020. We reviewed medical charts and imaging studies of patients. Post-ablation MRIs were used to calculate ablation volumes. Seventeen MRgLITT procedures were performed in 16 patients. One cooling catheter/laser fiber assemblies were placed per patient. Indications for surgery were intractable epilepsy due to TLE (n = 7), suspected low-grade glioma (n = 4), radiological cortical dysplasia (n = 1), hypothalamic hamartoma (n = 1), and MR-negative foci (n = 3). Ablations were made using 30 to 70% of the maximal energy of the Visualase system. We used serial ablations as needed along the tract of the catheter by pulling back the optic fiber; the length of the lesion ranged between 7.4 and 38.1 mm. Ablation volume ranged between 0.27 and 6.78 mm3. Immediate post-ablation MRI demonstrated good ablation of the epileptic lesion in 16/17 cases. In one case with mesial temporal sclerosis, no ablation was performed due to suboptimal position of the catheter. That patient was successfully reoperated at a later date. Mean follow-up was 14.9 months (± 11.6 months). Eleven patients had follow-up longer than 12 months. Good seizure control (Engel I, A) was achieved in 7/11 patients (63%) and 1/11 (9%) had significant improvement in seizure frequency (Angle IIIa). Three patients (27%) did not experience improvement in their seizure frequency (Engel IV, B), and one of these patients died during the follow-up period from sudden unexpected death of epilepsy (SUDEP). No immediate or delayed neurological complications were documented in any of the cases during the follow-up period. MRgLITT is a promising technique and can be used safely as an alternative to open resection in both lesional and non-lesional intractable epilepsy cases. In our local series, the success rate of epilepsy surgery was comparable to recent publications.

Background: Cerebrospinal fluid (CSF) is essential for the medical workup of patients with neurological conditions and for disease-modifying clinical trials. Post- lumbar puncture (LP) headache is influenced by both operator and patient-related factors, including needle type and gauge, age, and gender. Objectives: We aimed to assess whether CSF volume measured based on pre-procedural brain MRI is associated with the risk of developing a post-LP headache. Methods: In total, n = 117 participants (n = 58 Parkinson's disease patients, and n = 59 healthy controls) underwent an LP and CSF collection. Of those, n = 89 underwent MRI scans prior to the LP procedure acquiring high-resolution 3D magnetization-prepared rapid gradient echo (MP-RAGE) T1-weighted images using a 3 T MR scanner. Clinical and behavioral assessments were performed for all participants, and CSF was assessed for content. The T1-weighted images were segmented producing gray matter, white matter, and CSF probability maps. Results: Thirteen participants (11.1%) experienced post-LP headache. They were younger (p = .033) and had lower CSF volumes (p = .040) compared to participants that did not develop a post LP headache. Conclusions: The results of this pilot study suggest that low CSF volumes might increase the risk for the occurrence of post-LP adverse events and should be taken into consideration when planning LP's.

To study the repeatability of plasma volume (vp) extracted from dynamic-contrast-enhanced (DCE) MRI in order to define threshold values for significant longitudinal changes, and to assess changes in patients with high-grade-glioma (HGG). Twenty eight healthy subjects, of which eleven scanned twice, were used to assess the repeatability of vp within the normal-appearing brain tissue and to define threshold values for significant changes based on least-detected-differences (LDD) of mean vp values and histogram comparisons using earth-mover’s-distance (EMD). Sixteen patients with HGG were scanned longitudinally with eight patients scanned before and following bevacizumab therapy. Longitudinal changes were assessed based on defined threshold values in comparison to RANO criteria. The threshold values for significant changes were: LDD = 0.0024 (ml/100 ml, 21%) for mean vp and EMD = 4.14. In patients, in 20/24 comparisons, no significant longitudinal changes were detected for vp within the normal-appearing brain tissue. Concurring results were obtained between changes in lesion volume (RANO criteria) and LDD or EMD values in cases diagnosed with progressive-disease, yet in about 50% of cases diagnosed with partial-response preliminary results demonstrated significant increase in vp despite significant reductions in lesion volume. In two patients, these changes preceded progression detected at follow-up scans. In general, a good concordance was obtained between LDD and EMD. This study shows high repeatability of vp and provides threshold values for significant changes in longitudinal assessment of patients with brain tumors. Preliminary results suggest the use of vp-DCE parameter to improve assessment of therapy response in patients with high-grade-glioma.

BACKGROUND High-grade gliomas (HGGs) induce both vasogenic edema and extensive infiltration of tumor cells, both of which present with similar appearance on conventional MRI. Using current radiological criteria, differentiation between these tumoral and nontumoral areas within the nonenhancing lesion area remains challenging. PURPOSE To use radiomics patch-based analysis, based on conventional MRI, for the classification of the nonenhancing lesion area in patients with HGG into tumoral and nontumoral components. STUDY TYPE Prospective. SUBJECTS In all, 179 MRI scans were obtained from 102 patients: 67 patients with HGG and 35 patients with brain metastases. A subgroup of 15 patients with HGG were scanned before and following administration of bevacizumab. FIELD STRENGTH/SEQUENCE Pre and postcontrast agent T1 -weighted-imaging (WI), T2 WI, FLAIR, diffusion-tensor-imaging (DTI), and dynamic-contrast-enhanced (DCE)-MRI at 3T. ASSESSMENT A total of 225 histograms and gray-level-co-occurrence matrix-based features were extracted from the nonenhancing lesion area. Tumoral volumes of interest (VOIs) were defined at the peritumoral area in patients with HGG; nontumoral VOIs were defined in patients with brain metastasis. Twenty machine-learning algorithms including support-vector-machine (SVM), k-nearest neighbor, decision-trees, and ensemble classifiers were tested. The best classifier was trained on the entire labeled data, and was used to classify the entire data. STATISTICAL TESTS Dimensional reduction was performed on the 225 features using principal component analysis. Classification results were evaluated based on the sensitivity, specificity, and accuracy of each of the 20 classifiers, first based on a training and testing dataset (80% of the labeled data) in a 5-fold manner, and next by applying the best classifier to the validation data (the remaining 20% of the labeled data). Results were additionally evaluated by assessing differences in dynamic-contrast-enhanced plasma-volume (vp ) and volume-transfer-constant (ktrans ) values between the two components using Mann-Whitney U-test/t-test. RESULTS The best classification into tumoral and nontumoral lesion components was obtained using a linear SVM classifier, with average accuracy of 87%, sensitivity 86%, and specificity of 89% (for the training and testing data). Significantly higher vp and ktrans values (P < 0.0001) were detected in the tumoral compared to the nontumoral component. Preliminary classification results in a subgroup of patients treated with bevacizumab demonstrated a reduction mainly in the nontumoral component following administration of bevacizumab, enabling early assessment of disease progression in some patients. DATA CONCLUSION A radiomics patch-based analysis enables classification of the nonenhancing lesion area in patients with HGG. Preliminary results were promising and the proposed method has the potential to assist in clinical decision-making and to improve therapy response assessment in patients with HGG. LEVEL OF EVIDENCE 1 Technical Efficacy Stage 4 J. Magn. Reson. Imaging 2018.

BACKGROUND AND PURPOSE: Current imaging assessment of high-grade brain tumors relies on the Response Assessment in Neuro-Oncology criteria, which measure gross volume of enhancing and nonenhancing lesions from conventional MRI sequences. These assessments may fail to reliably distinguish tumor and nontumor. This study aimed to classify enhancing and nonenhancing lesion areas into tumor-versus-nontumor components. MATERIALS AND METHODS: A total of 140 MRI scans obtained from 32 patients with high-grade gliomas and 6 patients with brain metastases were included. Classification of lesion areas was performed using a support vector machine classifier trained on 4 components: enhancing and nonenhancing, tumor and nontumor, based on T1-weighted, FLAIR, and dynamic-contrast-enhancing MRI parameters. Classification results were evaluated by 2-fold cross-validation analysis of the training set and MR spectroscopy. Longitudinal changes of the component volumes were compared with Response Assessment in Neuro-Oncology criteria. RESULTS: Normalized T1-weighted values, FLAIR, plasma volume, volume transfer constant, and bolus-arrival-time parameters differentiated components. High sensitivity and specificity (100%) were obtained within the enhancing and nonenhancing areas. Longitudinal changes in component volumes correlated with the Response Assessment in Neuro-Oncology criteria in 27 patients; 5 patients (16%) demonstrated an increase in tumor component volumes indicating tumor progression. These changes preceded Response Assessment in Neuro-Oncology assessments by several months. Seven patients treated with bevacizumab showed a shift to an infiltrative pattern of progression. CONCLUSIONS: This study proposes an automatic classification method: segmented Response Assessment in Neuro-Oncology criteria based on advanced imaging that reliably differentiates tumor and nontumor components in high-grade gliomas. The segmented Response Assessment in Neuro-Oncology criteria may improve therapy-response assessment and provide earlier indication of progression.

Normal brain cells depend on glucose metabolism, yet they have the flexibility to switch to the usage of ketone bodies during caloric restriction. In contrast, tumor cells lack genomic and metabolic flexibility and are largely dependent on glucose. Ketogenic-diet (KD) was suggested as a therapeutic option for malignant brain cancer. This study aimed to detect metabolic brain changes in patients with malignant brain gliomas on KD using proton magnetic-resonance-spectroscopy (1H-MRS). Fifty MR scans were performed longitudinally in nine patients: four patients with recurrent glioblastoma (GB) treated with KD in addition to bevacizumab; one patient with gliomatosis-cerebri treated with KD only; and four patients with recurrent GB who did not receive KD. MR scans included conventional imaging and 1H-MRS acquired from normal appearing-white-matter (NAWM) and lesion. High adherence to KD was obtained only in two patients, based on high urine ketones; in these two patients ketone bodies, Acetone and Acetoacetate were detected in four MR spectra—three within the NAWM and one in the lesion area −4 and 25 months following initiation of the diet. No ketone-bodies were detected in the control group. In one patient with gliomatosis-cerebri, who adhered to the diet for 3 years and showed stable disease, an increase in glutamin + glutamate and reduction in N-Acetyl-Aspartate and myo-inositol were detected during KD. 1H-MRS was able to detect ketone-bodies in patients with brain tumors who adhered to KD. Yet it remains unclear whether accumulation of ketone bodies is due to increased brain uptake or decreased utilization of ketone bodies within the brain.

Thyrotropin (TSH)-secreting pituitary tumors are the rarest functioning pituitary tumors. Nonetheless, they are not infrequently plurihormonal, as they may express/secrete hormones made by other pituitary cells derived from the Pit-1 lineage such as growth hormone (GH), prolactin (PRL), and α-subunit (αSU). However, adrenocorticotropin (ACTH) or gonadotropin secretion by such a tumor is exceptional. Although double pituitary tumors are rare, they often combine ACTH and GH secretion. A 41-year-old presented almost 2 years after delivering her 10th child; she had thyrotoxicosis (goiter and palpitations) masquerading as autoimmune postpartum thyroiditis. She was still breastfeeding and amenorrheic. She proved to have TSH, GH, PRL, and ACTH hypersecretion. Imaging revealed an invasive pituitary macrotumor. She had stigmata neither of Cushing’s disease nor of acromegaly. Prior to surgery, hormonal control was achieved for close to 1 year by combined octreotide and cabergoline treatment with significant shrinking of the tumor. Following surgery, pathology revealed a collision tumor; the dominant lesion was positive for GH, βTSH, βFSH, and αSU and expressed both Pit-1 and SF-1.The smaller lesion was a corticotroph tumor. We report an unusual plurihormonal tumor co-expressing Pit-1 and SF-1 along with hormones made by cells of both lineages. Its simultaneous occurrence adjacent to a corticotroph tumor raises questions regarding the pathogenesis of these tumors. We propose the possibility of a stem cell tumor with multiple lineage differentiation. We hypothesize that pregnancy might have played a permissive role in tumorigenesis.

Paraneoplastic limbic encephalitis (PLE) is a rare disease with established diagnostic criteria. We describe a case of an uncommon presentation of PLE in a female who presented with a one- year duration of short-term memory loss and mild behavioral changes who was eventually diagnosed with PLE associated with breast cancer. Our case demonstrates atypical presentation of PLE, with chronic presentation and an uncharacteristic mild neurological symptoms. This case aims to highlight the importance of a diagnostic work up of autoimmune encephalitis in selected cases that does not present with common diagnostic criteria.

The interstitium-to-plasma rate constant (kep), extracted from dynamic contrast enhancement (DCE-MRI) MRI data, seems to have an important role in the assessment of patients with brain tumors. This parameter is affected by the slow behavior of the system, and thus is expected to be highly dependent on acquisition duration. The aim of this study was to optimize the scan duration and protocol of DCE-MRI for accurate estimation of the kep parameter in patients with high grade brain tumors. The effects of DCE-MRI scan duration and protocol design (continuous vs integrated scanning) on the estimated pharmacokinetic (PK) parameters and on model selection, were studied using both simulated and patient data. Scan duration varied, up to 60min for simulated data, and up to 25min in 25 MRI scans obtained from patients with high grade brain tumors, with continuous and integrated scanning protocols. Converging results were obtained from simulated and real data. Significant effect of scan duration was detected on kep. Scan duration of 9min, with integrated protocol in which the data are acquired continuously for 5min, and additional volumes at 7 and 9min, was sufficient for accurate estimation of even low kep values, with an average error of 3%. Over-estimation of the PK parameters was detected for scan duration 12min. An integrated protocol of 9min is suggested as optimal for clinical use in patients with high grade brain tumors. Lower acquisition time may result in over-estimation of kep when using ETM, and therefore care should be taken using model selection.

We report on a series of nine patients with high grade glioma (HGG) who developed punctate contrast-enhancing foci on MRI, several years after tumor treatment. The lesions were considered suspicious for tumor progression at their onset, but were proven over time to be benign in nature. Five of the patients were treated for glioblastoma; 3 for anaplastic astrocytoma, and one for anaplastic oligodendroglioma. Median age of the patients at diagnosis was 48 years (31–62 years). The mean time of onset of “suspicious spots” following treatment was 51 months after diagnosis (6–170 months). Of note, median overall survival of the group is 96 months; with none of the nine patients deceased, and only 2 patients known to have progression. The remainder of the 7 patients are free of active tumor and being followed off treatment. No apparent clinical manifestations of the lesions have been observed. The majority of the punctate lesions were of a dynamic nature; they appeared and spontaneously disappeared over time, without intervention. All lesions developed within the field of radiation treatment; some were contralateral to the tumor. Radiological characteristics of the lesions including analysis of SWI, DWI, and DCE magnetic resonance imaging sequences will be reported. Punctate enhancing foci in the region of radiation treatment are phenomena which may be manifestation of delayed treatment sequelae in HGG. Patients with these lesions are on average of younger age and have a particularly long survival. These lesions appeared several years following oncological treatment. The foci should be initially followed more closely until shown to be of a non-progressive nature; they should not be presumed to be indicative of tumor recurrence. Possible etiology of the lesions may be related to vascular changes induced by radiation.

To study the repeatability of plasma volume (vTwenty eight healthy subjects, of which eleven scanned twice, were used to assess the repeatability of vThe threshold values for significant changes were: LDD = 0.0024 (ml/100 ml, 21%) for mean vThis study shows high repeatability of v

We present a novel method for fiber-based comparison of diffusion tensor imaging (DTI) scans of groups of subjects. The method entails initial preprocessing and fiber reconstruction by tractography of each brain in its native coordinate system. Several diffusion parameters are sampled along each fiber and used in subsequent comparisons. A spatial correspondence between subjects is established based on geometric similarity between fibers in a template set (several choices for template are explored), and fibers in all other subjects. Diffusion parameters between groups are compared statistically for each template fiber. Results are presented at single fiber resolution. As an initial exploratory step in neurological population studies this method points to the locations affected by the pathology of interest, without requiring a hypothesis. It does not make any grouping assumptions on the fibers and no manual intervention is needed. The framework was applied here to 18 healthy subjects and 23 amyotrophic lateral sclerosis (ALS) patients. The results are compatible with previous findings and with the tract based spatial statistics (TBSS) method. Hum Brain Mapp 37:477-490, 2016. © 2015 Wiley Periodicals, Inc.

Cerebral blood volume (CBV) is an important parameter for the assessment of brain tumors, usually obtained using dynamic susceptibility contrast (DSC) MRI. However, this method often suffers from low spatial resolution and high sensitivity to susceptibility artifacts and usually does not take into account the effect of tissue permeability. The plasma volume (v p) can also be extracted from dynamic contrast enhancement (DCE) MRI. The aim of this study was to investigate whether DCE can be used for the measurement of cerebral blood volume in place of DSC for the assessment of patients with brain tumors. Twenty-eight subjects (17 healthy subjects and 11 patients with glioblastoma) were scanned using DCE and DSC. v p and CBV values were measured and compared in different brain components in healthy subjects and in the tumor area in patients. Significant high correlations were detected between v p and CBV in healthy subjects in the different brain components; white matter, gray matter, and arteries, correlating with the known increased tissue vascularity, and within the tumor area in patients. This work proposes the use of DCE as an alternative method to DSC for the assessment of blood volume, given the advantages of its higher spatial resolution, its lower sensitivity to susceptibility artifacts, and its ability to provide additional information regarding tissue permeability.

Background Bevacizumab (BVZ) is an antiangiogenic agent approved by the Food and Drug Administration that is used for the treatment of recurrent glioblastoma. Complications related to impaired healing may adversely affect patients resected for recurrent high-grade glioma (HGG) after treatment with BVZ. Objective To examine the complication rate, outcome, and tumor vasculature in patients resected for recurrent HGG after treatment with BVZ. Methods Data were reviewed retrospectively from patients undergoing surgery for recurrent HGG after treatment with BVZ. Results were compared with a control group of recurrently operated BVZ-naive HGG. Tumor samples and magnetic resonance imaging scans were analyzed. Results Fifteen patients underwent HGG resection after progression after BVZ. Forty-four BVZ-naive patients who underwent surgeries for tumor recurrence were included as controls. Median time from BVZ treatment to surgery was 30 days (2–107). Median overall survival from time of tumor diagnosis was 21.0 months (12–83.0), and median survival from post-BVZ surgery was 5.0 months (2.0–19.0), compared with 8.1 months in BVZ-naive controls measured from time of their last reoperation. Five of the 15 patients survived 6 or more months after post-BVZ surgery. Nine patients developed postsurgical complications requiring intervention. Complication rates for surgery after BVZ treatment were 66.7% compared with 38.6% in the control group (P = 0.077). We did not see overt changes in histopathology or immunohistochemistry staining; however, tumor vasculature in tumors resected after treatment with BVZ showed a significant decrease in mean vessel density. Conclusions Surgery for recurrent HGG may be feasible in a select group of patients. Mean tumor vessel density may be decreased after treatment with BVZ.

High-grade gliomas (HGGs) induce both vasogenic edema and extensive infiltration of tumor cells, both of which present with similar appearance on conventional MRI. Using current radiological criteria, differentiation between these tumoral and nontumoral areas within the nonenhancing lesion area remains challenging.To use radiomics patch-based analysis, based on conventional MRI, for the classification of the nonenhancing lesion area in patients with HGG into tumoral and nontumoral components.Prospective.In all, 179 MRI scans were obtained from 102 patients: 67 patients with HGG and 35 patients with brain metastases. A subgroup of 15 patients with HGG were scanned before and following administration of bevacizumab.Pre and postcontrast agent TA total of 225 histograms and gray-level-co-occurrence matrix-based features were extracted from the nonenhancing lesion area. Tumoral volumes of interest (VOIs) were defined at the peritumoral area in patients with HGG; nontumoral VOIs were defined in patients with brain metastasis. Twenty machine-learning algorithms including support-vector-machine (SVM), k-nearest neighbor, decision-trees, and ensemble classifiers were tested. The best classifier was trained on the entire labeled data, and was used to classify the entire data.Dimensional reduction was performed on the 225 features using principal component analysis. Classification results were evaluated based on the sensitivity, specificity, and accuracy of each of the 20 classifiers, first based on a training and testing dataset (80% of the labeled data) in a 5-fold manner, and next by applying the best classifier to the validation data (the remaining 20% of the labeled data). Results were additionally evaluated by assessing differences in dynamic-contrast-enhanced plasma-volume (vThe best classification into tumoral and nontumoral lesion components was obtained using a linear SVM classifier, with average accuracy of 87%, sensitivity 86%, and specificity of 89% (for the training and testing data). Significantly higher vA radiomics patch-based analysis enables classification of the nonenhancing lesion area in patients with HGG. Preliminary results were promising and the proposed method has the potential to assist in clinical decision-making and to improve therapy response assessment in patients with HGG.1 Technical Efficacy Stage 4 J. Magn. Reson. Imaging 2018.

BACKGROUND White matter hyperintensities (WMH) were shown to predict cognitive decline following stroke or transient ischemic attack (TIA). However, WMH are only one among other radiological markers of cerebral small vessel disease (SVD). OBJECTIVE The aim of this study was to determine whether adding other SVD markers to WMH improves prediction of post-stroke cognitive performances. METHODS Consecutive first-ever stroke or TIA patients (n = 266) from the Tel Aviv Acute Brain Stroke Cohort (TABASCO) study were enrolled. MRI scans were performed within seven days of stroke onset. We evaluated the relationship between cognitive performances one year following stroke, and previously suggested total SVD burden score including WMH, lacunes, cerebral microbleeds (CMB), and perivascular spaces (PVS). RESULTS Significant negative associations were found between WMH and cognition (p

This study proposes an automatic method for identification and quantification of different tissue components: the non-enhanced infiltrative tumor, vasogenic edema and enhanced tumor areas, at the subject level, in patients with glioblastoma (GB) based on dynamic contrast enhancement (DCE) and dynamic susceptibility contrast (DSC) MRI. Nineteen MR data sets, obtained from 12 patients with GB, were included. Seven patients were scanned before and 8 weeks following bevacizumab initiation. Segmentation of the tumor area was performed based on the temporal data of DCE and DSC at the group-level using k-means algorithm, and further at the subject-level using support vector machines algorithm. The obtained components were associated to different tissues types based on their temporal characteristics, calculated perfusion and permeability values and MR-spectroscopy. The method enabled the segmentation of the tumor area into the enhancing permeable component; the non-enhancing hypoperfused component, associated with vasogenic edema; and the non-enhancing hyperperfused component, associated with infiltrative tumor. Good agreement was obtained between the group-level, unsupervised and subject-level, supervised classification results, with significant correlation (r = 0.93, p < 0.001) and average symmetric root-mean-square surface distance of 2.5 ± 5.1 mm. Longitudinal changes in the volumes of the three components were assessed alongside therapy. Tumor area segmentation using DCE and DSC can be used to differentiate between vasogenic edema and infiltrative tumors in patients with GB, which is of major clinical importance in therapy response assessment.

Neurosyphilis is a rare disease that until the 2000s was almost eradicated due to population awareness of HIV and efficient treatment. Since then, the prevalence of the entity is rising due to risk-associated behaviour such as unprotected intercourse. Neurosyphilis is still a difficult entity to diagnose especially when combined with acute HIV infection which can influence the usual clinical course of disease. In rare occasions, both acute HIV and early syphilis infection can present as mono or multiple cranial nerve palsies. This case demonstrates a rare manifestation of misdiagnosed early syphilis infection combined with acute HIV infection in a 34-year-old man with prior history of unprotected sex with men.

Purpose Stroke imaging studies during the acute phase are likely to precede several vascular brain mechanisms, which have an important role in patient outcome. The aim of this study was to identify within the lesion area during the subacute phase (≥1 day) reactive tissue, which may have the potential for recovery. Methods Twenty seven stroke patients from two cohorts were included. MRI performed during the subacute phase included conventional, perfusion and diffusion imaging. In cohort I, unsupervised multiparametric classification of the lesion area was performed. In cohort II threshold based classification was performed during the subacute phase, and radiological outcome was assessed at follow-up scan. Results Three tissue classes were identified in cohort I, referred to as irreversibly damaged, intermediary, and reactive tissue. Based on threshold values defined in cohort I, the reactive tissue was identified in 11/13 patients in cohort II, and showed tissue preservation/partial recovery in 9/11 patients at follow-up scan. The irreversibly damaged tissue was identified in 7/13 patients in cohort II, and predicted tissue necrosis in all cases. Conclusion Identification of reactive tissue following stroke during the subacute phase can improve radiological assessment, contribute to the understanding of brain recovery processes and has implications for new therapeutic approaches. Magn Reson Med 72:1381–1388, 2014. © 2013 Wiley Periodicals, Inc.

a b s t r a c t Background: Lesion size in fluid attenuation inversion recovery (FLAIR) images is an important clinical parameter for patient assessment and follow-up. Although manual delineation of lesion areas consid- ered as ground truth, it is time-consuming, highly user-dependent and difficult to perform in areas of indistinct borders. In this study, an automatic methodology for FLAIR lesion segmentation is proposed, and its application in patients with brain tumors undergoing therapy; and in patients following stroke is demonstrated. Materials and methods: FLAIR lesion segmentation was performed in 57 magnetic resonance imaging (MRI) data sets obtained from 44 patients: 28 patients with primary brain tumors; 5 patients with recurrent- progressive glioblastoma (rGB) who were scanned longitudinally during anti-angiogenic therapy (18 MRI scans); and 11 patients following ischemic stroke. Results: FLAIR lesion segmentation was obtained in all patients. When compared to manual delineation, a high visual similarity was observed, with an absolute relative volume difference of 16.80% and 20.96% and a volumetric overlap error of 24.87% and 27.50% obtained for two raters: accepted values for automatic methods. Quantitative measurements of the segmented lesion volumes were in line with qualitative radiological assessment in four patients who received anti-anogiogenic drugs. In stroke patients the proposed methodology enabled identification of the ischemic lesion and differentiation from other FLAIR hyperintense areas, such as pre-existing disease. Conclusion: This study proposed a replicable methodology for FLAIR lesion detection and quantification and for discrimination between lesion of interest and pre-existing disease. Results from this study show the wide clinical applications of this methodology in research and clinical practice. © 2013 Published by Elsevier Ireland Ltd.

Current methods for evaluation of treatment response in glioblastoma are inaccurate, limited and time-consuming. This study aimed to develop a multi-modal MRI automatic classification method to improve accuracy and efficiency of treatment response assessment in patients with recurrent glioblastoma (GB).A modification of the k-Nearest-Neighbors (kNN) classification method was developed and applied to 59 longitudinal MR data sets of 13 patients with recurrent GB undergoing bevacizumab (anti-angiogenic) therapy. Changes in the enhancing tumor volume were assessed using the proposed method and compared with Macdonald's criteria and with manual volumetric measurements. The edema-like area was further subclassified into peri- and non-peri-tumoral edema, using both the kNN method and an unsupervised method, to monitor longitudinal changes.Automatic classification using the modified kNN method was applicable in all scans, even when the tumors were infiltrative with unclear borders. The enhancing tumor volume obtained using the automatic method was highly correlated with manual measurements (N=33, r=0.96, p0.0001), while standard radiographic assessment based on Macdonald's criteria matched manual delineation and automatic results in only 68% of cases. A graded pattern of tumor infiltration within the edema-like area was revealed by both automatic methods, showing high agreement. All classification results were confirmed by a senior neuro-radiologist and validated using MR spectroscopy.This study emphasizes the important role of automatic tools based on a multi-modal view of the tissue in monitoring therapy response in patients with high grade gliomas specifically under anti-angiogenic therapy.

Normal brain cells depend on glucose metabolism, yet they have the flexibility to switch to the usage of ketone bodies during caloric restriction. In contrast, tumor cells lack genomic and metabolic flexibility and are largely dependent on glucose. Ketogenic-diet (KD) was suggested as a therapeutic option for malignant brain cancer. This study aimed to detect metabolic brain changes in patients with malignant brain gliomas on KD using proton magnetic-resonance-spectroscopy (

Introduction: Current imaging assessment of high grade brain tumors relies on the revised assessment in neuro oncology (RANO) criteria relating to gross volumetric estimations of enhancing and non-enhancing lesions from conventional MRI sequences. These assessments may fail to reliably distinguish between tumor and non-tumor processes. This study aimed to classify the enhancing and non-enhancing lesion areas into tumor versus non-tumor components in order to improve therapy response assessment. Materials and Methods: A total of 140 MRI scans obtained from 32 patients with high grade brain tumors and six patients with brain-metastasis were included. Classification of lesion areas into 4 components: enhancing and non-enhancing, tumor and non-tumor, was performed using support-vector-machine classifier based on T1 weighted, FLAIR and dynamic contrast enhancing (DCE) MRI. Classification results were evaluated by two-fold cross validation analysis of the training set and MR-Spectroscopy. Longitudinal changes of the four components were compared to RANO-criteria. Results: The four components were automatically classified in all patients. Normalized T1 weighted values, vp and ktrans parameters significantly differentiated between components. High sensitivity and specificity (100%) were obtained within the enhancing lesion areas; and 90% sensitivity and 96% specificity within the non-enhancing areas. In 27 patients, longitudinal changes in the component volumes were consistent with RANO-criteria; however, in five patients (16%), changes detected in component volumes revealed tumor progression which preceded diagnosis based on RANO-criteria by several months. Conclusions: Automatic classification based on advanced imaging allows for reliable differentiation between tumor and non-tumor components in high grade glioma. Segmented RANO (sRANO) can refine current criteria to improve therapy response assessment.

Background Recent studies have demonstrated that even survivors of mild stroke experience residual damage, which persists and in fact increases in subsequent years. About 45% of stroke victims remain with different levels of disability. Identifying factors associated with poststroke cognitive and neurological decline could potentially yield more effective therapeutic opportunities. Aims and hypothesis We hypothesize that data based on biochemical, neuroimaging, genetic and psychological measures can, in aggregate, serve as better predictors for subsequent disability, cognitive and neurological deterioration, and suggest possible interventions. Design The Tel-Aviv Brain Acute Stroke Cohort (TABASCO) study is an ongoing, prospective cohort study that will recruit approximately 1125 consecutive first-ever mild–moderate stroke patients. It is designed to evaluate the association between predefined demographic, psychological, inflammatory, biochemical, neuroimaging and genetic markers, measured during the acute phase, and long-term outcome: subsequent cognitive deterioration, vascular events (including recurrent strokes), falls, affect changes, functional everyday difficulties and mortality. Discussion This study is an attempt to comprehensively investigate the long-term outcome of mild–moderate strokes. Its prospective design will provide quantitative data on stroke recurrence, the incidence of other vascular events and the evaluation of cognitive, affective and functional decline. Identifying the factors associated with poststroke cognitive and functional decline could potentially yield more effective therapeutic approaches.

Our objective was to quantify and better understand white matter (WM) impairment in patients with amyotrophic lateral sclerosis (ALS) and to propose a model based on diffusion tensor imaging (DTI) for diagnosing patients with suspected ALS with upper motor neuron (UMN) signs. Twenty-six ALS patients (24 with prominent UMN signs and two with an isolated lower-motor neuron (LMN) syndrome) and 22 healthy volunteers were examined using DTI. Data analysis included voxel-based WM tract-based spatial statistics (TBSS), volume-of-interest analysis of the TBSS results and stream-line tractography analysis. Converging evidence revealed WM impairment along the corticospinal tracts and in the mid-body of the corpus callosum. This was demonstrated by reduced fractional anisotropy values caused by increased radial diffusivity, without significant changes in axial diffusivity. There were no significant correlations between diffusivity indices and patients' disability or disease duration. A discriminant analysis model based on the tractography results was designed to distinguish between patients with UMN signs and controls, yielding 87.5% sensitivity and 85% specificity. In conclusion, DTI can detect WM impairment in patients with ALS in several brain regions, and might be a sensitive tool for the diagnosis of ALS in the early stages of the disease with UMN involvement.

Characterization and quantification of magnetic resonance perfusion images is important for clinical interpretation, though this calls for a reproducible and accurate method of analysis and a robust healthy reference. The few studies which have examined the perfusion of the healthy brain using dynamic susceptibility contrast (DSC) imaging were largely limited to manual definition of the regions of interest (ROI) and results were dependent on the location of the ROI. The current study aimed to develop a methodology for DSC data analysis and to obtain reference values of healthy subjects. Twenty three healthy volunteers underwent DSC. An unsupervised multiparametric clustering method was applied to four perfusion parameters. Three clusters were defined and identified as: dura-blood-vessels, gray matter and white matter and their vascular characteristics were obtained. Additionally, regional perfusion differences were studied and revealed a prolonged mean transient time and a trend for higher vascularity in the posterior compared with the anterior and middle cerebral vascular territories. While additional studies are required to confirm our findings, this result may have important clinical implications. The proposed unsupervised multiparametric method enabled accurate tissue differentiation, is easy replicable and has a wide range of applications in both pathological and healthy brains.

Mental time travel allows individuals to mentally project themselves backwards and forwards in subjective time. This case report describes a young woman suddenly rendered amnesic as a result of bilateral hippocampal damage following an epileptic seizure and brain anoxia. Her neuropsychological profile was characterized by a high-average general level of cognitive functioning, selective deficit in episodic memory of past events and a significant difficulty to envisage her personal future. This case provides clinical support for the concept of mental time travel with its retrospective and prospective components and for the hippocampus being its critical neural substrate.

Differentiation between treatment-related changes and progressive disease (PD) remains a major clinical challenge in the follow-up of patients with high grade brain tumors. The aim of this study was to differentiate between treatment-related changes and PD using dynamic contrast enhanced (DCE) MRI. Twenty patients were scanned using conventional, DCE-MRI and MR spectroscopy (total of 44 MR scans). The enhanced lesion area was extracted using independent components analysis of the DCE data. Pharmacokinetic parameters were estimated from the DCE data based on the Extended-Tofts-Model. Voxel based classification for treatment-related changes versus PD was performed in a patient-wise leave-one-out manner, using a support vector machine classifier. DCE parameters, K (trans), v e, k ep and v p, significantly differentiated between the tissue types. Classification results were validated using spectroscopy data showing significantly higher choline/creatine values in the extracted PD component compared to areas with treatment-related changes and normal appearing white matter, and high correlation between choline/creatine values and the percentage of the identified PD component within the lesion area (r = 0.77, p