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Glioma detection and segmentation is a challenging task for radiologists and clinicians. The research reported in this paper seeks to develop a better clinical decision support algorithm for clinicians diagnosis. This paper presents a probabilistic method for detection and segmentation between abnormal tissue regions and brain tumour (tumour core and edema) portions from Magnetic Resonance Imaging (MRI). A framework is constructed to learn structure of undirected graphical models that can represent the spatial relationships among variables and apply it to glioma segmentation. Compared with the pixel of image, the superpixel is more consistent with human visual cognition and contains less redundancy, thus, the superpixels are considered as the basic unit of structure learning and glioma segmentation scheme. ℓ1-regularization techniques are applied to learn the appropriate structure for modeling graphical models. Conditional Random Fields (CRF) are used to model the spatial interactions among image superpixel regions and their measurements. A number of features including statistics features, the combined features from the local binary pattern as well as gray level run length, curve features, and fractal features were extracted from each superpixel. The features are then passed by ℓ1-regularization to ensure a robust classification. The proposed method is compared with support vector machine and Fuzzy c-means to classify each superpixel into normal and abnormal tissue. The proposed system is tested for the presence of low grade as well as high grade glioma tumors on images collected from BRATS2013, BRATS2015 data set and Henan Provincial People’s Hospital (HNPPH) data set. The experiments performed provides similarity between segmented and truth image up to 91.5% by correlation method. [ABSTRACT FROM AUTHOR]

Content-based image retrieval (CBIR) techniques have currently gained increasing popularity in the medical field because they can use numerous and valuable archived images to support clinical decisions. In this paper, we concentrate on developing a CBIR system for retrieving brain tumors in T1-weighted contrast-enhanced MRI images. Specifically, when the user roughly outlines the tumor region of a query image, brain tumor images in the database of the same pathological type are expected to be returned. We propose a novel feature extraction framework to improve the retrieval performance. The proposed framework consists of three steps. First, we augment the tumor region and use the augmented tumor region as the region of interest to incorporate informative contextual information. Second, the augmented tumor region is split into subregions by an adaptive spatial division method based on intensity orders; within each subregion, we extract raw image patches as local features. Third, we apply the Fisher kernel framework to aggregate the local features of each subregion into a respective single vector representation and concatenate these per-subregion vector representations to obtain an image-level signature. After feature extraction, a closed-form metric learning algorithm is applied to measure the similarity between the query image and database images. Extensive experiments are conducted on a large dataset of 3604 images with three types of brain tumors, namely, meningiomas, gliomas, and pituitary tumors. The mean average precision can reach 94.68%. Experimental results demonstrate the power of the proposed algorithm against some related state-of-the-art methods on the same dataset. [ABSTRACT FROM AUTHOR]

Gliomas are the most frequent type of primary brain tumours. Low grade gliomas (LGGs, WHO grade II gliomas) may grow very slowly for the long periods of time, however they inevitably cause death due to the phenomenon known as the malignant transformation. This refers to the transition of LGGs to more aggressive forms of high grade gliomas (HGGs, WHO grade III and IV gliomas). In this paper we propose a mathematical model describing the spatio-temporal transition of LGGs into HGGs. Our modelling approach is based on two cellular populations with transitions between them being driven by the tumour microenvironment transformation occurring when the tumour cell density grows beyond a critical level. We show that the proposed model describes real patient data well. We discuss the relationship between patient prognosis and model parameters. We approximate tumour radius and velocity before malignant transformation as well as estimate the onset of this process. [ABSTRACT FROM AUTHOR]

Malignant gliomas remain incurable with a poor prognosis despite of aggressive treatment. We have been studying the development of brain tumors in a glioma rat model, where rats develop brain tumors after prenatal exposure to ethylnitrosourea (ENU), and there is a sizable interval between when the first pathological changes are noted and tumors become detectable with MRI. Our aim to define a molecular timeline through proteomic profiling of the cerebrospinal fluid (CSF) such that brain tumor commitment can be revealed earlier than at the presymptomatic stage. A comparative proteomic approach was applied to profile CSF collected serially either before, at and after the time MRI becomes positive. Elastic net (EN) based models were developed to infer the timeline of normal or tumor development respectively, mirroring a chronology of precisely timed, "clocked", adaptations. These CSF changes were later quantified by longitudinal entropy analyses of the EN predictive metric. False discovery rates (FDR) were computed to control the expected proportion of the EN models that are due to multiple hypothesis testing. Our ENU rat brain tumor dating EN model indicated that protein content in CSF is programmed even before tumor MRI detection. The findings of the precisely timed CSF tumor microenvironment changes at presymptomatic stages, deviation from the normal development timeline, may provide the groundwork for the understanding of adaptation of the brain environment in tumorigenesis to devise effective brain tumor management strategies. [ABSTRACT FROM AUTHOR]

Objectives: The extent of peritumoral tumor cell infiltrations in glioblastoma contributes to poor prognosis. We aimed to assess additive prognostic value of Minkowski functionals in analyzing heterogeneity of peritumoral hyperintensity on T2WI in glioblastoma patients. Methods: Clinical data (age, sex, extent of surgical resection), O6-methylguanine-DNA methyltransferase (MGMT) promoter methylation status and pre-operative T2WI of 113 pathologically confirmed glioblastoma patients (from our institution, n = 61; from the Cancer Imaging Archive, n = 52) were retrospectively reviewed. The patients were randomly grouped into a training set (n = 80) and a test set (n = 33). Peritumoral T2 hyperintensity was manually segmented and Minkowski functionals—a texture analysis method capturing heterogeneity of MR images—were computed as a function of 11 grayscale thresholds. The Cox proportional hazards models were fitted with clinical variables, Minkowski functionals features as well as both combined. The risk prediction performances of the Minkowski functionals and combined models were validated on a separate test dataset. The sex-specific survival difference of the entire cohort was analyzed according to MGMT methylation status via Kaplan-Meier survival curves. Results: Thirty-three Minkowski features (11 area, 11 perimeter and 11 genus) for each patient were acquired giving a total of 3729 features. Cox regression models fitted with clinical data, Minkowski features, and both combined had incremental concordance indices of 0.577 (P = 0.02), 0.706 (P = 0.02) and 0.714 (P = 0.01) respectively. The prediction error rate of the combined model—having clinical and Minkowski features—was lower than that of Minkowski functionals model (0.135 and 0.161, respectively) when validated on a test dataset. No sex-specific survival difference was found according to MGMT methylation status (male, P = 0.2; female, P = 0.22). Conclusions: Minkowski functionals features computed from peritumoral hyperintensity can capture heterogeneity of glioblastoma on T2WI and have additive prognostic value in predicting survival, demonstrating their potential in complementing currently available prognostic parameters. [ABSTRACT FROM AUTHOR]

Background: Low-grade gliomas cause significant neurological morbidity by brain invasion. There is no universally accepted objective technique available for detection of enlargement of low-grade gliomas in the clinical setting; subjective evaluation by clinicians using visual comparison of longitudinal radiological studies is the gold standard. The aim of this study is to determine whether a computer-assisted diagnosis (CAD) method helps physicians detect earlier growth of low-grade gliomas.Methods and Findings: We reviewed 165 patients diagnosed with grade 2 gliomas, seen at the University of Alabama at Birmingham clinics from 1 July 2017 to 14 May 2018. MRI scans were collected during the spring and summer of 2018. Fifty-six gliomas met the inclusion criteria, including 19 oligodendrogliomas, 26 astrocytomas, and 11 mixed gliomas in 30 males and 26 females with a mean age of 48 years and a range of follow-up of 150.2 months (difference between highest and lowest values). None received radiation therapy. We also studied 7 patients with an imaging abnormality without pathological diagnosis, who were clinically stable at the time of retrospective review (14 May 2018). This study compared growth detection by 7 physicians aided by the CAD method with retrospective clinical reports. The tumors of 63 patients (56 + 7) in 627 MRI scans were digitized, including 34 grade 2 gliomas with radiological progression and 22 radiologically stable grade 2 gliomas. The CAD method consisted of tumor segmentation, computing volumes, and pointing to growth by the online abrupt change-of-point method, which considers only past measurements. Independent scientists have evaluated the segmentation method. In 29 of the 34 patients with progression, the median time to growth detection was only 14 months for CAD compared to 44 months for current standard of care radiological evaluation (p < 0.001). Using CAD, accurate detection of tumor enlargement was possible with a median of only 57% change in the tumor volume as compared to a median of 174% change of volume necessary to diagnose tumor growth using standard of care clinical methods (p < 0.001). In the radiologically stable group, CAD facilitated growth detection in 13 out of 22 patients. CAD did not detect growth in the imaging abnormality group. The main limitation of this study was its retrospective design; nevertheless, the results depict the current state of a gold standard in clinical practice that allowed a significant increase in tumor volumes from baseline before detection. Such large increases in tumor volume would not be permitted in a prospective design. The number of glioma patients (n = 56) is a limitation; however, it is equivalent to the number of patients in phase II clinical trials.Conclusions: The current practice of visual comparison of longitudinal MRI scans is associated with significant delays in detecting growth of low-grade gliomas. Our findings support the idea that physicians aided by CAD detect growth at significantly smaller volumes than physicians using visual comparison alone. This study does not answer the questions whether to treat or not and which treatment modality is optimal. Nonetheless, early growth detection sets the stage for future clinical studies that address these questions and whether early therapeutic interventions prolong survival and improve quality of life. [ABSTRACT FROM AUTHOR]

Glioblastoma multiforme (GBM) is the most common type of malignant gliomas, characterized by genetic instability, intratumoral histopathological variability and unpredictable clinical behavior. Disappointing results in the treatment of gliomas with surgery, radiation and chemotherapy have fueled a search for new therapeutic targets and treatment modalities. Here we report new approach towards RNA interference therapy of glioblastoma multiforme based on the magnetic nanoparticles delivery of the double-stranded RNA (dsRNA) with homological sequences to mRNA of tenascin-C (TN-C), named ATN-RNA. The obtained nanocomposite consisted of polyethyleneimine (PEI) coated magnetic nanoparticles conjugated to the dsRNA show high efficiency in ATN-RNA delivery, resulting not only in significant TN-C expression level suppressesion, but also impairing the tumor cells migration. Moreover, synthesized nanomaterials show high contrast properties in magnetic resonance imaging (MRI) and low cytotoxicity combining with lack of induction of interferon response. We believe that the present work is a successful combination of effective, functional, non-immunostimulatory dsRNA delivery system based on magnetic nanoparticles with high potential for further application in GBM therapy. [ABSTRACT FROM AUTHOR]

Purpose: Perfusion and diffusion magnetic resonance imaging (MRI) provide important biomarkers for brain tumor analysis. Our aim was to investigate if regions of increased perfusion or tumor with restricted diffusion on the immediate post-operative MRI examination would be predictive of time to tumor progression in patients with high-grade gliomas. Materials and methods: Twenty-three patients with high-grade gliomas were retrospectively analyzed. We measured the perfusion at the resection area and evaluated the presence or absence of the restricted diffusion in residual tumor masses. The associations of the perfusion, diffusion and contrast enhancement (delayed static enhancement (DSE)) characteristics with time to tumor progression were statistically calculated. We also evaluated if the location of the tumor progression was concordant to the areas of the elevated perfusion, tumor type restricted diffusion and enhancement. Results: Patients with >200 days to progression are more likely to have no elevated relative cerebral blood volume (rCBV) ratio (p = 0.0004), no tumor restriction (p = 0.024), and no DSE (p = 0.052). The elevated mean rCBV ratio (p<0.001) and tumor type restricted diffusion (p = 0.002) were significantly associated with a higher risk of progression. All cases with rCBV ratio of >1.5 progressed in 275 days or earlier. Tumors tended to progress at the area where patients with post-operative MRIs showed elevated perfusion (p = 0.006), tumor-type restricted diffusion (p = 0.005) and DSE (p = 0.008). Conclusions: Post-operative analysis of rCBV, tumor type restricted diffusion and enhancement characteristics are predictive of time to progression, risk of progression and where tumor progression is likely to occur. [ABSTRACT FROM AUTHOR]

Purpose: Standard radiological/topographical classifications of gliomas often do not reflect the real extension of the tumor within the lobar-cortical anatomy. Furthermore, these systems do not provide information on the relationship between tumor growth and the subcortical white matter architecture. We propose the use of an anatomically standardized grid system (the Brain-Grid) to merge serial morphological magnetic resonance imaging (MRI) scans with a representative tractographic atlas. Two illustrative cases are presented to show the potential advantages of this classification system. Methods: MRI scans of 39 patients (WHO grade II and III gliomas) were analyzed with a standardized grid created by intersecting longitudinal lines on the axial, sagittal, and coronal planes. The anatomical landmarks were chosen from an average brain, spatially normalized to the Montreal Neurological Institute (MNI) space and the Talairach space. Major white matter pathways were reconstructed with a deterministic tracking algorithm on a reference atlas and analyzed using the Brain-Grid system. Results: In all, 48 brain grid voxels (areas defined by 3 coordinates, axial (A), coronal (C), sagittal (S) and numbers from 1 to 4) were delineated in each MRI sequence and on the tractographic atlas. The number of grid voxels infiltrated was consistent, also in the MNI space. The sub-cortical insula/basal ganglia (A3-C2-S2) and the fronto-insular region (A3-C2-S1) were most frequently involved. The inferior fronto-occipital fasciculus, anterior thalamic radiation, uncinate fasciculus, and external capsule were the most frequently associated pathways in both hemispheres. Conclusions: The Brain-Grid based classification system provides an accurate observational tool in all patients with suspected gliomas, based on the comparison of grid voxels on a morphological MRI and segmented white matter atlas. Important biological information on tumor kinetics including extension, speed, and preferential direction of progression can be observed and even predicted with this system. This novel classification can easily be applied to both prospective and retrospective cohorts of patients and increase our comprehension of glioma behavior. [ABSTRACT FROM AUTHOR]

Objectives: This study aimed to assess the correlation of temporal muscle thickness (TMT), measured on routine cranial magnetic resonance (MR) images, with lumbar skeletal muscles obtained on computed tomography (CT) images in brain metastasis patients to establish a new parameter estimating skeletal muscle mass on brain MR images. Methods: We retrospectively analyzed the cross-sectional area (CSA) of skeletal muscles at the level of the third lumbar vertebra on computed tomography scans and correlated these values with TMT on MR images of the brain in two independent cohorts of 93 lung cancer and 61 melanoma patients (overall: 154 patients) with brain metastases. Results: Pearson correlation revealed a strong association between mean TMT and CSA in lung cancer and melanoma patients with brain metastases (0.733; p<0.001). The two study cohorts did not differ significantly in patient characteristics, including age (p = 0.661), weight (p = 0.787), and height (p = 0.123). However, TMT and CSA measures differed significantly between male and female patients in both lung cancer and melanoma patients with brain metastases (p<0.001). Conclusion: Our data indicate that TMT, measured on routine cranial MR images, is a useful surrogate parameter for the estimation of skeletal muscle mass in patients with brain metastases. Thus, TMT may be useful for prognostic assessment, treatment considerations, and stratification or a selection factor for clinical trials in patients with brain metastases. Further studies are needed to assess the association between TMT and clinical frailty parameters, and the usefulness of TMT in patients with primary brain tumors. [ABSTRACT FROM AUTHOR]

Introduction: Aim was to develop a full automatic clustering approach of the time-activity curves (TAC) from dynamic 18F-FET PET and evaluate its association with IDH1 mutation status and survival in patients with gliomas. Methods: Thirty-seven patients (mean age: 45±13 y) with newly diagnosed gliomas and dynamic 18F-FET PET before any histopathologic investigation or treatment were retrospectively included. Each dynamic 18F-FET PET was realigned to the first image and spatially normalized in the Montreal Neurological Institute template. A tumor mask was semi-automatically generated from Z-score maps. Each brain tumor voxel was clustered in one of the 3 following centroids using dynamic time warping and k-means clustering (centroid #1: slowly increasing slope; centroid #2: rapidly increasing followed by slowly decreasing slope; and centroid #3: rapidly increasing followed by rapidly decreasing slope). The percentage of each dynamic 18F-FET TAC within tumors and other conventional 18F-FET PET parameters (maximum and mean tumor-to-brain ratios [TBRmax and TBRmean], time-to-peak [TTP] and slope) was compared between wild-type and IDH1 mutant tumors. Their prognostic value was assessed in terms of progression free-survival (PFS) and overall survival (OS) by Kaplan-Meier estimates. Results: Twenty patients were IDH1 wild-type and 17 IDH1 mutant. Higher percentage of centroid #1 and centroid #3 within tumors were positively (P = 0.016) and negatively (P = 0.01) correlated with IDH1 mutated status. Also, TBRmax, TBRmean, TTP, and slope discriminated significantly between tumors with and without IDH1 mutation (P range 0.01 to 0.04). Progression occurred in 22 patients (59%) at a median of 13.1 months (7.6–37.6 months) and 13 patients (35%) died from tumor progression. Patients with a percentage of centroid #1 > 90% had a longer survival compared with those with a percentage of centroid #1 < 90% (P = 0.003 for PFS and P = 0.028 for OS). This remained significant after stratification on IDH1 mutation status (P = 0.029 for PFS and P = 0.034 for OS). Compared to other conventional 18F-FET PET parameters, TTP and slope were associated with PFS and OS (P range 0.009 to 0.04). Conclusions: Based on dynamic 18F-FET PET acquisition, we developed a full automatic clustering approach of TAC which appears to be a valuable noninvasive diagnostic and prognostic marker in patients with gliomas. [ABSTRACT FROM AUTHOR]

A multi-center imaging trial by the American College of Radiology Imaging Network (ACRIN) “A Multicenter, phase II assessment of tumor hypoxia in glioblastoma using 18F Fluoromisonidazole (FMISO) with PET and MRI (ACRIN 6684)”, was conducted to assess hypoxia in patients with glioblastoma (GBM). The aims of this study were to support the role of proton magnetic resonance spectroscopic imaging (1H MRSI) as a prognostic marker for brain tumor patients in multi-center clinical trials. Seventeen participants from four sites had analyzable 3D MRSI datasets acquired on Philips, GE or Siemens scanners at either 1.5T or 3T. MRSI data were analyzed using LCModel to quantify metabolites N-acetylaspartate (NAA), creatine (Cr), choline (Cho), and lactate (Lac). Receiver operating characteristic curves for NAA/Cho, Cho/Cr, lactate/Cr, and lactate/NAA were constructed for overall survival at 1-year (OS-1) and 6-month progression free survival (PFS-6). The OS-1 for the 17 evaluable patients was 59% (10/17). Receiver operating characteristic analyses found the NAA/Cho in tumor (AUC = 0.83, 95% CI: 0.61 to 1.00) and in peritumoral regions (AUC = 0.95, 95% CI 0.85 to 1.00) were predictive for survival at 1 year. PFS-6 was 65% (11/17). Neither NAA/Cho nor Cho/Cr was effective in predicting 6-month progression free survival. Lac/Cr in tumor was a significant negative predictor of PFS-6, indicating that higher lactate/Cr levels are associated with poorer outcome. (AUC = 0.79, 95% CI: 0.54 to 1.00). In conclusion, despite the small sample size in the setting of a multi-center trial comprising different vendors, field strengths, and varying levels of expertise at data acquisition, MRS markers NAA/Cho, Lac/Cr and Lac/NAA predicted overall survival at 1 year and 6-month progression free survival. This study validates that MRSI may be useful in evaluating the prognosis in glioblastoma and should be considered for incorporating into multi-center clinical trials. [ABSTRACT FROM AUTHOR]

Purpose: Peritumoral edema impedes the full delineation of fiber tracts due to partial volume effects in image voxels that contain a mixture of cerebral parenchyma and extracellular water. The purpose of this study is to investigate the effect of incorporating a free water (FW) model of edema for white matter tractography in the presence of edema. Materials and methods: We retrospectively evaluated 26 consecutive brain tumor patients with diffusion MRI and T2-weighted images acquired presurgically. Tractography of the arcuate fasciculus (AF) was performed using the two-tensor unscented Kalman filter tractography (UKFt) method, the UKFt method with a reduced fiber tracking stopping fractional anisotropy (FA) threshold (UKFt+rFA), and the UKFt method with the addition of a FW compartment (UKFt+FW). An automated white matter fiber tract identification approach was applied to delineate the AF. Quantitative measurements included tract volume, edema volume, and mean FW fraction. Visual comparisons were performed by three experts to evaluate the quality of the detected AF tracts. Results: The AF volume in edematous brain hemispheres was significantly larger using the UKFt+FW method (p<0.0001) compared to UKFt, but not significantly larger (p = 0.0996) in hemispheres without edema. The AF size increase depended on the volume of edema: a significant correlation was found between AF volume affected by (intersecting) edema and AF volume change with the FW model (Pearson r = 0.806, p<0.0001). The mean FW fraction was significantly larger in tracts intersecting edema (p = 0.0271). Compared to the UKFt+rFA method, there was a significant increase of the volume of the AF tract that intersected the edema using the UKFt+FW method, while the whole AF volumes were similar. Expert judgment results, based on the five patients with the smallest AF volumes, indicated that the expert readers generally preferred the AF tract obtained by using the FW model, according to their anatomical knowledge and considering the potential influence of the final results on the surgical route. Conclusion: Our results indicate that incorporating biophysical models of edema can increase the sensitivity of tractography in regions of peritumoral edema, allowing better tract visualization in patients with high grade gliomas and metastases. [ABSTRACT FROM AUTHOR]

Accurate and automatic brain metastases target delineation is a key step for efficient and effective stereotactic radiosurgery (SRS) treatment planning. In this work, we developed a deep learning convolutional neural network (CNN) algorithm for segmenting brain metastases on contrast-enhanced T1-weighted magnetic resonance imaging (MRI) datasets. We integrated the CNN-based algorithm into an automatic brain metastases segmentation workflow and validated on both Multimodal Brain Tumor Image Segmentation challenge (BRATS) data and clinical patients' data. Validation on BRATS data yielded average DICE coefficients (DCs) of 0.75±0.07 in the tumor core and 0.81±0.04 in the enhancing tumor, which outperformed most techniques in the 2015 BRATS challenge. Segmentation results of patient cases showed an average of DCs 0.67±0.03 and achieved an area under the receiver operating characteristic curve of 0.98±0.01. The developed automatic segmentation strategy surpasses current benchmark levels and offers a promising tool for SRS treatment planning for multiple brain metastases. [ABSTRACT FROM AUTHOR]

Purpose: There is an increasing need for small animal in vivo imaging in murine orthotopic glioma models. Because dedicated small animal scanners are not available ubiquitously, the applicability of a clinical CT scanner for visualization and measurement of intracerebrally growing glioma xenografts in living mice was validated. Materials and Methods: 2.5x106 U87MG cells were orthotopically implanted in NOD/SCID/ᵞc-/- mice (n = 9). Mice underwent contrast-enhanced (300 μl Iomeprol i.v.) imaging using a micro-CT (80 kV, 75 μAs, 360° rotation, 1,000 projections, scan time 33 s, resolution 40 x 40 x 53 μm) and a clinical CT scanner (4-row multislice detector; 120 kV, 150 mAs, slice thickness 0.5 mm, feed rotation 0.5 mm, resolution 98 x 98 x 500 μm). Mice were sacrificed and the brain was worked up histologically. In all modalities tumor volume was measured by two independent readers. Contrast-to-noise ratio (CNR) and Signal-to-noise ratio (SNR) were measured from reconstructed CT-scans (0.5 mm slice thickness; n = 18). Results: Tumor volumes (mean±SD mm3) were similar between both CT-modalities (micro-CT: 19.8±19.0, clinical CT: 19.8±18.8; Wilcoxon signed-rank test p = 0.813). Moreover, between reader analyses for each modality showed excellent agreement as demonstrated by correlation analysis (Spearman-Rho >0.9; p<0.01 for all correlations). Histologically measured tumor volumes (11.0±11.2) were significantly smaller due to shrinkage artifacts (p<0.05). CNR and SNR were 2.1±1.0 and 1.1±0.04 for micro-CT and 23.1±24.0 and 1.9±0.7 for the clinical CTscanner, respectively. Conclusion: Clinical CT scanners may reliably be used for in vivo imaging and volumetric analysis of brain tumor growth in mice. [ABSTRACT FROM AUTHOR]

Background and Purpose: To evaluate the ability of IA MR perfusion to characterize meningioma blood supply. Methods: Studies were performed in a suite comprised of an x-ray angiography unit and 1.5T MR scanner that permitted intraprocedural patient movement between the imaging modalities. Patients underwent intra-arterial (IA) and intravenous (IV) T2* dynamic susceptibility MR perfusion immediately prior to meningioma embolization. Regional tumor arterial supply was characterized by digital subtraction angiography and classified as external carotid artery (ECA) dural, internal carotid artery (ICA) dural, or pial. MR perfusion data regions of interest (ROIs) were analyzed in regions with different vascular supply to extract peak height, full-width at half-maximum (FWHM), relative cerebral blood flow (rCBF), relative cerebral blood volume (rCBV), and mean transit time (MTT). Linear mixed modeling was used to identify perfusion curve parameter differences for each ROI for IA and IV MR imaging techniques. IA vs. IV perfusion parameters were also directly compared for each ROI using linear mixed modeling. Results: 18 ROIs were analyzed in 12 patients. Arterial supply was identified as ECA dural (n = 11), ICA dural (n = 4), or pial (n = 3). FWHM, rCBV, and rCBF showed statistically significant differences between ROIs for IA MR perfusion. Peak Height and FWHM showed statistically significant differences between ROIs for IV MR perfusion. RCBV and MTT were significantly lower for IA perfusion in the Dural ECA compared to IV perfusion. Relative CBF in IA MR was found to be significantly higher in the Dural ICA region and MTT significantly lower compared to IV perfusion. [ABSTRACT FROM AUTHOR]

To facilitate a more widespread use of volumetric tumor segmentation in clinical studies, there is an urgent need for reliable, user-friendly segmentation software. The aim of this study was therefore to compare three different software packages for semi-automatic brain tumor segmentation of glioblastoma; namely BrainVoyagerTM QX, ITK-Snap and 3D Slicer, and to make data available for future reference. Pre-operative, contrast enhanced T1-weighted 1.5 or 3 Tesla Magnetic Resonance Imaging (MRI) scans were obtained in 20 consecutive patients who underwent surgery for glioblastoma. MRI scans were segmented twice in each software package by two investigators. Intra-rater, inter-rater and between-software agreement was compared by using differences of means with 95% limits of agreement (LoA), Dice’s similarity coefficients (DSC) and Hausdorff distance (HD). Time expenditure of segmentations was measured using a stopwatch. Eighteen tumors were included in the analyses. Inter-rater agreement was highest for BrainVoyager with difference of means of 0.19 mL and 95% LoA from -2.42 mL to 2.81 mL. Between-software agreement and 95% LoA were very similar for the different software packages. Intra-rater, inter-rater and between-software DSC were ≥ 0.93 in all analyses. Time expenditure was approximately 41 min per segmentation in BrainVoyager, and 18 min per segmentation in both 3D Slicer and ITK-Snap. Our main findings were that there is a high agreement within and between the software packages in terms of small intra-rater, inter-rater and between-software differences of means and high Dice’s similarity coefficients. Time expenditure was highest for BrainVoyager, but all software packages were relatively time-consuming, which may limit usability in an everyday clinical setting. [ABSTRACT FROM AUTHOR]

Background: Glioma remains a diagnostic challenge because of its variable clinical presentation and a lack of reliable screening tools. Long noncoding RNAs (lncRNAs) regulate gene function in a wide range of pathophysiological processes and are therefore emerging biomarkers for prostate cancer, hepatic cancer, and other tumor diseases. However, the effective use of lncRNAs as biomarkers for the diagnosis of glioma remains unproven. Methods: This study included 42 glioma patients and 10 healthy controls. lncRNA and mRNA microarray chips were used to identify dysregulated lncRNAs in tumor tissue and tumor-adjacent normal tissue, and SYBR Green–based miRNA quantitative real-time reverse transcription polymerase chain reactions were used to validate upregulated lncRNAs. A receiver operating characteristic curve analysis was conducted to evaluate the diagnostic accuracy of the lncRNA identified as the candidate biomarker. Results: miR210HG levels were significantly higher in tumor tissue than in tumor-adjacent normal tissue in participating glioma patients. Serum miR210HG levels were also significantly higher in glioma patients than in healthy controls. The receiver operating characteristic curve showed that serum miR210HG was a specific diagnostic predictor of acute pulmonary embolism with an area under the curve of 0.8323 (95% confidence interval, 0.7347 to 0.9299, p < 0.001). Conclusion: Our findings indicate that miR210HG could be an important biomarker for the diagnosis of glioma, and, as such, large-scale investigations are urgently needed to pave the way from basic research to clinical use. [ABSTRACT FROM AUTHOR]

The differentiation between glioblastoma multiforme (GBM) and primary cerebral lymphoma (PCL) is important because the treatments are substantially different. The purpose of this article is to describe the MR imaging characteristics of GBM and PCL with emphasis on the quantitative ADC analysis in the tumor necrosis, the most strongly-enhanced tumor area, and the peritumoral edema. This retrospective cohort study collected 104 GBM (WHO grade IV) patients and 22 immune-competent PCL (diffuse large B cell lymphoma) patients. All these patients had pretreatment brain MR DWI and ADC imaging. Analysis of conventional MR imaging and quantitative ADC measurement including the tumor necrosis (ADCn), the most strongly-enhanced tumor area (ADCt), and the peritumoral edema (ADCe) were done. ROC analysis with optimal cut-off values and area-under-the ROC curve (AUC) was performed. For conventional MR imaging, there are statistical differences in tumor size, tumor location, tumor margin, and the presence of tumor necrosis between GBM and PCL. Quantitative ADC analysis shows that GBM tended to have significantly (P<0.05) higher ADC in the most strongly-enhanced area (ADCt) and lower ADC in the peritumoral edema (ADCe) as compared with PCL. Excellent AUC (0.94) with optimal sensitivity of 90% and specificity of 86% for differentiating between GBM and PCL was obtained by combination of ADC in the tumor necrosis (ADCn), the most strongly-enhanced tumor area (ADCt), and the peritumoral edema (ADCe). Besides, there are positive ADC gradients in the peritumoral edema in a subset of GBMs but not in the PCLs. Quantitative ADC analysis in these three areas can thus be implemented to improve diagnostic accuracy for these two brain tumor types. The histological correlation of the ADC difference deserves further investigation. [ABSTRACT FROM AUTHOR]

Background: Antiangiogenic therapies for glioblastoma (GBM) such as bevacizumab (BVZ), have been unable to extend survival in large patient cohorts. However, a subset of patients having angiogenesis-dependent tumors might benefit from these therapies. Currently, there are no biomarkers allowing to discriminate responders from non-responders before the start of the therapy. Methods: 40 patients from the randomized GENOM009 study complied the inclusion criteria (quality of images, clinical data available). Of those, 23 patients received first line temozolomide (TMZ) for eight weeks and then concomitant radiotherapy and TMZ. 17 patients received BVZ+TMZ for seven weeks and then added radiotherapy to the treatment. Clinical variables were collected, tumors segmented and several geometrical measures computed including: Contrast enhancing (CE), necrotic, and total volumes; equivalent spherical CE width; several geometric measures of the CE ‘rim’ geometry and a set of image texture measures. The significance of the results was studied using Kaplan-Meier and Cox proportional hazards analysis. Correlations were assessed using Spearman correlation coefficients. Results: Kaplan-Meier and Cox proportional hazards analysis showed that total, CE and inner volume (p = 0.019, HR = 4.258) and geometric heterogeneity of the CE areas (p = 0.011, HR = 3.931) were significant parameters identifying response to BVZ. The group of patients with either regular CE areas (small geometric heterogeneity, median difference survival 15.88 months, p = 0.011) or those with small necrotic volume (median survival difference 14.50 months, p = 0.047) benefited substantially from BVZ. Conclusion: Imaging biomarkers related to the irregularity of contrast enhancing areas and the necrotic volume were able to discriminate GBM patients with a substantial survival benefit from BVZ. A prospective study is needed to validate our results. [ABSTRACT FROM AUTHOR]

Objective: Several studies have analyzed a correlation between the apparent diffusion coefficient (ADC) derived from diffusion-weighted MRI and the tumor cellularity of corresponding histopathological specimens in brain tumors with inconclusive findings. Here, we compared a large dataset of ADC and cellularity values of stereotactic biopsies of glioblastoma patients using a new postprocessing approach including trajectory analysis and automatic nuclei counting. Materials and Methods: Thirty-seven patients with newly diagnosed glioblastomas were enrolled in this study. ADC maps were acquired preoperatively at 3T and coregistered to the intraoperative MRI that contained the coordinates of the biopsy trajectory. 561 biopsy specimens were obtained; corresponding cellularity was calculated by semi-automatic nuclei counting and correlated to the respective preoperative ADC values along the stereotactic biopsy trajectory which included areas of T1-contrast-enhancement and necrosis. Results: There was a weak to moderate inverse correlation between ADC and cellularity in glioblastomas that varied depending on the approach towards statistical analysis: for mean values per patient, Spearman’s ρ = -0.48 (p = 0.002), for all trajectory values in one joint analysis Spearman’s ρ = -0.32 (p < 0.001). The inverse correlation was additionally verified by a linear mixed model. Conclusions: Our data confirms a previously reported inverse correlation between ADC and tumor cellularity. However, the correlation in the current article is weaker than the pooled correlation of comparable previous studies. Hence, besides cell density, other factors, such as necrosis and edema might influence ADC values in glioblastomas. [ABSTRACT FROM AUTHOR]

Background: A critical challenge in the management of Glioblastoma Multiforme (GBM) tumors is the accurate diagnosis and assessment of tumor progression in a noninvasive manner. We have identified Membrane-type 1 matrix metalloproteinase (MT1-MMP) as an attractive biomarker for GBM imaging since this protein is actively involved in tumor growth and progression, correlates with tumor grade and is closely associated with poor prognosis in GBM patients. Here, we report the development of an immunoPET tracer for effective detection of MT1-MMP in GBM models. Methods: An anti-human MT1-MMP monoclonal antibody (mAb), LEM2/15, was conjugated to p-isothiocyanatobenzyl-desferrioxamine (DFO-NCS) for 89Zr labeling. Biodistribution and PET imaging studies were performed in xenograft mice bearing human GBM cells (U251) expressing MT1-MMP and non-expressing breast carcinoma cells (MCF-7) as negative control. Two orthotopic brain GBM models, patient-derived neurospheres (TS543) and U251 cells, with different degrees of blood-brain barrier (BBB) disruption were also used for PET imaging experiments. Results: 89Zr labeling of DFO-LEM2/15 was achieved with high yield (>90%) and specific activity (78.5 MBq/mg). Biodistribution experiments indicated that 89Zr-DFO-LEM2/15 showed excellent potential as a radiotracer for detection of MT1-MMP positive GBM tumors. PET imaging also indicated a specific and prominent 89Zr-DFO-LEM2/15 uptake in MT1-MMP+ U251 GBM tumors compared to MT1-MMP- MCF-7 breast tumors. Results obtained in orthotopic brain GBM models revealed a high dependence of a disrupted BBB for tracer penetrance into tumors. 89Zr-DFO-LEM2/15 showed much higher accumulation in TS543 tumors with a highly disrupted BBB than in U251 orthotopic model in which the BBB permeability was only partially increased. Histological analysis confirmed the specificity of the immunoconjugate in all GBM models. Conclusion: A new anti MT1-MMP-mAb tracer, 89Zr-DFO-LEM2/15, was synthesized efficiently. In vivo validation showed high-specific-contrast imaging of MT1-MMP positive GBM tumors and provided strong evidence for utility of MT1-MMP-targeted immunoPET as an alternate to nonspecific imaging of GBM. [ABSTRACT FROM AUTHOR]

Background: Precise location of intracranial lesions before surgery is important, but occasionally difficult. Modern navigation systems are very helpful, but expensive. A low-cost solution that could locate brain lesions and their surface projections in augmented reality would be beneficial. We used an iPhone to partially achieve this goal, and evaluated its accuracy and feasibility in a clinical neurosurgery setting. Methodology/Principal Findings: We located brain lesions in 35 patients, and using an iPhone, we depicted the lesion’s surface projection onto the skin of the head. To assess the accuracy of this method, we pasted computed tomography (CT) markers surrounding the depicted lesion boundaries on the skin onto 15 patients. CT scans were then performed with or without contrast enhancement. The deviations (D) between the CT markers and the actual lesion boundaries were measured. We found that 97.7% of the markers displayed a high accuracy level (D ≤ 5mm). In the remaining 20 patients, we compared our iPhone-based method with a frameless neuronavigation system. Four check points were chosen on the skin surrounding the depicted lesion boundaries, to assess the deviations between the two methods. The integrated offset was calculated according to the deviations at the four check points. We found that for the supratentorial lesions, the medial offset between these two methods was 2.90 mm and the maximum offset was 4.2 mm. Conclusions/Significance: This low-cost, image-based, iPhone-assisted, augmented reality solution is technically feasible, and helpful for the localization of some intracranial lesions, especially shallow supratentorial intracranial lesions of moderate size. [ABSTRACT FROM AUTHOR]

Purpose: To evaluate whether the combination of imaging biomarkers obtained by means of different 3 Tesla (3T) Magnetic Resonance Imaging (MRI) advanced techniques can improve the diagnostic accuracy in the differentiation between benign and malignant single ring-enhancing brain masses. Materials and Methods: 14 patients presenting at conventional 3T MRI single brain mass with similar appearance as regard ring enhancement, presence of peri-lesional edema and absence of hemorrhage signs were included in the study. All lesions were histologically proven: 5 pyogenic abscesses, 6 glioblastomas, and 3 metastases. MRI was performed at 3 Tesla and included Diffusion Weighted Imaging (DWI), Dynamic Susceptibility Contrast -Perfusion Weighted Imaging (DSC-PWI), Magnetic Resonance Spectroscopy (MRS), and Diffusion Tensor Imaging (DTI). Imaging biomarkers derived by those advanced techniques [Cerebral Blood Flow (CBF), relative Cerebral Blood Volume (rCBV), relative Main Transit Time (rMTT), Choline (Cho), Creatine (Cr), Succinate, N-Acetyl Aspartate (NAA), Lactate (Lac), Lipids, relative Apparent Diffusion Coefficient (rADC), and Fractional Anisotropy (FA)] were detected by two experienced neuroradiologists in joint session in 4 areas: Internal Cavity (IC), Ring Enhancement (RE), Peri-Lesional edema (PL), and Contralateral Normal Appearing White Matter (CNAWM). Significant differences between benign (n = 5) and malignant (n = 9) ring enhancing lesions were tested with Mann-Withney U test. The diagnostic accuracy of MRI biomarkers taken alone and MRI biomarkers ratios were tested with Receiver Operating Characteristic (ROC) analysis with an Area Under the Curve (AUC) ≥ 0.9 indicating a very good diagnostic accuracy of the variable. Results: Five MRI biomarker ratios achieved excellent accuracy: IC-rADC/PL-NAA (AUC = 1), IC-rADC/IC-FA (AUC = 0.978), RE-rCBV/RE-FA (AUC = 0.933), IC-rADC/RE-FA (AUC = 0.911), and IC-rADC/PL-FA (AUC = 0.911). Only IC-rADC achieved a very good diagnostic accuracy (AUC = 0.909) among MRI biomarkers taken alone. Conclusion: Although the major limitation of the study was the small sample size, preliminary results seem to suggest that combination of multiple 3T MRI biomarkers is a feasible approach to MRI biomarkers in order to improve diagnostic accuracy in the differentiation between benign and malignant single ring enhancing brain masses. Further studies in larger cohorts are needed to reach definitive conclusions. [ABSTRACT FROM AUTHOR]

Objective: Intravoxel incoherent motion (IVIM) is an MRI technique with potential applications in measuring brain tumor perfusion, but its clinical impact remains to be determined. We assessed the usefulness of IVIM-metrics in predicting survival in newly diagnosed glioblastoma. Methods: Fifteen patients with glioblastoma underwent MRI including spin-echo echo-planar DWI using 13 b-values ranging from 0 to 1000 s/mm2. Parametric maps for diffusion coefficient (D), pseudodiffusion coefficient (D*), and perfusion fraction (f) were generated for contrast-enhancing regions (CER) and non-enhancing regions (NCER). Regions of interest were manually drawn in regions of maximum f and on the corresponding dynamic susceptibility contrast images. Prognostic factors were evaluated by Kaplan-Meier survival and Cox proportional hazards analyses. Results: We found that fCER and D*CER correlated with rCBFCER. The best cutoffs for 6-month survival were fCER>9.86% and D*CER>21.712 x10−3mm2/s (100% sensitivity, 71.4% specificity, 100% and 80% positive predictive values, and 80% and 100% negative predictive values; AUC:0.893 and 0.857, respectively). Treatment yielded the highest hazard ratio (5.484; 95% CI: 1.162–25.88; AUC: 0.723; P = 0.031); fCER combined with treatment predicted survival with 100% accuracy. Conclusions: The IVIM-metrics fCER and D*CER are promising biomarkers of 6-month survival in newly diagnosed glioblastoma. [ABSTRACT FROM AUTHOR]

Purpose: The aim of this study was to evaluate the benefit of a combined treatment, surgery followed by adjuvant hypofractionated stereotactic radiosurgery (HSRS) on the tumor bed, in oligometastatic patients with single, large brain metastasis (BM). Methods and Materials: Fom January 2011 to March 2015, 69 patients underwent complete surgical resection followed by HSRS with a total dose of 30Gy in 3 daily fractions. Clinical outcome was evaluated by neurological examination and MRI 2 months after radiotherapy and then every 3 months. Local progression was defined as radiographic increase of the enhancing abnormality in the irradiated volume, and brain distant progression as the presence of new brain metastases or leptomeningeal enhancement outside the irradiated volume. Surgical morbidity and radiation-therapy toxicity, local control (LC), brain distant progression (BDP), and overall survival (OS) were evaluated. Results: The median preoperative volume and maximum diameter of BM was 18.5cm3 (range 4.1–64.2cm3) and 3.6cm (range 2.1-5-4cm); the median CTV was 29.0cm3 (range 4.1–203.1cm3) and median PTV was 55.2cm3 (range 17.2–282.9cm3). The median follow-up time was 24 months (range 4–33 months). The 1-and 2-year LC in site of treatment was 100%; the median, 1-and 2-year BDP was 11.9 months, 19.6% and 33.0%; the median, 1-and 2-year OS was 24 months (range 4–33 months), 91.3% and 73.0%. No severe postoperative morbidity or radiation therapy toxicity occurred in our series. Conclusions: Multimodal approach, surgery followed by HSRS, can be an effective treatment option for selected patients with single, large brain metastases from different solid tumors. [ABSTRACT FROM AUTHOR]

Positron emission tomography using radiolabeled amino acid (PET-AA) appears to be promising in distinguishing between recurrent tumour and radionecrosis in the follow-up of brain metastasis (BM). The amino acid transporter LAT1 and its cofactor CD98, which are involved in AA uptake, have never been investigated in BM. The aim of our study was to determine and compare the expression of LAT1 and CD98 in BM and in non-tumoral brain tissue (NT). The expression of LAT1 and CD98 were studied by immunohistochemistry in 67 BM, including 18 BM recurrences after radiotherapy, in 53 NT, and in 13 cases of patients with previously irradiated brain tumor and investigated by [18F] FDOPA-PET. LAT1 and CD98 expression were detected in 98.5% and 59.7% of BM respectively and were significantly associated with BM tissue as compared to NT (p<0.001). LAT1 expression in recurrent BM was significantly increased as compared to newly occurring BM. Ten cases investigated by [18F] FDOPA-PET corresponding to recurrent BM displayed significant [18F] FDOPA uptake and LAT1 overexpression whereas three cases corresponding to radionecrosis showed no or low uptake and LAT1 expression. LAT1 expression level and [18F] FDOPA uptake were significantly correlated. In conclusion, we hypothesized that BM may overexpress the AA transporter LAT1. We have shown that LAT1 overexpression was common in BM and was specific for BM as compared to healthy brain. These results could explain the specific BM uptake on PET-AA. [ABSTRACT FROM AUTHOR]

Leptomeningeal dissemination of a primary brain tumor is a condition which is challenging to treat, as it often occurs in rather late disease stages in highly pretreated patients. Its prognosis is dismal and there is still no accepted standard of care. We report here a good clinical effect with a partial response in three out of nine patients and a stable disease with improvement on symptoms in two more patients following systemic anti-angiogenic treatment with bevacizumab (BEV) alone or in combination with chemo- and/or radiotherapy in a series of patients with leptomeningeal dissemination from primary brain tumors (diffuse astrocytoma WHO°II, anaplastic astrocytoma WHO°III, anaplastic oligodendroglioma WHO°III, primitive neuroectodermal tumor and glioblastoma, both WHO°IV). This translated into effective symptom control in five out of nine patients, but only moderate progression-free and overall survival times were reached. Partial responses as assessed by RANO criteria were observed in three patients (each one with anaplastic oligodendroglioma, primitive neuroectodermal tumor and glioblastoma). In these patients progression-free survival (PFS) intervals of 17, 10 and 20 weeks were achieved. In three patients (each one with diffuse astrocytoma, anaplastic astrocytoma and primitive neuroectodermal tumor) stable disease was observed with PFS of 13, 30 and 8 weeks. Another three patients (all with glioblastoma) were primary non-responders and deteriorated rapidly with PFS of 3 to 4 weeks. No severe adverse events were seen. These experiences suggest that the combination of BEV with more conventional therapy schemes with chemo- and/or radiotherapy may be a palliative treatment option for patients with leptomeningeal dissemination of brain tumors. [ABSTRACT FROM AUTHOR]

In this study, we evaluated the dependence of saturation pulse length on APT imaging of diffuse gliomas using a parallel transmission-based technique. Twenty-two patients with diffuse gliomas (9 low-grade gliomas, LGGs, and 13 high-grade gliomas, HGGs) were included in the study. APT imaging was conducted at 3T with a 2-channel parallel transmission scheme using three different saturation pulse lengths (0.5 s, 1.0 s, 2.0 s). The 2D fast spin-echo sequence was used for imaging. Z-spectrum was obtained at 25 frequency offsets from -6 to +6 ppm (step 0.5 ppm). A point-by-point B0 correction was performed with a B0 map. Magnetization transfer ratio (MTRasym) and ΔMTRasym (contrast between tumor and normal white matter) at 3.5 ppm were compared among different saturation lengths. A significant increase in MTRasym (3.5 ppm) of HGG was found when the length of saturation pulse became longer (3.09 ± 0.54% at 0.5 s, 3.83 ± 0.67% at 1 s, 4.12 ± 0.97% at 2 s), but MTRasym (3.5 ppm) was not different among the saturation lengths in LGG. ΔMTRasym (3.5 ppm) increased with the length of saturation pulse in both LGG (0.48 ± 0.56% at 0.5 s, 1.28 ± 0.56% at 1 s, 1.88 ± 0.56% at 2 s and HGG (1.72 ± 0.54% at 0.5 s, 2.90 ± 0.49% at 1 s, 3.83 ± 0.88% at 2 s). In both LGG and HGG, APT-weighted contrast was enhanced with the use of longer saturation pulses. [ABSTRACT FROM AUTHOR]

The subventricular zone (SVZ) has been implicated in the origination, development, and biological behavior of gliomas. Tumor-SVZ contact is also postulated to be a poor prognostic factor in glioblastomas. We aimed to evaluate the prognostic consequence of the anatomical involvement of low-grade gliomas with the SVZ. To that end, we reviewed 143 patients with diffuse astrocytomas, and tumor lesions were manually delineated on magnetic resonance images. We initially investigated the prognostic role of SVZ contact in all patients. Additionally, we investigated the influence of the anatomical proximity of the tumor lesion centroids to the SVZ in the SVZ-involved patient cohorts, as well as location within the SVZ. We found SVZ contact with tumors to be a significant prognostic factor of overall survival in all patients with diffuse astrocytomas (p = 0.027). In the SVZ-involved cohort, a shorter distance from the tumor centroid to the SVZ (≤30 mm) correlated with shorter overall survival (p = 0.022) on univariate analysis. However, there was no significant difference in overall survival with respect to the SVZ region involved with the tumor (p = 0.930). Multivariate analysis showed that a shorter distance between the tumor centroid and the SVZ (p = 0.039) was significantly associated with poor overall survival in SVZ-involved patients. Hence, this study helps establish the prognostic role of the anatomical interaction of tumors with the SVZ in low-grade astrocytomas. [ABSTRACT FROM AUTHOR]

Objective: Meningioma of the cranio-cervical junction is a rare diagnosis and demand a thorough surgical planning as radical excision of these tumors is difficult. In this context recurrence is most likely due to regrowth of residual tumor. The aim of this study was to evaluate the clinical course of patients operated for craniocervical meningioma (CCM) and to investigate the histological features of these tumors and their impact on recurrence rate. Methods: All patients who were operated for CCM at our institution between 2003 and 2012 were identified. Presenting symptoms, MRI findings, surgical approaches and recurrence rate were reviewed retrospectively using medical charts. Histological features of the included tumors were studied focusing on subtypes and MIB-1 immunoreactivity and compared with MIB-1 immunoreactivity in an age and gender-matched control group of patients with supratentorial meningioma. Results: 18 patients with CCM with a mean age of 56.2 years and median follow-up of 60 months were included in the study. Sensory or motor deficit was the most frequent presenting symptom followed by neck pain and lower cranial nerve palsy. Simpson grade II resection was achieved in 16 patients and Simpson grade III resection in two patients. Mortality, morbidity and recurrence rates were 16.7%, 5.5% and 5.5%, respectively. According to the WHO-grading all were found to be grade I meningiomas. Histological subtypes included meningotheliomatous (10), transitional (2), fibrillar (2), angiomatous (3) and secretory (1) meningioma. The mean MIB-1 labeling index in the study group was significantly higher than in the control group, (7.2% and 3.6%, respectively), p < 0.05. There was no correlation between MIB-1 levels and tumor recurrence. Conclusions: CCM seems to have a benign character. Despite a significantly higher MIB-1 index, a high rate of recurrence was not observed. Therefore, approaches with high morbidity are not justified. Nevertheless, in view of the challenging approaches with limited access to the lesion, CCM should be considered a distinctive clinical subgroup. [ABSTRACT FROM AUTHOR]

Background: Cytotoxic chemotherapy can be very effective for the treatment of cancer but toxicity on normal tissues often limits patient tolerance and often causes long-term adverse effects. The objective of this study was to assist in the preclinical development of using modified, non-living bacterially-derived minicells to deliver the potent chemotherapeutic doxorubicin via epidermal growth factor receptor (EGFR) targeting. Specifically, this study sought to evaluate the safety and efficacy of EGFR targeted, doxorubicin loaded minicells (designated EGFRminicellsDox) to deliver doxorubicin to spontaneous brain tumors in 17 companion dogs; a comparative oncology model of human brain cancers. Methodology/Principle Findings: EGFRminicellsDox were administered weekly via intravenous injection to 17 dogs with late-stage brain cancers. Biodistribution was assessed using single-photon emission computed tomography (SPECT) and magnetic resonance imaging (MRI). Anti-tumor response was determined using MRI, and blood samples were subject to toxicology (hematology, biochemistry) and inflammatory marker analysis. Targeted, doxorubicin-loaded minicells rapidly localized to the core of brain tumors. Complete resolution or marked tumor regression (>90% reduction in tumor volume) were observed in 23.53% of the cohort, with lasting anti-tumor responses characterized by remission in three dogs for more than two years. The median overall survival was 264 days (range 49 to 973). No adverse clinical, hematological or biochemical effects were observed with repeated administration of EGFRminicellsDox (30 to 98 doses administered in 10 of the 17 dogs). Conclusions/Significance: Targeted minicells loaded with doxorubicin were safely administered to dogs with late stage brain cancer and clinical activity was observed. These findings demonstrate the strong potential for clinical applications of targeted, doxorubicin-loaded minicells for the effective treatment of patients with brain cancer. On this basis, we have designed a Phase 1 clinical study of EGFR-targeted, doxorubicin-loaded minicells for effective treatment of human patients with recurrent glioblastoma. [ABSTRACT FROM AUTHOR]

Objectives: Evaluate types and prevalence of all, incidental, and clinically relevant incidental intracranial findings, i.e. those referred to primary physician or clinical specialist, in a cohort between 50 and 66 years from the Nord-Trøndelag Health (HUNT) study. Types of follow-up, outcome of repeated neuroimaging and neurosurgical treatment were assessed. Material and Methods: 1006 participants (530 women) underwent MRI of the head at 1.5T consisting of T1 weighted sagittal IR-FSPGR volume, axial T2 weighted, gradient echo T2* weighted and FLAIR sequences plus time of flight cerebral angiography covering the circle of Willis. The nature of a finding and if it was incidental were determined from previous radiological examinations, patient records, phone interview, and/or additional neuroimaging. Handling and outcome of the clinically relevant incidental findings were prospectively recorded. True and false positives were estimated from the repeated neuroimaging. Results: Prevalence of any intracranial finding was 32.7%. Incidental intracranial findings were present in 27.1% and clinically relevant findings in 15.1% of the participants in the HUNT MRI cohort. 185 individuals (18.4%) were contacted by phone about their findings. 40 participants (6.2%) underwent ≥ 1 additional neuroimaging session to establish etiology. Most false positives were linked to an initial diagnosis of suspected glioma, and overall positive predictive value of initial MRI was 0.90 across different diagnoses. 90.8% of the clinically relevant incidental findings were developmental and acquired cerebrovascular pathologies, the remaining 9.2% were intracranial tumors, of which extra-axial tumors predominated. In total, 3.9% of the participants were referred to a clinical specialist, and 11.7% to their primary physician. 1.4% underwent neurosurgery/radiotherapy, and 1 (0.1%) experienced a procedure related postoperative deficit. Conclusions: In a general population between 50 and 66 years most intracranial findings on MRI were incidental, and >15% of the cohort was referred to clinical-follow up. Hence good routines for handling of findings need to be in place to ensure timely and appropriate handling. [ABSTRACT FROM AUTHOR]

Purpose: (S)-4-(3-[18F]Fluoropropyl)-L-glutamic acid (18F-FSPG) is a novel radiopharmaceutical for Positron Emission Tomography (PET) imaging. It is a glutamate analogue that can be used to measure xC- transporter activity. This study was performed to assess the feasibility of 18F-FSPG for imaging orthotopic brain tumors in small animals and the translation of this approach in human subjects with intracranial malignancies. Experimental Design: For the small animal study, GS9L glioblastoma cells were implanted into brains of Fischer rats and studied with 18F-FSPG, the 18F-labeled glucose derivative 18F-FDG and with the 18F-labeled amino acid derivative 18F-FET. For the human study, five subjects with either primary or metastatic brain cancer were recruited (mean age 50.4 years). After injection of 300 MBq of 18F-FSPG, 3 whole-body PET/Computed Tomography (CT) scans were obtained and safety parameters were measured. The three subjects with brain metastases also had an 18F-FDG PET/CT scan. Quantitative and qualitative comparison of the scans was performed to assess kinetics, biodistribution, and relative efficacy of the tracers. Results: In the small animals, the orthotopic brain tumors were visualized well with 18F-FSPG. The high tumor uptake of 18F-FSPG in the GS9L model and the absence of background signal led to good tumor visualization with high contrast (tumor/brain ratio: 32.7). 18F-FDG and 18F-FET showed T/B ratios of 1.7 and 2.8, respectively. In the human pilot study, 18F-FSPG was well tolerated and there was similar distribution in all patients. All malignant lesions were positive with 18F-FSPG except for one low-grade primary brain tumor. In the 18F-FSPG-PET-positive tumors a similar T/B ratio was observed as in the animal model. Conclusions: 18F-FSPG is a novel PET radiopharmaceutical that demonstrates good uptake in both small animal and human studies of intracranial malignancies. Future studies on larger numbers of subjects and a wider array of brain tumors are planned. Trial Registration: ClinicalTrials.gov [ABSTRACT FROM AUTHOR]

Background: During the last decade, the use of 5-aminolevulinic acid (5-ALA) has been steadily increasing in neurosurgery. The study's main objectives were to prospectively evaluate the effectiveness and safety of 5-ALA when used in clinical practice setting on high-grade gliomas’ patients. Methods: National, multicenter and prospective observational study. Inclusion criteria: authorized conditions of use of 5-ALA. Exclusion criteria: contraindication to 5-ALA, inoperable or partial resected tumors, pregnancy and children. Epidemiological, clinical, laboratory, radiological, and safety data were collected. Effectiveness was assessed using complete resection of the tumor, and progression-free and overall survival probabilities. Results: Between May 2010 and September 2014, 85 patients treated with 5-ALA were included, and 77 were suitable for the effectiveness analysis. Complete resection was achieved in 41 patients (54%). Surgeons considered suboptimal the fluorescence of 5-ALA in 40% of the patients assessed. The median duration of follow-up was 12.3 months. The progression-free survival probability at 6 months was 58%. The median duration overall survival was 14.2 months. Progression tumor risk factors were grade of glioma, age and resection degree; and death risk factors were grade of glioma and gender. No severe adverse effects were reported. At one month after surgery, new or increased neurological morbidity was 6.5%. Hepatic enzymes were frequently increased within the first month after surgery; however, they subsequently normalized, and this was found to have no clinical significance. Conclusion: In clinical practice, the 5-ALA showed a good safety profile, but the benefits related to 5-ALA have not been yet clearly shown. The improved differentiation expected by fluorescence between normal and tumor cerebral tissue was suboptimal in a relevant number of patients; in addition, the expected higher degree of resection was lower than in clinical trials as well as incomplete resection was not identified as a prognostic factor risk for death. Because optimal fluorescence was correlated to higher complete resection rate, further research is needed to identify patients (or tumors) with more surgery benefits when using the 5-ALA. [ABSTRACT FROM AUTHOR]

Objectives: To explore the feasibility and safety of retroperitoneal laparoscopic resection of paraganglioma (RLPG) in a large study population. Methods: In a six-year period, 49 patients with primary retroperitoneal paragangliomas (PG) underwent retroperitoneal laparoscopic surgery in a single center. Medical records were reviewed, and collected the following data, which were clinical characteristics, perioperative data (operative time, estimated blood loss, intraoperative hemodynamic changes, intraoperative and postoperative complications, and open conversions), and follow-up data (recurrence or distant metastases). Results: All PGs were removed with negative tumor margin confirmed by postoperative histopathology. The operative time of RLPG was 101.59±31.12 minutes, and the estimated blood loss was 169.78±176.70ml. Intraoperative hypertensive and hypotensive episodes occurred in 25 cases and 27 cases, respectively. Two open conversions occurred. Two intraoperative complications occurred but were successfully managed endoscopically. Postoperative complications were minor and unremarkable. No local recurrence or distant metastasis were observed during the follow-up period. Conclusions: Our experience indicates the feasibility and safety of resection of PGs in a relatively large study population. [ABSTRACT FROM AUTHOR]

Early diagnosis of low grade glioma has been a challenge to clinicians. Positron Emission Tomography (PET) using 18F-FDG as a radio-tracer has limited utility in this area because of the high background in normal brain tissue. Other radiotracers such as 18F-Fluorocholine (18F-FCH) could provide better contrast between tumor and normal brain tissue but with high incidence of false positives. In this study, the potential application of a dual tracer 18F-FCH/18F-FDG-PET is investigated in order to improve the sensitivity of PET imaging for low grade glioma diagnosis based on a mouse orthotopic xenograft model. BALB/c nude mice with and without orthotopic glioma xenografts from U87 MG-luc2 glioma cell line are used for the study. The animals are subjected to 18F-FCH and 18F-FDG PET imaging, and images acquired from two separate scans are superimposed for analysis. The 18F-FCH counts are subtracted from the merged images to identify the tumor. Micro-CT, bioluminescence imaging (BLI), histology and measurement of the tumor diameter are also conducted for comparison. Results show that there is a significant contrast in 18F-FCH uptake between tumor and normal brain tissue (2.65 ± 0.98), but with a high false positive rate of 28.6%. The difficulty of identifying the tumor by 18F-FDG only is also proved in this study. All the tumors can be detected based on the dual tracer technique of 18F-FCH/ 18F-FDG-PET imaging in this study, while the false-positive caused by 18F-FCH can be eliminated. Dual tracer 18F-FCH/18F-FDG PET imaging has the potential to improve the visualization of low grade glioma. 18F-FCH delineates tumor areas and the tumor can be identified by subtracting the 18F-FCH counts. The sensitivity was over 95%. Further studies are required to evaluate the possibility of applying this technique in clinical trials. [ABSTRACT FROM AUTHOR]

Mutations in isocitrate dehydrogenase 1 and 2 (IDH1/2) are frequently found in brain tumors, and the resulting onco–metabolite, 2–hydroxyglutarate (2HG), has been suggested to be a potential diagnostic and prognostic biomarker of the diseases. Indeed, recent studies have demonstrated the feasibility of non–invasively detecting 2HG by using proton magnetic resonance spectroscopy (1H–MRS). Due to severe spectral overlaps of 2HG with its background metabolites and spectral baselines, however, the majority of those previous studies employed spectral editing methods with long echo times (TEs) instead of the most commonly used short TE approach with spectral fitting. Consequently, the results obtained with spectral editing methods may potentially be prone to errors resulting from substantial signal loss due to relaxation. Given that the spectral region where the main signal of 2HG resides is particularly sensitive to spectral baseline in metabolite quantification, we have investigated the impact of incorporating voxel–specifically measured baselines into the spectral basis set on the performance of the conventional short TE approach in 2HG detection in rodent models (Fisher 344 rats; n = 19) of IDH1/2 mutant–overexpressing F98 glioma at 9.4T. Metabolite spectra were acquired (SPECIAL sequence) for a tumor region and the contralateral normal region of the brain for each animal. For the estimation of spectral baselines metabolite–nulled spectra were obtained (double–inversion–recovery SPECIAL sequence) for each individual voxels. Data were post–processed with and without the measured baselines using MRUI and LCModel—the two most widely used data post–processing packages. Our results demonstrate that in–vivo detection of 2HG using the conventional short TE approach is challenging even at 9.4T. However, incorporation of voxel–specifically measured spectral baselines may potentially improve its performance. Upon more thorough validation in a larger number of animals and more importantly in human patients, the potential utility of the proposed short TE acquisition with voxel–specific baseline measurement approach in 2HG detection may need to be considered in the study design. [ABSTRACT FROM AUTHOR]

Purpose: Diffusion Tensor Imaging (DTI) is a powerful imaging technique that has led to improvements in the diagnosis and prognosis of cerebral lesions and neurosurgical guidance for tumor resection. Traditional tensor modeling, however, has difficulties in differentiating tumor-infiltrated regions and peritumoral edema. Here, we describe the supertoroidal model, which incorporates an increase in surface genus and a continuum of toroidal shapes to improve upon the characterization of Glioblastoma multiforme (GBM). Materials and Methods: DTI brain datasets of 18 individuals with GBM and 18 normal subjects were acquired using a 3T scanner. A supertoroidal model of the diffusion tensor and two new diffusion tensor invariants, one to evaluate diffusivity, the toroidal volume (TV), and one to evaluate anisotropy, the toroidal curvature (TC), were applied and evaluated in the characterization of GBM brain tumors. TV and TC were compared with the mean diffusivity (MD) and fractional anisotropy (FA) indices inside the tumor, surrounding edema, as well as contralateral to the lesions, in the white matter (WM) and gray matter (GM). Results: The supertoroidal model enhanced the borders between tumors and surrounding structures, refined the boundaries between WM and GM, and revealed the heterogeneity inherent to tumor-infiltrated tissue. Both MD and TV demonstrated high intensities in the tumor, with lower values in the surrounding edema, which in turn were higher than those of unaffected brain parenchyma. Both TC and FA were effective in revealing the structural degradation of WM tracts. Conclusions: Our findings indicate that the supertoroidal model enables effective tensor visualization as well as quantitative scalar maps that improve the understanding of the underlying tissue structure properties. Hence, this approach has the potential to enhance diagnosis, preoperative planning, and intraoperative image guidance during surgical management of brain lesions. [ABSTRACT FROM AUTHOR]

Background: The therapeutic efficacy of stereotactic radiosurgery for glioblastoma is not well understood, and there needs to be an effective biomarker to identify patients who might benefit from this treatment. This study investigated the efficacy of computed tomography (CT) perfusion imaging as an early imaging biomarker of response to stereotactic radiosurgery in a malignant rat glioma model. Methods: Rats with orthotopic C6 glioma tumors received either mock irradiation (controls, N = 8) or stereotactic radiosurgery (N = 25, 12 Gy in one fraction) delivered by Helical Tomotherapy. Twelve irradiated animals were sacrificed four days after stereotactic radiosurgery to assess acute CT perfusion and histological changes, and 13 irradiated animals were used to study survival. Irradiated animals with survival >15 days were designated as responders while those with survival ≤15 days were non-responders. Longitudinal CT perfusion imaging was performed at baseline and regularly for eight weeks post-baseline. Results: Early signs of radiation-induced injury were observed on histology. There was an overall survival benefit following stereotactic radiosurgery when compared to the controls (log-rank P<0.04). Responders to stereotactic radiosurgery showed lower relative blood volume (rBV), and permeability-surface area (PS) product on day 7 post-stereotactic radiosurgery when compared to controls and non-responders (P<0.05). rBV and PS on day 7 showed correlations with overall survival (P<0.05), and were predictive of survival with 92% accuracy. Conclusions: Response to stereotactic radiosurgery was heterogeneous, and early selection of responders and non-responders was possible using CT perfusion imaging. Validation of CT perfusion indices for response assessment is necessary before clinical implementation. [ABSTRACT FROM AUTHOR]