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Significant progress has been made recently with the contribution of technological advances in studies on brain cancer. Regarding this, identifying and correctly classifying tumors is a crucial task in the field of medical imaging. The disease-related tumor classification problem, on which deep learning technologies have also become a focus, is very important in the diagnosis and treatment of the disease. The use of deep learning models has shown promising results in recent years. However, the sparsity of ground truth data in medical imaging or inconsistent data sources poses a significant challenge for training these models. The utilization of StyleGANv2-ADA is proposed in this paper for augmenting brain MRI slices to enhance the performance of deep learning models. Specifically, augmentation is applied solely to the training data to prevent any potential leakage. The StyleGanv2-ADA model is trained with the Gazi Brains 2020, BRaTS 2021, and Br35h datasets using the researchers' default settings. The effectiveness of the proposed method is demonstrated on datasets for brain tumor classification, resulting in a notable improvement in the overall accuracy of the model for brain tumor classification on all the Gazi Brains 2020, BraTS 2021, and Br35h datasets. Importantly, the utilization of StyleGANv2-ADA on the Gazi Brains 2020 Dataset represents a novel experiment in the literature. The results show that the augmentation with StyleGAN can help overcome the challenges of working with medical data and the sparsity of ground truth data. Data augmentation employing the StyleGANv2-ADA GAN model yielded the highest overall accuracy for brain tumor classification on the BraTS 2021 and Gazi Brains 2020 datasets, together with the BR35H dataset, achieving 75.18%, 99.36%, and 98.99% on the EfficientNetV2S models, respectively. This study emphasizes the potency of GANs for augmenting medical imaging datasets, particularly in brain tumor classification, showcasing a notable increase in overall accuracy through the integration of synthetic GAN data on the used datasets., (© 2024. The Author(s).)

Typical longitudinal radiographic assessment of brain tumors relies on side-by-side qualitative visualization of serial magnetic resonance images (MRIs) aided by quantitative measurements of tumor size. However, when assessing slowly growing tumors and/or complex tumors, side-by-side visualization and quantification may be difficult or unreliable. Whole-brain, patient-specific "digital flipbooks" of longitudinal scans are a potential method to augment radiographic side-by-side reads in clinical settings by enhancing the visual perception of changes in tumor size, mass effect, and infiltration across multiple slices over time. In this approach, co-registered, consecutive MRI scans are displayed in a slide deck, where one slide displays multiple brain slices of a single timepoint in an array (eg, 3 × 5 "mosaic" view of slices). The flipbooks are viewed similarly to an animated flipbook of cartoons/photos so that subtle radiographic changes are visualized via perceived motion when scrolling through the slides. Importantly, flipbooks can be created easily with free, open-source software. This article describes the step-by-step methodology for creating flipbooks and discusses clinical scenarios for which flipbooks are particularly useful. Example flipbooks are provided in Supplementary Material., (© The Author(s) 2024. Published by Oxford University Press on behalf of the Society for Neuro-Oncology. All rights reserved. For commercial re-use, please contact reprints@oup.com for reprints and translation rights for reprints. All other permissions can be obtained through our RightsLink service via the Permissions link on the article page on our site—for further information please contact journals.permissions@oup.com.)

Brain tumors are a threat to life for every other human being, be it adults or children. Gliomas are one of the deadliest brain tumors with an extremely difficult diagnosis. The reason is their complex and heterogenous structure which gives rise to subjective as well as objective errors. Their manual segmentation is a laborious task due to their complex structure and irregular appearance. To cater to all these issues, a lot of research has been done and is going on to develop AI-based solutions that can help doctors and radiologists in the effective diagnosis of gliomas with the least subjective and objective errors, but an end-to-end system is still missing. An all-in-one framework has been proposed in this research. The developed end-to-end multi-task learning (MTL) architecture with a feature attention module can classify, segment, and predict the overall survival of gliomas by leveraging task relationships between similar tasks. Uncertainty estimation has also been incorporated into the framework to enhance the confidence level of healthcare practitioners. Extensive experimentation was performed by using combinations of MRI sequences. Brain tumor segmentation (BraTS) challenge datasets of 2019 and 2020 were used for experimental purposes. Results of the best model with four sequences show 95.1% accuracy for classification, 86.3% dice score for segmentation, and a mean absolute error (MAE) of 456.59 for survival prediction on the test data. It is evident from the results that deep learning-based MTL models have the potential to automate the whole brain tumor analysis process and give efficient results with least inference time without human intervention. Uncertainty quantification confirms the idea that more data can improve the generalization ability and in turn can produce more accurate results with less uncertainty. The proposed model has the potential to be utilized in a clinical setup for the initial screening of glioma patients., (© 2024. The Author(s) under exclusive licence to Society for Imaging Informatics in Medicine.)

Background: We sought to analyze, in well-defined clinical setting, the first 100 patients treated at the intraoperative MRI (iMRI) hybrid surgical theatre at our facility in a population-based setting to evaluate which pathologies are best approached with iMRI assisted surgeries, as this is not yet clearly defined., Methods: Patients undergoing surgery in the 3T iMRI hybrid surgical theatre at our neurosurgical department between December 2017 to May 2021 were included after informed consent. Demographic, clinical, surgical, histological, radiological and outcome parameters, as well as variables related to iMRI, were retrospectively collected and analyzed. Patients were subdivided into adult and pediatric cohorts., Results: Various neurosurgical procedures were performed; resection of tumors and epileptic foci, endoscopic skull base procedures including pituitary lesions, deep brain stimulation (DBS) and laser interstitial thermal therapy (LITT). In total, 41 patients were pediatric. An iMRI scan was carried out in 96% of cases and led to continuation of surgery in 50% of cases, mainly due to visualized remaining pathological tissue (95.2%). Median time to iMRI from intubation was 280 min and median total duration of surgery was 445 min. The majority of patients experienced no postoperative complications (70%), 13 patients suffered permanent postoperative deficits, predominantly visual., Conclusion: Herein, we demonstrate the first 100 patients undergoing neurosurgery aided by iMRI at our facility since introduction. Indications for surgery differed between pediatric and adult patients. The iMRI was utilized for tumor surgeries, particularly adult low-grade gliomas and pediatric tumors, as well as for epilepsy surgery and DBS. In this heterogenous population, iMRI led to continuation of surgery in 50%. To establish the benefit in maximizing the extent of resection in these brain pathologies future studies are recommended., Clinical Trial Number: Not applicable., (© 2024. The Author(s).)

To meet the needs of automated medical analysis of brain tumor magnetic resonance imaging, this study introduces an enhanced instance segmentation method built upon mask region-based convolutional neural network. By incorporating squeeze-and-excitation networks, a channel attention mechanism, and concatenated attention neural network, a spatial attention mechanism, the model can more adeptly focus on the critical regions and finer details of brain tumors. Residual network-50 combined attention module and feature pyramid network as the backbone network to effectively capture multi-scale characteristics of brain tumors. At the same time, the region proposal network and region of interest align technology were used to ensure that the segmentation area matched the actual tumor morphology. The originality of the research lies in the deep residual network that combines attention mechanism with feature pyramid network to replace the backbone based on mask region convolutional neural network, achieving an improvement in the efficiency of brain tumor feature extraction. After a series of experiments, the precision of the model is 90.72%, which is 0.76% higher than that of the original model. Recall was 91.68%, an increase of 0.95%; Mean Intersection over Union was 94.56%, an increase of 1.39%. This method achieves precise segmentation of brain tumor magnetic resonance imaging, and doctors can easily and accurately locate the tumor area through the segmentation results, thereby quickly measuring the diameter, area, and other information of the tumor, providing doctors with more comprehensive diagnostic information., (© 2024. The Author(s).)

Chemotherapy in brain tumors is tailored based on tumor type, grade, and molecular markers, which are crucial for predicting responses and survival outcomes. This review summarizes the role of chemotherapy in gliomas, glioneuronal and neuronal tumors, ependymomas, choroid plexus tumors, medulloblastomas, and meningiomas, discussing standard treatment protocols and recent developments in targeted therapies.Furthermore, the studies reporting the integration of MRI-based radiomics and deep learning models for predicting treatment outcomes are reviewed. Advances in MRI-based radiomics and deep learning models have significantly enhanced the prediction of chemotherapeutic benefits, survival prediction following chemotherapy, and differentiating tumor progression with psuedoprogression. These non-invasive techniques offer valuable insights into tumor characteristics and treatment responses, facilitating personalized therapeutic strategies. Further research is warranted to refine these models and expand their applicability across different brain tumor types., (Copyright © 2024 Elsevier B.V. All rights reserved.)

While MR imaging is the main imaging modality to assess brain tumors, PET imaging has a specific role. Among the many tracers that have been proposed and are still being developed, 2-[ 18 F]fluoro-2-deoxy-d-glucose ([ 18 F]FDG) and O-(2-[ 18 F]-fluoroethyl)-l-tyrosine ([ 18 F]FET) PET remain the most solidly established in the clinics. In particular, [ 18 F]FET has gained increased acceptance due to its higher sensitivity. In this paper, we present an overview of the current clinical status of brain tumor imaging, with emphasis on PET imaging., Competing Interests: Disclosure The authors received no financial support for the study, authorship, and/or publication of this article., (Copyright © 2024 Elsevier Inc. All rights reserved.)

The precise assessment of vascular heterogeneity in brain tumors is vital for diagnosing, grading, predicting progression, and guiding treatment decisions. However, currently, there is a significant shortage of high-resolution imaging approaches. Herein, we propose a contrast-enhanced susceptibility-weighted imaging (CE-SWI) utilizing the minimalist dextran-modified Fe 3 O 4 nanoparticles (Dextran@Fe 3 O 4 NPs) for ultrahigh-resolution mapping of vasculature in brain tumors. The Dextran@Fe 3 O 4 NPs are prepared via a facile coprecipitation method under room temperature, and exhibit small hydrodynamic size (28 nm), good solubility, excellent biocompatibility, and high transverse relaxivity ( r 2 *, 159.7 mM -1 s -1 ) under 9.4 T magnetic field. The Dextran@Fe 3 O 4 NPs-enhanced SWI can increase the contrast-to-noise ratio (CNR) of cerebral vessels to 2.5 times that before injection and achieves ultrahigh-spatial-resolution visualization of microvessels as small as 0.1 mm in diameter. This advanced imaging capability not only allows for the detailed mapping of both enlarged peritumoral drainage vessels and the intratumoral microvessels, but also facilitates the sensitive imaging detection of vascular permeability deterioration in a C6 cells-bearing rat glioblastoma model. Our proposed Dextran@Fe 3 NPs-enhanced SWI provides a powerful imaging technique with great clinical translation potential for the precise theranostics of brain tumors.4 NPs-enhanced SWI provides a powerful imaging technique with great clinical translation potential for the precise theranostics of brain tumors.

We explored the structural and functional changes of the healthy hemisphere of the brain after surgery in children with intracranial space-occupying lesions. We enrolled 32 patients with unilateral intracranial space-occupying lesions for brain imaging and cognitive assessment. Voxel-based morphometry and surface-based morphometry analyses were used to investigate the structural images of the healthy hemisphere. Functional images were analyzed using regional homogeneity, amplitude of low-frequency fluctuations, and fractional-amplitude of low-frequency fluctuations. Voxel-based morphometry and surface-based morphometry analysis used the statistical model built into the CAT 12 toolbox. Paired t-tests were used for functional image and cognitive test scores. For structural image analysis, we used family-wise error correction of peak level (p < 0.05), and for functional image analysis, we use Gaussian random-field theory correction (voxel p < 0.001, cluster p < 0.05). We found an increase in gray matter volume in the healthy hemisphere within six months postoperatively, mainly in the frontal lobe. Regional homogeneity and fractional-amplitude of low-frequency fluctuations also showed greater functional activity in the frontal lobe. The results of cognitive tests showed that psychomotor speed and motor speed decreased significantly after surgery, and reasoning increased significantly after surgery. We concluded that in children with intracranial space-occupying lesions, the healthy hemisphere exhibits compensatory structural and functional effects within six months after surgery. This effect occurs mainly in the frontal lobe and is responsible for some higher cognitive compensation. This may provide some guidance for the rehabilitation of children after brain surgery., (© 2024. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.)

Purpose: The differentiation between adverse radiation effects (ARE) and tumor recurrence or progression (TRP) is a major decision-making point in the follow-up of patients with brain tumors. The advent of immunotherapy, targeted therapy and radiosurgery has made this distinction difficult to achieve in several clinical situations. Contrast clearance analysis (CCA) is a useful technique that can inform clinical decisions but has so far only been histologically validated in the context of high-grade gliomas., Methods: This is a series of 7 patients, treated between 2018 and 2023, for various brain pathologies including brain metastasis, atypical meningioma, and high-grade glioma. MRI with contrast clearance analysis was used to inform clinical decisions and patients underwent surgical resection as indicated. The histopathology findings were compared with the CCA findings in all cases., Results: All seven patients had been treated with gamma knife radiosurgery and were followed up with periodic MR imaging. All patients underwent CCA when the necessity to distinguish tumor recurrence from radiation necrosis arose, and subsequently underwent surgery as indicated. Concordance of CCA findings with histological findings was found in all cases (100%)., Conclusions: Based on prior studies on GBM and the surgical findings in our series, delayed contrast extravasation MRI findings correlate well with histopathology across a wide spectrum of brain tumor pathologies. CCA can provide a quick diagnosis and have a direct impact on patients' treatment and outcomes., (© 2024. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.)

The preoperative diagnosis of brain tumors is important for therapeutic planning as it contributes to the tumors' prognosis. In the last few years, the development in the field of artificial intelligence and machine learning has contributed greatly to the medical area, especially the diagnosis of the grades of brain tumors through radiological images and magnetic resonance images. Due to the complexity of tumor descriptors in medical images, assessing the accurate grade of glioma is a major challenge for physicians. We have proposed a new classification system for glioma grading by integrating novel MRI features with an ensemble learning method, called Ensemble Learning based on Adaptive Power Mean Combiner (EL-APMC). We evaluate and compare the performance of the EL-APMC algorithm with twenty-one classifier models that represent state-of-the-art machine learning algorithms. Results show that the EL-APMC algorithm achieved the best performance in terms of classification accuracy (88.73%) and F1-score (93.12%) over the MRI Brain Tumor dataset called BRATS2015. In addition, we showed that the differences in classification results among twenty-two classifier models have statistical significance. We believe that the EL-APMC algorithm is an effective method for the classification in case of small-size datasets, which are common cases in medical fields. The proposed method provides an effective system for the classification of glioma with high reliability and accurate clinical findings., (© 2024. The Author(s).)

The increasing global incidence of glioma tumors has raised significant healthcare concerns due to their high mortality rates. Traditionally, tumor diagnosis relies on visual analysis of medical imaging and invasive biopsies for precise grading. As an alternative, computer-assisted methods, particularly deep convolutional neural networks (DCNNs), have gained traction. This research paper explores the recent advancements in DCNNs for glioma grading using brain magnetic resonance images (MRIs) from 2015 to 2023. The study evaluated various DCNN architectures and their performance, revealing remarkable results with models such as hybrid and ensemble based DCNNs achieving accuracy levels of up to 98.91%. However, challenges persisted in the form of limited datasets, lack of external validation, and variations in grading formulations across diverse literature sources. Addressing these challenges through expanding datasets, conducting external validation, and standardizing grading formulations can enhance the performance and reliability of DCNNs in glioma grading, thereby advancing brain tumor classification and extending its applications to other neurological disorders.

Hybrid PET/MR imaging offers a unique opportunity to acquire MR imaging and PET information during a single imaging session. PET/MR imaging has numerous advantages, including enhanced diagnostic accuracy, improved disease characterization, and better treatment planning and monitoring. It enables the immediate integration of anatomic, functional, and metabolic imaging information, allowing for personalized characterization and monitoring of neurologic diseases. This review presents recent advances in PET/MR imaging and highlights advantages in clinical practice for neuro-oncology, epilepsy, and neurodegenerative disorders. PET/MR imaging provides valuable information about brain tumor metabolism, perfusion, and anatomic features, aiding in accurate delineation, treatment response assessment, and prognostication., (Copyright © 2023 Elsevier Inc. All rights reserved.)

Objectives: Language reorganization may follow tumor invasion of the dominant hemisphere. Tumor location, grade, and genetics influence the communication between eloquent areas and tumor growth dynamics, which are drivers of language plasticity. We evaluated tumor-induced language reorganization studying the relationship of fMRI language laterality to tumor-related variables (grade, genetics, location), and patient-related variables (age, sex, handedness)., Methods: The study was retrospective cross-sectional. We included patients with left-hemispheric tumors (study group) and right-hemispheric tumors (controls). We calculated five fMRI laterality indexes (LI): hemispheric, temporal lobe, frontal lobe, Broca's area (BA), Wernicke's area (WA). We defined LI ≥ 0.2 as left-lateralized (LL) and LI < 0.2 as atypical lateralized (AL). Chi-square test (p < 0.05) was employed to identify the relationship between LI and tumor/patient variables in the study group. For those variables having significant results, confounding factors were evaluated in a multinomial logistic regression model., Results: We included 405 patients (235 M, mean age: 51 years old) and 49 controls (36 M, mean age: 51 years old). Contralateral language reorganization was more common in patients than controls. The statistical analysis demonstrated significant association between BA LI and patient sex (p = 0.005); frontal LI, BA LI, and tumor location in BA (p < 0.001); hemispheric LI and fibroblast growth factor receptor (FGFR) mutation (p = 0.019); WA LI and O6-methylguanine-DNA methyltransferase promoter (MGMT) methylation in high-grade gliomas (p = 0.016)., Conclusions: Tumor genetics, pathology, and location influence language laterality, possibly due to cortical plasticity. Increased fMRI activation in the right hemisphere was seen in patients with tumors in the frontal lobe, BA and WA, FGFR mutation, and MGMT promoter methylation., Key Points: • Patients harboring left-hemispheric tumors present with contralateral translocation of language function. Influential variables for this phenomenon included frontal tumor location, BA location, WA location, sex, MGMT promoter methylation, and FGFR mutation. • Tumor location, grade, and genetics may influence language plasticity, thereby affecting both communication between eloquent areas and tumor growth dynamics. • In this retrospective cross-sectional study, we evaluated language reorganization in 405 brain tumor patients by studying the relationship of fMRI language laterality to tumor-related variables (grade, genetics, location), and patient-related variables (age, sex, handedness)., (© 2023. The Author(s).)

Purpose: Task-based BOLD fMRI and DTI-fiber tracking have become part of the routine presurgical work-up of brain tumor patients in many institutions. However, their potential impact on both surgical treatment and neurologic outcome remains unclear, in despite of the high costs and complex implementation., Methods: We retrospectively investigated whether performing fMRI and DTI-ft preoperatively substantially impacted surgical planning and patient outcome in a series of brain tumor patients. We assessed (i) the quality of fMRI and DTI-ft results, by using a scale of 0-2 (0 = failed mapping; 1 = intermediate confidence; 2 = good confidence), (ii) whether functional planning substantially contributed to defining the surgical strategy to be undertaken (i.e., no surgery, biopsy, or resection, with or without ESM), the surgical entry point and extent of resection, and (iii) the incidence of neurological deficits post-operatively., Results: Twenty-seven patients constituted the study population. The mean confidence rating was 1.9/2 for fMRI localization of the eloquent cortex and lateralization of the language function and 1.7/2 for DTI-ft results. Treatment strategy was altered in 33% (9/27) of cases. Surgical entry point was modified in 8% (2/25) of cases. The extent of resection was modified in 40% (10/25). One patient (1/25, 4%) developed one new functional deficit post-operatively., Conclusion: Functional MR mapping - which must not be considered an alternative to ESM - has a critical role preoperatively, potentially modifying treatment strategy or increasing the neurosurgeons' confidence in the surgical approach hypothesized based on conventional imaging., (© 2023. Fondazione Società Italiana di Neurologia.)

Aim: This study aimed to evaluate the diagnostic value of ultrahigh-field magnetic resonance imaging (MRI) for brain tumors in clinical practice., Methods: Thirty patients with brain tumors underwent 7- and 3-T MRI. The performance and diagnostic confidence of 7- and 3-T MRI in the visualization of tumor details such as internal structure and feeding artery were evaluated by radiologists. Contrast-enhanced region performance and tumor detail diagnostic confidence score (DCS) were calculated and compared between 7 and 3T using Wilcoxon rank sum test., Results: In 19 with obvious enhancement and 11 cases without obvious enhancement, 7- and 3-T MRI showed similar performance. The tumors' internal structure and feeding artery were more clearly depicted by 7-T MRI (62.2% and 54.4%, respectively) than by 3-T MRI (2.2% and 6.7%, respectively). Furthermore, the mean DCSs of both internal structure and feeding artery were higher at 7T than at 3T (internal structure: 16.29 ± 9.67 vs. -5.79 ± 4.12, p = 0.028; feeding artery: 21.96 ± 6.93 vs. 4.46 ± 7.07, p = 0.028). The DCS was more significantly improved in the senior radiologist group., Conclusion: Better visualization of brain tumor details and higher tumor detail diagnostic confidence can be obtained with 7-T MRI., (© 2022 The Authors. CNS Neuroscience & Therapeutics published by John Wiley & Sons Ltd.)

Purpose: To develop an MR multitasking-based dynamic imaging for cerebrovascular evaluation (MT-DICE) technique for simultaneous quantification of permeability and leakage-insensitive perfusion with a single-dose contrast injection., Methods: MT-DICE builds on a saturation-recovery prepared multi-echo fast low-angle shot sequence. The k-space is randomly sampled for 7.6 min, with single-dose contrast agent injected 1.5 min into the scan. MR multitasking is used to model the data into six dimensions, including three spatial dimensions for whole-brain coverage, a saturation-recovery time dimension, and a TE dimension for dynamic INLINEMATH measurements in eight healthy subjects and, in three of them, inter-session repeatability of permeability and leakage-insensitive perfusion parameters. Its feasibility was also demonstrated in four patients with brain tumors., Results: MT-DICE INLINEMATH values of normal gray matter and white matter were in excellent agreement with reference values (intraclass correlation coefficients = 0.860/0.962 for gray matter and 0.925/0.975 for white matter ). Both permeability and perfusion parameters demonstrated good to excellent intersession agreement with the lowest intraclass correlation coefficients at 0.694. Contrast kinetic parameters in all healthy subjects and patients were within the literature range., Conclusion: Based on dynamic INLINEMATH mapping, MT-DICE allows for simultaneous quantification of permeability and leakage-insensitive perfusion metrics with a single-dose contrast injection., (© 2022 The Authors. Magnetic Resonance in Medicine published by Wiley Periodicals LLC on behalf of International Society for Magnetic Resonance in Medicine.)

Relative cerebral blood volume (rCBV) obtained from dynamic susceptibility contrast (DSC) MRI is adversely impacted by contrast agent leakage in brain tumors. Using simulations, we previously demonstrated that multi-echo DSC-MRI protocols provide improvements in contrast agent dosing, pulse sequence flexibility, and rCBV accuracy. The purpose of this study is to assess the in-vivo performance of dual-echo acquisitions in patients with brain tumors (n = 59). To verify pulse sequence flexibility, four single-dose dual-echo acquisitions were tested with variations in contrast agent dose, flip angle, and repetition time, and the resulting dual-echo rCBV was compared to standard single-echo rCBV obtained with preload (double-dose). Dual-echo rCBV was comparable to standard double-dose single-echo protocols (mean (standard deviation) tumor rCBV 2.17 (1.28) vs. 2.06 (1.20), respectively). High rCBV similarity was observed (CCC = 0.96), which was maintained across both flip angle (CCC = 0.98) and repetition time (CCC = 0.96) permutations, demonstrating that dual-echo acquisitions provide flexibility in acquisition parameters. Furthermore, a single dual-echo acquisition was shown to enable quantification of both perfusion and permeability metrics. In conclusion, single-dose dual-echo acquisitions provide similar rCBV to standard double-dose single-echo acquisitions, suggesting contrast agent dose can be reduced while providing significant pulse sequence flexibility and complementary tumor perfusion and permeability metrics.

Purpose: This study aims to compare the quality of images resulting from magnetic resonance imaging of patients who underwent intracranial MRI simulation using two different setups (treatment position with mask immobilization and standard diagnostic setup). Due to a larger number of channels and lack of mask immobilization in the standard diagnostic setup, we would like to evaluate whether this is an appropriate technique for MRI treatment planning., Methods: In total, 70 patients who underwent MR imaging of the brain at 1.5T were included in the study (48 for 6‑channel flex coil, 22 for 24-channel HNU face bill coil). Contrast-enhanced 3D T1w and T2 FLAIR images were acquired. Images were subjectively compared for artifact appearance and general image quality by three radiographers. Objective comparison of contrast rate, contrast-to-noise ratio, and signal-to-noise ratio was also performed., Results: FLAIR and contrast-enhanced 3D T1w images showed various artifacts, such as susceptibility and movement artifacts. There were no statistically significant differences regarding the evaluation of movement artifacts between two coils and two different immobilization methods. There were also no statistically significant differences (p > 0.05) between the 6‑channel flex coil and 24-channel HNU face bill coil regarding qualitative general image quality and objective measures., Conclusion: There were no statistically significant differences between the occurrence of movement artifacts, overall image quality, and objective image quality in treatment position with mask immobilization and standard diagnostic setup. Based on this result, we can conclude that a standard diagnostic setup is also applicable in intracranial MRI treatment planning with no loss to image quality. Registration of the imaging plans was not performed in this study; therefore, it might still be necessary to perform measurements of tumor delineation matching and geometrical accuracy acceptance in our institution.

Background: Animal brain tumor models can be useful educational tools for the training of neurosurgical residents in risk-free environments. Magnetic resonance imaging (MRI) technologies have not used these models to quantitate tumor, normal gray and white matter, and total tissue removal during complex neurosurgical procedures. This pilot study was carried out as a proof of concept to show the feasibility of using brain tumor models combined with 7-T MRI technology to quantitatively assess tissue removal during subpial tumor resection., Methods: Seven ex vivo calf brain hemispheres were used to develop the 7-T MRI segmentation methodology. Three brains were used to quantitate brain tissue removal using 7-T MRI segmentation methodology. Alginate artificial brain tumor was created in 4 calf brains to assess the ability of 7-T MRI segmentation methodology to quantitate tumor and gray and white matter along with total tissue volumes removal during a subpial tumor resection procedure., Results: Quantitative studies showed a correlation between removed brain tissue weights and volumes determined from segmented 7-T MRIs. Analysis of baseline and postresection alginate brain tumor segmented 7-T MRIs allowed quantification of tumor and gray and white matter along with total tissue volumes removed and detection of alterations in surrounding gray and white matter., Conclusions: This pilot study showed that the use of animal tumor models in combination with 7-T MRI technology provides an opportunity to increase the granularity of data obtained from operative procedures and to improve the assessment and training of learners., (Copyright © 2021 Elsevier Inc. All rights reserved.)

This article provides an overview of the current status of ultrahigh-field 7-T magnetic resonance (MR) imaging in neuro-oncology, specifically for the management of patients with brain tumors. It includes a discussion of areas across the pretherapeutic, peritherapeutic, and posttherapeutic stages of patient care where 7-T MR imaging is currently being exploited and holds promise. This discussion includes existing technical challenges, barriers to clinical integration, as well as our impression of the future role of 7-T MR imaging as a clinical tool in neuro-oncology., Competing Interests: Disclosure The authors have received research funding from GE Healthcare., (Copyright © 2020 Elsevier Inc. All rights reserved.)

Functional magnetic resonance imaging (fMRI) is useful for localizing eloquent cortex in the brain prior to neurosurgery. Language and motor paradigms offer a wide range of tasks to test brain regions within the language and motor networks. With the help of fMRI, hemispheric language dominance can be determined. It also is possible to localize specific motor and sensory areas within the motor and sensory gyri. These findings are critical for presurgical planning. The most important factor in presurgical fMRI is patient performance. Patient interview and instruction time are crucial to ensure that patients understand and comply with the fMRI paradigm., Competing Interests: Disclosure N.P. Brennan and M. Gene have nothing to disclose. A. Holodny is the Owner/President of fMRI Consultants, LLC, a purely educational entity., (Copyright © 2020 Elsevier Inc. All rights reserved.)

Purpose: The aim of this study was to generate a multivariate model using various MRI markers of blood flow and vascular permeability and accumulation of 18 F-fluorodeoxyglucose (FDG) to predict the extent of hypoxia in an 18 F-fluoromisonidazole (FMISO)-positive region., Methods: Fifteen patients aged 27-74 years with brain tumors (glioma, n = 13; lymphoma, n = 1; germinoma, n = 1) were included. MRI scans were performed using a 3T scanner, and dynamic contrast-enhanced (DCE) perfusion and arterial spin labeling images were obtained. K trans and V p maps were generated using the DCE images. FDG and FMISO positron emission tomography scans were also obtained. A model for predicting FMISO positivity was generated on a voxel-by-voxel basis by a multivariate logistic regression model using all the MRI parameters with and without FDG. Receiver-operating characteristic curve analysis was used to detect FMISO positivity with multivariate and univariate analysis of each parameter. Cross-validation was performed using the leave-one-out method., Results: The area under the curve (AUC) was highest for the multivariate prediction model with FDG (0.892) followed by the multivariate model without FDG and univariate analysis with FDG and K trans (0.844 for all). In cross-validation, the multivariate model with FDG had the highest AUC (0.857 ± 0.08) followed by the multivariate model without FDG (0.834 ± 0.119)., Conclusion: A multivariate prediction model created using blood flow, vascular permeability, and glycometabolism parameters can predict the extent of hypoxia in FMISO-positive areas in patients with brain tumors.

Background: Intraoperative magnetic resonance imaging (IO-MRI) provides real-time assessment of extent of resection of brain tumor. Development of new enhancement during IO-MRI can confound interpretation of residual enhancing tumor, although the incidence of this finding is unknown., Objective: To determine the frequency of new enhancement during brain tumor resection on intraoperative 3 Tesla (3T) MRI. To optimize the postoperative imaging window after brain tumor resection using 1.5 and 3T MRI., Methods: We retrospectively evaluated 64 IO-MRI performed for patients with enhancing brain lesions referred for biopsy or resection as well as a subset with an early postoperative MRI (EP-MRI) within 72 h of surgery (N = 42), and a subset with a late postoperative MRI (LP-MRI) performed between 120 h and 8 wk postsurgery (N = 34). Three radiologists assessed for new enhancement on IO-MRI, and change in enhancement on available EP-MRI and LP-MRI. Consensus was determined by majority response. Inter-rater agreement was assessed using percentage agreement., Results: A total of 10 out of 64 (16%) of the IO-MRI demonstrated new enhancement. Seven of 10 patients with available EP-MRI demonstrated decreased/resolved enhancement. One out of 42 (2%) of the EP-MRI demonstrated new enhancement, which decreased on LP-MRI. Agreement was 74% for the assessment of new enhancement on IO-MRI and 81% for the assessment of new enhancement on the EP-MRI., Conclusion: New enhancement occurs in intraoperative 3T MRI in 16% of patients after brain tumor resection, which decreases or resolves on subsequent MRI within 72 h of surgery. Our findings indicate the opportunity for further study to optimize the postoperative imaging window., (Copyright © 2019 by the Congress of Neurological Surgeons.)

Neuroimaging is essential in survey of patients with brain tumors. An important objectives of neuroimaging are highly reliable non-invasive diagnosis, treatment planning and evaluation of treatment outcomes. Magnetic resonance imaging (MRI) is one of the modern neuroimaging methods. This technique ensures analysis of structural cerebral changes, vascular and metabolic characteristics of brain tumors. It is necessary to standardize imaging parameters and unify protocols and methods considering a widespread use of MRI for brain tumors. In our practice, we use our own experience, world literature data and evidence-based international guidelines on the diagnosis of various brain diseases. The purpose of this review is to study the modern principles of magnetic resonance imaging in adults with brain tumors in neurosurgical practice.

Context: Relative cerebral blood volume (rCBV) and percentage signal recovery (PSR) obtained from T2* dynamic susceptibility contrast magnetic resonance imaging are important parameters for brain tumor assessment., Aim: To study the accuracy of PSR in the differentiation of low-grade glioma, high-grade glioma, lymphoma, and metastases particularly in comparison to rCBV., Settings and Design: Retrospective observational study., Subjects and Methods: Study included pathologically confirmed cases of 10 low-grade glioma, 22 high-grade glioma, 6 lymphoma, and 12 metastases (Total 50). PSR, relative PSR (rPSR), and rCBV were calculated., Statistical Analysis Used: Accuracy of these parameters studied statistically using analysis of variance and ROC (Receiver operating characteristic) curves., Results: rCBV was higher in metastases (3.45 ± 2.82) and high-grade glioma (3.47 ± 1.62), whereas was low in lymphoma (1.03 ± 0.74) and low-grade glioma (1.43 ± 0.47) with P value of 0.030. PSR was low in metastases (48 ± 16.18), intermediate in glioma (73.24 ± 6.39 and 88.26 ± 6.05, high and low grade), and high in lymphoma (112.16 ± 10.57) with P value < 0.000. rPSR was higher for lymphoma (1.73 ± 0.57) than high-grade glioma (0.85 ± 0.11) and metastasis (0.69 ± 0.19) with P value <.000. Area under ROC for PSR was greater than rCBV in differentiating metastases from lymphoma (1.00 vs 0.13), high-grade glioma from lymphoma (1.00 vs 0.38), high-grade glioma from metastases (0.89 vs 0.58), and high-grade glioma from low-grade glioma (0.96 vs 0.03) with excellent curve characteristics. F values for PSR and rPSR from ANOVA analysis were 71.47 and 36.77, was better than rCBV (3.84) in differentiating these groups., Conclusions: Percentage of signal recovery shows low recovery values in metastases, intermediate recovery values in glioma, and overshoot in lymphoma. PSR values show lower overlap than rCBV between lymphoma and metastases; and between high grade glioma and metastases. PSR difference is also higher than rCBV between low- and high-grade gliomas. Hence, PSR can potentially help as an additional perfusion parameter in the preoperative differentiation of these tumors., Competing Interests: None

Objectives: To investigate whether clinical condition, imaging session, and locations affect repeatability of amide proton transfer-weighted (APTw) magnetic resonance imaging (MRI) in the brain., Materials and Methods: Three APTw MRI data sets were acquired, involving two intrasession scans and one intersession scan for 19 healthy, 15 glioma, and 12 acute stroke adult participants (mean age 53.8, 54.6, and 68.5, respectively) on a 3T MR scanner. The mean APTw signals from five locations in healthy brain (supratentorial and infratentorial locations) and from entire tumor and stroke lesions (supratentorial location) were calculated. The within-subject coefficient of variation (wCV) and intraclass correlation coefficient (ICC) were calculated for each clinical conditions, image sessions, and anatomic locations. Differences in APTw signals between sessions were analyzed using repeated-measures analysis of variance., Results: The ICC and wCV were 0.96 (95% confidence interval [CI], 0.91-0.99) and 16.1 (12.6-21.3) in glioma, 0.93 (0.82-0.98) and 15.0 (11.4-20.6) in stroke, and 0.84 (0.72-0.91) and 34.0 (28.7-41.0) in healthy brain. There were no significant differences in APTw signal between three sessions, irrespective of disease condition and location. The ICC and wCV were 0.85 (0.68-0.94) and 27.4 (21.8-35.6) in supratentorial, and 0.44 (- 0.18 to 0.76) and 32.7 (25.9 to 42.9) in infratentorial locations. There were significant differences in APTw signal between supra- (mean, 0.49%; 95% CI, 0.38-0.61) and infratentorial locations (1.09%, 0.98-1.20; p < 0.001)., Conclusion: The repeatability of APTw signal was excellent in supratentorial locations, while it was poor in infratentorial locations due to severe B0 inhomogeneity and susceptibility which affects MTR asymmetry., Key Points: • In supratentorial locations, APTw MRI showed excellent intrasession and intersession repeatability in brains of healthy controls and patients with glioma, as well as in stroke-affected regions. • APTw MRI showed excellent repeatability in supratentorial locations, but poor repeatability in infratentorial locations. • Considering poor repeatability in the infratentorial locations, the use of APTw MRI in longitudinal assessment in infratentorial locations is not indicated.

Purpose: Childhood brain tumors (CBTs) and their treatment increase the risk of secondary neoplasms (SNs). We studied the incidence of secondary craniospinal tumors with magnetic resonance imaging (MRI) screening in a national cohort of survivors of CBT treated with radiotherapy, and we analyzed the Finnish Cancer Registry (FCR) data on SNs in survivors of CBT with radiotherapy registered as a part of the primary tumor treatment. Methods: A total of 73 survivors of CBT participated in the MRI study (mean follow-up of 19 ± 6.2 years). The incidence of SNs in a cohort of CBT patients ( N  = 569) was retrieved from the FCR (mean follow-up of 11 ± 12.9 years). Brain tumors were diagnosed at age ≤16 years between the years 1970 and 2008 in the clinical study and the years 1963 and 2010 in the FCR population. Results: Secondary brain tumors, meningiomas in all and schwannoma in one, were found in 6 of the 73 (8.2%) survivors with a mean of 23 ± 4.3 years after the diagnosis of the primary tumor. The cumulative incidence was 10.2% (95% confidence interval [CI] 3.9-25.1) in 25 years of follow-up. In the FCR data, the 25-year cumulative incidence of SNs was 2.4% (95% CI 1.3-4.1); only two brain tumors, no meningiomas, were registered. Conclusion: Survivors of CBT treated with radiotherapy have a high incidence of meningiomas, which are rarely registered in the FCR.

Purpose: Preoperative functional MRI (fMRI) is limited by a muted BOLD response caused by abnormal vasoreactivity and resultant neurovascular uncoupling adjacent to malignant brain tumors. We propose to overcome this limitation and more accurately identify eloquent areas adjacent to brain tumors by independently assessing vasoreactivity using breath-holding and incorporating these data into the fMRI analysis., Methods: Local vasoreactivity using a breath-holding paradigm with the same timing as the functional motor and language tasks was determined in 16 patients (9 glioblastomas, 1 anaplastic astrocytoma, 5 low grade astrocytomas, and 1 metastasis) and 6 healthy control subjects. We derived an fMRI model based on an observed vaso-task response dependency that takes into account the altered hemodynamics adjacent to brain tumors., Results: In both healthy controls and brain tumor subjects, we found a statistical dependency between breath-hold and task BOLD response. In tumor subjects, activation maps that take into account this vaso-task dependency demonstrated clinically meaningful areas of activation that were not seen using the task-only analysis in about half of the cases studied. This included localization of language areas adjacent to brain tumors., Conclusions: The present preliminary results demonstrate that neurovascular uncoupling known to affect the accuracy of BOLD fMRI adjacent to brain tumors may be, at least partially, overcome by incorporating an observed vaso-task dependency in the BOLD signal analysis., (Copyright © 2019 Elsevier B.V. All rights reserved.)

Background: Ultra-high-field magnetic resonance imaging (MRI) of the brain is attractive for image guidance during neurosurgery because of its high tissue contrast and detailed vessel visualization. However, high-field MRI is prone to distortion artifacts, which may compromise image guidance. Here we investigate intra- and extracranial distortions in 7-T MRI scans., Methods: Five patients with and 5 patients without skin-adhesive fiducials received magnetization-prepared T1-weighted 7-T MRI and standard 3-T MRI scans. The 7- and 3-T images were rigidly coregistered and compared. Intracranial distortions were evaluated qualitatively, whereas shifts at the skin surface and shifts of the center positions of skin-adhesive fiducials were measured quantitatively. Moreover, we present an illustrative case of an ultra-high-field image-guided skull base meningioma resection., Results: We found excellent intracranial correspondence between 3- and 7-T MRI scans. However, the average maximum skin shift was 6.8 ± 2.0 mm in group A and 5.2 ± 0.9 mm in group B. The average maximum difference between the skin-adhesive fiducial positions was 5.6 ± 3.1 mm in group B. In our tumor resection case, the meningioma blood supply could be targeted early thanks to 7-T image guidance, which made subsequent tumor removal straightforward., Conclusions: There are no visible intracranial distortions in magnetization-prepared T1-weighted 7-T MRI cranial images. However, we found considerable extracranial shifts. These shifts render 7-T images unreliable for patient-to-image registration. We recommend performing patient-to-image registration on a routine (computed tomography scan or 3-T magnetic resonance) image and subsequently fusing the 7-T magnetic resonance image with the routine image on the image guidance machine, until this issue is resolved., (Copyright © 2019 Elsevier Inc. All rights reserved.)

Background and Purpose: Language task-based functional MRI (fMRI) is increasingly used for presurgical planning in patients with brain lesions. Different paradigms elicit activations of different components of the language network. The aim of this study is to optimize fMRI clinical usage by comparing the effectiveness of three language tasks for language lateralization and localization in a large group of patients with brain lesions., Methods: We analyzed fMRI data from a sequential retrospective cohort of 51 patients with brain lesions who underwent presurgical fMRI language mapping. We compared the effectiveness of three language tasks (Antonym Generation, Sentence Completion (SC), and Auditory Naming) for lateralizing language function and for activating cortex within patient-specific regions-of-interest representing eloquent language areas, and assessed the degree of spatial overlap of the areas of activation elicited by each task., Results: The tasks were similarly effective for lateralizing language within the anterior language areas. The SC task produced higher laterality indices within the posterior language areas and had a significantly higher agreement with the clinical report. Dice coefficients between the task pairs were in the range of .351-.458, confirming substantial variation in the components of the language network activated by each task., Conclusions: SC task consistently produced large activations within the dominant hemisphere and was more effective for lateralizing language within the posterior language areas. The low degree of spatial overlap among the tasks strongly supports the practice of using a battery of tasks to help the surgeon to avoid eloquent language areas., (© 2019 by the American Society of Neuroimaging.)

Background: Despite the multitude of available treatments, glioblastoma (GBM) remains an aggressive and uniformly fatal tumor. Laser interstitial thermal therapy (LITT) is a novel, minimally invasive treatment that holds promise for treating patients with GBM who are not candidates for traditional open craniotomy. However, due to the recent introduction of LITT into clinical practice, large series that evaluate safety and long-term outcomes after LITT are lacking., Objective: To present our institution's series of over 50 GBM patients treated with LITT, with regard to safety, efficacy, and outcomes., Methods: We performed a retrospective descriptive study of patients with histologically proven GBM who underwent LITT. Data collected included demographics, tumor location and volume, tumor genetic markers, treatment volume, perioperative complications, and long-term follow-up data., Results: We performed 58 LITT treatments for GBM in 54 patients over 5.5 yr. Forty-one were recurrent tumors while 17 were frontline treatments. Forty GBMs were lobar in location, while 18 were in deep structures (thalamus, insula, corpus callosum). Average tumor volume was 12.5 ± 13.4 cm3. Average percentage of tumor treated with the yellow thermal damage threshold (TDT) line (dose equivalent of 43°C for 2 min) was 93.3% ± 10.6%, and with the blue TDT line (dose equivalent of 43°C for 10 min) was 88.0% ± 14.2%. There were 7 perioperative complications (12%) and 2 mortalities (3.4%). Median overall survival after LITT for the total cohort was 11.5 mo, and median progression-free survival 6.6 mo., Conclusion: LITT appears to be a safe and effective treatment for GBM in properly selected patients., (© Congress of Neurological Surgeons 2018.)

This literature review analyzes the capabilities of magnetic resonance imaging (MRI)-based cerebral perfusion for differentiation between post-radiation changes (e.g., radionecrosis) and continued growth. The technique is compared with other highly informative radiodiagnostic techniques used in neuroradiology. The use of MR perfusion is important in a comprehensive examination protocol. Trends in the technique development are analyzed.

Background: This study aims to evaluate the impact of preoperative functional magnetic resonance imaging (fMRI) on clinical outcomes in patients with low grade glioma (LGG)., Methods: In a retrospective propensity-matched cohort study, we compared patients with LGG based on whether they underwent fMRI as part of preoperative assessment. Twelve patients with LGG who underwent preoperative fMRI were selected, and a contemporaneous group of 12 control patients with LGG who did not undergo fMRI were matched to the fMRI group based on age, sex, and 1p/19q status., Results: fMRI group subjects tended to have more aggressive surgeries (67% resection, 33% biopsy) than the control group (33% resection, 67% biopsy). There were no significant differences in outcomes between the 2 groups. Time between clinical assessment and surgery tended to be longer in the fMRI group (6.3 ± 4.2 weeks) than in the control group (2.7 ± 2.2 weeks). Extent of resection was similar between the 2 cohorts. fMRI group subjects had lower preoperative functional status and tended to have a greater postoperative functional status improvement than control group subjects. Mean survival was not significantly different (fMRI group 5-year survival: 88.9%, control group 5-year survival: 61.1%)., Conclusions: We evaluated the impact of preoperative fMRI in patients with LGG in this propensity-matched cohort study. This study has not demonstrated any significant difference in outcomes between the fMRI and control groups; however, there were nonsignificant trends for patients who underwent fMRI to undergo more aggressive surgical interventions and have a greater postoperative functional status improvement., (Crown Copyright © 2018. Published by Elsevier Inc. All rights reserved.)

Purpose: Presurgical fMRI is an important tool for surgery navigation in achieving maximum resection of a brain tumor. However, the functional localization accuracy may be compromised by spatial transformation from echo-planar images to high-resolution structural images. We evaluated functional localization errors associated with the spatial transformation process using three algorithms commonly applied to the presurgical fMRI in the clinic., Methods: MR images of 20 brain tumor patients for presurgical evaluation of eloquent areas near motor cortices were analyzed. All fMRI data were spatially transferred to 3D T1-weighted images using three algorithms: (a) coordinate matching (CM), (b) automated registration (AR), and (c) AR plus manual adjustment (AR adj ). Activation clusters overlaid on original echo-planar images were manually delineated on slice-matched 2D T1- weighted images and then transferred to the 3D T1-weighted image volume, and served as the reference localization. Functional localization errors were estimated by measuring the distance between the reference localization and the activation cluster after spatial transformation and then compared for the three algorithms., Results: The 3D Euclidean distance for AR (10.2 ± 4.9 mm) was found to be significantly larger (P < 0.05) than those for CM (5.6 ± 2.6 mm) and AR adj (5.8 ± 3.0 mm) algorithms. The difference between the localization errors in CM and AR adj was not statistically significant., Conclusions: A procedure was proposed to evaluate functional localization errors associated with spatial transformation in presurgical fMRI. Our results highlighted the necessity of routine quality control for the AR processing in the clinic., (© 2018 American Association of Physicists in Medicine.)

Purpose: To investigate and compare human judgment and machine learning tools for quality assessment of clinical MR spectra of brain tumors., Methods: A very large set of 2574 single voxel spectra with short and long echo time from the eTUMOUR and INTERPRET databases were used for this analysis. Original human quality ratings from these studies as well as new human guidelines were used to train different machine learning algorithms for automatic quality control (AQC) based on various feature extraction methods and classification tools. The performance was compared with variance in human judgment., Results: AQC built using the RUSBoost classifier that combats imbalanced training data performed best. When furnished with a large range of spectral and derived features where the most crucial ones had been selected by the TreeBagger algorithm it showed better specificity (98%) in judging spectra from an independent test-set than previously published methods. Optimal performance was reached with a virtual three-class ranking system., Conclusion: Our results suggest that feature space should be relatively large for the case of MR tumor spectra and that three-class labels may be beneficial for AQC. The best AQC algorithm showed a performance in rejecting spectra that was comparable to that of a panel of human expert spectroscopists. Magn Reson Med 79:2500-2510, 2018. © 2017 International Society for Magnetic Resonance in Medicine., (© 2017 International Society for Magnetic Resonance in Medicine.)

Objective: To report our experience in the use of 3 tesla intraoperative magnetic resonance imaging (MRI) in neurosurgical procedures for tumors, and to evaluate the criteria for increasing the extension of resection., Material and Methods: This retrospective study included all consecutive intraoperative MRI studies done for neuro-oncologic disease in the first 13 months after the implementation of the technique. We registered possible immediate complications, the presence of tumor remnants, and whether the results of the intraoperative MRI study changed the surgical management. We recorded the duration of surgery in all cases., Results: The most common tumor was recurrent glioblastoma, followed by primary glioblastoma and metastases. Complete resection was achieved in 28%, and tumor remnants remained in 72%. Intraoperative MRI enabled neurosurgeons to improve the extent of the resection in 85% of cases. The mean duration of surgery was 390±122minutes., Conclusion: Intraoperative MRI using a strong magnetic field (3 teslas) is a valid new technique that enables precise study of the tumor resection to determine whether the resection can be extended without damaging eloquent zones. Although the use of MRI increases the duration of surgery, the time required decreases as the team becomes more familiar with the technique., (Copyright © 2018 SERAM. Publicado por Elsevier España, S.L.U. All rights reserved.)

The sensitivity of fMRI in identification of eloquent cortical centers in the case of large infiltrative growing tumors and pronounced peritumoral edema may be reduced or significantly limited in some cases. The main cause is an attenuated Blood-Oxygen-Level-Dependent response (BOLD) caused by pathological vascular reactivity and subsequent neurovascular uncoupling of fMRI. In our study, we attempted to overcome these limitations and increase the sensitivity of this technique in identification of eloquent cortical areas adjacent to brain tumors by using vasoreactivity features of a breath-holding test and including these data in the BOLD analysis. Local vasoreactivity using a breath-holding paradigm with the same block design of both motor and speech tests was determined in 5 healthy volunteers and 3 patients in the preoperative period (two patients with high grade gliomas and one patient with single metastasis). A coherence-based model was developed for analysis of BOLD fMRI, which took into account altered hemodynamics in peritumoral zones. Obtained coherence maps demonstrated clinically more significant activation zones that were not seen with standard methods of fMRI processing. Thus, neurovascular uncoupling that is known to affect the accuracy of the BOLD fMRI response adjacent to brain tumors may be partially overcome by including an independent measurement of vasoreactivity using a breath-holding test in the BOLD analysis.

Background and Objective: In the last decade, an increasing number of positron emission tomography / magnetic resonance (PET/MR) tomographs were installed and many clinical studies were performed in the neurological field., Methods: Although PET/MR has many favorable properties to support the application in brain imaging, attenuation correction, and therefore accurate quantification, is a problem that still requires optimal solution., Results: In this review we have summarized the three main methods that are currently used to correct attenuation in PET/MR, namely atlas- or template-based methods, segmentation-based methods, and reconstruction-based methods. There is currently active ongoing research to refine available methods and improvements are reasonably expected in the next years. Clinical studies using PET/MR focused mainly on neurodegenerative and neurooncological disorders. PET/MR hybrids tomographs provided promising scientific results and were logistically more convenient for patients. Additionally, in order to explore all potential clinical benefits of this hybrid technology, the design and development of multimodal contrast agents has constantly increased the attention of radiochemists. Many PET/MR dual probes have been already devised, particularly in the nanotechnology field, sometimes preceding the identification of a clear diagnostic application in medicine., Conclusion: In the near future, we predict more clinical studies as the availability of PET/MR will further increase and new tracers for neurodegenerative disorders will accept broader clinical acceptance., (Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.)

A combination of morphological imaging of the brain with microstructural and functional imaging provides a comprehensive overview of the properties of individual tissues. While diffusion weighted imaging provides information about tissue cellularity, spectroscopic imaging allows us to evaluate the integrity of neurons and possible anaerobic glycolysis during tumor hypoxia, in addition to the presence of accelerated synthesis or degradation of cellular membranes; on the other hand, PET metabolic imaging is used to evaluate major metabolic pathways, determining the overall extent of the tumor ( 18 F-FET, 18 F-FDOPA, 18 F-FCH) or the degree of differentiation ( 18 F-FDG, 18 F-FLT, 18 F-FDOPA and 18 F-FET). Multi-parameter analysis of tissue characteristics and determination of the phenotype of the tumor tissue is a natural advantage of PET/MRI scanning. The disadvantages are higher cost and limited availability in all centers with neuro-oncology surgery. PET/MRI scanning of brain tumors is one of the most promising indications since the earliest experiments with integrated PET/MRI imaging systems, and along with hybrid imaging of neurodegenerative diseases, represent a new direction in the development of neuroradiology on the path towards comprehensive imaging at the molecular level., (Copyright © 2017 Elsevier B.V. All rights reserved.)

Neuroimaging plays an ever evolving role in the diagnosis, treatment planning, and post-therapy assessment of brain tumors. This review provides an overview of current magnetic resonance imaging (MRI) methods routinely employed in the care of the brain tumor patient. Specifically, we focus on advanced techniques including diffusion, perfusion, spectroscopy, tractography, and functional MRI as they pertain to noninvasive characterization of brain tumors and pretreatment evaluation. The utility of both structural and physiological MRI in the post-therapeutic brain evaluation is also reviewed with special attention to the challenges presented by pseudoprogression and pseudoresponse., (Copyright © 2017 by the Congress of Neurological Surgeons.)

Background and Objectives: Nowadays, clinical practice in Gamma Knife treatments is generally based on MRI anatomical information alone. However, the joint use of MRI and PET images can be useful for considering both anatomical and metabolic information about the lesion to be treated. In this paper we present a co-segmentation method to integrate the segmented Biological Target Volume (BTV), using [ 11 C]-Methionine-PET (MET-PET) images, and the segmented Gross Target Volume (GTV), on the respective co-registered MR images. The resulting volume gives enhanced brain tumor information to be used in stereotactic neuro-radiosurgery treatment planning. GTV often does not match entirely with BTV, which provides metabolic information about brain lesions. For this reason, PET imaging is valuable and it could be used to provide complementary information useful for treatment planning. In this way, BTV can be used to modify GTV, enhancing Clinical Target Volume (CTV) delineation., Methods: A novel fully automatic multimodal PET/MRI segmentation method for Leksell Gamma Knife ® treatments is proposed. This approach improves and combines two computer-assisted and operator-independent single modality methods, previously developed and validated, to segment BTV and GTV from PET and MR images, respectively. In addition, the GTV is utilized to combine the superior contrast of PET images with the higher spatial resolution of MRI, obtaining a new BTV, called BTV MRI . A total of 19 brain metastatic tumors, undergone stereotactic neuro-radiosurgery, were retrospectively analyzed. A framework for the evaluation of multimodal PET/MRI segmentation is also presented. Overlap-based and spatial distance-based metrics were considered to quantify similarity concerning PET and MRI segmentation approaches. Statistics was also included to measure correlation among the different segmentation processes. Since it is not possible to define a gold-standard CTV according to both MRI and PET images without treatment response assessment, the feasibility and the clinical value of BTV integration in Gamma Knife treatment planning were considered. Therefore, a qualitative evaluation was carried out by three experienced clinicians., Results: The achieved experimental results showed that GTV and BTV segmentations are statistically correlated (Spearman's rank correlation coefficient: 0.898) but they have low similarity degree (average Dice Similarity Coefficient: 61.87 ± 14.64). Therefore, volume measurements as well as evaluation metrics values demonstrated that MRI and PET convey different but complementary imaging information. GTV and BTV could be combined to enhance treatment planning. In more than 50% of cases the CTV was strongly or moderately conditioned by metabolic imaging. Especially, BTV MRI enhanced the CTV more accurately than BTV in 25% of cases., Conclusions: The proposed fully automatic multimodal PET/MRI segmentation method is a valid operator-independent methodology helping the clinicians to define a CTV that includes both metabolic and morphologic information. BTV MRI and GTV should be considered for a comprehensive treatment planning., (Copyright © 2017 Elsevier B.V. All rights reserved.)

Background: Segmentation of gliomas in multi-parametric (MP-)MR images is challenging due to their heterogeneous nature in terms of size, appearance and location. Manual tumor segmentation is a time-consuming task and clinical practice would benefit from (semi-) automated segmentation of the different tumor compartments., Methods: We present a semi-automated framework for brain tumor segmentation based on non-negative matrix factorization (NMF) that does not require prior training of the method. L1-regularization is incorporated into the NMF objective function to promote spatial consistency and sparseness of the tissue abundance maps. The pathological sources are initialized through user-defined voxel selection. Knowledge about the spatial location of the selected voxels is combined with tissue adjacency constraints in a post-processing step to enhance segmentation quality. The method is applied to an MP-MRI dataset of 21 high-grade glioma patients, including conventional, perfusion-weighted and diffusion-weighted MRI. To assess the effect of using MP-MRI data and the L1-regularization term, analyses are also run using only conventional MRI and without L1-regularization. Robustness against user input variability is verified by considering the statistical distribution of the segmentation results when repeatedly analyzing each patient's dataset with a different set of random seeding points., Results: Using L1-regularized semi-automated NMF segmentation, mean Dice-scores of 65%, 74 and 80% are found for active tumor, the tumor core and the whole tumor region. Mean Hausdorff distances of 6.1 mm, 7.4 mm and 8.2 mm are found for active tumor, the tumor core and the whole tumor region. Lower Dice-scores and higher Hausdorff distances are found without L1-regularization and when only considering conventional MRI data., Conclusions: Based on the mean Dice-scores and Hausdorff distances, segmentation results are competitive with state-of-the-art in literature. Robust results were found for most patients, although careful voxel selection is mandatory to avoid sub-optimal segmentation.

This review article describes advancement of magnetic resonance imaging technologies in radiation therapy planning, guidance, and adaptation of brain tumors. The potential for MR-guided radiation therapy to improve outcomes and the challenges in its adoption are discussed., (© The Author(s) 2017. Published by Oxford University Press on behalf of the Society for Neuro-Oncology. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

Background and Objective: Magnetic resonance-guided laser-induced thermotherapy (MR-LITT) is a minimally invasive technique that shows promise in neuro-oncology because of its superiority in delivering precise minimally invasive thermal energy with minimal collateral damage. In this analysis, we investigate initial data on the effect of MR-LITT on dural-based lesions., Methods: Five patients were identified with dural-based lesions (4 meningiomas, 1 solitary fibrous tumor) with clear evidence of radiologic progression. In all 5 cases, the tumors were localized to the lateral convexity or paramedian locations in the supratentorial space. All patients received MR-LITT and then a follow-up magnetic resonance imaging scan at 24 hours after treatment, at 1 month, and at each subsequent follow-up visit. Local control of the ablated tumor was evaluated with radiographic follow-up and symptomatic progression-free survival was recorded., Results: Five LITT treatments were performed on 5 patients with an average age of 65.2 years. The average tumor volume was 29.7 cm 3 and ablation dosage was 12.4 W. On average, 80% of the pretreatment lesion volume was ablated. The mean follow-up time was 59.3 weeks. In total, 2 patients (1 with an anaplastic meningioma and 1 with a solitary fibrous tumor) had radiographic evidence of disease progression. In the observed time of the 3 patients with no progression, there was a 52% reduction in tumor volume. There were no major perioperative complications., Conclusions: MR-LITT is a promising technology for dural-based lesion treatment. This initial study demonstrates that MR-LITT is safe and offers several advantages over open surgical treatment. Randomized studies are needed to evaluate its role as a treatment adjunct., (Copyright © 2016 Elsevier Inc. All rights reserved.)

Purpose: To determine whether half of the approved dose of gadobenate dimeglumine (MultiHance) is as effective as a full dose of gadoterate meglumine (Dotarem) for qualitative and quantitative cerebral blood volume (CBV) perfusion evaluation at 3T in patients with brain gliomas., Materials and Methods: We enrolled 65 adult patients in an interindividual comparative study. Patients were randomized to one of two study arms: 33 patients received 0.1 mmol/kg body weight (bw) of gadoterate, 32 patients received 0.05 mmol/kg bw of gadobenate. The patients underwent identical examinations at 3T. Arterial input function (AIF), tissue function (TF), and the maximum tumor CBV (CBV&#95;T) were obtained from each patient. The quality of the CBV maps were independently reviewed by two neuroradiologists blinded to the administered contrast agent., Results: The administration of a half dose of gadobenate led to a roughly 40% reduction in signal drop compared to that achieved with a full dose of gadoterate (P values for AIF and TF maximum and integral were <0.01); quantitative and qualitative assessment of CBV maps revealed no difference between contrast agents (P values for CBV&#95;T of high- and low-grade gliomas, image quality evaluation were 0.87, 0.48, >0.65, respectively) CONCLUSION: The CBV maps obtained with a half dose gadobenate (0.05 mmol/kg bw) are of comparable diagnostic quality as the corresponding images acquired with a full dose of gadoterate (0.1 mmol/kg bw)., Level of Evidence: 2 J. Magn. Reson. Imaging 2017;45:500-506., (© 2016 International Society for Magnetic Resonance in Medicine.)

Background: Managing difficult-to-access lesions or surgically accessible lesions in fragile patients is a central problem in neurosurgery. MRI-guided interstitial laser ablation (ILA) is a minimally invasive option that may provide a safe means of treating these challenging patients., Objective: We aim to (1) evaluate safety, efficacy, and preliminary outcomes within a diverse and large series of ILA treatments; and (2) report technical details and operative trends that proved useful over time in the authors' experience and that may be of use to neurosurgeons who perform ILA., Methods: A retrospective evaluation of ILA patients was performed in terms of demographics, surgical techniques, and clinical outcomes., Results: A total of 133 intracranial lesions in 120 patients were treated with ILA, including glioblastomas (GBM), other gliomas, metastases, epilepsy foci, and radionecrosis. The rate of complications/unexpected readmission was 6.0%, and the mortality rate was 2.2%. With high-grade tumors, tumor volumes >3 cm in diameter trended toward a higher rate of complication (p = 0.056). Median progression-free survival (PFS) and overall survival (OS) for recurrent GBM were 7.4 and 11.6 months, respectively. As a frontline treatment for newly diagnosed GBM, median PFS and OS were 5.9 and 11.4 months, respectively. For metastases, median PFS was not yet reached, and OS was 17.2 months., Conclusion: Our series suggests that ILA is a safe and efficacious treatment for a variety of intracranial pathologies, can be tailored to treat difficult-to-access lesions, and may offer a novel alternative to open craniotomy in properly selected patients., (© 2018 The Author(s) Published by S. Karger AG, Basel.)

The role of radiomics in the diagnosis, monitoring, and therapy planning of brain tumors is becoming increasingly clear. Incorporation of quantitative approaches in radiology, in combination with increased computer power, offers unique insights into macroscopic tumor characteristics and their direct association with the underlying pathophysiology. This article presents the most recent findings in radiomics and radiogenomics with respect to identifying potential imaging biomarkers with prognostic value that can lead to individualized therapy. In addition, a brief introduction to the concept of big data and its significance in medicine is presented., (Copyright © 2016 Elsevier Inc. All rights reserved.)

Purpose: Tumor heterogeneity in medical imaging is a current research trend due to its potential relationship with tumor malignancy. The aim of this study is to analyze the effect of dynamic range and matrix size changes on the results of different heterogeneity measures., Materials and Methods: Four patients harboring three glioblastomas and one metastasis were considered. Sixteen textural heterogeneity measures were computed for each patient, with a configuration including co-occurrence matrices (CM) features (local heterogeneity) and run-length matrices (RLM) features (regional heterogeneity). The coefficient of variation measured agreement between the textural measures in two types of experiments: (i) fixing the matrix size and changing the dynamic range and (ii) fixing the dynamic range and changing the matrix size., Results: None of the measures considered were robust under dynamic range changes. The CM Entropy and the RLM high gray-level run emphasis (HGRE) were the outstanding textural features due to their robustness under matrix size changes. Also, the RLM low gray-level run emphasis (LGRE) provided robust results when the dynamic range considered was sufficiently high (more than 8 levels). All of the remaining textural features were not robust., Conclusion: Tumor texture studies based on images with different characteristics (e.g. multi-center studies) should first fix the dynamic range to be considered. For studies involving images of different resolutions either (i) only robust measures should be used (in our study CM entropy, RLM HGRE and/or RLM LGRE) or (ii) images should be resampled to match those of the lowest resolution before computing the textural features., (Copyright © 2016 Elsevier Ltd. All rights reserved.)

The interstitium-to-plasma rate constant (k ep ), 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 k ep 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 k ep . 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 k ep values, with an average error of 3%. Over-estimation of the PK parameters was detected for scan duration <12min, being more pronounced at low k ep values (<0.1min -1 ). For the model selection maps, significantly lower percentage of the full extended-Tofts-model (ETM) was selected in patients at scan duration of 5min compared to >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 k ep when using ETM, and therefore care should be taken using model selection., (Copyright © 2016 Elsevier Inc. All rights reserved.)