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Brain AVMs treated with stereotactic radiosurgery typically demonstrate a minimum latency period of 1-3 years between treatment and nidus obliteration. Assessment of treatment response is usually limited to evaluation of AVM nidus structural changes using conventional MR imaging and MRA techniques. This report describes the use of 4D Flow MRI to also measure radiation-induced hemodynamic changes in a Spetzler-Martin grade III AVM, which were detectable as early as 6 months after treatment.

Background: Patients with primary brain tumors demonstrate heterogeneous patterns of cognitive dysfunction, which we explore using latent profile analysis (LPA) to identify cognitive phenotypes and their trajectories in patients receiving radiotherapy (RT)., Methods: Ninety-six patients completed neuropsychological testing before and post-RT (3, 6, 12-months) on a prospective longitudinal trial, including measures of processing speed, executive function, language, and verbal and visual memory. Models with 2-4 classes were examined. Demographic and clinical data were examined across phenotypes and post-RT cognitive change was evaluated., Results: The optimal model identified three unique cognitive phenotypes including a group of patients with generalized impairments (11.5%), a group with isolated verbal memory impairments (21.9%), and a group with minimal impairments (66.7%). The Verbal Memory phenotype had fewer years of education (p=.007) and a greater proportion of males (p<.001); the Generalized group had a greater proportion of patients with IDH-wild type gliomas and showed greater symptoms of anxiety and poorer quality of life (p-values<.05); and the Minimal Impairment phenotype had higher rates of IDH-Mutant gliomas. Approximately 50% of patients declined on at least one cognitive domain with memory the most vulnerable. Patients that declined reported greater symptoms of depression (p=.007) and poorer quality of life (p=.025)., Conclusions: We identified three distinct cognitive phenotypes in patients with primary brain tumors receiving RT, each associated with unique demographic and clinical (e.g., IDH mutational status) profiles, with mood symptoms associated with late cognitive decline. This patient-centered approach enhances our understanding of clinical profiles associated with cognitive dysfunction and treatment-related neurotoxicity., (© 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.)

Purpose To develop and validate a deep learning (DL) method to detect and segment enhancing and nonenhancing cellular tumor on pre- and posttreatment MRI scans in patients with glioblastoma and to predict overall survival (OS) and progression-free survival (PFS). Materials and Methods This retrospective study included 1397 MRI scans in 1297 patients with glioblastoma, including an internal set of 243 MRI scans (January 2010 to June 2022) for model training and cross-validation and four external test cohorts. Cellular tumor maps were segmented by two radiologists on the basis of imaging, clinical history, and pathologic findings. Multimodal MRI data with perfusion and multishell diffusion imaging were inputted into a nnU-Net DL model to segment cellular tumor. Segmentation performance (Dice score) and performance in distinguishing recurrent tumor from posttreatment changes (area under the receiver operating characteristic curve [AUC]) were quantified. Model performance in predicting OS and PFS was assessed using Cox multivariable analysis. Results A cohort of 178 patients (mean age, 56 years ± 13 [SD]; 116 male, 62 female) with 243 MRI timepoints, as well as four external datasets with 55, 70, 610, and 419 MRI timepoints, respectively, were evaluated. The median Dice score was 0.79 (IQR, 0.53-0.89), and the AUC for detecting residual or recurrent tumor was 0.84 (95% CI: 0.79, 0.89). In the internal test set, estimated cellular tumor volume was significantly associated with OS (hazard ratio [HR] = 1.04 per milliliter; P < .001) and PFS (HR = 1.04 per milliliter; P < .001) after adjustment for age, sex, and gross total resection (GTR) status. In the external test sets, estimated cellular tumor volume was significantly associated with OS (HR = 1.01 per milliliter; P < .001) after adjustment for age, sex, and GTR status. Conclusion A DL model incorporating advanced imaging could accurately segment enhancing and nonenhancing cellular tumor, distinguish recurrent or residual tumor from posttreatment changes, and predict OS and PFS in patients with glioblastoma. Keywords: Segmentation, Glioblastoma, Multishell Diffusion MRI Supplemental material is available for this article. © RSNA, 2024.

Background: Evaluating longitudinal changes in gliomas is a time-intensive process with significant interrater variability. Automated segmentation could reduce interrater variability and increase workflow efficiency for assessment of treatment response. We sought to evaluate whether neural networks would be comparable to expert assessment of pre- and posttreatment diffuse gliomas tissue subregions including resection cavities., Methods: A retrospective cohort of 647 MRIs of patients with diffuse gliomas (average 55.1 years; 29%/36%/34% female/male/unknown; 396 pretreatment and 251 posttreatment, median 237 days post-surgery) from 7 publicly available repositories in The Cancer Imaging Archive were split into training (536) and test/generalization (111) samples. T1, T1-post-contrast, T2, and FLAIR images were used as inputs into a 3D nnU-Net to predict 3 tumor subregions and resection cavities. We evaluated the performance of networks trained on pretreatment training cases (Pre-Rx network), posttreatment training cases (Post-Rx network), and both pre- and posttreatment cases (Combined networks)., Results: Segmentation performance was as good as or better than interrater reliability with median dice scores for main tumor subregions ranging from 0.82 to 0.94 and strong correlations between manually segmented and predicted total lesion volumes (0.94 <  R 2 values < 0.98). The Combined network performed similarly to the Pre-Rx network on pretreatment cases and the Post-Rx network on posttreatment cases with fewer false positive resection cavities (7% vs 59%)., Conclusions: Neural networks that accurately segment pre- and posttreatment diffuse gliomas have the potential to improve response assessment in clinical trials and reduce provider burden and errors in measurement., Competing Interests: The authors I.V., G.M.M., R.X.S., and N.W. are employees at Cortechs.ai. N.W. and A.M.D. are on the board of directors at Cortechs.ai. J.D.R., S.Bas., N.F., S.K. and T.M.S. are on the medical advisory board of Cortechs.ai., (© The Author(s) 2024. Published by Oxford University Press, the Society for Neuro-Oncology and the European Association of Neuro-Oncology.)

Purpose: Brain metastases are common among adult patients with solid malignancies and are increasingly being treated with stereotactic radiosurgery (SRS). As more patients with brain metastases are becoming eligible for SRS, there is a need for practical review of patient selection and treatment considerations., Methods and Materials: Two patient cases were identified to use as the foundation for a discussion of a wide and representative range of management principles: (A) SRS alone for 5 to 15 lesions and (B) a large single metastasis to be treated with pre- or postoperative SRS. Patient selection, fractionation, prescription dose, treatment technique, and dose constraints are discussed. Literature relevant to these cases is summarized to provide a framework for treatment of similar patients., Results: Treatment of brain metastases with SRS requires many considerations including optimal patient selection, fractionation selection, and plan optimization., Conclusions: Case-based practice guidelines developed by the Radiosurgery Society provide a practical guide to the common scenarios noted above affecting patients with metastatic brain tumors., (© 2023 Published by Elsevier Inc. on behalf of American Society for Radiation Oncology.)

Brain metastases are an increasing global public health concern, even as survival rates improve for patients with metastatic disease. Both metastases and the sequelae of their treatment are key determinants of the inter-related priorities of patient survival, function, and quality of life, mandating a multidimensional approach to clinical care and research. At a virtual National Cancer Institute Workshop in September, 2022, key stakeholders convened to define research priorities to address the crucial areas of unmet need for patients with brain metastases to achieve meaningful advances in patient outcomes. This Policy Review outlines existing knowledge gaps, collaborative opportunities, and specific recommendations regarding consensus priorities and future directions in brain metastases research. Achieving major advances in research will require enhanced coordination between the ongoing efforts of individual organisations and consortia. Importantly, the continual and active engagement of patients and patient advocates will be necessary to ensure that the directionality of all efforts reflects what is most meaningful in the context of patient care., Competing Interests: Declaration of interests TSA, DKS, PSS, JAH, MGE, JSB-S, PGP, CNC, and MMA are employees of the US National Institutes of Health. BME received consulting fees from Medicenna, MedQIA, Servier, Chimerix, Sumitomo Dainippon Pharma Oncology, ImmunoGenesis, Ellipses Pharma, Alpheus Medical, Curtana Pharma, Sagimet Biosciences, and Sapience Therapeutics; and other support from Siemens. SCF received grants from Siemens and Neosoma; consulting fees from Medicenna, MedQIA, Servier, Chimerix, Sumitomo Dainippon Pharma Oncology, ImmunoGenesis, Ellipses Pharma, Alpheus Medical, Curtana Pharma, Sagimet Biosciences, and Sapience Therapeutics; and other services from Siemens. AAA received grants from Varian and NH TheraAguix, and consulting fees from Novartis and Seagen. DMT received grants from Varian Medical Systems, Blue Earth Diagnostics, and NovoCure, and consulting fees from Boston Scientific. RK received grants from Medtronic, Blue Earth Diagnostics, NovoCure, GT Medical Technologies, AstraZeneca, Exelixis, Viewray, Brainlab, and Cantex Pharmaceuticals; consulting fees from Kazia Therapeutics, Elekta, Viewray, Castle Biosciences, and NovoCure; travel support from Elekta, Accuray, NovoCure, and Peerview Institute for Medical Education; other support from Elekta, Accuray, Novocure, and the Peerview Institute for Medical Education; and is on the Viewray Medical Advisory Board. CKA received grants from PUMA, Lilly, Merck, Seattle Genetics, Nektar, Tesaro, G1-Therapeutics, ZION, Novartis, Pfizer, AstraZeneca, Elucida, and Caris; licences from UpToDate and Jones and Bartlett; other support from Genentech, Eisai, IPSEN, Seattle Genetics, AstraZeneca, Novartis, Immunomedics, Elucida, and Athenex; and is on the Genentech board. PWS received consulting fees from Varian. JH-G has funding from the National Institutes of Health (NIH)/National Cancer Institute (NCI) and received payment for a lecture from Aptitude Health. DNY has a Robert Wood Johnson Foundation Medical Grant and Brockman Foundation Medical Grant. ICGO received grants from Bristol Myers Squibb, Merck, and Pfizer; and consulting fees from Bristol Myers Squibb, Array, Novartis, Sintetica, and Leal Therapeutics. AM received grants from Eisai/H3B Pharmaceutical, Takeda Millenium Pharm, Lilly, Pfizer, MTEM, Merck, Roche, Zion, Norvatis, Dantari, and Genentech; payment from Taiho; research support from Tempus and PUMA; and was on the boards for Seagen and Eli Lilly. EG received grants from Celgene, Denovo Biopharma, MedImmune, and Servier Pharmaceuticals; and is on the boards for Karyopharm Therapeutics, Kiyatec, and Boston Scientific. VG received grants from ImmunoChem Therapeutics. PKB received grants from Mirati, Eli Lilly, Kinnate, Merck, NIH, the Breast Cancer Research Foundation, Damon Runyon, AACR, the Terry and Jean de Gunzburg MGH Research Scholar Fund, and the Demetra fund; consulting fees from Axiom Healthcare, Pfizer, Dantari, Advice Connect inspire, ElevateBio, Sintetica, SK Life Sciences, Voyager Therapeutics, Kazia, MPM Capital, Medscape, Eli Lilly, and Tesaro; other payments from Medscape and Pfizer; other support from GSK, Genentech-Roche, Eli Lilly, AstraZeneca, Kazia, Merck, Mirati, and Pfizer; and was the Chair of Society of Annual Neuro-Oncology Meetings. LC has grants from CDC/Johns Hopkins, DSI, Hological, and Myriad; US patent US7734496B1; stock from UNH; and a leadership role at Touch4Life and MD HBEB. MPM received consulting fees from Kazia, Novocure, Zap, Xoft, Karyopharm, and Sapience; has stocks at Oncoceutics and Chimerix; and is on the boards for Mevion, Oncoceutics, and Xcision. MK received grants from AbbVie, Bristol Myers Squibb, Daiichi Sankyo, BioNTech, CNS pharmaceuticals, Immorna Therapeutics, Celldex Therapeutics, and Astellas; consulting fees from Novocure and George Clinical; miscellaneous payment from Jax Lab, GSK, Voyager Therapeutics, and Johnson and Johnson; and is on the board for Berg Pharmaceuticals. MSA received grants from Seagen, AstraZeneca, Bristol Myers Squibb, Bayer, Incyte, Pharmacyclics, Novocure, Mimivax, and Merck; consulting fees from Bayer, Novocure, Kiyatec, Insightec, GSK, Xoft, Nuvation, Cellulartity, SDP Oncology, Apollomics, Prelude, Janssen, Tocagen, Voyager Therapeutics, Viewray, Caris Lifesciences, Pyramid Biosciences, Anheart Therapeutics, Varian Medical Systems, Theraguix, and Menarini Ricerche; has stocks from Mimivax, Cytodyn, and Medlnnovate Advisors; and is on the boards for Cairn Therapeutics, Pyramid Biosciences, Modifi Biosciences, and Bugworks. MHG has grant number U54CA261717 from the NIH/NCI and received consulting fees from Midatech. JL has research funding from Bristol Myers Squibb. MMK has a grant (number R50CA276015) from the NIH/NCI and Blue Earth Diagnostics; and is on the boards for the NCCN CNS Cancers Guidelines Committee, International Journal of Radiation Oncology*Biology*Physics, Neuro-Oncology, and the External Advisory Board for Stanford U54 MetNet. JR received grants from Black Diamond Therapeutics, Blueprint Medicines, Hummingbird, Merck Sharp & Dohme, Vall d’Hebron Institute of Oncology/Cancer Core Europe, Yingli, AadiBioscience, Amgen, Bayer, Bicycle Therapeutics, BioAtla, BioMed Valley Discoveries, Cellestia, Curis, CytomX, Deciphera, ForeBio, GenMab, GlaxoSmithKline, Hummingbird, Hucthinson MediPharma, Ideaya, Kelun-Biotech, Linnaeus Therapeutics, Loxo Oncology, Merus, Mirati, Novartis, Nuvation, Pfizer, Roche Pharmaceuticals, Spectrum Pharmaceuticals, Symphogen, Taiho, Takeda-Millennium, and Tango Therapeutics; consulting fees from Alnylam Pharmaceuticals, Avoro Capital Advisors, Boxer Capital, the Chinese University of Hong Kong, Clarion Healthcare, Columbus Venture Partners, Cullgen, Debiopharm, Incyte, Macrogenics, Merus, Monte Rosa Therapeutics, Oncology One, Pfizer, Sardona Therapeutics, Tang Advisors, and the Vall d’Hebron Institute of Oncology/Ministero De Empleo Y Seguridad Social; travel support from European Society for Medical Oncology; is on boards for AadiBioscience, Ellipses Pharma, Envision Pharma Limited, Incyte, IONCTURA, Merus, and Monte Rosa Therapeutics; and is on the steering committee for the Vall d’Hebron Institute of Oncology/Ministero De Empleo Y Seguridad Social. AB received support from NIH grant number P30 CA008748, has four US patents, and is on the Evren Technologies Scientific Advisory Board. HT has grants from BMS Bristol Myers Squibb, Novartis, Merck, Genentech, Eisai, GSK, RAPT, and Dragonfly; and received consulting fees from BMS Bristol Myers Squibb, Novartis, Merck, Genentech, Eisai, Iovance, Pfizer, Karyopharm, Boxer Capital, Jazz Pharma, and Medicenna. All other authors declare no competing interests., (Copyright © 2023 Elsevier Ltd. All rights reserved.)

The NCCN Guidelines for Central Nervous System (CNS) Cancers focus on management of the following adult CNS cancers: glioma (WHO grade 1, WHO grade 2-3 oligodendroglioma [1p19q codeleted, IDH-mutant], WHO grade 2-4 IDH-mutant astrocytoma, WHO grade 4 glioblastoma), intracranial and spinal ependymomas, medulloblastoma, limited and extensive brain metastases, leptomeningeal metastases, non-AIDS-related primary CNS lymphomas, metastatic spine tumors, meningiomas, and primary spinal cord tumors. The information contained in the algorithms and principles of management sections in the NCCN Guidelines for CNS Cancers are designed to help clinicians navigate through the complex management of patients with CNS tumors. Several important principles guide surgical management and treatment with radiotherapy and systemic therapy for adults with brain tumors. The NCCN CNS Cancers Panel meets at least annually to review comments from reviewers within their institutions, examine relevant new data from publications and abstracts, and reevaluate and update their recommendations. These NCCN Guidelines Insights summarize the panel's most recent recommendations regarding molecular profiling of gliomas.

Advances in computational neuroimaging techniques have expanded the armamentarium of imaging tools available for clinical applications in clinical neuroscience. Non-invasive, in vivo brain MRI structural and functional network mapping has been used to identify therapeutic targets, define eloquent brain regions to preserve, and gain insight into pathological processes and treatments as well as prognostic biomarkers. These tools have the real potential to inform patient-specific treatment strategies. Nevertheless, a realistic appraisal of clinical utility is needed that balances the growing excitement and interest in the field with important limitations associated with these techniques. Quality of the raw data, minutiae of the processing methodology, and the statistical models applied can all impact on the results and their interpretation. A lack of standardization in data acquisition and processing has also resulted in issues with reproducibility. This limitation has had a direct impact on the reliability of these tools and ultimately, confidence in their clinical use. Advances in MRI technology and computational power as well as automation and standardization of processing methods, including machine learning approaches, may help address some of these issues and make these tools more reliable in clinical use. In this review, we will highlight the current clinical uses of MRI connectomics in the diagnosis and treatment of neurological disorders; balancing emerging applications and technologies with limitations of connectivity analytic approaches to present an encompassing and appropriate perspective., (Copyright © 2021 The Authors. Published by Elsevier Inc. All rights reserved.)

Abstract: Gliomas are the most common primary brain cancer, yet are extraordinarily challenging to treat because they can be aggressive and infiltrative, locally recurrent, and resistant to standard treatments. Furthermore, the treatments themselves, including radiation therapy, can affect patients' neurocognitive function and quality of life. Noninvasive imaging is the standard of care for primary brain tumors, including diagnosis, treatment planning, and monitoring for treatment response. This article explores the ways in which advanced imaging has and will continue to transform radiation treatment for patients with gliomas, with a focus on cognitive preservation and novel biomarkers, as well as precision radiotherapy and treatment adaptation. Advances in novel imaging techniques continue to push the field forward, to more precisely guided treatment planning, radiation dose escalation, measurement of therapeutic response, and understanding of radiation-associated injury., (Copyright © 2021 Wolters Kluwer Health, Inc. All rights reserved.)

Stereotactic radiosurgery (SRS) is used to treat cerebral arteriovenous malformations (AVMs). However, early evaluation of efficacy is difficult as structural magnetic resonance imaging (MRI)/magnetic resonance angiography (MRA) often does not demonstrate appreciable changes within the first 6 months. The aim of this study was to evaluate the use of four-dimensional (4D) flow MRI to quantify hemodynamic changes after SRS as early as 2 months. This was a retrospective observational study, which included 14 patients with both pre-SRS and post-SRS imaging obtained at multiple time points from 1 to 27 months after SRS. A 3T MRI Scanner was used to obtain T 2 single-shot fast spin echo, time-of-flight MRA, and postcontrast 4D flow with three-dimensional velocity encoding between 150 and 200 cm/s. Post-hoc two-dimensional cross-sectional flow was measured for the dominant feeding artery, the draining vein, and the corresponding contralateral artery as a control. Measurements were performed by two independent observers, and reproducibility was assessed. Wilcoxon signed-rank tests were used to compare differences in flow, circumference, and pulsatility between the feeding artery and the contralateral artery both before and after SRS; and differences in nidus size and flow and circumference of the feeding artery and draining vein before and after SRS. Arterial flow (L/min) decreased in the primary feeding artery (mean: 0.1 ± 0.07 vs. 0.3 ± 0.2; p < 0.05) and normalized in comparison to the contralateral artery (mean: 0.1 ± 0.07 vs. 0.1 ± 0.07; p = 0.068). Flow decreased in the draining vein (mean: 0.1 ± 0.2 vs. 0.2 ± 0.2; p < 0.05), and the circumference of the draining vein also decreased (mean: 16.1 ± 8.3 vs. 15.7 ± 6.7; p < 0.05). AVM volume decreased after SRS (mean: 45.3 ± 84.8 vs. 38.1 ± 78.7; p < 0.05). However, circumference (mm) of the primary feeding artery remained similar after SRS (mean: 15.7 ± 2.7 vs. 16.1 ± 3.1; p = 0.600). 4D flow may be able to demonstrate early hemodynamic changes in AVMs treated with radiosurgery, and these changes appear to be more pronounced and occur earlier than the structural changes on standard MRI/MRA. Level of Evidence: 4 Technical Efficacy Stage: 1., (© 2020 International Society for Magnetic Resonance in Medicine.)

Background: Radiation recall pneumonitis (RRP) is a poorly understood clinical syndrome in which patients develop radiation pneumonitis triggered by a systemic agent, often years after the completion of radiation therapy. Immune checkpoint blockade agents have only recently been posited as a trigger for RRP. Here, we present three cases of immunotherapy-induced RRP., Case Presentation: Our first patient was diagnosed with primary lung adenocarcinoma, and 4.5 years after completing radiation therapy developed symptomatic RRP immediately following a second dose of nivolumab-containing immunotherapy regimen. Our second patient was diagnosed with primary bladder cancer metastatic to the mediastinum, which was treated twice with radiation therapy. He developed RRP in the days following his second course of ipilimumab-pembrolizumab which was months after his second course of radiation that he received. Our final patient was diagnosed with metastatic small cell lung cancer and received local consolidative radiation therapy in addition to whole-brain radiation. He developed RRP on the 11 th day after concluding his 4 th cycle of nivolumab-ipilimumab, approximately 7 months after having had completed chest radiation therapy., Conclusions: Immunotherapy-induced RRP is a rare diagnosis which can present more focally than traditional immunotherapy pneumonitis and which must be clinically differentiated from other local processes such as pneumonia. Further research should explore the mechanisms underlying these radiation recall reactions as many patients receive radiation and immunotherapy during the course of their cancer treatment., Competing Interests: AS reports research funding and honoraria from Pfizer and Varian Medical Systems, and consultant fees from AstraZeneca and Merck. ABS is the scientific founder and has an equity interest in Toragen Inc. outside the submitted work. The terms of this arrangement have been reviewed and approved by the University of California, San Diego in accordance with its conflict of interest policies. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2021 Riviere, Sumner, Cornell, Sandhu, Murphy, Hattangadi-Gluth, Bruggeman, Kim, Randall and Sharabi.)

Purpose: The Open Payments transparency program publishes data on industry-physician payments, in part to discourage relationships considered inappropriate including gifts, meals, and speaker's bureau fees. We evaluated trends in physician-level payments to test whether implementation of Open Payments resulted in fewer industry-radiation oncologist (RO) interactions or shifted interactions toward those considered more appropriate compared with medical oncologists (MOs) and other hospital-based physicians (HBPs)., Methods and Materials: We performed a retrospective, population-based cohort study of practicing US ROs versus MOs and HBPs in 2014 matched to general (nonresearch) payments between 2014 and 2018. Trends in payments were analyzed and reported by nature of payment. Values of payments to ROs from the top 10 companies were identified., Results: From 2014 to 2018, 3379 (90.3%) ROs accepted 106,930 payments totaling $40.8 million. The per-physician number and value of payments was lower in radiation oncology than in medical oncology and higher than HBPs. The proportion of ROs accepting payments increased from 61.8% in 2014 to 64.2% in 2018; the proportion of MOs accepting payments decreased from 78.7% to 77.7%; and the proportion of HBPs decreased from 40.8% to 37.5%, respectively. The annual per-physician value and number of payments accepted by ROs and MOs increased. Payments in entertainment, meals, travel and lodging, and gifts increased among ROs and remained stable or decreased among MOs and HBPs. Consulting payments increased across all groups. Top RO payors produced novel cancer therapeutics, hydrogel spacers, radiation treatment machines, and opioids., Conclusions: Industry payments to ROs have become more common since OP's inception, while becoming less common for MOs and HBPs. Payments to ROs and MOs have become more frequent and of modestly increasing value compared with other HBPs, for whom the value is decreasing. No large changes in the nature of relationships were seen in ROs. Increased engagement with financial conflicts of interest is needed in radiation oncology., (Copyright © 2020 Elsevier Inc. All rights reserved.)

The NCCN Guidelines for Central Nervous System (CNS) Cancers focus on management of adult CNS cancers ranging from noninvasive and surgically curable pilocytic astrocytomas to metastatic brain disease. The involvement of an interdisciplinary team, including neurosurgeons, radiation therapists, oncologists, neurologists, and neuroradiologists, is a key factor in the appropriate management of CNS cancers. Integrated histopathologic and molecular characterization of brain tumors such as gliomas should be standard practice. This article describes NCCN Guidelines recommendations for WHO grade I, II, III, and IV gliomas. Treatment of brain metastases, the most common intracranial tumors in adults, is also described.

Objectives: The objectives of this systematic review were to (a) identify supportive-care (psychosocial/behavioral, pharmacological, complementary, or alternative) interventions that have been evaluated via randomized controlled trials (RCTs) to improve patient-reported health-related quality of life (HRQoL) among adults with brain tumors, (b) evaluate the quality of the intervention studies, and (c) evaluate if developed interventions have been efficacious at improving HRQoL, as compared with control conditions in RCTs., Methods: This systematic review was conducted using preferred reporting items for systematic reviews and meta-analyses (PRISMA) guidelines. Four databases were searched for RCTs of supportive-care interventions for adults with brain tumors, primary or metastatic, that included a patient-reported HRQoL outcome. Quality of the included studies was assessed using the Effective Public Health Practice Project Quality Assessment Tool for Quantitative Studies., Results: Ten RCTs involving 640 patients with either a primary or metastatic brain tumor investigating supportive-care interventions with a HRQoL outcome were identified. In terms of quality, three of the studies received a "strong" rating, three received a "moderate" rating, and four of the studies received a "weak" rating. Only two of the interventions (ie, a home-based psychosocial intervention and individualized acupuncture with standard rehabilitation) demonstrated improvements in HRQoL over control conditions., Conclusions: HRQoL is of the utmost importance when treating patients with brain tumors. Yet there is a notable paucity of research to inform clinical decisions and evidence-based practice. More high-quality studies of interventions aimed at improving HRQoL are needed., (© 2018 John Wiley & Sons, Ltd.)

Background and Purpose: Treatment with bevacizumab is standard of care for recurrent high-grade gliomas; however, monitoring response to treatment following bevacizumab remains a challenge. The purpose of this study was to determine whether quantifying the sharpness of the fluid-attenuated inversion recovery hyperintense border using a measure derived from texture analysis-edge contrast-improves the evaluation of response to bevacizumab in patients with high-grade gliomas., Materials and Methods: MRIs were evaluated in 33 patients with high-grade gliomas before and after the initiation of bevacizumab. Volumes of interest within the FLAIR hyperintense region were segmented. Edge contrast magnitude for each VOI was extracted using gradients of the 3D FLAIR images. Cox proportional hazards models were generated to determine the relationship between edge contrast and progression-free survival/overall survival using age and the extent of surgical resection as covariates., Results: After bevacizumab, lower edge contrast of the FLAIR hyperintense region was associated with poorer progression-free survival ( P = .009) and overall survival ( P = .022) among patients with high-grade gliomas. Kaplan-Meier curves revealed that edge contrast cutoff significantly stratified patients for both progression-free survival (log-rank χ 2 = 8.3, P = .003) and overall survival (log-rank χ 2 = 5.5, P = .019)., Conclusions: Texture analysis using edge contrast of the FLAIR hyperintense region may be an important predictive indicator in patients with high-grade gliomas following treatment with bevacizumab. Specifically, low FLAIR edge contrast may partially reflect areas of early tumor infiltration. This study adds to a growing body of literature proposing that quantifying features may be important for determining outcomes in patients with high-grade gliomas., (© 2018 by American Journal of Neuroradiology.)

Brain AVMs treated with stereotactic radiosurgery typically demonstrate a minimum latency period of 1-3 years between treatment and nidus obliteration. Assessment of treatment response is usually limited to evaluation of AVM nidus structural changes using conventional MR imaging and MRA techniques. This report describes the use of 4D Flow MRI to also measure radiation-induced hemodynamic changes in a Spetzler-Martin grade III AVM, which were detectable as early as 6 months after treatment., (© 2018 by American Journal of Neuroradiology.)

Before treatment delivery of respiratory-gated radiation therapy (RT) in patients with implanted fiducials, both the patient position and the gating window thresholds must be set. In linac-based RT, this is currently done manually and setup accuracy will therefore be dependent on the skill of the user. In this study, we present an automatic method for finding the patient position and the gating window thresholds. Our method uses sequentially acquired anterior-posterior (AP) and lateral fluoroscopic imaging with simultaneous breathing amplitude monitoring and intends to reach 100% gating accuracy while keeping the duty cycle as high as possible. We retrospectively compared clinically used setups to the automatic setups by our method in five pancreatic cancer patients treated with hypofractionated RT. In 15 investigated fractions, the average (±standard deviation) differences between the clinical and automatic setups were -0.4 ± 0.8 mm, -1.0 ± 1.1 mm, and 1.8 ± 1.3 mm in the left-right (LR), the AP, and the superior-inferior (SI) direction, respectively. For the clinical setups, typical interfractional setup variations were 1-2 mm in the LR and AP directions, and 2-3 mm in the SI direction. Using the automatic method, the duty cycle could be improved in six fractions, in four fractions the duty cycle had to be lowered to improve gating accuracy, and in five fractions both duty cycle and gating accuracy could be improved. Our automatic method has the potential to increase accuracy and decrease user dependence of setup for patients with implanted fiducials treated with respiratory-gated RT. After fluoroscopic image acquisition, the calculated patient shifts and gating window thresholds are calculated in 1-2 s. The method gives the user the possibility to evaluate the effect of different patient positions and gating window thresholds on gating accuracy and duty cycle. If deemed necessary, it can be used at any time during treatment delivery., (© 2018 The Authors. Journal of Applied Clinical Medical Physics published by Wiley Periodicals, Inc. on behalf of American Association of Physicists in Medicine.)

For many years, the diagnosis and classification of gliomas have been based on histology. Although studies including large populations of patients demonstrated the prognostic value of histologic phenotype, variability in outcomes within histologic groups limited the utility of this system. Nonetheless, histology was the only proven and widely accessible tool available at the time, thus it was used for clinical trial entry criteria, and therefore determined the recommended treatment options. Research to identify molecular changes that underlie glioma progression has led to the discovery of molecular features that have greater diagnostic and prognostic value than histology. Analyses of these molecular markers across populations from randomized clinical trials have shown that some of these markers are also predictive of response to specific types of treatment, which has prompted significant changes to the recommended treatment options for grade III (anaplastic) gliomas., (Copyright © 2017 by the National Comprehensive Cancer Network.)

Purpose: Single-isocenter, volumetric-modulated arc therapy (VMAT) stereotactic radiosurgery (SRS) for multiple brain metastases (multimets) can deliver highly conformal dose distributions and reduce overall patient treatment time compared to other techniques. However, treatment planning for multimet cases is highly complex due to variability in numbers and sizes of brain metastases, as well as their relative proximity to organs-at-risk (OARs). The purpose of this study was to automate the VMAT planning of multimet cases through a knowledge-based planning (KBP) approach that adapts single-target SRS dose predictions to multiple target predictions., Methods: Using a previously published artificial neural network (ANN) KBP system trained on single-target, linac-based SRS plans, 3D dose distribution predictions for multimet patients were obtained by treating each brain lesion as a solitary target and subsequently combining individual dose predictions into a single distribution. Spatial dose distributions di(r→) for each of the i = 1…N lesions were merged using the combination function d(r→)=∑iNdin(r→)1/n. The optimal value of n was determined by minimizing root-mean squared (RMS) difference between clinical multimet plans and predicted dose per unit length along the line profile joining each lesion in the clinical cohort. The gradient measure GM=[3/4π]1/3V50%1/3-V100%1/3 is the primary quality metric for SRS plan evaluation at our institution and served as the main comparative metric between clinical plans and the KBP results. A total of 41 previously treated multimet plans, with target numbers ranging from N = 2-10, were used to validate the ANN predictions and subsequent KBP auto-planning routine. Fully deliverable KBP plans were developed by converting predicted dose distribution into patient-specific optimization objectives for the clinical treatment planning system (TPS). Plan parity was maintained through identical arc configuration and target normalization. Overall plan quality improvements were quantified by calculating the difference between SRS quality metrics (QMs): ΔQM = QM clinical  - QM KBP . In addition to GM, investigated QMs were: volume of brain receiving ≥ 10 Gy (V 10 Gy ), volume of brain receiving ≥ 5 Gy (ΔV 5 Gy ), heterogeneity index (HI), dose to 0.1 cc of the brainstem (D 0.1 cc ), dose to 1% of the optic chiasm (D 1% ), and interlesion dose (D IL ). In addition to this quantitative analysis, overall plan quality was assessed via blinded plan comparison of the manual and KBP treatment plans by SRS-specializing physicians., Results: A dose combination factor of n = 8 yielded an integrated dose profile RMS difference of 2.9% across the 41-patient cohort. Multimet dose predictions exhibited ΔGM = 0.07 ± 0.10 cm against the clinical sample, implying either further normal tissue sparing was possible or that dose predictions were slightly overestimating achievable dose gradients. The latter is the more likely explanation, as this bias vanished when dose predictions were converted to deliverable KBP plans ΔGM = 0.00 ± 0.08 cm. Remaining QMs were nearly identical or showed modest improvements in the KBP sample. Equivalent QMs included: ΔV 10 Gy  = 0.37 ± 3.78 cc, ΔHI = 0.02 ± 0.08 and ΔD IL  = -2.22 ± 171.4 cGy. The KBP plans showed a greater degree of normal tissue sparing as indicated by brain ΔV 5 Gy  = 4.11± 24.05 cc, brainstem ΔD 0.1 cc  = 42.8 ± 121.4 cGy, and chiasm ΔD 1%  = 50.8 ± 83.0 cGy. In blinded review by SRS-specializing physicians, KBP-generated plans were deemed equivalent or superior in 32/41(78.1%) of the cases., Conclusion: Heuristic KBP-driven automated planning in linac-based, single-isocenter treatments for multiple brain metastases maintained or exceeded overall plan quality., (© 2017 American Association of Physicists in Medicine.)

Purpose: To examine characteristics of medical malpractice claims involving radiation oncologists closed during a 10-year period., Methods and Materials: Malpractice claims filed against radiation oncologists from 2003 to 2012 collected by a nationwide liability insurance trade association were analyzed. Outcomes included the nature of claims and indemnity payments, including associated presenting diagnoses, procedures, alleged medical errors, and injury severity. We compared the likelihood of a claim resulting in payment in relation to injury severity categories (death as referent) using binomial logistic regression., Results: There were 362 closed claims involving radiation oncology, 102 (28%) of which were paid, resulting in $38 million in indemnity payments. The most common alleged errors included "improper performance" (38% of closed claims, 18% were paid; 29% [$11 million] of total indemnity), "errors in diagnosis" (25% of closed claims, 46% were paid; 44% [$17 million] of total indemnity), and "no medical misadventure" (14% of closed claims, 8% were paid; less than 1% [$148,000] of total indemnity). Another physician was named in 32% of claims, and consent issues/breach of contract were cited in 18%. Claims for injury resulting in death represented 39% of closed claims and 25% of total indemnity. "Improper performance" was the primary alleged error associated with injury resulting in death. Compared with claims involving death, major temporary injury (odds ratio [OR] 2.8, 95% confidence interval [CI] 1.29-5.85, P=.009), significant permanent injury (OR 3.1, 95% CI 1.48-6.46, P=.003), and major permanent injury (OR 5.5, 95% CI 1.89-16.15, P=.002) had a higher likelihood of a claim resulting in indemnity payment., Conclusions: Improper performance was the most common alleged malpractice error. Claims involving significant or major injury were more likely to be paid than those involving death. Insights into the nature of liability claims against radiation oncologists may help direct efforts to improve quality of care and minimize the risk of being sued., (Copyright © 2017 Elsevier Inc. All rights reserved.)

Background and Purpose: ADC as a marker of tumor cellularity has been promising for evaluating the response to therapy in patients with glioblastoma but does not successfully stratify patients according to outcomes, especially in the upfront setting. Here we investigate whether restriction spectrum imaging, an advanced diffusion imaging model, performed after an operation but before radiation therapy, could improve risk stratification in patients with newly diagnosed glioblastoma relative to ADC., Materials and Methods: Pre-radiation therapy diffusion-weighted and structural imaging of 40 patients with glioblastoma were examined retrospectively. Restriction spectrum imaging and ADC-based hypercellularity volume fraction (restriction spectrum imaging-FLAIR volume fraction, restriction spectrum imaging-contrast-enhanced volume fraction, ADC-FLAIR volume fraction, ADC-contrast-enhanced volume fraction) and intensities (restriction spectrum imaging-FLAIR 90th percentile, restriction spectrum imaging-contrast-enhanced 90th percentile, ADC-FLAIR 10th percentile, ADC-contrast-enhanced 10th percentile) within the contrast-enhanced and FLAIR hyperintensity VOIs were calculated. The association of diffusion imaging metrics, contrast-enhanced volume, and FLAIR hyperintensity volume with progression-free survival and overall survival was evaluated by using Cox proportional hazards models., Results: Among the diffusion metrics, restriction spectrum imaging-FLAIR volume fraction was the strongest prognostic metric of progression-free survival ( P = .036) and overall survival ( P = .007) in a multivariate Cox proportional hazards analysis, with higher values indicating earlier progression and shorter survival. Restriction spectrum imaging-FLAIR 90th percentile was also associated with overall survival ( P = .043), with higher intensities, indicating shorter survival. None of the ADC metrics were associated with progression-free survival/overall survival. Contrast-enhanced volume exhibited a trend toward significance for overall survival ( P = .063)., Conclusions: Restriction spectrum imaging-derived cellularity in FLAIR hyperintensity regions may be a more robust prognostic marker than ADC and conventional imaging for early progression and poorer survival in patients with glioblastoma. However, future studies with larger samples are needed to explore its predictive ability., (© 2017 by American Journal of Neuroradiology.)

Background and Purpose: Brain radiotherapy is limited in part by damage to white matter, contributing to neurocognitive decline. We utilized diffusion tensor imaging (DTI) with multiple b-values (diffusion weightings) to model the dose-dependency and time course of radiation effects on white matter., Materials and Methods: Fifteen patients with high-grade gliomas treated with radiotherapy and chemotherapy underwent MRI with DTI prior to radiotherapy, and after months 1, 4-6, and 9-11. Diffusion tensors were calculated using three weightings (high, standard, and low b-values) and maps of fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity (λ ∥ ), and radial diffusivity (λ ⊥ ) were generated. The region of interest was all white matter., Results: MD, λ ∥ , and λ ⊥ increased significantly with time and dose, with corresponding decrease in FA. Greater changes were seen at lower b-values, except for FA. Time-dose interactions were highly significant at 4-6months and beyond (p<.001), and the difference in dose response between high and low b-values reached statistical significance at 9-11months for MD, λ ∥ , and λ ⊥ (p<.001, p<.001, p=.005 respectively) as well as at 4-6months for λ ∥ (p=.04)., Conclusions: We detected dose-dependent changes across all doses, even <10Gy. Greater changes were observed at low b-values, suggesting prominent extracellular changes possibly due to vascular permeability and neuroinflammation., (Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.)

Stereotactic body radiotherapy (SBRT) shows promise in unresectable pancreatic cancer, though this treatment modality has high rates of normal tissue toxicity. This study explores the dosimetric utility of daily adaptive re-planning with pancreas SBRT. We used a previously developed supercomputing online re-planning environment (SCORE) to re-plan 10 patients with pancreas SBRT. Tumor and normal tissue contours were deformed from treatment planning computed tomographies (CTs) and transferred to daily cone-beam CT (CBCT) scans before re-optimizing each daily treatment plan. We compared the intended radiation dose, the actual radiation dose, and the optimized radiation dose for the pancreas tumor planning target volume (PTV) and the duodenum. Treatment re-optimization improved coverage of the PTV and reduced dose to the duodenum. Within the PTV, the actual hot spot (volume receiving 110% of the prescription dose) decreased from 4.5% to 0.5% after daily adaptive re-planning. Within the duodenum, the volume receiving the prescription dose decreased from 0.9% to 0.3% after re-planning. It is noteworthy that variation in the amount of air within a patient׳s stomach substantially changed dose to the PTV. Adaptive re-planning with pancreas SBRT has the ability to improve dose to the tumor and decrease dose to the nearby duodenum, thereby reducing the risk of toxicity., (Copyright © 2015 American Association of Medical Dosimetrists. All rights reserved.)

The NCCN Clinical Practice Guidelines in Oncology (NCCN Guidelines) for Central Nervous System (CNS) Cancers provide interdisciplinary recommendations for managing adult CNS cancers. Primary and metastatic brain tumors are a heterogeneous group of neoplasms with varied outcomes and management strategies. These NCCN Guidelines Insights summarize the NCCN CNS Cancers Panel's discussion and highlight notable changes in the 2015 update. This article outlines the data and provides insight into panel decisions regarding adjuvant radiation and chemotherapy treatment options for high-risk newly diagnosed low-grade gliomas and glioblastomas. Additionally, it describes the panel's assessment of new data and the ongoing debate regarding the use of alternating electric field therapy for high-grade gliomas., (Copyright © 2015 by the National Comprehensive Cancer Network.)

Background: Proton therapy in pediatrics may improve the risk/benefit profile of radiotherapy at a greater upfront financial cost, but it may prove to be cost effective if chronic medical complications can be avoided. Tools to assist with decision making are needed to aid in selecting pediatric patients for protons, and cost-effectiveness models can provide an objective method for this., Methods: A Markov cohort-simulation model was developed to assess the expected costs and effectiveness for specific radiation doses to the hypothalamus with protons versus photons in pediatric patients. Costing data included cost of investment and the diagnosis and management of growth hormone deficiency. Longitudinal outcomes data were used to inform risk parameters for the model. With costs in 2012 US dollars and effectiveness measured in quality-adjusted life years, incremental cost-effectiveness ratios were used to measure outcomes., Results: Proton therapy was cost effective for some scenarios based on the difference in hypothalamic sparing. Although some scenarios were not cost effective, others were not only cost effective for proton therapy but also demonstrated that protons were cost saving compared with photons., Conclusions: The current results provide the first evidence-based guide for identifying children with brain tumors who may benefit the most from proton therapy with respect to endocrine dysfunction. Proton therapy may be more cost effective for scenarios in which radiation dose to the hypothalamus can be spared, but protons may not be cost effective when tumors are involving or directly adjacent to the hypothalamus if there is a high dose to this structure., (© 2015 American Cancer Society.)

Purpose: Current liver SBRT protocols rely on the calculation of "effective volume" without accounting for the biologic effect of fraction size to estimate the risk of liver toxicity, which subsequently defines tumor prescription doses. This study compared effective volume and liver toxicity predictions with and without correction for fraction size., Methods and Materials: The effective volume was determined for 18 liver SBRT plans with and without biologic normalization using the linear quadratic formula. Lyman-Kutcher-Burman normal tissue complication probability models estimated the risk of liver toxicity. Effective volumes and corresponding toxicity predictions were compared with and without biologic normalization., Results: Accounting for the biologic difference of larger fraction size reduced the effective volume in all treatment plans compared with the unadjusted effective volume (median effective volume 0.21 vs 0.32). The lower effective volume with biologic normalization substantially reduced the estimated risk of liver toxicity (average risk of toxicity 32% vs 4.5%)., Conclusions: This study demonstrates that accounting for the biologic effect of fraction size with effective volume significantly decreases predicted hepatic toxicity, which suggests that the risk of liver toxicity may be overestimated in clinical practice if biologic normalization is omitted. The effective volume toxicity model has proven safe in prospective clinical trials, though safe dose escalation with liver SBRT may be feasible.

The NCCN Guidelines for Central Nervous System Cancers provide multidisciplinary recommendations for the clinical management of patients with cancers of the central nervous system. These NCCN Guidelines Insights highlight recent updates regarding the management of metastatic brain tumors using radiation therapy. Use of stereotactic radiosurgery (SRS) is no longer limited to patients with 3 or fewer lesions, because data suggest that total disease burden, rather than number of lesions, is predictive of survival benefits associated with the technique. SRS is increasingly becoming an integral part of management of patients with controlled, low-volume brain metastases., (Copyright © 2014 by the National Comprehensive Cancer Network.)

Diffusion-weighted imaging (DWI) has been at the forefront of cancer imaging since the early 2000s. Before its application in clinical oncology, this powerful technique had already achieved widespread recognition due to its utility in the diagnosis of cerebral infarction. Following this initial success, the ability of DWI to detect inherent tissue contrast began to be exploited in the field of oncology. Although the initial oncologic applications for tumor detection and characterization, assessing treatment response, and predicting survival were primarily in the field of neurooncology, the scope of DWI has since broadened to include oncologic imaging of the prostate gland, breast, and liver. Despite its growing success and application, misconceptions about the underlying physical basis of the DWI signal exist among researchers and clinicians alike. In this review, we provide a detailed explanation of the biophysical basis of diffusion contrast, emphasizing the difference between hindered and restricted diffusion, and elucidating how diffusion parameters in tissue are derived from the measurements via the diffusion model. We describe one advanced DWI modeling technique, called restriction spectrum imaging (RSI). This technique offers a more direct in vivo measure of tumor cells, due to its ability to distinguish separable pools of water within tissue based on their intrinsic diffusion characteristics. Using RSI as an example, we then highlight the ability of advanced DWI techniques to address key clinical challenges in neurooncology, including improved tumor conspicuity, distinguishing actual response to therapy from pseudoresponse, and delineation of white matter tracts in regions of peritumoral edema. We also discuss how RSI, combined with new methods for correction of spatial distortions inherent in diffusion MRI scans, may enable more precise spatial targeting of lesions, with implications for radiation oncology and surgical planning. See all articles in this Cancer Research section, "Physics in Cancer Research.", (©2014 American Association for Cancer Research.)

Background: Black patients with metastatic colorectal cancer have inferior survival compared to white patients. The purpose of this study was to examine disparity in specialist consultation and multimodality treatment and the impact that treatment inequality has on survival., Methods: We identified 9935 non-Hispanic white and 1281 black patients with stage IV colorectal cancer aged 66 years and older from the Surveillance, Epidemiology, and End Results (SEER)-Medicare linked database. Logistic regression models identified race-based differences in consultation rates and subsequent treatment with surgery, chemotherapy, or radiation. Multivariable Cox regression models identified potential factors that explain race-based survival differences. All statistical tests were two-sided., Results: Black patients had lower rates of consultation with surgery, medical oncology, and radiation oncology. Among patients seen in consultation, black patients received less surgery directed at the primary tumor, liver- or lung-directed surgery, chemotherapy, and radiotherapy. Unadjusted survival analysis found a 15% higher chance of dying for black patients compared with white patients (hazard ratio [HR] = 1.15; 95% confidence interval (CI) = 1.08 to 1.22; P < .001). Adjustment for patient, tumor, and demographic variables marginally reduced the risk of death (HR = 1.08; 95% CI = 1.01 to 1.15; P = .03). After adjustment for differences in treatment, the increased risk of death for black patients disappeared., Conclusions: Our study shows racial disparity in specialist consultation as well as subsequent treatment with multimodality therapy for metastatic colorectal cancer, and it suggests that inferior survival for black patients may stem from this treatment disparity. Further research into the underlying causes of this inequality will improve access to treatment and survival in metastatic colorectal cancer.