Large Brain Tumors Research Articles

NEURO DEEP FUZZY GENETIC ALGORITHM APPROACH FOR CLASSIFICATION AND DETECTION OF BRAIN TUMOR FROM LARGE DATASETS

Brain tumors represent one of the most critical and life-threatening diseases. Early detection and accurate classification are essential for effective treatment planning and survival rate improvement. With the exponential growth of medical data, particularly in imaging and diagnostic datasets, traditional algorithms face limitations in handling large-scale, high-dimensional data efficiently. Conventional machine learning and diagnostic methods often struggle with classification accuracy, computational complexity, and overfitting in large, noisy datasets. Addressing these issues is crucial for the development of robust diagnostic tools capable of handling real-world clinical data. This paper presents a novel hybrid approach combining Neural Networks, Deep Learning, Fuzzy Logic, and Genetic Algorithms, termed Neuro Deep Fuzzy Genetic Algorithm (NDFGA), for the classification and detection of brain tumors from large datasets. Neural Networks and Deep Learning architectures are leveraged for feature extraction and hierarchical learning. Fuzzy Logic improves interpretability and manages uncertainty in medical data, while Genetic Algorithms optimize feature selection and model parameters. This hybrid method is designed to maximize classification accuracy while minimizing false positives and computational overhead. The proposed approach was tested on a large brain tumor dataset comprising over 10,000 MRI scans. The NDFGA approach demonstrated superior performance compared to standalone methods. It achieved a classification accuracy of 97.8%, a sensitivity of 96.5%, and a specificity of 98.1%. The model also showed improved robustness in handling large datasets, reducing false positives by 12% and computational time by 15% compared to traditional methods. This hybrid model presents a scalable and efficient solution for brain tumor detection, especially in clinical environments.

P08.04.B DOES PSYCHO-ONCOLOGICAL CARE AFFECT HEALTH-RELATED QUALITY OF LIFE AND PATIENT AND CAREGIVER SATISFACTION IN IDH WILD-TYPE GLIOMA? - A PROSPECTIVE STUDY

Abstract BACKGROUND Isocitrate dehydrogenase wild-type (IDHwt) gliomas are uncurable primary tumors of the brain and impose a high burden on affected patients and caregivers. In addition to neurological symptoms, changes in cognition and personality are common and should be diagnosed and treated early. About 75% of patients with brain tumors suffer from psychosocial distress at their first consultation. Health-related quality of life (HR-QoL) is significantly reduced by anxiety and negative mood, following glioma diagnosis. Brain tumor diagnosis also affects caregivers negatively. Recent publications show that caregiver and patient satisfaction influence each other, with caregivers generally being less satisfied than patients. In addition to specific tumor and symptomatic therapy, psycho-oncological care is an important element in a comprehensive treatment approach and may lead to increased HR-QoL and patient and caregiver satisfaction. However, there are few prospective datasets focusing on these aspects. MATERIAL AND METHODS We investigated the impact of psycho-oncological care on HR-QoL and patient and caregiver satisfaction in a large brain tumor center. Data from the regional brain tumor registry and electronic medical charts were used to compile the prospective patient cohort. Standardized questionnaires were used to investigate HR-QoL (EORTC QLQ C-30 and BN-20) and satisfaction (EORTC PATSAT-C33). Univariable and multiple linear regression analysis was applied to test the influence of psycho-oncological care on both aspects. RESULTS A homogenous cohort of 61 patients was investigated, of whom 29 (47.5%) received psycho-oncological care. We analyzed 141 EORTC QLQ-C30, 139 EORTC QLQ-BN20, 129 EORTC PATSAT-C33 questionnaires from patients, and 115 EORTC PATSAT-C33 questionnaires from caregivers. We show that patients who received at least one psycho-oncological consultation had significantly worse role functioning (p = 0.001) and a negatively influenced global health status (p = 0.038). Psycho-oncological care had no significant correlation with the satisfaction of patients. Caregivers of patients with psycho-oncological care documented inferior satisfaction with information exchange of doctors (p = 0.036). CONCLUSION We conclude that receiving psycho-oncological care is associated with changes in HR-QoL and patient and caregiver satisfaction. Utmost efforts should be made to integrate intensively and frequently psycho-oncological care on a daily-practice basis. It will be subject of future prospective studies to investigate kind and frequency of interventions that are suited to improve HR-QoL and treatment satisfaction in patients with IDHwt gliomas and their caregivers, and how to complement supportive therapies better to achieve optimal psychosocial outcomes for these patients and their caregivers.

Does the distance to the cancer center affect psycho-oncological care and emergency visits of patients with IDH wild-type gliomas? A retrospective study.

Malignant isocitrate dehydrogenase wild-type (IDHwt) gliomas impose a high symptomatic and psychological burden. Wide distances from patients' homes to cancer centers may affect the delivery of psycho-oncological care. Here, we investigated, in a large brain tumor center with a rural outreach, the initiation of psycho-oncological care depending on spatial distance and impact of psycho-oncological care on emergency visits. Electronic patient charts, the regional tumor registry, and interviews with the primary care physicians were used to investigate clinical data, psycho-oncological care, and emergency unit visits. Interrelations with socio-demographic, clinical, and treatment aspects were investigated using univariable and multivariable binary logistic regression analysis and the Pearson's Chi-square test. Of 491, 229 adult patients of this retrospective cohort fulfilled the inclusion criteria for analysis. During the last three months of their lives, 48.9% received at least one psycho-oncological consultation, and 37.1% visited the emergency unit at least once. The distance from the cancer center did neither affect the initiation of psycho-oncological care nor the rate of emergency unit visits. Receiving psycho-oncological care did not correlate with the frequency of emergency unit visits in the last three months of life. We conclude that the distance of IDHwt glioma patients' homes from their cancer center, even in a rural area, does not significantly influence the rate of psycho-oncological care.

Direct dosimetric comparison of linear accelerator vs. Gamma Knife fractionated stereotactic radiotherapy (fSRT) of large brain tumors.

The purpose of this study was to directly compare the plan quality of Gamma Knife (GK) (Elekta, Stockholm, Sweden)- vs linear accelerator (LINAC)-based delivery techniques for fractionated stereotactic radiotherapy (fSRT) of large brain metastases. Eighteen patients with clinical target volumes (CTVs) larger than 9.5 cc were selected to generate comparative plans for the prescription dose of 9 Gy × 3 fractions, utilizing the Eclipse (Varian, Palo Alto, US) vs Leksell GammaPlan (LGP) (Elekta, Stockholm, Sweden) treatment planning systems (TPS). Each GK plan was first developed using LGP's automatic planning, followed by manual adjustments/refinements. The same MRI and structures, including CTVs and organs at risk, were then DICOM-transferred to the Eclipse TPS. Volumetric Modulated Arc Therapy (VMAT) and Dynamic Conformal Arc (DCA) plans for a Truebeam, with high-definition multi-leaf collimators (MLCs), were developed on these MR images and structures using a single isocenter and 3 non-coplanar arcs. No planning target volume (PTV) margins were added, and no heterogeneity correction was used for either TPS. GK plans were prescribed to the 50% isodose line, and Eclipse VMAT and DCA plans allowed a maximum dose up to 170% and ∼125%, respectively. Gradient index (GI), Paddick Conformity Index (PCI), V20GyRind, and V4GyRind of all 3 techniques were calculated and compared. One-way analysis of variance (ANOVA) was performed to determine the statistical significance of the differences of these planning indices for the 3 planning techniques. A total of eighteen treatment targets were analyzed. Median CTV volume was 14.4 cc (range 9.5 cc - 55.9 cc). Mean ± standard deviation of PCI were 0.85 ± 0.03, 0.90 ± 0.03, and 0.72 ± 0.11 for GK, VMAT and DCA plans, respectively. They were respectively 2.64 ± 0.17, 2.46 ± 0.18, and 2.83 ± 0.48 for GI; 15.33 ± 8.45 cc, 10.47 ± 4.32 cc and 23.51 ± 16 cc for V20GyRind; and 316.28 ± 138.35 cc, 317.81 ± 108.21 cc, and 394.85 ± 142.16 cc for V4GyRind. The differences were statistically significant with p < 0.01 for all indices, except for V4GyRind (p > 0.129). In conclusion, a direct dosimetric comparison using the same MRI scan and contours was performed to evaluate the plan quality of various fSRT delivery techniques for CTV > 9.5 cc. LINAC VMAT plans provided the best dosimetric outcome in regard to PCI, GI, and V20GyRind. GK outcomes were similar to LINAC VMAT plans while LINAC DCA outcomes were significantly worse. Even though GK has a smaller physical penumbra, LINAC VMAT outperformed GK in this study due to enhanced penumbra sharpening and better beam optimization.

SURG-29. CAN NEOADJUVANT CHEMOTHERAPY INCREASE EXTENT OF RESECTION IN DIFFUSE LOWER-GRADE GLIOMA?

Abstract INTRODUCTION Maximal safe surgical resection remains front-line treatment for diffuse lower-grade gliomas (DLGGs). Greater extent of resection (EOR) can delay transformation, control seizures, and improve survival. EOR is limited by the infiltrative nature of DLGGs and eloquent brain location preponderance. We investigated the role of neoadjuvant chemotherapy in tumour volume reduction (TVR) for cases in which a meaningful EOR was deemed unachievable. METHODS Retrospective review (2000-2020) of patients in a large tertiary UK brain tumor centre who serendipitously underwent management that did or could mimic a neoadjuvant chemotherapy pathway. Inclusion criteria: &amp;gt;18 years at diagnosis; histologically-proven WHO grade 2 supratentorial glioma; received chemotherapy alone after biopsy then +/- debulking. Tumour volume delta +/- EOR were calculated on serial MRI T2/FLAIR sequences using a semi-automated quantitative analysis tool (Smartbrush, BrainLab® AG). RESULTS Group 1 (neoadjuvant chemotherapy and then surgery, n=4): debulking was considered unachievable initially but then possible post-chemotherapy. Median TVR post-chemotherapy was 16.90% (range 0.45–64.90%). Mean EOR was 68.67% (33.72–100%). Median overall survival (OS) and progression free survival (PFS) were 85 (18–154) and 62 (13–153) months, respectively. Group 2 (biopsy followed by chemotherapy alone, n=7): debulking was considered unachievable initially. Median TVR post-chemotherapy was 25.68% (-294.95–46.02%, one patient progressed during chemotherapy). Median OS and PFS were 92 (6–135) and 27 (3–80) months, respectively. On re-review, and based on Group 1 results, some Group 2 patients may have been able to undergo debulking with meaningful EOR post-chemotherapy. CONCLUSIONS Chemotherapy can have a significant impact on reducing tumour volumes, such that cases initially deemed unsuitable for debulking may be converted into those in which a meaningful EOR can be achieved. Larger, multicentre, retrospective studies, and prospective trials are needed to determine the role of chemotherapy as a neoadjuvant tool in the management of DLGGs.

Numerical and experimental evaluation of ultrasound-assisted convection enhanced delivery to transfer drugs into brain tumors

Central Nervous System (CNS) malignant tumors are a leading cause of death worldwide with a high mortality rate. While numerous strategies have been proposed to treat CNS tumors, the treatment efficacy is still low mainly due to the existence of the Blood–Brain Barrier (BBB). BBB is a natural cellular layer between the circulatory system and brain extracellular fluid, limiting the transfer of drug particles and confining the routine treatment strategies in which drugs are released in the blood. Consequently, direct drug delivery methods have been devised to bypass the BBB. However, the efficiency of these methods is not enough to treat deep and large brain tumors. In the study at hand, the effect of focused ultrasound (FUS) waves on enhancing drug delivery to brain tumors, through ultrasound-assisted convection-enhanced delivery (UCED), has been investigated. First, brain mimicking gels were synthesized to mimic the CNS microenvironment, and the drug solution was injected into them. Second, FUS waves with the resonance frequency of 1.1 MHz were applied to the drug injected zone. Next, a finite element (FE) model was developed to evaluate the pre-existing equation in the literature for describing the drug delivery via acoustic streaming in brain tissue. Experimental results showed that the FUS transducer was able to enhance the drug volume distribution up to 500% relative to convection-enhanced delivery alone (CED). Numerical analysis showed that the FE model could replicate the experimental penetration depths with a mean difference value of less than 21%, and acoustic streaming plays a significant role in UCED. Therefore, the results of this study could open a new way to develop FE models of the brain to better evaluate the UCED and reduce the costs of conducting clinical and animal studies.

Analysis and Comparison of Treatment Planning Software for Normal Tissue Dose for Large and Small brain Tumors Treated with a Non-Invasive Stereotactic Radiosurgery Instrument

<h3>Purpose/Objective(s)</h3> Patients with metastatic brain tumors may be treated with a stereotactic radiosurgery (SRS) platform or a linear accelerator (LINAC)-based platform. Recently, Leksell GammaPlan (LGP) received an update that made an optimization algorithm. Our objective was to review and compare older, completed plans with the newer "optimized" plans to establish if there were improvements on plan parameters, namely, Gradient Index (GI), Selectivity Index (SI), and Paddick Conformity Index (PCI). <h3>Materials/Methods</h3> We reviewed our institutional database in order to identify and gather patients with brain metastases treated by SRS. We chose patients with varying lesion sizes to see if there were any significant differences in how the optimization algorithm would treat large lesions (>5 cc), what we defined as very small (<2 cc), small (2-3 cc) and medium-sized lesions (3-4 cc). All lesions were originally treated with a 900 cGy x3 fractionation scheme. Optimization within the LGP software was performed on these plans while maintaining at least 99.51% coverage of the lesion volume as well as normalizing each plan to prescribe to the 50% isodose line in order to preserve the integrity of the original SRS plans. Because PCI is SI * coverage, and coverage was considered to be unity, only values of SI were directly observed. <h3>Results</h3> The cohorts had improvements overall in both GI and SI. 30 patients with metastases were identified that were treated using SRS. 15 of which had large lesions, 5 of which had medium-sized lesions, 5 of which had small lesions, and 5 of which had very small lesions. The GI improved for the very small on average by 0.492 (14.88%), for the small on average by 0.482 (16.27%), for the medium on average by 0.37 (12.66%), and for the large by 0.176 (6.63%). The SI improved for the very small on average by 0.144 (25.71%), for the small on average by 0.096 (12.83%), for the medium on average by 0.132 (22.92%). For the large tumors, SI on average lowered by 0.017 (2.05%). It is important to note that SI for only large tumors has appeared to marginally decrease. <h3>Conclusion</h3> From the advent of the new LGP optimization algorithm, utilizing this new update may be associated with improvement in dose falloff and local control of the tumor volume. Our data suggests that for lesions of all sizes, the optimization significantly improves all parameters in question for Gamma Knife treatment planning.

Volume prediction for large brain metastases after hypofractionated gamma knife radiosurgery through artificial neural network.

The effectiveness of single-session gamma knife radiosurgery (GKRS) for small metastatic brain tumors has been proven, but hypofractionated GKRS (hfGKRS) for large brain metastases (BM) from the linear quadratic (LQ) model is uncertain. The purpose of this study was to investigate volume changes large BM after hfGKRS from the LQ model and predict volume changes using artificial neural network (ANN). We retrospectively investigated the clinical findings of 28 patients who underwent hfGKRS with large BM (diameter >3 cm or volume >10 cc). A total of 44 tumors were extracted from 28 patients with features. We randomly divided 30 large brain tumors as training set and 14 large brain tumors as test set. To predict the volume changes after hfGKRS, we used ANN models (single-layer perceptron (SLP) and multi-layer perceptron (MLP)). The volume reduction was 96% after hfGKRS for large BM from the LQ model. ANN model predicted volume changes with 70% and 80% accuracy for SLP and MLP, respectively. Even in large BM, hfGKRS from the LQ model could be a good treatment option. Additionally, the MLP model could predict volume changes with 80% accuracy after hfGKRS for large BM.

Dissecting the roles of the Tuberin protein in the subcellular localization of the G2/M Cyclin, Cyclin B1.

Tuberin is a major component of the protein regulatory complex known as the Tuberous Sclerosis Complex and plays a crucial role in cell cycle progression and protein synthesis. Mutations in the Tuberin gene, TSC2, lead to the formation of benign tumors in many organ systems and causes the Tuberous Sclerosis Complex disorder. Genotypes ranging from point mutations to large deletions in the TSC2 gene have been clinically characterized with a wide range of phenotypes from skin tumors to large brain tumors. Our lab has previously demonstrated that Tuberin can directly bind and regulate the timing of nuclear transport of the G2/M cyclin, Cyclin B1. Herein we study the consequence of one clinically relevant truncation in the Tuberin protein on cell cycle function. We demonstrate that exogenous expression of a fragment of the N-term region of Tuberin alters the subcellular localization of Cyclin B1 and increases cell proliferation. This adds to our body of information about the residues within Tuberin responsible for regulating the cytoplasmic retention of Cyclin B1 and supports the phenotypic data seen in the clinic with Tuberous Sclerosis Complex patients harbouring similar large deletions in Tuberin.

Artificial intelligence in the radiomic analysis of glioblastomas: A review, taxonomy, and perspective.

Radiological imaging techniques, including magnetic resonance imaging (MRI) and positron emission tomography (PET), are the standard-of-care non-invasive diagnostic approaches widely applied in neuro-oncology. Unfortunately, accurate interpretation of radiological imaging data is constantly challenged by the indistinguishable radiological image features shared by different pathological changes associated with tumor progression and/or various therapeutic interventions. In recent years, machine learning (ML)-based artificial intelligence (AI) technology has been widely applied in medical image processing and bioinformatics due to its advantages in implicit image feature extraction and integrative data analysis. Despite its recent rapid development, ML technology still faces many hurdles for its broader applications in neuro-oncological radiomic analysis, such as lack of large accessible standardized real patient radiomic brain tumor data of all kinds and reliable predictions on tumor response upon various treatments. Therefore, understanding ML-based AI technologies is critically important to help us address the skyrocketing demands of neuro-oncology clinical deployments. Here, we provide an overview on the latest advancements in ML techniques for brain tumor radiomic analysis, emphasizing proprietary and public dataset preparation and state-of-the-art ML models for brain tumor diagnosis, classifications (e.g., primary and secondary tumors), discriminations between treatment effects (pseudoprogression, radiation necrosis) and true progression, survival prediction, inflammation, and identification of brain tumor biomarkers. We also compare the key features of ML models in the realm of neuroradiology with ML models employed in other medical imaging fields and discuss open research challenges and directions for future work in this nascent precision medicine area.

Weakly Supervised Skull Stripping of Magnetic Resonance Imaging of Brain Tumor Patients.

Automatic brain tumor segmentation is particularly challenging on magnetic resonance imaging (MRI) with marked pathologies, such as brain tumors, which usually cause large displacement, abnormal appearance, and deformation of brain tissue. Despite an abundance of previous literature on learning-based methodologies for MRI segmentation, few works have focused on tackling MRI skull stripping of brain tumor patient data. This gap in literature can be associated with the lack of publicly available data (due to concerns about patient identification) and the labor-intensive nature of generating ground truth labels for model training. In this retrospective study, we assessed the performance of Dense-Vnet in skull stripping brain tumor patient MRI trained on our large multi-institutional brain tumor patient dataset. Our data included pretreatment MRI of 668 patients from our in-house institutional review board-approved multi-institutional brain tumor repository. Because of the absence of ground truth, we used imperfect automatically generated training labels using SPM12 software. We trained the network using common MRI sequences in oncology: T1-weighted with gadolinium contrast, T2-weighted fluid-attenuated inversion recovery, or both. We measured model performance against 30 independent brain tumor test cases with available manual brain masks. All images were harmonized for voxel spacing and volumetric dimensions before model training. Model training was performed using the modularly structured deep learning platform NiftyNet that is tailored toward simplifying medical image analysis. Our proposed approach showed the success of a weakly supervised deep learning approach in MRI brain extraction even in the presence of pathology. Our best model achieved an average Dice score, sensitivity, and specificity of, respectively, 94.5, 96.4, and 98.5% on the multi-institutional independent brain tumor test set. To further contextualize our results within existing literature on healthy brain segmentation, we tested the model against healthy subjects from the benchmark LBPA40 dataset. For this dataset, the model achieved an average Dice score, sensitivity, and specificity of 96.2, 96.6, and 99.2%, which are, although comparable to other publications, slightly lower than the performance of models trained on healthy patients. We associate this drop in performance with the use of brain tumor data for model training and its influence on brain appearance.

Embryonal tumor with multilayered rosettes; rare pediatric CNS tumor. A case report and review of literature

Embryonal tumor with multilayered rosettes (ETMR), C19MC-altered is a newly designated entity of the embryonal tumors of the central nervous system (CNS) according to the 2016 WHO classification system of CNS. Characteristically, these tumors are newly defined based on their specific molecular genetic amplification in chromosome 19q13.42 found at locus C19MC. To the best of our knowledge, we present the first reported case of ETMR in Saudi Arabian pediatric population. A 2-year-old boy presented to the hospital with generalized tonic-colonic seizure, vomiting, irritability, and inability to walk. Computed tomography (CT) scan showed a large left thalamic supratentorial brain tumor. The tumor measured 6.1 × 5.6 × 5.6 cm and was characterized by cystic changes, prominent vasculature, and calcifications. Histopathology, immunohistochemistry examination, and fluorescence in situ hybridization (FISH) analysis confirmed the diagnosis of ETMR. In addition to reporting this rare case, we provide a brief literature review, treatment options, patient outcome, and disease prognosis.

A New Benchmark of the Sharpest Dose Fall-Off for Hypo-Fractionated Radiosurgery of Large Single Target Brain Lesions

Previous studies have characterized dose gradient patterns for various hypo-fractionated brain radiosurgery (hSRS) treatment platforms. The Gamma Knife Icon (GKI) has consistently exhibited either superior or non-inferior peripheral dose fall-off and normal brain sparing characteristics when compared to other Linac-based hSRS treatment platforms. Given the prevalence of Linac-based treatments, identifying planning techniques to optimize treatment parameters is desirable. In this study, we investigated a novel Linac-based treatment approach that aimed to create the sharpest dose fall-off for hSRS of large brain lesions.A cohort of patient cases (n = 10) with single brain lesions (volume 27.6+/-8.1 mL, range 20.-42.1 mL) treated with GKI at our institution were selected as sample test cases for our study. A non-coplanar unconstrained VMAT (NCU-VMAT) treatment planning approach was developed, and its script was implemented on a commercial treatment planning system for clinical Linac treatment equipped with the latest high-definition multi-leaf collimators (MLCs). Treatment plans produced via the NCU-VMAT approach were then compared against further optimized treatment plans from GKI, as well as conventional coplanar and non-coplanar VMAT treatment planning approaches. The comparison was carried out using DVH-derived parameters including target volume coverage, target dose conformity, modified dose fall-off index defined as the volume of 50% prescribed target dose divided by the target volume (PIV50).For each case studied, NCU-VMAT achieved practically identical target coverage (0.98 ± 0.01) and Paddick dose conformity index (0.87 ± 0.02) compared to optimized GKI treatments. The mean PIV50 values were 2.99 ± 0.14, 3.77 ± 0.22, and 3.36 ± 0.19 for optimized GKI, conventional coplanar, and non-coplanar VMAT treatment plans, respectively. These results were in excellent agreement with previously published studies. However, the NCU-VMAT technique yielded a mean PIV50 of 2.41 ± 0.07. This represents an improvement of approximately 40% (P < 0.001, paired two-tailed Student t-test) over all existing approaches including GKI. Further analyses revealed that PIV50 of NCU-VMAT approached the theoretical minimum for all the studied cases.Our results demonstrate that in treatment of large brain tumors, a treatment planning approach using Bremsstrahlung x-ray based Linacs can achieve superior dose fall-off for intracranial hSRS compared to GKI. We dispel the myth that physical characteristics of Cobalt γ-rays are needed to create the sharpest dose fall-off. Given the prevalence of Linac-based treatments compared to GKI, we present a novel optimized planning technique that achieves a new benchmark of sharpest dose fall-off.T. Nano: None. O. Morin: None. B.P. Ziemer: None. D. Raleigh: None. L. Boreta: None. J.L. Nakamura: None. S.E. Fogh: Independent Contractor; Accuray. P.K. Sneed: None. S. Hervey-Jumper: None. P.V. Theodosopoulos: None. S.E. Braunstein: Advisory Board; Radiation Oncology Questions, LLC.L. Ma: Patent/License Fees/Copyright; University of California Regents.

Visual Outcomes in Surgically Treated Intracranial Meningiomas.

Intracranial meningiomas that arise from the medial sphenoid ridge, anterior clinoid process, tuberculum sellae, or planum sphenoidale often impair vision by compressing the optic nerves and optic chiasm. Although many studies have reported visual outcome following surgery for these tumors, documentation has often been incomplete and not validated by patient self-report. Retrospective study of 40 patients drawn from a single, academic, medical center. We used a unique method of assessing visual outcome based on whether the change in visual function affected the preoperatively better-sighted or worse-sighted eye in the belief that this method would correlate with effects on activities of daily living (ADL). To elicit patient self-reports of those effects, we conducted telephone interviews of 25 patients with a standard questionnaire. We also assessed putative ophthalmic, imaging, and surgical predictors of visual outcome. Visual improvement occurred in 61% of patients with preoperative monocular visual dysfunction, but only 22% of patients reported improvement in their ability to conduct ADL, and 17% lost vision. Visual outcomes were better in patients with preoperative binocular visual dysfunction, where visual improvement occurred in 73% and no patient lost vision in the preoperatively better-sighted eye. However, only 27% of patients with preoperative binocular visual dysfunction reported improvement in their ability to conduct ADL. Long duration of vision impairment, presence of optic disc pallor, large tumor size, and imaging-based preoperative optic canal involvement did not preclude a favorable visual outcome. Aggressive surgical reduction in displacement of the optic nerves was not necessary to obtain a favorable visual outcome and sometimes led to an unfavorable visual outcome. In this study, surgery often improved vision, especially in patients with preoperative binocular visual dysfunction. But patients indicated that the effect on their ability to perform ADL was more modest. Moreover, 17% of patients with preoperative monocular visual dysfunction lost vision in the only affected eye, often to a considerable degree. In those patients, surgery would be justified primarily to relieve the concern of having a large brain tumor and to prevent tumor growth. Preoperative ophthalmic and imaging features poorly predicted visual outcomes. Favorable visual outcomes occurred without aggressive surgical debulking of the tumors.

Underreporting of Vestibular Schwannoma Incidence Within National Brain Tumor and Cancer Registries in the United States.

Reports using large brain tumor and cancer registries suggest that the incidence of vestibular schwannoma is considerably lower in the United States compared with other countries. The current study compares the incidence and disease characteristics of vestibular schwannoma within a large tertiary referral center's brain tumor and cancer registry using nationally mandated reporting protocols to disease incidence in the same population using an externally validated population-based consortium. Population-based study spanning 1,945,007 person-years. Large tertiary referral center. Adults with sporadic vestibular schwannoma. Disease incidence rates from 2004 to 2016. From 2004 to 2016, the incidence of vestibular schwannoma in the tumor registry was 1.3 per 100,000 person-years whereas the population-based cohort had an incidence of 4.4 per 100,000 person-years. From 2012 to 2016, the incidence in the tumor registry was 1.4 per 100,000 person-years compared with 5.2 in the population-based cohort. Patients within the population-based cohort were significantly more likely to have smaller tumors at diagnosis (78% intracanalicular versus 45%; p = 0.004) and consequently more likely to undergo management consisting of observation with serial imaging as opposed to treatment with either microsurgery or radiosurgery (71% versus 28%; p = 0.001). The reliance on pathology specimens and cancer-related treatment data for the national registration of new cancer and brain tumor diagnoses may introduce selection bias and underreporting of benign brain tumors that frequently involve observation as a primary treatment modality. This selection bias likely accounts for the discrepant incidence rates of vestibular schwannoma reported between the United States and other countries.

Hypofractionated frameless gamma knife radiosurgery for large metastatic brain tumors.

Hypofractionated stereotactic radiosurgery has become an alternative for metastatic brain tumors (METs). We aimed to analyze the efficacy and safety of frameless hypofractionated Gamma Knife radiosurgery (hfGKRS) in the management of unresected, large METs. All patients who were managed with hfGKRS for unresected, large METs (> 4 cm3) between June 2017 and June 2020 at a single center were reviewed in this retrospective study. Local control (LC), progression-free survival (PFS), overall survival (OS), and toxicities were investigated. A total of 58 patients and 76 METs with regular follow-up were analyzed. LC rate was 98.5% at six months, 96.0% at one year, and 90.6% at 2 years during a median follow-up of 12 months (range, 2-37). The log-rank test indicated no difference in the distribution of LC for any clinical or treatment variable. PFS was 86.7% at 6 months, 66.6% at 1 year, and 58.5% at 2 years. OS was 81% at 6 months, 63.6% at one year, and 50.7% at 2 years. On the log-rank test, clinical parameters such as control status of primary cancer, presence of extracranial metastases, RTOG-RPA class, GPA group, and ds-GPA group were significantly associated with PFS and OS. Patients presented with grade 1 (19.0%), grade 2 (3.5%) and grade 3 (5.2%) side effects. Radiation necrosis was not observed in any patients. Our current results suggest that frameless hfGKRS for unresected, large METs is a rational alternative in selected patients with promising results.

Redistributing Central Target Dose Hot Spots for Hypofractionated Radiosurgery of Large Brain Tumors: A Proof-of-Principle Study.

The present proof-of-principle study investigated radiobiological effects of redistributing central target dose hot spots across different treatment fractions during hypofractionated stereotactic radiosurgery (HSRS) of large intracranial tumors. Redistribution of central target dose hot spots during HSRS was simulated, and its effects were evaluated in eight cases of brain metastases. To assess dose variations in the target across N number of treatment fractions, a generalized biologically effective dose (gBED) was formulated. The gBED enhancement ratio was defined as the ratio of gBED in the tested treatment plan (with central target dose hot spot redistributions across fractions) to gBED in the conventional treatment plan (without central target dose hot spot redistributions). At a median αvalue of 0.3/Gy, the tested treatment plans resulted in average gBED increases of 15.6±3.5% and 8.3±1.8% for α/β ratios of 2 and 10Gy, respectively. In comparison with conventional treatment plans, the differences in the Paddick conformity index and gradient index did not exceed 2%. Redistributing central target dose hot spots across different treatment fractions during HSRS may be considered promising for enhancing gBED in the target. It may be beneficial for management of large intracranial neoplasms; thus, it warrants further clinical testing.

Changes In The Size Of Large Metastatic Brain Tumors During Fractionated Stereotactic Radiotherapy

Changes In The Size Of Large Metastatic Brain Tumors During Fractionated Stereotactic Radiotherapy

Abstract A09: Cerebrospinal fluid (CSF) as a source of ctDNA for diagnosis and monitoring of pediatric patients with midline diffuse gliomas

Abstract Background: Midline diffuse gliomas are aggressive pediatric tumors, characterized molecularly by the presence of H3K27 mutation. These tumors are extremely malignant, with median overall survival of less than a year. Localized mainly in the pons or thalamic regions, they are not amenable to a gross total resection; however, a biopsy is needed for pathologic and molecular diagnosis. In this scenario, liquid biopsy is of utmost importance and has the potential to spare the risk of morbidity with surgical procedures, determine diagnosis and prognosis, as well as serve as a tool to identify potential targetable alterations. The objective of this pilot feasibility study is to explore the use of CSF ctDNA using ddPCR and next-generation sequencing tools to diagnose and monitor patients with midline diffuse gliomas. Methods: We extracted CSF ct DNA collected from external ventricular drain in two patients diagnosed with midline diffuse glioma (one thalamic glioblastoma, one DIPG). ctDNA was extracted from 2 mL of CSF, quantification was done by quibit, and samples were processed first with ddPCR for detection of H3K27M point mutation followed by comprehensive profiling by whole-exome sequencing using Illumina HiSeq2500 sequencer. We assessed the feasibility of identifying diagnostic point mutations, as well as potential evolution of the tumor molecular landscape at disease progression. Results: The first case, a thalamic GBM, had tissue available for molecular analysis; targeted RNA sequencing was performed on a clinical basis detecting H3K27M mutation (VAF=43%) and a PDGFRA N659K mutation (VAF=43%). ddPCR analysis of the CSF ctDNA identified the H3K27M mutation with VAF of 14%. Whole-exome sequencing (WES) confirmed the presence of H3K27M point mutation at VAF 11% and PDGFRA mutation at VAF 13%. This patient received radiation and chemotherapy but progressed rapidly and passed 7 months after the diagnosis. The second case, a DIPG diagnosed upon radiologicl and clinical criteria, was previously treated with conventional focal radiation and needed an EVD upon massive leptomeningeal progression with associated meningitis. CSF was then processed for ctDNA analysis. ddPCR confirmed the presence of H3K27M mutation with VAF of 48%. WES confirmed the presence of H3K27M mutation (VAF 14%) and additional TP53 R273C point mutation with VAF of 87%. This patient passed roughly 11 months post diagnosis. Conclusion: We have demonstrated the feasibility of detection of molecular markers in CSF through ddPCR and NGS platform to not only to assist in diagnosis of pediatric midline diffuse gliomas, but also to monitor these patients for additional/new molecular events that may be targetable. Building on these results, we are currently implementing a targeted sequencing panel to establish the specificity of this method in a large pediatric brain tumor cohort. Citation Format: Liana Nobre, Robert Siddaway, Monique Johnson, Scott Ryall, Michal Zapotocky, Julie Bennet, Uri Tabori, Cynthia Hawkins. Cerebrospinal fluid (CSF) as a source of ctDNA for diagnosis and monitoring of pediatric patients with midline diffuse gliomas [abstract]. In: Proceedings of the AACR Special Conference on Advances in Liquid Biopsies; Jan 13-16, 2020; Miami, FL. Philadelphia (PA): AACR; Clin Cancer Res 2020;26(11_Suppl):Abstract nr A09.

Two-Session Radiosurgery for Large Primary Tumors Affecting the Brain

IntroductionSurgery is an option for patients with large, symptomatic primary tumors affecting the brain. However, surgery might not be suitable for all tumors, especially those located in sensitive areas such as the pineal region and the hypothalamus. Single-session stereotactic radiosurgery (SRS) might not provide an adequate dose for long-term local control due to the initial tumor volume and the involvement of radiation sensitive organs at risk (OARs). Two-session radiosurgery has been described as a feasible strategy for dose escalation in large secondary brain tumors. This report describes a series of patients treated upfront with two-session radiosurgery for primary tumors affecting the brain.Materials and methodsFrom May 2017 to January 2020, eight patients with primary tumors affecting the brain were treated with two-session radiosurgery due to either an initial large tumor volume or tumor localization and the involvement of OARs. The response was assessed by imaging and clinical evaluations.ResultsA total of eight patients were treated, nine tumors were treated with two-session radiosurgery, four patients had tumors in the pineal region (50%), and the rest were in the hypothalamic region (25%) or elsewhere. The mean tumor volume for the first SRS session was 15 mL (range 5.2 to 51.6 mL), the mean prescription dose was 13 Gy, and the timespan between both sessions was 30 days (range, 30 to 42 days). During the second session, tumor volume was reduced to 73.6% (range, -20% to 98.7%) of the original dimension, mean tumor volume was 5 mL (range, 0.1 to 17.8 ml), mean prescription dose for the second session was 16.2 Gy estimated by time, dose, and fractionation and by bioequivalent dose under alpha-beta values often to be equivalent to a single dose of 15.8 Gy. Doses to the OARs for the optic pathway were equivalent to a single maximum dose of 9.75 Gy (range, 7.12 to 10.92), and to the brainstem, the equivalent was a maximum dose of 12.3 Gy (range, 5.6 to 15.07).At last follow-up, at a mean of 336.5 days (range, 65 to 962 days), seven patients were alive, five tumors had a partial response (PR), and three had stable disease in accordance to Response Evaluation Criteria in Solid Tumors (RECIST) criteria. One patient died 435 days after treatment, the Karnofsky Performance Status (KPS) was 90 at the first session, 90 at the second session, and was maintained at last follow-up. No adverse radiation effects were reported.ConclusionsTwo-stage SRS proved to be a safe method to escalate dose in proportionately large volume primary brain tumors whose histology is expected to have a quick biological response to radiation. Longer follow-up is needed to determine the long-term effectiveness by tumor subtypes of two-stage SRS in the same manner as it has been proven in single session SRS series in smaller tumor volumes.