Search Results (20)

Objective: Traditional imaging modalities for the planning of Gamma Knife radiosurgery (GKRS) are non-specific and do not accurately delineate intracranial neoplasms. This study aimed to evaluate the utility of positron emission tomography (PET) for the planning of GKRS for intracranial neoplasms (ICNs) and the post-GKRS applications of PET for patient care. Methods: PubMed, Scopus, and ScienceDirect were searched in order to assemble relevant studies regarding the uses of PET in conjunction with GKRS for ICN treatment. PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines were followed to identify relevant studies on the use of PET in conjunction with GKRS. Particular emphasis was placed on review articles and medical research investigating tumor delineation and post-operative care. Relevant studies were selected and assessed based on quality measures, including study design, sample size, and significance. Inclusion and exclusion criteria were used to examine the yield of the initial search (n = 105). After a secondary review, the included results were identified (n = 50). Results: This study revealed that PET imaging is highly accurate for the planning of GKRS. In fact, many cases indicate that it is more specific than traditional imaging modalities. PET is also capable of complementing traditional imaging techniques through combination imaging. This showed significant efficacy for the planning of GKRS for ICNs. Conclusions: While PET shows a multitude of applications for the treatment of ICNs with GKRS, further research is necessary to assemble a complete set of clinical guidelines for treatment specifications. Importantly, future studies need a greater standardization of methods and expanded trials with a multitude of radiotracers. Full article

Introduction: The group of so-called “sellar-region masses” consists of a heterogeneous group of neoplasms and tumor-mimicking lesions, whose differential diagnosis may be challenging due to the overlapping of clinical and radiological features, which can be found both in “common” and “uncommon” lesions. The choice of a correct treatment strategy is still arduous and requires histological analysis. Gamma Knife Radiosurgery (GKRS) has already been reported as a safe and effective treatment in these cases. The objective of this study is to evaluate single-center pre-operative data, post-operative outcomes, and long-term follow-up in patients treated with GKRS for unusual sellar tumors. Methods: We retrospectively identified and analyzed nine patients treated with GKRS from 2004 to 2015, according to a standard protocol. Lesions consist of hypothalamic hamartoma (HH), Rathke’s cleft cist (RCC), Langerhans cell histiocytosis (LCH), spindle cell oncocytoma (SCO), choroid plexus papilloma (CPP), and ossifying fibroma (OF). The diagnosis was histologically confirmed in six patients that underwent surgery, while in three patients, diagnosis was based on characteristic clinical and radiological findings (two HH and one RCC). Pre-operative and post-operative data were retrieved from medical archives, and long-term follow-up was obtained through clinical and neuroradiological periodic examination. Results: In our series, all the “rare” sellar lesions treated, had a successful radiographic and clinical response in a medium-long follow-up period. Conclusions: The long-term follow-up results suggest that GKRS is a safe and effective treatment in rare sellar lesions, with very low toxicity. To the best of our knowledge, this report represents the largest series of unusual sellar lesions treated with GKRS in a single high-volume center, suggesting that GKRS might be an effective non-invasive adjuvant treatment option. Further studies and a larger number of patients are needed to confirm if residuals of these rare sellar lesions might regress on their own without treatment or if other non-invasive treatments could be as effective as GKRS. Full article

Background/Objectives: Gamma knife radiosurgery (GKRS) is widely performed as an adjuvant management of patients with residual or recurrent pituitary adenoma (PA). However, the variability in the tumor volume response to GKRS emphasizes the need for reliable predictors of treatment outcomes. The application of radiomics, an analytical approach for quantitative imaging, remains unexplored in predicting treatment responses for PAs. This study aimed to pioneer the use of radiomic MRI analysis to predict the volumetric response of PA to GKRS. Methods: This retrospective observational cohort study involved 81 patients who underwent GKRS for PA. Pre-treatment 3-Tesla MRI scans were used to extract radiomic features capturing the intensity, shape, and texture of the tumors. Radiomic signatures were generated using the least absolute shrinkage and selection operator (LASSO) for feature selection, in conjunction with several classifiers: random forest, naïve Bayes, kNN, logistic regression, neural network, and SVM. Results: The models demonstrated predictive performance in the test folds, with AUC values ranging from 0.759 to 0.928 and R² values between 0.272 and 0.665. Single-sequence T1w, dual-sequence T1w + CE-T1w, and multi-modality including clinicopathological (CP) parameters (CP + T1w + CE-T1w) achieved rather similar prognostic performance in the test folds, with respective AUCs of 0.928, 0.899, and 0.909. All these radiomics models significantly outperformed a benchmark model involving only CP features (AUC = 0.846). Conclusions: This study represents a radiomic analysis focused on predicting the volume response of PAs to GKRS to facilitate treatment individualization. The developed MRI-based radiomics models exhibited superior classification performance compared with the benchmark model composed solely of standard clinicopathological parameters. Full article

Background/Objective: This study explores the use of AI-powered radiomics to classify and monitor brain metastasis progression and regression following Gamma Knife radiosurgery (GKRS) based on MRI imaging. A clinical decision support application was developed using Streamlit to provide real-time, AI-driven predictions for treatment monitoring. Methods: MRI scans from 60 patients (3194 images) were analyzed using a transfer learning-enhanced AlexNet deep learning model. Class imbalance was mitigated through dynamic class weighting and data augmentation to ensure equitable performance across all classes. Optimized preprocessing pipelines ensured dataset standardization. Model performance was evaluated using accuracy, precision, recall, F1-scores, and AUC, with 95% confidence intervals. Additionally, a comparative analysis of Gamma Knife radiosurgery (GKRS) outcomes and predictive modeling demonstrated strong correlations between tumor volume evolution and treatment response. The AI predictions and visualizations were integrated into a Streamlit-based application to ensure clinical usability and ease of access. The AI-driven approach effectively classified progression and regression patterns, reinforcing its potential for clinical integration. Results: The transfer learning model achieved flawless classification accuracy (100%; 95% CI: 100–100%) along with perfect precision, recall, and F1-scores. The AUC score of 1.0000 (95% CI: 1.0000–1.0000) indicated excellent discrimination between progression and regression cases. Compared to the baseline AlexNet model (99.53% accuracy; 95% CI: 98.90–100.00%), the TL-enhanced model resolved all misclassifications. Tumor volume analysis identified the baseline size as a key predictor of progression (Pearson r = 0.795, r = 0.795, r = 0.795, p < 0.0001, p < 0.0001, and p < 0.0001). The training time (420.12 s) was faster than ResNet-50 (443.38 s) and EfficientNet-B0 (439.87 s), while achieving equivalent metrics. Despite 100% accuracy, the model requires multi-center validation for generalizability. Conclusions: This study demonstrates that transfer learning with dynamic class weighting provides a highly accurate and reliable framework for monitoring brain metastases post-GKRS. The Streamlit-based AI application enhances clinical decision-making by improving diagnostic precision and reducing variability. Explainable AI techniques, such as Grad-CAM visualizations, improve interpretability and support clinical adoption. These findings emphasize the transformative potential of AI in personalized treatment strategies, extending applications to genomic profiling, survival modeling, and longitudinal follow-ups for brain metastasis management. Full article

Background: Gamma Knife Radiosurgery (GKRS), a specific type of Stereotactic Radiosurgery (SRS), has developed as a significant modality in the treatment of glioblastoma, particularly in conjunction with standard chemotherapy. The goal of this study is to evaluate the efficacy of combining GKRS with surgical resection and chemotherapy in enhancing therapeutic effects for glioblastoma patients aged 55 years and older. Methods: This prospective clinical study, conducted in accordance with the STROBE guidelines, involved 49 glioblastoma patients aged 55 years and older, treated between January 2013 and January 2023. Data were collected prospectively, and strict adherence to the STUPP protocol was maintained. Only patients who conformed to the STUPP protocol were included in the analysis. Due to concerns regarding the cognitive impairment associated with conventional radiotherapy, and at the patients’ request, a radiosurgery plan was offered. Radiosurgery was administered for 4–8 weeks following surgical resection. Any patients who had not received previous radiotherapy received open surgical tumor removal, followed by GKRS along with adjuvant chemotherapy. Results: In this prospective clinical study of 49 glioblastoma patients aged 55 years and older, the average lifespan post-histopathological diagnosis was established at 22.3 months (95% CI: 12.0–28.0 months). The median time before disease progression was 14.3 months (95% CI: 13.0–29.7 months). The median duration until the first recurrence after treatment was 15.2 months, with documented cases varying between 4 and 33 months. The Gamma Knife Radiosurgery (GKRS) treatment involved a median marginal recommended dose of 12.5 Gy, targeting an average volume of 5.7 cm³ (range: 1.6–39 cm³). Local recurrence occurred in 21 patients, while distant recurrence was identified in 8 patients. Within the cohort, 34 patients were subjected to further therapeutic approaches, including reoperation, a second GKRS session, the administration of bevacizumab and irinotecan, and PCV chemotherapy. A cognitive function assessment revealed that the patients treated with GKRS experienced significantly less cognitive decline compared to the historical controls, who were treated with conventional radiotherapy. The median MMSE scores declined by 1.9 points over 12 months, and the median MoCA scores declined by 2.9 points. Conclusion: This study demonstrates that Gamma Knife Radiosurgery (GKRS), when integrated with surgical resection and adjuvant chemotherapy, offers a substantial benefit for glioblastoma patients aged 55 years and older. The data reveal that GKRS not only prolongs overall survival and progression-free survival but also significantly reduces cognitive decline compared to conventional radiotherapy. These findings underscore the efficacy and safety of GKRS, advocating for its incorporation into standard treatment protocols for older glioblastoma patients. The potential of GKRS to improve patient outcomes while preserving cognitive function is compelling and warrants further research to optimize and confirm its role in glioblastoma management. Full article

Introduction: Accurate prediction of tumor dynamics following Gamma Knife radiosurgery (GKRS) is critical for optimizing treatment strategies for patients with brain metastases (BMs). Traditional machine learning (ML) algorithms have been widely used for this purpose; however, recent advancements in deep learning, such as autoencoders, offer the potential to enhance predictive accuracy. This study aims to evaluate the efficacy of autoencoders compared to traditional ML models in predicting tumor progression or regression after GKRS. Objectives: The primary objective of this study is to assess whether integrating autoencoder-derived features into traditional ML models can improve their performance in predicting tumor dynamics three months post-GKRS in patients with brain metastases. Methods: This retrospective analysis utilized clinical data from 77 patients treated at the “Prof. Dr. Nicolae Oblu” Emergency Clinic Hospital-Iasi. Twelve variables, including socio-demographic, clinical, treatment, and radiosurgery-related factors, were considered. Tumor progression or regression within three months post-GKRS was the primary outcome, with 71 cases of regression and 6 cases of progression. Traditional ML models, such as Logistic Regression, Support Vector Machine (SVM), K-Nearest Neighbors (KNN), Extra Trees, Random Forest, and XGBoost, were trained and evaluated. The study further explored the impact of incorporating features derived from autoencoders, particularly focusing on the effect of compression in the bottleneck layer on model performance. Results: Traditional ML models achieved accuracy rates ranging from 0.91 (KNN) to 1.00 (Extra Trees). Integrating autoencoder-derived features generally enhanced model performance. Logistic Regression saw an accuracy increase from 0.91 to 0.94, and SVM improved from 0.85 to 0.96. XGBoost maintained consistent performance with an accuracy of 0.94 and an AUC of 0.98, regardless of the feature set used. These results demonstrate that hybrid models combining deep learning and traditional ML techniques can improve predictive accuracy. Conclusion: The study highlights the potential of hybrid models incorporating autoencoder-derived features to enhance the predictive accuracy and robustness of traditional ML models in forecasting tumor dynamics post-GKRS. These advancements could significantly contribute to personalized medicine, enabling more precise and individualized treatment planning based on refined predictive insights, ultimately improving patient outcomes. Full article

This study assesses the predictive performance of six machine learning models and a 1D Convolutional Neural Network (CNN) in forecasting tumor dynamics within three months following Gamma Knife radiosurgery (GKRS) in 77 brain metastasis (BM) patients. The analysis meticulously evaluates each model before and after hyperparameter tuning, utilizing accuracy, AUC, and other metrics derived from confusion matrices. The CNN model showcased notable performance with an accuracy of 98% and an AUC of 0.97, effectively complementing the broader model analysis. Initial findings highlighted that XGBoost significantly outperformed other models with an accuracy of 0.95 and an AUC of 0.95 before tuning. Post-tuning, the Support Vector Machine (SVM) demonstrated the most substantial improvement, achieving an accuracy of 0.98 and an AUC of 0.98. Conversely, XGBoost showed a decline in performance after tuning, indicating potential overfitting. The study also explores feature importance across models, noting that features like “control at one year”, “age of the patient”, and “beam-on time for volume V1 treated” were consistently influential across various models, albeit their impacts were interpreted differently depending on the model’s underlying mechanics. This comprehensive evaluation not only underscores the importance of model selection and hyperparameter tuning but also highlights the practical implications in medical diagnostic scenarios, where the accuracy of positive predictions can be crucial. Our research explores the effects of staged Gamma Knife radiosurgery (GKRS) on larger tumors, revealing no significant outcome differences across protocols. It uniquely considers the impact of beam-on time and fraction intervals on treatment efficacy. However, the investigation is limited by a small patient cohort and data from a single institution, suggesting the need for future multicenter research. Full article

Gamma knife radiosurgery (GKRS), a form of stereotactic radiosurgery (SRS), has gained importance in treating glioblastoma alongside conventional chemotherapy. This study aims to assess the efficacy of combining GKRS with surgery and chemotherapy to enhance treatment outcomes for glioblastoma patients. This prospective clinical study, adhering to STROBE guidelines, assessed 121 glioblastoma patients from June 2008 to December 2022. All patients who had not undergone prior radiotherapy underwent open surgical tumor resection, GKRS, and adjuvant chemotherapy. In the analyzed cohort, the median survival post-diagnosis was 21.2 months (95% CI: 11.4–26.7) and the median progression-free survival was 13.6 months (95% CI: 12.5–28.3). The median time to first recurrence post-treatment was 14.5 months (range: 4–33 months). The median prescribed dose for GKRS was 12 Gy (range: 10–17 Gy), with a median target volume of 6.0 cm³ (range: 1.6–68 cm³). Post GKRS, 92 patients experienced local recurrence, 21 experienced distant recurrence, and 87 received additional treatment, indicating diverse responses and treatment engagement. This study evaluates the use of GKRS for glioblastomas, emphasizing its efficacy and complications in a single-center trial. It suggests integrating GKRS into initial treatment and for recurrences, highlighting the comparable survival rates but underscoring the need for further research. Full article

This study aimed to implement a deep learning-based super-resolution (SR) technique that can assist in the diagnosis and surgery of trigeminal neuralgia (TN) using magnetic resonance imaging (MRI). Experimental methods applied SR to MRI data examined using five techniques, including T2-weighted imaging (T2WI), T1-weighted imaging (T1WI), contrast-enhancement T1WI (CE-T1WI), T2WI turbo spin–echo series volume isotropic turbo spin–echo acquisition (VISTA), and proton density (PD), in patients diagnosed with TN. The image quality was evaluated using the peak signal-to-noise ratio (PSNR) and structural similarity index (SSIM). High-quality reconstructed MRI images were assessed using the Leksell coordinate system in gamma knife radiosurgery (GKRS). The results showed that the PSNR and SSIM values achieved by SR were higher than those obtained by image postprocessing techniques, and the coordinates of the images reconstructed in the gamma plan showed no differences from those of the original images. Consequently, SR demonstrated remarkable effects in improving the image quality without discrepancies in the coordinate system, confirming its potential as a useful tool for the diagnosis and surgery of TN. Full article

Objective: Gamma knife radiosurgery (GKRS) has served as an adjunctive treatment in Cushing’s disease (CD) for decades and has become a vital part of therapy in the management of CD. Biological effective dose (BED) is a radiobiological parameter with time correction, considering the cellular deoxyribonucleic acid repairment. We aimed to investigate the safety and efficacy of GKRS for CD and evaluate the association of BED and treatment outcome. Methods: A cohort study of 31 patients with CD received GKRS in West China Hospital between June 2010 and December 2021. Endocrine remission was defined as normalization of 24 h urinary free cortisol (UFC) or serum cortisol ≤ 50 nmol/L after a 1 mg dexamethasone suppression test. Result: The mean age was 38.6 years old, and females accounted for 77.4%. GKRS was the initial treatment for 21 patients (67.7%), and 32.3% of patients underwent GKRS after surgery due to residual disease and recurrence. The mean endocrine follow-up duration was 22 months. The median marginal dose was 28.0 Gy, and the median BED was 221.5 Gy_2.47. Fourteen patients (45.1%) experienced control of hypercortisolism in the absence of pharmacological treatment, and the median duration to remission was 20.0 months. The cumulative rates of endocrine remission at 1, 2, and 3 years after GKRS were 18.9%, 55.3%, and 72.21%, respectively. The total complication rate was 25.8%, and the mean duration from GKRS to hypopituitary was 17.5 months. The new hypopituitary rate at 1, 2, and 3 years were 7.1%, 30.3%, and 48.4%, respectively. A high BED level (BED > 205 Gy_2.47) was associated with better endocrine remission than a low BED level (BED ≤ 205 Gy_2.47), while no significant differences were found between the BED level and hypopituitarism. Conclusions: GKRS was a second-line therapeutic option for CD with satisfactory safety and efficacy. BED should be considered during GKRS treatment planning, and optimization of BED is a potentially impactful avenue toward improving the efficacy of GKRS. Full article

(1) Background: Surgical resection for the removal of brain metastases often fails to prevent tumor recurrence within the surgical cavity; hence, researchers are divided as to the benefits of radiation treatment following surgical resection. This retrospective study assessed the effects of post-operative stereotactic radiosurgery (SRS) on local tumor control and overall survival. (2) Methods: This study examined the demographics, original tumor characteristics, and surgical outcomes of 97 patients who underwent Gamma Knife Radiosurgery (GKRS) treatment (103 brain metastases). Kaplan–Meier plots and Cox regression were used to correlate clinical features to tumor control and overall survival. (3) Results: The overall tumor control rate was 75.0% and overall 12-month survival was 89.6%. Tumor control rates in the radiation group versus the non-radiation group were as follows: 12 months (83.1% vs. 57.7%) and 24 months (66.1% vs. 50.5%). During the 2-year follow-up period after SRS, the intracranial response rate was higher in the post-craniotomy radiation group than in the non-radiation group (p = 0.027). Cox regression multivariate analysis determined that post-craniotomy irradiation of the surgical cavity is predictive of tumor control (p = 0.035). However, EGFR mutation was not predictive of overall survival or tumor control. (4) Conclusions: Irradiating the surgical cavity after surgery can enhance local tumor control; however, it does not have a significant effect on overall survival. Full article

Purpose: Grade II meningiomas are rarer than Grade I, and when operated on, bear a higher risk of local recurrence, with a 5-year progression free survival (PFS) ranging from 59 to 90%. Radiotherapy (RT) or radiosurgery, such as Gamma Knife radiosurgery (GKRS) can reduce the risk of relapse in patients with residual disease, even if their role, particularly after gross total resection (GTR), is still under debate. Main goal of this study was to compare the outcomes of different post-surgical management of grade II meningiomas, grouped by degree of surgical removal (Simpson Grade); next in order we wanted to define the role of GKRS for the treatment of residual disease or relapse. Methods: from November 2016 to November 2020 all patients harboring grade II meningiomas, were divided into three groups, based on post-surgical management: (1) wait and see, (2) conventional adjuvant radiotherapy and (3) stereotactic GKRS radiosurgery. Relapse rate and PFS were registered at the time of last follow up and results were classified as stable, recurrence next to or distant from the surgical cavity. In the second part of the study we collected data of all patients who underwent GKRS in our Centers from November 2017 to November 2020. Results: A total of 37 patients were recruited, including seven patients with multiple meningiomas. Out of 47 meningiomas, 33 (70.2%) were followed with a wait and see strategy, six (12.7%) were treated with adjuvant radiotherapy, and 8 patients (17.0%) with adjuvant GKRS. Follow up data were available for 43 (91.4%) meningiomas. Within the wait and see group, recurrence rates differed based on Simpson grades, lower recurrence rates being observed in three Simpson I cases (30%) compared to twelve relapses (60%) in patients with Simpson grade II/III. Finally, out of the 24 meningiomas undergoing GKRS (8 residual and 16 recurrence), 21 remained stable at follow up. Conclusions: Gross total resection (GTR) Simpson II and III have a significantly worse outcome as compared to Simpson I. The absence of adjuvant treatment leads to significant worsening of the disease progression curve. Adjuvant radiotherapy, especially GKRS, provides good local control of the disease and should be considered as an adjuvant treatment in all cases where Simpson I resection is not possible. Full article

Background: Peritumoral edema may be a prohibitive side effect in treating large incidental meningiomas with stereotactic radiosurgery. An approach that limits peritumoral edema and achieves tumor control with SRS would be an attractive management option for large incidental meningiomas. Methods: This is a retrospective cohort study of patients with large incidental meningiomas (≥2 mL in volume and/or 2 cm in diameter) treated with gamma knife radiosurgery (GKRS) between 2000 and 2019 in Taiwan and followed up for 5 years. The outcomes of a pathophysiological approach targeting the dural feeding artery site with a higher marginal dose (18–20 Gy) to enhance vascular damage and the parenchymal margin of the tumor with a lower dose (9–11 Gy) to reduce parenchymal damage were compared with those of a conventional approach targeting the tumor center with a higher dose and tumor margin with a lower dose (12–14 Gy). Results: A total of 53 incidental meningiomas were identified, of which 23 (43.4%) were treated with a pathophysiological approach (4 cases underwent a two-stage approach) and 30 (56.7%) were treated with a conventional approach. During a median follow-up of 3.5 (range 1–5) years, tumor control was achieved in 19 (100%) incidental meningiomas that underwent a single-stage pathophysiological approach compared with 29 (96.7%) incidental meningiomas that underwent a conventional approach (log-rank test: p = 0.426). Peritumoral edema developed in zero (0%) incidental meningiomas that underwent a single stage pathophysiological approach compared to seven (23.3%) incidental meningiomas that underwent a conventional approach (log-rank test: p = 0.023). Conclusions: Treatment of large incidental meningiomas with a pathophysiological approach with GKRS achieves similar rates of tumor control and reduces the risk of peritumoral edema. GKRS with a pathophysiological approach may be a reasonable management strategy for large incidental meningiomas. Full article

Objective: The leading treatment option for dural carotid–cavernous sinus fistula is an endovascular approach with immediate improvement. Alternatively, radiosurgery is a slow response for obliterating the fistula and poses a radiation risk to the optic apparatus and the associated cranial nerves and blood vessels. In this study, we retrieved cases from a prospective database to assess the ophthalmological outcomes and complications in treating dural carotid cavernous sinus fistula with gamma knife radiosurgery (GKRS). Material and Methods: We retrieved a total of 65 cases of carotid cavernous sinus fistula treated with GKRS with margin dose of 18–20 Gy from 2003 to 2018 and reviewed the ophthalmological records required for our assessment. Results: The mean target volume was 2 ± 1.43 cc. The onset of symptom alleviated after GKRS was 3.71 ± 7.68 months. There were two cases with residual chemosis, two with cataract, two with infarction, one with transient optic neuropathy, and four with residual cranial nerve palsy, but none with glaucoma or dry eyes. In MRA analysis, total obliteration of the fistula was noted in 64 cases with no detectable ICA stenosis nor cavernous sinus thrombosis. In the Cox regression analysis, post-GKRS residual cranial nerve palsy was highly correlated to targeted volume (p < 0.05) and age (p < 0.05). The occurrence of post-GKRS cataract was related to the initial symptom of chemosis (p < 0.05). Conclusion: GKRS for carotid cavernous sinus fistula offers a high obliteration rate and preserves the cavernous sinus vascular structure while conferring a low risk of treatment complications such as adverse radiation risk to the optic apparatus and adjacent cranial nerves. Full article

Seizures are the most common presentation in patients with cerebral cavernous malformations (CCMs). Based on the hypothesis that the volume or proportion of gray matter (GM) displaced by CCMs is associated with the risk of seizure, we developed an algorithm by which to quantify the volume and proportion of displaced GM and the risk of seizure. Image analysis was conducted on 111 patients with solitary CCMs (divided into seizure and nonseizure groups) from our gamma knife radiosurgery (GKRS) database from February 2005 and March 2020. The CCM algorithm proved effective in quantifying the GM and CCM using T1WI MRI images. In the seizure group, 11 of the 12 patients exhibited seizures at the initial presentation, and all CCMs in the seizure group were supratentorial. The location of the limbic lobe within the CCM was significantly associated with the risk of seizure (OR = 19.6, p = 0.02). The risk of seizure increased when the proportion of GM displaced by the CCM exceeded 31%. It was also strongly correlated with the volume of displaced GM. The volume and proportion of displaced GM were both positively correlated with the risk of seizure presentation/development and thus could be used to guide seizure prophylaxis in CCM patients. Full article