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Background: We proposed an algorithm to automate the components within the identification of components within the nidus of cerebral arteriovenous malformations (AVMs) which may be used to analyze the relationship between its diffuseness and treatment outcomes following stereotactic radiosurgery (SRS). Objectives: to determine the impact of the diffuseness of the AVM nidus on SRS outcomes. Methods: This study conducted regular follow-ups of 209 patients with unruptured AVMs who underwent SRS. The diffuseness of the AVM nidus was estimated by quantifying the proportions of vascular nidal component, brain parenchyma, and cerebrospinal fluid in T2-weighted MRIs. We used Cox regression analysis to characterize the association between nidal diffuseness and treatment outcomes in terms of obliteration rate and radiation-induced change (RICs) rate following SRS. Results: The median AVM volume was 20.7 cm3. The median duration of imaging follow-up was 51 months after SRS. The overall AVM obliteration rate was 68.4%. RICs were identified in 156 of the 209 patients (74.6%). The median proportions of the nidus of AVM and brain parenchyma components within the prescription isodose range were 30.2 and 52.2%, respectively. Cox regression multivariate analysis revealed that the only factor associated with AVM obliteration rate after SRS was AVM volume. However, a larger AVM volume (>20 mL) and a larger proportion of brain parenchyma (>50%) within the prescription isodose range were both correlated with a higher RIC rate following SRS. Conclusions: The diffuseness of the nidus indeed appears to affect the RIC rate following SRS in patients with unruptured AVMs.

Objective The neuromodulatory effects of focused ultrasound (FUS) have been demonstrated in animal epilepsy models; however, the safety and efficacy of FUS in humans with epilepsy have not been well established. Patients with drug-resistant epilepsy (DRE) undergoing stereo-electroencephalography (SEEG) provide an opportunity to investigate the neuromodulatory effects of FUS in humans. Methods Patients with DRE undergoing SEEG for localization of the seizure onset zone (SOZ) were prospectively enrolled. FUS was delivered to the SOZ using a neuronavigation-guided FUS system (ceiling spatial-peak temporal-average intensity level = 2.8 W/cm2 , duty cycle = 30%, modulating duration = 10 min). Simultaneous SEEG recordings were obtained during sonication and for 3 days after treatment. Seizures, interictal epileptiform discharges, and adverse events after FUS were monitored. Results Six patients met the eligibility criteria and completed FUS treatment. A decrease in seizure frequency was observed in two patients within the 3-day follow-up; however, one patient presented an increase in the frequency of subclinical seizures. Posttreatment magnetic resonance imaging revealed neither lesion nor brain edema. Significant changes in spectral power of SEEG were noted at the targeted electrodes during FUS treatment. One patient reported subjective scalp heating during FUS, and one patient developed transient naming and memory impairment that resolved within 3 weeks after FUS. Significance FUS can be safely delivered to the SOZ of patients with DRE, resulting in significant changes in spectral power of SEEG. A larger sample cohort and pursuing optimal sonication parameters will be required to elucidate the neuromodulatory effects of FUS when used for seizure control.

OBJECTIVEIn this study, the authors investigated high-frequency oscillation (HFO) networks during seizures in order to determine how HFOs spread from the focal cerebral cortex and become synchronized across various areas of the brain.METHODSAll data were obtained from stereoelectroencephalography (SEEG) signals in patients with drug-resistant temporal lobe epilepsy (TLE). The authors calculated intercontact cross-coefficients between all pairs of contacts to construct HFO networks in 20 seizures that occurred in 5 patients. They then calculated HFO network topology metrics (i.e., network density and component size) after normalizing seizure duration data by dividing each seizure into 10 intervals of equal length (labeled I1–I10).RESULTSFrom the perspective of the dynamic topologies of cortical and subcortical HFO networks, the authors observed a significant increase in network density during intervals I5–I10. A significant increase was also observed in overall energy during intervals I3–I8. The results of subnetwork analysis revealed that the number of components continuously decreased following the onset of seizures, and those results were statistically significant during intervals I3–I10. Furthermore, the majority of nodes were connected to a single dominant component during the propagation of seizures, and the percentage of nodes within the largest component grew significantly until seizure termination.CONCLUSIONSThe consistent topological changes that the authors observed suggest that TLE is affected by common epileptogenic patterns. Indeed, the findings help to elucidate the epileptogenic network that characterizes TLE, which may be of interest to researchers and physicians working to improve treatment modalities for epilepsy, including resection, cortical stimulation, and neuromodulation treatments that are responsive to network topologies.

Purpose Our purpose was to determine whether the coverage of brain parenchyma within the 12 Gy radiosurgical volume (V12) correlates with the development of radiation-induced changes (RICs) in patients with unruptured cerebral arteriovenous malformations (AVM) after undergoing stereotactic radiosurgery (SRS). Methods and Materials This study conducted regular follow-up examinations of 165 patients with unruptured AVMs who had previously undergone SRS. The RICs identified in T2-weighted magnetic resonance imaging (MRI) scans at any time point in the first 3 years after SRS were labeled “early RICs.” The RICs identified in T2-weighted MRI scans at 5-year follow-up brain images were labeled “late RICs.” Fully automated segmentation was used to analyze the MRI scans from these patients, whereupon the volume and proportion of brain parenchyma within the V12 was calculated. Logistic regression analysis was used to characterize the factors affecting the incidence of early and late RICs of any grade after SRS. Results The median duration of follow-up was 70 months (range, 36-222). Early RICs were identified in 124 of the 165 patients with the highest grades as followed: grade 1 (103 patients), grade 2 (19 patients), and grade 3 (2 patients). Only 103 patients had more than 5 years follow-up, and late RICs were identified in 70 of 103 patients. Seventeen of 70 patients with late RICs were symptomatic. The median volume and proportion of brain parenchyma within the V12 was 22.4 cm3 (range, 0.6-63.9) and 58.7% (range, 18.4-76.8). Univariate analysis revealed that AVM volume and the brain volume within the V12 were correlated with the incidence of both early and late RICs after SRS. Multivariable analysis revealed that only the brain volume within the V12 was significantly associated with the incidence of early and late RICs after SRS. Conclusions In patients with unruptured AVM, the volume of brain parenchyma within the V12 was an important factor associated with the incidence of early and late RICs after SRS. Before SRS, meticulous radiosurgical planning to reduce brain parenchyma coverage within the V12 could reduce the risk of complications.

OBJECTIVE Gamma Knife radiosurgery (GKRS) is a common treatment modality for vestibular schwannoma (VS). The ability to predict treatment response is important in patient counseling and decision-making. The authors developed an algorithm that can automatically segment and differentiate cystic and solid tumor components of VS. They also investigated associations between the quantified radiological features of each component and tumor response after GKRS. METHODS This is a retrospective study comprising 323 patients with VS treated with GKRS. After preprocessing and generation of pretreatment T2-weighted (T2W)/T1-weighted with contrast (T1WC) images, the authors segmented VSs into cystic and solid components by using fuzzy C-means clustering. Quantitative radiological features of the entire tumor and its cystic and solid components were extracted. Linear regression models were implemented to correlate clinical variables and radiological features with the specific growth rate (SGR) of VS after GKRS. RESULTS A multivariable linear regression model of radiological features of the entire tumor demonstrated that a higher tumor mean signal intensity (SI) on T2W/T1WC images (p < 0.001) was associated with a lower SGR after GKRS. Similarly, a multivariable linear regression model using radiological features of cystic and solid tumor components demonstrated that a higher solid component mean SI (p = 0.039) and a higher cystic component mean SI (p = 0.004) on T2W/T1WC images were associated with a lower SGR after GKRS. A larger cystic component proportion (p = 0.085) was associated with a trend toward a lower SGR after GKRS. CONCLUSIONS Radiological features of VSs on pretreatment MRI that were quantified using fuzzy C-means were associated with tumor response after GKRS. Tumors with a higher tumor mean SI, a higher solid component mean SI, and a higher cystic component mean SI on T2W/T1WC images were more likely to regress in volume after GKRS. Those with a larger cystic component proportion also trended toward regression after GKRS. Further refinement of the algorithm may allow direct prediction of tumor response.