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 drugresistant 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/cm 2 , 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.

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BackgroundGamma knife radiosurgery (GKRS) is a common treatment for cerebral arterio-venous malformations (AVMs), particularly in cases where the malformation is deep-seated, large, or in eloquent areas of the brain. Unfortunately, these procedures can result in radiation injury to brain parenchyma. The fact that every AVM is unique in its vascular morphology makes it nearly impossible to exclude brain parenchyma from isodose radiation exposure during the formulation of a GKRS plan. Calculating the percentages of the various forms of tissue exposed to specific doses of radiation is crucial to understanding the clinical responses and causes of brain parenchyma injury following GKRS for AVM.MethodsIn this study, we developed a fully automated algorithm using unsupervised classification via fuzzy c-means clustering for the analysis of T2 weighted images used in a Gamma knife plan. This algorithm is able to calculate the percentages of nidus, brain tissue, and cerebrospinal fluid (CSF) within the prescription isodose radiation exposure region.ResultsThe proposed algorithm was used to assess the treatment plan of 25 patients with AVM who had undergone GKRS. The Dice similarity index (SI) was used to determine the degree of agreement between the results obtained using the algorithm and a visually guided manual method (the gold standard) performed by an experienced neurosurgeon. In the nidus, the SI was (74.86 ± 1.30%) (mean ± standard deviation), the sensitivity was (83.05 ± 11.91)%, and the specificity was (86.73 ± 10.31)%. In brain tissue, the SI was (79.50 ± 6.01)%, the sensitivity was (73.05 ± 9.77)%, and the specificity was (85.53 ± 7.13)%. In the CSF, the SI was (69.57 ± 15.26)%, the sensitivity was (89.86 ± 5.87)%, and the specificity was (92.36 ± 4.35)%.ConclusionsThe proposed clustering algorithm provides precise percentages of the various types of tissue within the prescription isodose region in the T2 weighted images used in the GKRS plan for AVM. Our results shed light on the causes of brain radiation injury after GKRS for AVM. In the future, this system could be used to improve outcomes and avoid complications associated with GKRS treatment.

We report the results of a long-term follow-up study of 50 patients who underwent removal of temporal neocortex with preservation of deeper limbic structures as surgical therapy for intractable temporal lobe epilepsy. The follow-up period ranged from 3 to 15 years. Preoperative EEG investigations were based on interictal discharges alone. Three factors were predictive of a good outcome: (a) A clear unilateral anterior-midtemporal focus (p less than 0.01), (b) stereotypical onset of temporal lobe seizure (p less than 0.005), and (c) greater volume of tissue removed at operation (p less than 0.05). Overall results showed that 62% of patients experienced an outcome of "cure" or "almost cure," as classified according to a modified version of Crandall's criteria (Crandall's I and II). Those who experienced a significant reduction in seizures but who continued to have intractable epilepsy (Crandall's III) were not considered to have had a good result. Overall outcome compares favorably with other that of centers using different surgical approaches and indicates that neocorticectomy is a suitable procedure in a highly selected population even when limited resources are available.

Determination of the volumes of acute cerebral infarct in the magnetic resonance imaging harbors prognostic values. However, semiautomatic method of segmentation is time-consuming and with high interrater variability. Using diffusion weighted imaging and apparent diffusion coefficient map from patients with acute infarction in 10 days, we aimed to develop a fully automatic algorithm to measure infarct volume. It includes an unsupervised classification with fuzzy C-means clustering determination of the histographic distribution, defining self-adjusted intensity thresholds. The proposed method attained high agreement with the semiautomatic method, with similarity index 89.9 ± 6.5%, in detecting cerebral infarct lesions from 22 acute stroke patients. We demonstrated the accuracy of the proposed computer-assisted prompt segmentation method, which appeared promising to replace the laborious, time-consuming, and operator-dependent semiautomatic segmentation.