Summary:  Purpose: We examined presurgical factors that independently influence surgical outcome after corpus callosotomy. For adequate measurement of the surgical outcome, we analyzed seizure outcome of drop attacks, postoperative overall daily function, and family satisfaction.Methods: At least 2 years after callosotomy (mean, 40.0 months), we retrospectively investigated 52 patients with drop attacks. As presurgical factors, we analyzed the age at surgery, age at seizure onset, age at drop attack onset, sex, hemiparesis, severe mental retardation, EEG abnormality, MRI abnormality, and extent of callosal section (total or partial callosotomy). Stepwise logistic regression was used for analysis.Results: Satisfactory outcome (seizure cessation or >90% seizure reduction) was achieved in 85% of patients with drop attacks, 32% of those with generalized tonic seizures, and 31% of those with generalized tonic‐clonic seizures. The families assessed the overall daily function as improved in 62% of patients, unchanged in 23%, and impaired in 15%. Family satisfaction with callosotomy was achieved in 83% of patients (definitely satisfied, 39%, somewhat satisfied, 44%). Total callosotomy is independently predictive of satisfactory reduction of drop attacks (p = 0.013). A younger age is independently predictive of improvement of overall daily function (impaired and improved: p = 0.004) and family satisfaction (unsatisfied and somewhat satisfied, p = 0.018; unsatisfied and definitely satisfied, p = 0.0006).Conclusions: In the present study, we found that total callosotomy is more effective for treatment of drop attacks than partial callosotomy and that children receive more benefit than adults after callosotomy.

A warning prior to seizure onset can help improve the quality of life for epilepsy patients. The feasibility of a wearable system for predicting epileptic seizures using anomaly detection based on machine learning is evaluated. An original telemeter is developed for continuous measurement of R-R intervals derived from an electrocardiogram. A bespoke smartphone app calculates the indices of heart rate variability in real time from the R-R intervals, and the indices are monitored using multivariate statistical process control by the smartphone app. The proposed system was evaluated on seven epilepsy patients. The accuracy and reliability of the R-R interval measurement, which was examined in comparison with the reference electrocardiogram, showed sufficient performance for heart rate variability analysis. The results obtained using the proposed system were compared with those obtained using the existing video and electroencephalogram assessments; it was noted that the proposed method has a sensitivity of 85.7% in detecting heart rate variability change prior to seizures. The false positive rate of 0.62 times/h was not significantly different from the healthy controls. The prediction performance and practical advantages of portability and real-time operation are demonstrated in this study.

BACKGROUND AND PURPOSE: Arterial spin-labeling MR imaging with multiple postlabeling delays has a potential to evaluate various hemodynamic parameters. To clarify whether arterial spin-labeling MR imaging can identify CBF and perfusion delay in patients with Moyamoya disease, we compared arterial spin-labeling, DSC, and ¹⁵O-gas PET in terms of their ability to identify these parameters. MATERIALS AND METHODS: Eighteen patients with Moyamoya disease (5 men, 13 women; ages, 21–55 years) were retrospectively analyzed. CBF values of pulsed continuous arterial spin-labeling using 2 postlabeling delays (short arterial spin-labeling, 1525 ms; delayed arterial spin-labeling, 2525 ms) were compared with CBF values measured by ¹⁵O-gas PET. All plots were divided into 2 groups by the cutoff of time-based parameters (the time of the maximum observed concentration, TTP, MTT, delay of MTT to cerebellum, and disease severity [symptomatic or not]). The ratio of 2 arterial spin-labeling CBFs (delayed arterial spin-labeling CBF to short arterial spin-labeling CBF) was compared with time-based parameters: time of the maximum observed concentration, TTP, and MTT. RESULTS: The short arterial spin-labeling–CBF values were significantly correlated with the PET-CBF values (r = 0.63; P = .01). However, the short arterial spin-labeling–CBF value dropped in the regions with severe perfusion delay. The delayed arterial spin-labeling CBF overestimated PET-CBF regardless of the degree of perfusion delay. Delayed arterial spin-labeling CBF/short arterial spin-labeling CBF was well correlated with the time of the maximum observed concentration, TTP, and MTT (ρ = 0.71, 0.64, and 0.47, respectively). CONCLUSIONS: Arterial spin-labeling using 2 postlabeling delays may detect PET-measured true CBF and perfusion delay in patients with Moyamoya disease. Provided its theoretic basis and limitations are considered, noninvasive arterial spin-labeling could be a useful alternative for evaluating the hemodynamics of Moyamoya disease.