Effects of propofol on cortico-cortical evoked potentials in the dorsal language white matter pathway.

OBJECTIVE: In order to evaluate the clinical utility even under general anesthesia, the present study aimed to clarify the effect of anesthesia on the cortico-cortical evoked potentials (CCEPs). METHODS: We analyzed 14 patients' data in monitoring the integrity of the dorsal language pathway by using CCEPs both under general anesthesia with propofol and remifentanil and awake condition, with the main aim of clarifying the effect of anesthesia on the distribution and waveform of CCEPs. RESULTS: The distribution of larger CCEP response sites, including the locus of the maximum CCEP response site, was marginally affected by anesthesia. With regard to similarity of waveforms, the mean waveform correlation coefficient indicated a strong agreement. CCEP N1 amplitude increased by an average of 25.8% from general anesthesia to waking, except three patients. CCEP N1 latencies had no correlation in changes between the two conditions. CONCLUSIONS: We demonstrated that the distribution of larger CCEP responses was marginally affected by anesthesia and that the CCEP N1 amplitude had tendency to increase from general anesthesia to the awake condition. SIGNIFICANCE: The CCEP method provides the efficiency of intraoperative monitoring for dorsal language white matter pathway even under general anesthesia.

Intraoperative Electrophysiologic Mapping of Medial Frontal Motor Areas and Functional Outcomes.

OBJECTIVE: To propose a method for intraoperative mapping and monitoring of the medial frontal motor areas (MFMA). METHODS: We estimated the location of the MFMA using the corticocortical evoked potential (CCEP) provoked by electric stimuli to the primary motor area (M1) of the upper limb. We localized or defined the MFMA by recording the motor evoked potentials (MEPs) provoked by electric stimuli to the medial frontal cortex around the estimated area. We monitored the patients' motor function during awake craniotomy and sequentially recorded the MEPs of the upper and/or lower limbs. This method was applied to 8 patients. RESULTS: Four patients who had part of the areas identified as the MFMA removed showed transient hemiparesis postoperatively (supplementary motor area [SMA] syndrome). The MEP from the M1 was preserved in the 4 patients. The resection of the identified MFMA might have caused their SMA syndrome. The CCEP showed a strong connection between the M1 and the SMA of the upper limb. Our method did not provoke any seizures. CONCLUSIONS: This is a safe and sensitive method for intraoperative mapping and monitoring of the MFMA by combining electrophysiologic monitoring and awake craniotomy. It is clinically useful for mapping the MFMA and can prevent permanent motor deficits.

Clinical impact of intraoperative CCEP monitoring in evaluating the dorsal language white matter pathway.

In order to preserve postoperative language function, we recently proposed a new intraoperative method to monitor the integrity of the dorsal language pathway (arcuate fasciculus; AF) using cortico-cortical evoked potentials (CCEPs). Based on further investigations (20 patients, 21 CCEP investigations), including patients who were not suitable for awake surgery (five CCEP investigations) or those without preoperative neuroimaging data (eight CCEP investigations including four with untraceable tractography due to brain edema), we attempted to clarify the clinical impact of this new intraoperative method. We monitored the integrity of AF by stimulating the anterior perisylvian language area (AL) by recording CCEPs from the posterior perisylvian language area (PL) consecutively during both general anesthesia and awake condition. After tumor resection, single-pulse electrical stimuli were also applied to the floor of the removal cavity to record subcortico-cortical evoked potentials (SCEPs) at AL and PL in 12 patients (12 SCEP investigations). We demonstrated that (1) intraoperative dorsal language network monitoring was feasible even when patients were not suitable for awake surgery or without preoperative neuroimaging studies, (2) CCEP is a dynamic marker of functional connectivity or integrity of AF, and CCEP N1 amplitude could even become larger after reduction of brain edema, (3) a 50% CCEP N1 amplitude decline might be a cut-off value to prevent permanent language dysfunction due to impairment of AF, (4) a correspondence (<2.0 ms difference) of N1 onset latencies between CCEP and the sum of SCEPs indicates close proximity of the subcortical stimulus site to AF (<3.0 mm). Hum Brain Mapp 38:1977-1991, 2017. © 2017 Wiley Periodicals, Inc.

Visualization of heterogeneity and regional grading of gliomas by multiple features using magnetic resonance-based clustered images.

Preoperative glioma grading is important for therapeutic strategies and influences prognosis. Intratumoral heterogeneity can cause an underestimation of grading because of the sampling error in biopsies. We developed a voxel-based unsupervised clustering method with multiple magnetic resonance imaging (MRI)-derived features using a self-organizing map followed by K-means. This method produced novel magnetic resonance-based clustered images (MRcIs) that enabled the visualization of glioma grades in 36 patients. The 12-class MRcIs revealed the highest classification performance for the prediction of glioma grading (area under the receiver operating characteristic curve = 0.928; 95% confidential interval = 0.920-0.936). Furthermore, we also created 12-class MRcIs in four new patients using the previous data from the 36 patients as training data and obtained tissue sections of the classes 11 and 12, which were significantly higher in high-grade gliomas (HGGs), and those of classes 4, 5 and 9, which were not significantly different between HGGs and low-grade gliomas (LGGs), according to a MRcI-based navigational system. The tissues of classes 11 and 12 showed features of malignant glioma, whereas those of classes 4, 5 and 9 showed LGGs without anaplastic features. These results suggest that the proposed voxel-based clustering method provides new insights into preoperative regional glioma grading.

Voxel-based clustered imaging by multiparameter diffusion tensor images for glioma grading.

Gliomas are the most common intra-axial primary brain tumour; therefore, predicting glioma grade would influence therapeutic strategies. Although several methods based on single or multiple parameters from diagnostic images exist, a definitive method for pre-operatively determining glioma grade remains unknown. We aimed to develop an unsupervised method using multiple parameters from pre-operative diffusion tensor images for obtaining a clustered image that could enable visual grading of gliomas. Fourteen patients with low-grade gliomas and 19 with high-grade gliomas underwent diffusion tensor imaging and three-dimensional T1-weighted magnetic resonance imaging before tumour resection. Seven features including diffusion-weighted imaging, fractional anisotropy, first eigenvalue, second eigenvalue, third eigenvalue, mean diffusivity and raw T2 signal with no diffusion weighting, were extracted as multiple parameters from diffusion tensor imaging. We developed a two-level clustering approach for a self-organizing map followed by the K-means algorithm to enable unsupervised clustering of a large number of input vectors with the seven features for the whole brain. The vectors were grouped by the self-organizing map as protoclusters, which were classified into the smaller number of clusters by K-means to make a voxel-based diffusion tensor-based clustered image. Furthermore, we also determined if the diffusion tensor-based clustered image was really helpful for predicting pre-operative glioma grade in a supervised manner. The ratio of each class in the diffusion tensor-based clustered images was calculated from the regions of interest manually traced on the diffusion tensor imaging space, and the common logarithmic ratio scales were calculated. We then applied support vector machine as a classifier for distinguishing between low- and high-grade gliomas. Consequently, the sensitivity, specificity, accuracy and area under the curve of receiver operating characteristic curves from the 16-class diffusion tensor-based clustered images that showed the best performance for differentiating high- and low-grade gliomas were 0.848, 0.745, 0.804 and 0.912, respectively. Furthermore, the log-ratio value of each class of the 16-class diffusion tensor-based clustered images was compared between low- and high-grade gliomas, and the log-ratio values of classes 14, 15 and 16 in the high-grade gliomas were significantly higher than those in the low-grade gliomas (p < 0.005, p < 0.001 and p < 0.001, respectively). These classes comprised different patterns of the seven diffusion tensor imaging-based parameters. The results suggest that the multiple diffusion tensor imaging-based parameters from the voxel-based diffusion tensor-based clustered images can help differentiate between low- and high-grade gliomas.

Long-term seizure outcome following resective surgery for epilepsy: to be or not to be completely cured?

Surgical intervention is expected to improve the quality of life in patients with intractable epilepsy by providing adequate seizure control. Although many previous studies showed various rates of seizure freedom, definite conclusions have not yet been made regarding outcomes. In order to clarify the long-term postoperative outcome for a period up to 10 years, a retrospective review of our patients was performed longitudinally by using the survival analysis method. The postoperative state of epilepsy in 76 patients who underwent resection surgery was assessed based on Engel's criteria. In addition, Kaplan-Meier survival analysis was used to calculate the probability of seizure freedom. In this patient group, abnormal lesion were detected by MRI in 70 out of 76 cases, and the ictal onset zone was finally identified within temporal lobe in 51 cases. The most favorable outcome, defined as Engel Class Ia, was observed in 26 (37%), 24 (40%), and 18 (41%) cases at 2, 5, and 10 years after surgery, respectively. The Kaplan-Meier survival curve in the overall group estimated the probability of seizure freedom as 75% (95% confidence interval [CI] 70-80%), 67% (62-72%), and 51% (45-57%) at 2, 5, and 10 years follow up, respectively. Half of all seizure recurrences occurred within the first 2 postoperative years. In this study, we showed that long-term favorable outcome of seizure control following resection surgery can be achieved in more than half of the patients.