Safety of slow-pulsed transcranial electrical stimulation in acute spike suppression.

We examined the effects of slow-pulsed transcranial electrical stimulation (TES) in suppressing epileptiform discharges in seven adults with refractory epilepsy. An MRI-based realistic head model was constructed for each subject and co-registered with 256-channel dense EEG (dEEG). Interictal spikes were localized, and TES targeted the cortical source of each subject's principal spike population. Targeted spikes were suppressed in five subject's (29/35 treatment days overall), and nontargeted spikes were suppressed in four subjects. Epileptiform activity did not worsen. This study suggests that this protocol, designed to induce long-term depression (LTD), is safe and effective in acute suppression of interictal epileptiform discharges.

An improved artifacts removal method for high dimensional EEG.

BACKGROUND: Multiple noncephalic electrical sources superpose with brain signals in the recorded EEG. Blind source separation (BSS) methods such as independent component analysis (ICA) have been shown to separate noncephalic artifacts as unique components. However, robust and objective identification of artifact components remains a challenge in practice. In addition, with high dimensional data, ICA requires a large number of observations for stable solutions. Moreover, using signals from long recordings to provide the large observation set might violate the stationarity assumption of ICA due to signal changes over time. NEW METHOD: Instead of decomposing all channels simultaneously, subsets of channels are randomly selected and decomposed with ICA. With reduced dimensionality of the subsets, much less amount of data is required to derive stable components. To characterize each independent component, an artifact relevance index (ARI) is calculated by template matching each component with a model of the artifact. Automatic artifact identification is then implemented based on the statistical distribution of ARI of the numerous components generated. RESULTS: The proposed permutation resampling for identification matching (PRIM) method effectively removed eye blink artifacts from both simulated and real EEG. COMPARISON WITH EXISTING METHOD: The average topomap correlation coefficient between the cleaned EEG and the ground truth is 0.89±0.01 for PRIM, compared with 0.64±0.05 for conventional ICA based method. The average relative root-mean-square error is 0.40±0.01 for PRIM, compared with 0.66±0.10 for conventional method. CONCLUSIONS: The proposed method overcame limitations of conventional ICA based method and succeeded in removing eye blink artifacts automatically.

Response assessment in locally advanced head and neck cancer based on RECIST and volume measurements using cone beam CT images.

The purpose of this work was to find potential trends in RECIST measurements and volume regressions obtained from weekly cone-beam computed tomography images and to evaluate their relationship to clinical outcomes in locally advanced head and neck cancer. We examined thirty head and neck cancer patients who underwent a pre-treatment planning CT and weekly cone-beam computed tomography (CBCT) during the 5-7 week treatment period. The gross tumor volume (GTV) and lymph nodes were manually contoured on the treatment planning CT. The regions of interest enclosed by delineated contours were converted to binary masks and warped to weekly CBCT images using the 3D deformation field obtained by deformable image registration. The RECIST diameters and volumes were measured from these warped masks. Different predictor variables based on these measurements were calculated and correlated with clinical outcomes, based on a clinical exam and a PET imaging study. We found that there was substantial regression of the gross tumor volume over the treatment course (average gross tumor volume regression of 25%). Among the gross tumor volume predicators, it was found that the early regression of gross tumor volume showed a marginal statistical significance (p = 0.045) with complete response and non-complete response treatment outcomes. RECIST diameter measurements during treatment varied very little and did not correlate with clinical outcomes. We concluded that regression of the gross tumor volume obtained from weekly CBCT images is a promising predictor of clinical outcomes for head and neck patients. A larger sample is needed to confirm its statistical significance.

Methods for examining electrophysiological coherence in epileptic networks.

Epilepsy may reflect a focal abnormality of cerebral tissue, but the generation of seizures typically involves propagation of abnormal activity through cerebral networks. We examined epileptiform discharges (spikes) with dense array electroencephalography (dEEG) in five patients to search for the possible engagement of pathological networks. Source analysis was conducted with individual electrical head models for each patient, including sensor position measurement for registration with MRI with geodesic photogrammetry; tissue segmentation and skull conductivity modeling with an atlas skull warped to each patient's MRI; cortical surface extraction and tessellation into 1 cm(2) equivalent dipole patches; inverse source estimation with either minimum norm or cortical surface Laplacian constraints; and spectral coherence computed among equivalent dipoles aggregated within Brodmann areas with 1 Hz resolution from 1 to 70 Hz. These analyses revealed characteristic source coherence patterns in each patient during the pre-spike, spike, and post-spike intervals. For one patient with both spikes and seizure onset localized to a single temporal lobe, we observed a cluster of apparently abnormal coherences over the involved temporal lobe. For the other patients, there were apparently characteristic coherence patterns associated with the discharges, and in some cases these appeared to reflect abnormal temporal lobe synchronization, but the coherence patterns for these patients were not easily related to an unequivocal epileptogenic zone. In contrast, simple localization of the site of onset of the spike discharge, and/or the site of onset of the seizure, with non-invasive 256 dEEG was useful in predicting the characteristic site of seizure onset for those cases that were verified by intracranial EEG and/or by surgical outcome.

Deformable planning CT to cone-beam CT image registration in head-and-neck cancer.

PURPOSE: The purpose of this work was to implement and validate a deformable CT to cone-beam computed tomography (CBCT) image registration method in head-and-neck cancer to eventually facilitate automatic target delineation on CBCT. METHODS: Twelve head-and-neck cancer patients underwent a planning CT and weekly CBCT during the 5-7 week treatment period. The 12 planning CT images (moving images) of these patients were registered to their weekly CBCT images (fixed images) via the symmetric force Demons algorithm and using a multiresolution scheme. Histogram matching was used to compensate for the intensity difference between the two types of images. Using nine known anatomic points as registration targets, the accuracy of the registration was evaluated using the target registration error (TRE). In addition, region-of-interest (ROI) contours drawn on the planning CT were morphed to the CBCT images and the volume overlap index (VOI) between registered contours and manually delineated contours was evaluated. RESULTS: The mean TRE value of the nine target points was less than 3.0 mm, the slice thickness of the planning CT. Of the 369 target points evaluated for registration accuracy, the average TRE value was 2.6 +/- 0.6 mm. The mean TRE for bony tissue targets was 2.4 +/- 0.2 mm, while the mean TRE for soft tissue targets was 2.8 +/- 0.2 mm. The average VOI between the registered and manually delineated ROI contours was 76.2 +/- 4.6%, which is consistent with that reported in previous studies. CONCLUSIONS: The authors have implemented and validated a deformable image registration method to register planning CT images to weekly CBCT images in head-and-neck cancer cases. The accuracy of the TRE values suggests that they can be used as a promising tool for automatic target delineation on CBCT.