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Puneet Plaha, Nikunj K. Patel and Steven S. Gill

Object. The goal of this study was to determine the safety and efficacy of bilateral subthalamic region stimulation in the treatment of essential tremor (ET).

Methods. Following induction of general anesthesia, four patients with disabling tremor that had proved to be refractory to pharmacotherapy underwent magnetic resonance imaging—guided deep brain stimulation (DBS) of the bilateral subthalamic region. Tremor was assessed by applying the Fahn-Tolosa-Marín Tremor Rating Scale at baseline and again at the 12-month follow-up examination.

Following surgery the total tremor score improved by 80.1% (from a baseline mean score of 63 ± 15.1 to a score of 11.8 ± 3.9 at 12 months postoperatively). There was a significant improvement (p < 0.0001) in the mean tremor score of the upper limb (postural and action component) from a baseline score of 3 ± 0.9 to a score of 0.5 ± 0.5 at 12 months postoperatively. In two patients with Score 4 head tremor complete arrest of the tremor was observed at 12 months. Motor function scores of the upper limb for drawing spirals, pouring water, and drawing lines improved significantly (p < 0.05) by 66.7, 76.9, and 58.3%, respectively. Handwriting improved by 68%, but this gain was not significant. The mean activities of daily living score at baseline was 20 ± 3.2; there was an 88.8% improvement in this score to 2.3 ± 1.5 at the 12-month evaluation. The voltage required for effective tremor control was low (mean 1.8 ± 0.2 V) and, along with the other parameters of DBS (frequency and pulse width), did not change significantly over the 12-month period. Tolerance to the action component of tremor was not seen. There was no procedural or stimulation-related complication.

Conclusions. Bilateral subthalamic region stimulation is effective in arresting tremor and head titubation, as well as functional disability in ET. Complications like dysarthria and disequilibrium were not seen. These patients required low voltages of stimulation and did not develop a tolerance to the treatment.

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Laurent J. Livermore, Martin Isabelle, Ian M. Bell, Oliver Edgar, Natalie L. Voets, Richard Stacey, Olaf Ansorge, Claire Vallance and Puneet Plaha

OBJECTIVE

Raman spectroscopy is a biophotonic tool that can be used to differentiate between different tissue types. It is nondestructive and no sample preparation is required. The aim of this study was to evaluate the ability of Raman spectroscopy to differentiate between glioma and normal brain when using fresh biopsy samples and, in the case of glioblastomas, to compare the performance of Raman spectroscopy to predict the presence or absence of tumor with that of 5-aminolevulinic acid (5-ALA)–induced fluorescence.

METHODS

A principal component analysis (PCA)–fed linear discriminant analysis (LDA) machine learning predictive model was built using Raman spectra, acquired ex vivo, from fresh tissue samples of 62 patients with glioma and 11 glioma-free brain samples from individuals undergoing temporal lobectomy for epilepsy. This model was then used to classify Raman spectra from fresh biopsies from resection cavities after functional guided, supramaximal glioma resection. In cases of glioblastoma, 5-ALA–induced fluorescence at the resection cavity biopsy site was recorded, and this was compared with the Raman spectral model prediction for the presence of tumor.

RESULTS

The PCA-LDA predictive model demonstrated 0.96 sensitivity, 0.99 specificity, and 0.99 accuracy for differentiating tumor from normal brain. Twenty-three resection cavity biopsies were taken from 8 patients after supramaximal resection (6 glioblastomas, 2 oligodendrogliomas). Raman spectroscopy showed 1.00 sensitivity, 1.00 specificity, and 1.00 accuracy for predicting tumor versus normal brain in these samples. In the glioblastoma cases, where 5-ALA–induced fluorescence was used, the performance of Raman spectroscopy was significantly better than the predictive value of 5-ALA–induced fluorescence, which showed 0.07 sensitivity, 1.00 specificity, and 0.24 accuracy (p = 0.0009).

CONCLUSIONS

Raman spectroscopy can accurately classify fresh tissue samples into tumor versus normal brain and is superior to 5-ALA–induced fluorescence. Raman spectroscopy could become an important intraoperative tool used in conjunction with 5-ALA–induced fluorescence to guide extent of resection in glioma surgery.