Malignant transformation of a cerebral dermoid cyst into a squamous cell carcinoma with malignant intraperitoneal spreading along a ventriculoperitoneal shunt: illustrative case.

BACKGROUND: Malignant progression of intracranial dermoid cysts into squamous cell carcinoma is extremely rare with only three reports published so far. Intracranial dermoid cysts are uncommon benign tumors lined by stratified squamous epithelium of embryonic ectodermal origin. OBSERVATIONS: Here, the authors present the case of a 64-year-old female with a recurrent temporal dermoid cyst. After surgery for the recurrent dermoid cyst, once in the early 1990s and another 16 years later, the patient presented with headache and nausea due to hydrocephalus. After implantation of a ventriculoperitoneal shunt, she deteriorated rapidly and died only 60 days after admission. Autopsy revealed malignant transformation of the epithelial lining of the dermoid cyst into a squamous cell carcinoma resulting in neoplastic meningiosis and intraperitoneal tumor spread along a previously implanted ventriculoperitoneal shunt. LESSONS: Malignant transformation should be considered in patients with dermoid cyst who show new leptomeningeal contrast enhancement. In the case of hydrocephalus, alternatives to peritoneal shunting should be considered.

Optimal deep brain stimulation sites and networks for cervical vs. generalized dystonia.

Dystonia is a debilitating disease with few treatment options. One effective option is deep brain stimulation (DBS) to the internal pallidum. While cervical and generalized forms of isolated dystonia have been targeted with a common approach to the posterior third of the nucleus, large-scale investigations regarding optimal stimulation sites and potential network effects have not been carried out. Here, we retrospectively studied clinical results following DBS for cervical and generalized dystonia in a multicenter cohort of 80 patients. We model DBS electrode placement based on pre- and postoperative imaging and introduce an approach to map optimal stimulation sites to anatomical space. Second, we investigate which tracts account for optimal clinical improvements, when modulated. Third, we investigate distributed stimulation effects on a whole-brain functional connectome level. Our results show marked differences of optimal stimulation sites that map to the somatotopic structure of the internal pallidum. While modulation of the striatopallidofugal axis of the basal ganglia accounted for optimal treatment of cervical dystonia, modulation of pallidothalamic bundles did so in generalized dystonia. Finally, we show a common multisynaptic network substrate for both phenotypes in the form of connectivity to the cerebellum and somatomotor cortex. Our results suggest a brief divergence of optimal stimulation networks for cervical vs. generalized dystonia within the pallidothalamic loop that merge again on a thalamo-cortical level and share a common whole-brain network.

A brain network for deep brain stimulation induced cognitive decline in Parkinson's disease.

Deep brain stimulation is an effective treatment for Parkinson's disease but can be complicated by side-effects such as cognitive decline. There is often a delay before this side-effect is apparent and the mechanism is unknown, making it difficult to identify patients at risk or select appropriate deep brain stimulation settings. Here, we test whether connectivity between the stimulation site and other brain regions is associated with cognitive decline following deep brain stimulation. First, we studied a unique patient cohort with cognitive decline following subthalamic deep brain stimulation for Parkinson's disease (n = 10) where reprogramming relieved the side-effect without loss of motor benefit. Using resting state functional connectivity data from a large normative cohort (n = 1000), we computed connectivity between each stimulation site and the subiculum, an a priori brain region functionally connected to brain lesions causing memory impairment. Connectivity between deep brain stimulation sites and this same subiculum region was significantly associated with deep brain stimulation induced cognitive decline (P < 0.02). We next performed a data-driven analysis to identify connections most associated with deep brain stimulation induced cognitive decline. Deep brain stimulation sites causing cognitive decline (versus those that did not) were more connected to the anterior cingulate, caudate nucleus, hippocampus, and cognitive regions of the cerebellum (PFWE < 0.05). The spatial topography of this deep brain stimulation-based circuit for cognitive decline aligned with an a priori lesion-based circuit for memory impairment (P = 0.017). To begin translating these results into a clinical tool that might be used for deep brain stimulation programming, we generated a 'heat map' in which the intensity of each voxel reflects the connectivity to our cognitive decline circuit. We then validated this heat map using an independent dataset of Parkinson's disease patients in which cognitive performance was measured following subthalamic deep brain stimulation (n = 33). Intersection of deep brain stimulation sites with our heat map was correlated with changes in the Mattis dementia rating scale 1 year after lead implantation (r = 0.39; P = 0.028). Finally, to illustrate how this heat map might be used in clinical practice, we present a case that was flagged as 'high risk' for cognitive decline based on intersection of the patient's deep brain stimulation site with our heat map. This patient had indeed experienced cognitive decline and our heat map was used to select alternative deep brain stimulation parameters. At 14 days follow-up the patient's cognition improved without loss of motor benefit. These results lend insight into the mechanism of deep brain stimulation induced cognitive decline and suggest that connectivity-based heat maps may help identify patients at risk and who might benefit from deep brain stimulation reprogramming.

Rescuing Suboptimal Outcomes of Subthalamic Deep Brain Stimulation in Parkinson Disease by Surgical Lead Revision.

BACKGROUND: Clinical trials have established subthalamic deep-brain-stimulation (STN-DBS) as a highly effective treatment for motor symptoms of Parkinson disease (PD), but in clinical practice outcomes are variable. Experienced centers are confronted with an increasing number of patients with partially "failed" STN-DBS, in whom motor benefit doesn't meet expectations. These patients require a complex multidisciplinary and standardized workup to identify the likely cause. OBJECTIVE: To describe outcomes in a series of PD patients undergoing lead revision for suboptimal motor benefit after STN-DBS surgery and characterize selection criteria for surgical revision. METHODS: We investigated 9 PD patients with STN-DBS, who had unsatisfactory outcomes despite intensive neurological management. Surgical revision was considered if the ratio of DBS vs levodopa-induced improvement of UPDRS-III (DBS-rr) was below 75% and the electrodes were found outside the dorsolateral STN. RESULTS: Fifteen electrodes were replaced via stereotactic revision surgery into the dorsolateral STN without any adverse effects. Median displacement distance was 4.1 mm (range 1.6-8.42 mm). Motor symptoms significantly improved (38.2 ± 6.6 to 15.5 ± 7.9 points, P < .001); DBS-rr increased from 64% to 190%. CONCLUSION: Patients with persistent OFFmotor symptoms after STN-DBS should be screened for levodopa-responsiveness, which can serve as a benchmark for best achievable motor benefit. Even small horizontal deviations of the lead from the optimal position within the dorsolateral STN can cause stimulation responses, which are markedly inferior to the levodopa response. Patients with an image confirmed lead displacement and preserved levodopa response are candidates for lead revision and can expect significant motor improvement from appropriate lead replacement.

Probabilistic mapping of the antidystonic effect of pallidal neurostimulation: a multicentre imaging study.

Deep brain stimulation of the internal globus pallidus is a highly effective and established therapy for primary generalized and cervical dystonia, but therapeutic success is compromised by a non-responder rate of up to 25%, even in carefully-selected groups. Variability in electrode placement and inappropriate stimulation settings may account for a large proportion of this outcome variability. Here, we present probabilistic mapping data on a large cohort of patients collected from several European centres to resolve the optimal stimulation volume within the pallidal region. A total of 105 dystonia patients with pallidal deep brain stimulation were enrolled and 87 datasets (43 with cervical dystonia and 44 with generalized dystonia) were included into the subsequent 'normative brain' analysis. The average improvement of dystonia motor score was 50.5 ± 30.9% in cervical and 58.2 ± 48.8% in generalized dystonia, while 19.5% of patients did not respond to treatment (<25% benefit). We defined probabilistic maps of anti-dystonic effects by aggregating individual electrode locations and volumes of tissue activated (VTA) in normative atlas space and ranking voxel-wise for outcome distribution. We found a significant relation between motor outcome and the stimulation volume, but not the electrode location per se. The highest probability of stimulation induced motor benefit was found in a small volume covering the ventroposterior globus pallidus internus and adjacent subpallidal white matter. We then used the aggregated VTA-based outcome maps to rate patient individual VTAs and trained a linear regression model to predict individual outcomes. The prediction model showed robustness between the predicted and observed clinical improvement, with an r2 of 0.294 (P < 0.0001). The predictions deviated on average by 16.9 ± 11.6 % from observed dystonia improvements. For example, if a patient improved by 65%, the model would predict an improvement between 49% and 81%. Results were validated in an independent cohort of 10 dystonia patients, where prediction and observed benefit had a correlation of r2 = 0.52 (P = 0.02) and a mean prediction error of 10.3% (±8.9). These results emphasize the potential of probabilistic outcome brain mapping in refining the optimal therapeutic volume for pallidal neurostimulation and advancing computer-assisted planning and programming of deep brain stimulation.