Deep brain stimulation therapy is an effective symptomatic treatment for Parkinson's disease, yet the precise mechanisms responsible for its therapeutic effects remain unclear. Although the targets of deep brain stimulation are grey matter structures, axonal modulation is known to play an important role in deep brain stimulation's therapeutic mechanism. Several white matter structures in proximity to the subthalamic nucleus have been implicated in the clinical benefits of deep brain stimulation for Parkinson's disease. We assessed the connectivity patterns that characterize clinically beneficial electrodes in Parkinson's disease patients, after deep brain stimulation of the subthalamic nucleus. We evaluated 22 patients with Parkinson's disease (11 females, age 57 ± 9.1 years, disease duration 13.3 ± 6.3 years) who received bilateral deep brain stimulation of the subthalamic nucleus at the National Institutes of Health. During an initial electrode screening session, one month after deep brain stimulation implantation, the clinical benefits of each contact were determined. The electrode was localized by coregistering preoperative magnetic resonance imaging and postoperative computer tomography images and the volume of tissue activated was estimated from stimulation voltage and impedance. Brain connectivity for the volume of tissue activated of deep brain stimulation contacts was assessed using probabilistic tractography with diffusion-tensor data. Areas most frequently connected to clinically effective contacts included the thalamus, substantia nigra, brainstem and superior frontal gyrus. A series of discriminant analyses demonstrated that the strength of connectivity to the superior frontal gyrus and the thalamus were positively associated with clinical effectiveness. The connectivity patterns observed in our study suggest that the modulation of white matter tracts directed to the superior frontal gyrus and the thalamus is associated with favourable clinical outcomes and may contribute to the therapeutic effects of deep brain stimulation. Our method can be further developed to reliably identify effective deep brain stimulation contacts and aid in the programming process.
As the COVID-19 pandemic continues to affect the international community, very little is known about its impact on the health and day-to-day activities of people with Parkinson’s disease (PwPD). To better understand the emotional and behavioral consequences of the public health policies implemented to mitigate the spread of SARS-CoV-2 in PwPD, and to explore the factors contributing to accessing alternative health care mechanisms, such as telehealth, we administered an anonymous knowledge, attitude, and practice survey to PwPD and care partners, via the mailing lists of the Parkinson’s Foundation and Columbia University Parkinson’s Disease Center of Excellence with an average response rate of 19.3%. Sufficient information was provided by 1,342 PwPD to be included in the final analysis. Approximately half of respondents reported a negative change in PD symptoms, with 45–66% reporting mood disturbances. Telehealth use increased from 9.7% prior to the pandemic to 63.5% during the pandemic. Higher income and higher education were associated with telehealth use. Services were more often used for doctor’s appointment than physical, occupational, speech, or mental health therapies. Almost half (46%) of PwPD preferred to continue using telehealth always or sometimes after the coronavirus outbreak had ended. Having received support/instruction for telehealth and having a care partner, friend, or family member to help them with the telehealth visit increased the likelihood of continuous use of telehealth after the pandemic ended. Taken together, PD symptoms and management practices were markedly affected by COVID-19. Given the observed demographic limitations of telehealth, expanding its implementation to include additional physical, occupational, psychological, and speech therapies, increasing support for telehealth, as well as reaching underserved (low income) populations is urgently required.
Deep brain stimulation (DBS) is an effective surgical treatment for movement disorders. Although stimulation sites for movement disorders such as Parkinson’s disease are established, the therapeutic mechanisms of DBS remain controversial. Recent research suggests that specific white-matter tract and circuit activation mediates symptom relief. To investigate these questions, we have developed a patient-specific open-source software pipeline called ‘DBSproc’ for (1) localizing DBS electrodes and contacts from postoperative CT images, (2) processing structural and diffusion MRI data, (3) registering all images to a common space, (4) estimating DBS activation volume from patient-specific voltage and impedance, and (5) understanding the DBS contact-brain connectivity through probabilistic tractography. In this paper, we explain our methodology and provide validation with anatomical and tractographic data. This method can be used to help investigate mechanisms of action of DBS, inform surgical and clinical assessments, and define new therapeutic targets.
Brain connectivity profiles seeding from deep brain stimulation (DBS) electrodes have emerged as informative tools to estimate outcome variability across DBS patients. Given the limitations of acquiring and processing patient-specific diffusion-weighted imaging data, most studies have employed normative atlases of the human connectome. To date, it remains unclear whether patient-specific connectivity information would strengthen the accuracy of such analyses. Here, we compared similarities and differences between patient-specific, disease-matched and normative structural connectivity data and retrospective estimation of clinical improvement that they may generate. Data from 33 patients suffering from Parkinson Disease who underwent surgery at three different centers were retrospectively collected. Stimulation-dependent connectivity profiles seeding from active contacts were estimated using three modalities, namely either patient-specific diffusion-MRI data, disease-matched or normative group connectome data (acquired in healthy young subjects). Based on these profiles, models of optimal connectivity were constructed and used to retrospectively estimate the clinical improvement in out of sample data. All three modalities resulted in highly similar optimal connectivity profiles that could largely reproduce findings from prior research based on a novel multi-center cohort. Connectivity estimates seeding from electrodes when using either patient-specific or normative connectomes correlated significantly to primary motor cortex (R = 0.57, p = 0.001, R=0.73, p=0.001), supplementary motor area (R = 0.40, p = 0.005, R = 0.43, p = 0.003), pre-supplementary motor area (R = 0.33, p = 0.022, R = 0.33, p = 0.031), but not to more frontal regions such as the dorsomedial prefrontal cortex (R = 0.21, p = 0.17, R = 0.18, p = 0.17). However, in a data-driven approach that estimated optimal whole-brain connectivity profiles, out-of-sample estimation of clinical improvements were made and ranged within a similar magnitude when applying either of the three modalities (R = 0.43 at p = 0.001 for patient-specific connectivity; R = 0.25, p = 0.048 for the age- and disease-matched group connectome; R = 0.31 at p = 0.028 for healthy-/young connectome). Conclusions: The use of patient-specific connectivity and normative connectomes lead to identical main conclusions about which brain areas are associated with clinical improvement. Still, although results were not significantly different, they hint at the fact that patient-specific connectivity may bear the potential of estimating slightly more variance when compared to group connectomes. Our findings further support the role of DBS electrode connectivity profiles as a promising method to guide surgical targeting and DBS programming.
Background With the explosion of COVID-19 globally, it was unclear if people with Parkinson’s disease (PD) were at increased risk for severe manifestations or negative outcomes. Objectives To report on people with PD who had suspected or confirmed COVID-19 to understand how COVID-19 manifested in PD patients. Methods We surveyed PD patients who reported COVID-19 to their Movement Disorders specialists at Columbia University Irving Medical Center and respondents from an online survey administered by the Parkinson’s Foundation that assessed COVID-19 symptoms, general clinical outcomes and changes in motor and non-motor PD symptoms. Results Forty-six participants with PD and COVID-19 were enrolled. Similar to the general population, the manifestations of COVID-19 among people with PD were heterogeneous ranging from asymptomatic carriers (1/46) to death (6/46). The most commonly reported COVID-19 symptoms were fever/chills, fatigue, cough, weight loss, and muscle pain. Worsening and new onset of motor and non-motor PD symptoms during COVID-19 illness were also reported, including dyskinesia, rigidity, balance disturbances, anxiety, depression, and insomnia. Conclusion We did not find sufficient evidence that PD is an independent risk factor for severe COVID-19 and death. Larger studies with controls are required to understand this further. Longitudinal follow-up of these participants will allow for observation of possible long-term effects of COVID-19 in PD patients. Supplementary Information The online version contains supplementary material available at 10.1007/s00415-021-10784-3.
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