Computational methods and technologies are critical for neurosurgery in general and in deep brain stimulation (DBS) in particular. They increasingly inform every aspect of clinical DBS therapy, from presurgical planning and hardware implantation to postoperative adjustment of stimulation parameters. Computational methods also occupy a prominent position within the DBS research sphere, where they facilitate efforts to better understand DBS' underlying mechanisms and optimize and individualize its delivery. This chapter provides a high-level overview of the various computational tools and methods that have been applied to DBS. First, we discuss the invaluable contribution of computational neuroimaging (primarily magnetic resonance imaging) to DBS, targeting and the role of postoperative methods of image analysis-specifically, electrode localization, volume of activated tissue modeling, and sweet-spot mapping-in precisely localizing DBS' targets in the brain and discerning optimal treatment loci. We then address the growing field of connectomics, which leverages specific magnetic resonance imaging (MRI) sequences and post-acquisition processing algorithms to explore how DBS operates at the level of brain-wide networks. Next, the search for electrophysiological and imaging-based biomarkers of optimal DBS therapy is explored. We lastly touch on the incipient field of spatial characterization analysis and discuss the ongoing development of adaptive, closed-loop DBS systems.
Background: Deep brain stimulation of the subcallosal cingulate area (SCC-DBS) is a promising neuromodulatory therapy for treatment-resistant depression (TRD). Biomarkers of optimal target engagement are needed to guide surgical targeting and stimulation parameter selection and to reduce variance in clinical outcome. Objective/Hypothesis: We aimed to characterize the relationship between stimulation location, white matter tract engagement, and clinical outcome in a large (n = 60) TRD cohort treated with SCC-DBS. A smaller cohort (n = 22) of SCC-DBS patients with differing primary indications (bipolar disorder/anorexia nervosa) was utilized as an out-of-sample validation cohort. Methods: Volumes of tissue activated (VTAs) were constructed in standard space using high-resolution structural MRI and individual stimulation parameters. VTA-based probabilistic stimulation maps (PSMs) were generated to elucidate voxelwise spatial patterns of efficacious stimulation. A whole-brain tractogram derived from Human Connectome Project diffusion-weighted MRI data was seeded with VTA pairs, and white matter streamlines whose overlap with VTAs related to outcome (‘discriminative’ streamlines; Puncorrected < 0.05) were identified using t-tests. Linear modelling was used to interrogate the potential clinical relevance of VTA overlap with specific structures. Results: PSMs varied by hemisphere: high-value left-sided voxels were located more anterosuperiorly and squarely in the lateral white matter, while the equivalent right-sided voxels fell more posteroinferiorly and involved a greater proportion of grey matter. Positive discriminative streamlines localized to the bilateral (but primarily left) cingulum bundle, forceps minor/rostrum of corpus callosum, and bilateral uncinate fasciculus. Conversely, negative discriminative streamlines mostly belonged to the right cingulum bundle and bilateral uncinate fasciculus. The best performing linear model, which utilized information about VTA volume overlap with each of the positive discriminative streamline bundles as well as the negative discriminative elements of the right cingulum bundle, explained significant variance in clinical improvement in the primary TRD cohort (R = 0.46, P < 0.001) and survived repeated 10-fold cross-validation (R = 0.50, P = 0.040). This model was also able to predict outcome in the out-of-sample validation cohort (R = 0.43, P = 0.047). Conclusion(s): These findings reinforce prior indications of the importance of white matter engagement to SCC-DBS treatment success while providing new insights that could inform surgical targeting and stimulation parameter selection decisions.
Subcallosal cingulate deep brain stimulation produces long-term clinical improvement in approximately half of patients with severe treatment-resistant depression. We hypothesized that both structural and functional brain attributes may be important in determining responsiveness to this therapy. In a treatment-resistant depression subcallosal cingulate deep brain stimulation cohort, we retrospectively examined baseline and longitudinal differences in MRI-derived brain volume (n = 65) and 18F-fluorodeoxyglucose-PET glucose metabolism (n = 21) between responders and non-responders. Support vector machines were subsequently trained to classify patients’ response status based on extracted baseline imaging features. A machine learning model incorporating preoperative frontopolar, precentral/frontal opercular and orbitofrontal local volume values classified binary response status (12 months) with 83% accuracy [leave-one-out cross-validation (LOOCV): 80% accuracy] and explained 32% of the variance in continuous clinical improvement. It was also predictive in an out-of-sample subcallosal cingulate deep brain stimulation cohort (n = 21) with differing primary indications (bipolar disorder/anorexia nervosa; 76% accuracy). Adding preoperative glucose metabolism information from rostral anterior cingulate cortex and temporal pole improved model performance, enabling it to predict response status in the treatment-resistant depression cohort with 86% accuracy (LOOCV: 81% accuracy) and explain 67% of clinical variance. Response-related patterns of metabolic and structural post-deep brain stimulation change were also observed, especially in anterior cingulate cortex and neighbouring white matter. Areas where responders differed from non-responders—both at baseline and longitudinally—largely overlapped with depression-implicated white matter tracts, namely uncinate fasciculus, cingulum bundle and forceps minor/rostrum of corpus callosum. The extent of patient-specific engagement of these same tracts (according to electrode location and stimulation parameters) also served as an independent predictor of treatment-resistant depression response status (72% accuracy; LOOCV: 70% accuracy) and augmented performance of the volume-based (88% accuracy; LOOCV: 82% accuracy) and combined volume/metabolism-based support vector machines (100% accuracy; LOOCV: 94% accuracy). Taken together, these results indicate that responders and non-responders to subcallosal cingulate deep brain stimulation exhibit differences in brain volume and metabolism, both pre- and post-surgery. Moreover, baseline imaging features predict response to treatment (particularly when combined with information about local tract engagement) and could inform future patient selection and other clinical decisions.
The habenula (Hb) is a small, evolutionarily conserved epithalamic structure implicated in functions such as reward and mood regulation. Prior imaging work suggests that Hb's structural and functional properties may relate to treatment response in depression and other mood disorders. We used multimodal MRI techniques to investigate the potential involvement of Hb in response to subcallosal cingulate area deep brain stimulation (SCC-DBS) for treatment-resistant mood disorders. Using an automated segmentation technique, we compared Hb volume at baseline and at a subsequent post-operative timepoint (4.4 ± 3.0 years after surgery) in a cohort of 32 patients who received SCC-DBS. Clinical response to treatment (≥50% decrease in HAMD-17 from baseline to 12 months post-operation) was significantly associated with longitudinal Hb volume change: responders tended to have increased Hb volume over time, while non-responders showed decreased Hb volume (t = 2.4, p = 0.021). We additionally used functional MRI (fMRI) in a subcohort of SCC-DBS patients (n = 12) to investigate immediate within-patient changes in Hb functional connectivity associated with SCC-DBS stimulation. Active DBS was significantly associated with increased Hb connectivity to several prefrontal and corticolimbic regions (TFCE-adjusted pBonferroni < 0.0001), many of which have been previously implicated in the neurocircuitry of depression. Taken together, our results suggest that Hb may play an important role in the antidepressant effect of SCC-DBS.
BackgroundNumerous neuromodulatory therapies are currently under investigation or in clinical use for the treatment of psychiatric conditions.Objective/hypothesisWe sought to catalogue past and present human research studies on psychiatric neuromodulation and identify relevant trends in this field.MethodsClinicalTrials.gov (https://www.clinicaltrials.gov/) and the International Clinical Trials Registry Platform (https://www.who.int/ictrp/en/) were queried in March 2020 for trials assessing the outcome of neuromodulation for psychiatric disorders. Relevant trials were categorized by variables such as neuromodulation modality, country, brain target, publication status, design, and funding source.ResultsFrom 72,086 initial search results, 1252 unique trials were identified. The number of trials registered annually has consistently increased. Half of all trials were active and a quarter have translated to publications. The largest proportion of trials involved depression (45%), schizophrenia (18%), and substance use disorders (14%). Trials spanned 37 countries; China, the second largest contributor (13%) after the United States (28%), has increased its output substantially in recent years. Over 75% of trials involved non-convulsive non-invasive modalities (e.g., transcranial magnetic stimulation), while convulsive (e.g., electroconvulsive therapy) and invasive modalities (e.g., deep brain stimulation) were less represented. 72% of trials featured approved or cleared interventions. Characteristic inter-modality differences were observed with respect to enrollment size, trial design/phase, and funding. Dorsolateral prefrontal cortex accounted for over half of focal neuromodulation trial targets. The proportion of trials examining biological correlates of neuromodulation has increased.Conclusion(s)These results provide a comprehensive overview of the state of psychiatric neuromodulation research, revealing the growing scope and internationalism of this field.
Abstract BACKGROUND The therapeutic challenge of glioblastoma (GBM) has catalyzed the development of clinical trials to evaluate novel interventions. With increased understanding of GBM biology and technological advances, the neurosurgeon's role in neuro-oncology has evolved. OBJECTIVE To evaluate the current landscape of procedure-based clinical trials for GBM to characterize this evolution, gain insight into past failures, and accordingly outline implications for future research and practice that may inform future studies. METHODS The ClinicalTrials.gov database was searched for surgical/procedural trials in individuals with GBM. Demographics, specific intervention, trial phase, and main outcome measures were abstracted. RESULTS A total of 224 of 2311 GBM trials (9.7%) were identified as procedural, with the majority being based in the United States (155/224, 69.2%), single-center (155/224, 69.2%), and not randomized (176/224, 78.6%). Primary and recurrent GBMs were evenly addressed. The leading interventions were local delivery of therapeutics (50.0%), surgical techniques (33.9%), such as image-guided surgery, and novel device applications (14.3%). Phase I designs predominated (82/224, 36.6%). The top primary outcome was safety/tolerability/feasibility (88/224, 39.3%), followed by survival (46/224, 20.5%). Approximately 17% of studies were terminated, withdrawn, or suspended. Fifty-two linked publications were identified, among which 42 were classified as having a positive result. CONCLUSION Procedural interventions comprised ∼10% of all registered GBM trials. Local delivery of therapeutics, use of surgical imaging techniques and novel device applications, predominantly through phase I designs, represent the evolved role of the neurosurgeon in neuro-oncology. Improved reporting of trial designs, outcomes, and results are needed to better inform the field and increase efficiency.
Background: Chronic pain is a debilitating condition that imposes a tremendous burden on health-care systems around the world. While frontline treatments for chronic pain involve pharmacological and psychological approaches, neuromodulation can be considered for treatment-resistant cases. Neuromodulatory approaches for pain are diverse in both modality and target and their mechanism of action is incompletely understood. Objectives: The objectives of this study were to (i) understand the current landscape of pain neuromodulation research through a comprehensive survey of past and current registered clinical trials (ii) investigate the network underpinnings of these neuromodulatory treatments by performing a connectomic mapping analysis of cortical and subcortical brain targets that have been stimulated for pain relief. Methods: A search for clinical trials involving pain neuromodulation was conducted using 2 major trial databases (ClinicalTrials.gov and the International Clinical Trials Registry Platform). Trials were categorized by variables and analyzed to gain an overview of the contemporary research landscape. Additionally, a connectomic mapping analysis was performed to investigate the network connectivity patterns of analgesic brain stimulation targets using a normative connectome based on a functional magnetic resonance imaging dataset. Results: In total, 487 relevant clinical trials were identified. Noninvasive cortical stimulation and spinal cord stimulation trials represented 49.3 and 43.7% of this count, respectively, while deep brain stimulation trials accounted for <3%. The mapping analysis revealed that superficial target connectomics overlapped with deep target connectomics, suggesting a common pain network across the targets. Conclusions: Research for pain neuromodulation is a rapidly growing field. Our connectomic network analysis reinforced existing knowledge of the pain matrix, identifying both well-described hubs and more obscure structures. Further studies are needed to decode the circuits underlying pain relief and determine the most effective targets for neuromodulatory treatment.
Using 3T functional MRI, Elias et al. show that subcallosal cingulate DBS acutely alters activity in brain regions implicated in mood, including dorsal anterior cingulate cortex, in patients with symptoms of depression. The observed changes correlate with both immediate mood fluctuations and long-term antidepressant outcomes. Deep brain stimulation targeting the subcallosal cingulate area, a hub with multiple axonal projections, has shown therapeutic potential for treatment-resistant mood disorders. While subcallosal cingulate deep brain stimulation drives long-term metabolic changes in corticolimbic circuits, the brain areas that are directly modulated by electrical stimulation of this region are not known. We used 3.0 T functional MRI to map the topography of acute brain changes produced by stimulation in an initial cohort of 12 patients with fully implanted deep brain stimulation devices targeting the subcallosal cingulate area. Four additional subcallosal cingulate deep brain stimulation patients were also scanned and employed as a validation cohort. Participants underwent resting state scans (n = 78 acquisitions overall) during (i) inactive deep brain stimulation; (ii) clinically optimal active deep brain stimulation; and (iii) suboptimal active deep brain stimulation. All scans were acquired within a single MRI session, each separated by a 5-min washout period. Analysis of the amplitude of low-frequency fluctuations in each sequence indicated that clinically optimal deep brain stimulation reduced spontaneous brain activity in several areas, including the bilateral dorsal anterior cingulate cortex, the bilateral posterior cingulate cortex, the bilateral precuneus and the left inferior parietal lobule (P-Bonferroni < 0.0001). Stimulation-induced dorsal anterior cingulate cortex signal reduction correlated with immediate within-session mood fluctuations, was greater at optimal versus suboptimal settings and was related to local cingulum bundle engagement. Moreover, linear modelling showed that immediate changes in dorsal anterior cingulate cortex, posterior cingulate cortex and precuneus activity could predict individual long-term antidepressant improvement. A model derived from the primary cohort that incorporated amplitude of low-frequency fluctuations changes in these three areas (along with preoperative symptom severity) explained 55% of the variance in clinical improvement in that cohort. The same model also explained 93% of the variance in the out-of-sample validation cohort. Additionally, all three brain areas exhibited significant changes in functional connectivity between active and inactive deep brain stimulation states (P-Bonferroni < 0.01). These results provide insight into the network-level mechanisms of subcallosal cingulate deep brain stimulation and point towards potential acute biomarkers of clinical response that could help to optimize and personalize this therapy.
BACKGROUND:Deep brain stimulation (DBS) is a surgical neuromodulation procedure with a historically wide range of possible therapeutic indications, including movement disorders, neuropsychiatric conditions, and cognitive disorders. Ongoing research in this field is critical to gain further insights into the mechanisms of DBS, to discover novel brain targets for new and existing indications, and to refine targeting and post-operative programming techniques for the optimization of therapeutic outcomes.OBJECTIVE:To update on the state of DBS-related clinical human research by cataloging and summarizing clinical trials that have been completed or are currently ongoing in this field worldwide.METHODS:A search was conducted for clinical trials pertaining to DBS, currently listed on the ClinicalTrials.gov database. Trials were analyzed to generate a detailed overview of ongoing DBS-related research. Specifically, trials were categorized by trial start date, study completion status, clinical phase, projected subject enrollment, disorder, brain target, country of origin, device manufacturer, funding source, and study topic.RESULTS:In total, 384 relevant clinical trials were identified. The trials spanned 28 different disorders across 26 distinct brain targets, with almost 40% of trials being for conditions other than movement disorders. The majority of DBS trials have been US-based (41.9% of studies) but many countries are becoming increasingly active. The ratio of investigator-sponsored to industry-sponsored trials was 3:1. Emphasizing the need to better understand the mechanism of action of DBS, one-third of the studies predominantly focus on imaging or electrophysiological changes associated with DBS.CONCLUSIONS:This overview of current DBS-related clinical trials provides insight into the status of DBS research and what we can anticipate in the future concerning new brain targets, indications, techniques, and developing a better understanding of the mechanisms of action of DBS.
Deep brain stimulation (DBS) depends on precise delivery of electrical current to target tissues. However, the specific brain structures responsible for best outcome are still debated. We applied probabilistic stimulation mapping to a retrospective, multidisorder DBS dataset assembled over 15 years at our institution (ntotal = 482 patients; nParkinson disease = 303; ndystonia = 64; ntremor = 39; ntreatment‐resistant depression/anorexia nervosa = 76) to identify the neuroanatomical substrates of optimal clinical response. Using high‐resolution structural magnetic resonance imaging and activation volume modeling, probabilistic stimulation maps (PSMs) that delineated areas of above‐mean and below‐mean response for each patient cohort were generated and defined in terms of their relationships with surrounding anatomical structures. Our results show that overlap between PSMs and individual patients' activation volumes can serve as a guide to predict clinical outcomes, but that this is not the sole determinant of response. In the future, individualized models that incorporate advancements in mapping techniques with patient‐specific clinical variables will likely contribute to the optimization of DBS target selection and improved outcomes for patients. ANN NEUROL 2021;89:426–443
BACKGROUND:Panic attacks affect a sizeable proportion of the population. The neurocircuitry of panic remains incompletely understood.OBJECTIVE:To investigate the neuroanatomical underpinnings of panic attacks induced by deep brain stimulation (DBS) through (1) connectomic analysis of an obsessive-compulsive disorder patient who experienced panic attacks during inferior thalamic peduncle DBS; (2) appraisal of existing clinical reports on DBS-induced panic attacks.METHODS:Panicogenic, ventral contact stimulation was compared with benign stimulation at other contacts using volume of tissue activated (VTA) modelling. Networks associated with the panicogenic zone were investigated using state-of-the-art normative connectivity mapping. In addition, a literature search for prior reports of DBS-induced panic attacks was conducted.RESULTS:Panicogenic VTAs impinged primarily on the tuberal hypothalamus. Compared to non-panicogenic VTAs, panicogenic loci were significantly functionally coupled to limbic and brainstem structures, including periaqueductal grey and amygdala. Previous studies found stimulation of these areas can also provoke panic attacks.CONCLUSIONS:DBS in the region of the tuberal hypothalamus elicited panic attacks in a single obsessive-compulsive disorder patient and recruited a network of structures previously implicated in panic pathophysiology, reinforcing the importance of the hypothalamus as a hub of panicogenic circuitry.
Abstract BACKGROUND Surgery continues to be part of the mainstay of therapy for most primary CNS tumors. However, neurosurgical innovations advancing treatment options have stagnated. An understanding of past and current investigational trends is necessary to catalyze innovation in surgical trials. OBJECTIVE To evaluate the landscape of surgical clinical trials for non-diffusely infiltrating primary CNS tumors. METHODS ClinicalTrials.gov was searched on May 14th, 2019 for surgical/procedural trials based on non-diffusely infiltrating primary CNS tumors, with a focus on meningiomas, ependymomas, medulloblastomas, pituitary adenomas, vestibular scwhannomas, and chordomas. Key trial design parameters were extracted. Purely surgical interventions were classified as “technical” while fluorescence-guided and other intraoperative imaging modalities were classified as image-guided surgery. Any invasive mode of drug delivery (e.g. intra-arterial or intra-ventricular, local chemotherapy wafers, and oncolytic virus injection) was considered. RESULTS Among 944 total trial records (257 medulloblastomas, 254 ependymomas, 179 meningiomas, 156 pituitary adenomas, 56 vestibular schwannomas, and 48 chordomas) only 54 (5.7%) were procedural in nature. Ependymomas had the highest absolute number (18/254, 7%) while vestibular schwannomas had the highest percentage (6/56, 10.7%) of surgical trials. The majority of records were not randomized (41/54, 75.9%), not industry-funded (45/54, 83.3%), and were early Phase (30/54, 55.6%); there were only three Phase III trials. The relative number of new surgical trial registrations has not changed significantly over time (1990s: 5, 2000s: 19, and 2010s: 30). Approaches integrated with other disciplines, such as image-guided surgery (16/54, 29.6%) and local drug delivery (16/24, 29.6%), were among the leading categories of trials. CONCLUSIONS Despite the clinical role of surgery in management of non-diffusely infiltrating primary CNS tumors, a paucity of innovative surgical trials has been put forth. Multi-disciplinary approaches appear to be necessary for pushing the therapeutic envelope for individuals affected by these tumors, with imaging and drug development at the forefront.
Abstract BACKGROUND The therapeutic challenge of glioblastoma (GBM) has catalyzed the active pursuit of a high volume of clinical trials to evaluate novel interventions for this deadly disease. Our enhanced understanding of the biology of GBMs has translated into an evolution of the role of the neurosurgeon as well. In this study, we have evaluated the current landscape of surgical clinical trials in GBM to characterize this evolution, describe current trends, and identify potential gaps in methodological features. METHODS The ClinicalTrials.gov database was searched for surgical/procedural trials in individuals with GBM on May 14th, 2019 without date limitations. Demographics, specific intervention (e.g. technical, device use, or local drug delivery), phase, sample size, and main outcome measures were abstracted. RESULTS 270 of 2140 trials (12.6%) were identified as procedural. The majority were based in the USA (189/270, 70%), single-center (188/270, 70%), and not randomized by design (215/270, 80%). Primary and recurrent GBMs were evenly addressed. Industry-funding supported 106/270 (39%) of studies. The leading test intervention was local delivery of therapeutics (44.8%), followed by use of novel devices (33%). Surgical technique/procedures comprised 20%. Early Phase designs predominated (177/270, 65.5%) but 67 (24.8%) did not report Phase. The greatest surge in new registrations over the last decade was seen in Phase I trials. The top primary outcome was safety/tolerability/ feasibility (107/270, 39%), followed by survival (62/270, 22%); 35 (12.6%) did not report a primary outcome. Approximately 15% of studies were terminated, withdrawn or suspended. Only 6 records were associated with reported results. CONCLUSIONS In GBMs, procedural interventions comprise a notable proportion of trials. Local delivery of therapeutics and novel device applications, predominantly through Phase I designs, represent the evolved role of the neurosurgeon in neuro-oncology. Improved documentation of design, outcomes, and reporting of results are needed to better inform the field and increase efficiency.