Application of MRI Connectivity in Stereotactic Functional Neurosurgery

This thesis examines potential applications of advanced MRI-connectivity studies in stereotactic functional neurosurgery. Several new analysis methodologies are employed to: (1) build predictive models of DBS surgery outcome; (2) refine the surgical target and (3) help build a better understanding of the pathogenesis of the treated conditions and the mechanism of action of DBS therapy. The experimental component is divided into three main parts focusing on the following pathologies: (1) Parkinson’s disease (PD), (2) tremor and (3) trigeminal autonomic cephalalgias (TAC). Section I: In the first experiment (chapter 3), resting state fMRI was used to find radiological biomarkers predictive of response to L-DOPA in 19 patients undergoing subthalamic nucleus (STN) DBS for PD. A greater improvement in UPDRS-III scores following L-DOPA administration was characterized by higher resting state functional connectivity (fcMRI) between the prefrontal cortex and the striatum (p=0.001) and lower fcMRI between the pallidum (p=0.001), subthalamic nucleus (p=0.003) and the paracentral lobule. In the second experiment (chapter 4), structural (diffusion) connectivity was used to map out the influence of the hyperdirect pathways on outcome and identify the therapeutic ‘sweet spots’ in twenty PD patients undergoing STN-DBS. Clusters corresponding to maximum improvement in symptoms were in the posterior, superior and lateral portion of the STN. Greater connectivity to the primary motor area, supplementary motor area and prefrontal cortex was predictive of higher improvement in tremor, bradykinesia and rigidity, and rigidity respectively. The third experiment (chapter 5) examined pyramidal tract (PT) activation in 20 PD patients with STN-DBS. Volume of tissue activation (VTA) around DBS contacts were modelled in relation to the PT. VTA/ PT overlap predicted EMG activation thresholds. Sections II: Pilot data suggest that probabilistic tractography techniques can be used to segment the ventrolateral (VL) and ventroposterior (VP) thalamus based on cortical and cerebellar connectivity in nine patients who underwent thalamic DBS for tremor (chapter 6). The thalamic area, best representing the ventrointermedialis nucleus (VIM), was connected to the contralateral dentate cerebellar nucleus. Streamlines corresponding to the dentato-rubro-thalamic tract (DRT) connected M1 to the contralateral dentate nucleus via the dentato-thalamic area. Good response was seen when the active contact’s VTA was in the thalamic area with the highest connectivity to the contralateral dentate nucleus. Section III: The efficacy and safety of DBS in the ventral tegmental area (VTa) in the treatment of chronic cluster headache (CH) and short lasting unilateral neuralgiform headache attacks (SUNA) were examined (chapters 7 and 8). The optimum stimulation site within the VTa that best controls symptoms was explored (chapter 9). The average responders’ deep brain stimulation activation volume lay on the trigemino-hypothalamic tract, connecting the trigeminal system and other nociceptive brainstem nuclei, with the hypothalamus, and the prefrontal and mesial temporal areas

Spinal Cord Stimulation for Gait Disorders in Parkinson's Disease

BACKGROUND: Spinal cord stimulation (SCS) is a therapeutic procedure widely used in the management of refractory chronic pain. Evidence from case reports and small descriptive studies has emerged suggesting a role for SCS in patients with gait dysfunction, such as freezing of gait (FoG) and postural imbalance. These are severely debilitating symptoms of advanced Parkinson's disease (PD). OBJECTIVE: To establish the current evidence base for the potential application of SCS on gait and balance dysfunction in PD patients. METHODS: Three online databases were screened for relevant manuscripts. Two separate searches and four different search strategies were applied to yield relevant results. The main parameters of interest were postural and gait symptoms; secondary outcomes were Quality of Life (QoL) and adverse effects. RESULTS: Nineteen studies fulfilled the inclusion criteria. Motor improvements using section III of the Unified Parkinson's Disease Rating Score (UPDRS-III) were available in 13 studies. Measurements to assess FoG reported the following improvements: FoG questionnaires (in 1/19 studies); generalized freezing parameters (2); and walkway/wireless accelerometer measurements (2). Parameters of postural imbalance and falling improved as follows: BBS (1); posture sagittal vertical axis (1); and generalized data on postural instability (8). Two studies reported on adverse effects. QoL was shown to improve as follows: EQ-5D (2); ADL (1); SF-36 (1); BDI-II (1); PDQ-8 (1); HDRS (1); and VAS (5). CONCLUSION: SCS may have a therapeutic potential in advanced PD patients suffering from postural and gait-related symptoms. The existing evidence suggests that SCS positively affects patients' QoL with an acceptable safety profile in this patient population

Keep your Distance: Determining Sampling and Distance Thresholds in Machine Learning Monitoring

Machine Learning~(ML) has provided promising results in recent years across different applications and domains. However, in many cases, qualities such as reliability or even safety need to be ensured. To this end, one important aspect is to determine whether or not ML components are deployed in situations that are appropriate for their application scope. For components whose environments are open and variable, for instance those found in autonomous vehicles, it is therefore important to monitor their operational situation to determine its distance from the ML components' trained scope. If that distance is deemed too great, the application may choose to consider the ML component outcome unreliable and switch to alternatives, e.g. using human operator input instead. SafeML is a model-agnostic approach for performing such monitoring, using distance measures based on statistical testing of the training and operational datasets. Limitations in setting SafeML up properly include the lack of a systematic approach for determining, for a given application, how many operational samples are needed to yield reliable distance information as well as to determine an appropriate distance threshold. In this work, we address these limitations by providing a practical approach and demonstrate its use in a well known traffic sign recognition problem, and on an example using the CARLA open-source automotive simulator

Subthalamic nucleus deep brain stimulation for Parkinson's disease: current trends and future directions

Over the last three decades, extensive basic and clinical research has been performed on the use of subthalamic nucleus (STN) as the preferred deep brain stimulation (DBS) target for the treatment of Parkinson's disease (PD). The mechanism underlying the benefit for the motor symptoms in PD is related to the modulation of firing patterns within the hyperdirect projections from motor cortical areas, as well as within the afferent and efferent fibers to the motor STN. Advancements in neuroimaging techniques allow us to identify precisely the STN optimizing surgical targeting. In this review, we provide an update on the current uses of STN-DBS as a routine therapy as well as its experimental indications in PD, the critical aspects associated with its successful implementation and recent advances in DBS technology

Clinical outcomes after MRI connectivity-guided radiofrequency thalamotomy for tremor

OBJECTIVE: Radiofrequency thalamotomy (RF-T) is an established treatment for refractory tremor. It is unclear whether connectivity-guided targeting strategies could further augment outcomes. The aim of this study was to evaluate the efficacy and safety of MRI connectivity-guided RF-T in severe tremor. METHODS: Twenty-one consecutive patients with severe tremor (14 with essential tremor [ET], 7 with Parkinson's disease [PD]) underwent unilateral RF-T at a single institution between 2017 and 2020. Connectivity-derived thalamic segmentation was used to guide targeting. Changes in the Fahn-Tolosa-Marin Rating Scale (FTMRS) were recorded in treated and nontreated hands as well as procedure-related side effects. RESULTS: Twenty-three thalamotomies were performed (with 2 patients receiving a repeated intervention). The mean postoperative assessment time point was 14.1 months. Treated-hand tremor scores improved by 63.8%, whereas nontreated-hand scores deteriorated by 10.1% (p < 0.01). Total FTMRS scores were significantly better at follow-up compared with baseline (mean 34.7 vs 51.7, p = 0.016). Baseline treated-hand tremor severity (rho = 0.786, p < 0.01) and total FTMRS score (rho = 0.64, p < 0.01) best correlated with tremor improvement. The most reported side effect was mild gait ataxia (n = 11 patients). CONCLUSIONS: RF-T guided by connectivity-derived segmentation is a safe and effective option for severe tremor in both PD and ET

Subthalamic deep brain stimulation sweet spots and hyperdirect cortical connectivity in Parkinson’s disease

Objectives Firstly, to identify subthalamic region stimulation clusters that predict maximum improvement in rigidity, bradykinesia and tremor, or emergence of side-effects; and secondly, to map-out the cortical fingerprint, mediated by the hyperdirect pathways which predict maximum efficacy. Methods High angular resolution diffusion imaging in twenty patients with advanced Parkinson’s disease was acquired prior to bilateral subthalamic nucleus deep brain stimulation. All contacts were screened one-year from surgery for efficacy and side-effects at different amplitudes. Voxel-based statistical analysis of volumes of tissue activated models was used to identify significant treatment clusters. Probabilistic tractography was employed to identify cortical connectivity patterns associated with treatment efficacy. Results All patients responded well to treatment (46% mean improvement off medication UPDRS-III [p<0.0001]) without significant adverse events. Cluster corresponding to maximum improvement in tremor was in the posterior, superior and lateral portion of the nucleus. Clusters corresponding to improvement in bradykinesia and rigidity were nearer the superior border in a further medial and posterior location. The rigidity cluster extended beyond the superior border to the area of the zona incerta and Forel-H2 field. When the clusters where averaged, the coordinates of the area with maximum overall efficacy was X=-10(-9.5), Y=-13(-1) and Z=-7(-3) in MNI(AC-PC) space. Cortical connectivity to primary motor area was predictive of higher improvement in tremor; whilst that to supplementary motor area was predictive of improvement in bradykinesia and rigidity; and connectivity to prefrontal cortex was predictive of improvement in rigidity. Interpretation These findings support the presence of overlapping stimulation sites within the subthalamic nucleus and its superior border, with different cortical connectivity patterns, associated with maximum improvement in tremor, rigidity and bradykinesia

Accuracy, precision, and safety of stereotactic, frame-based, intraoperative MRI-guided and MRI-verified deep brain stimulation in 650 consecutive procedures

OBJECTIVE: Suboptimal lead placement is one of the most common indications for deep brain stimulation (DBS) revision procedures. Confirming lead placement in relation to the visible anatomical target with dedicated stereotactic imaging before terminating the procedure can mitigate this risk. In this study, the authors examined the accuracy, precision, and safety of intraoperative MRI (iMRI) to both guide and verify lead placement during frame-based stereotactic surgery. METHODS: A retrospective analysis of 650 consecutive DBS procedures for targeting accuracy, precision, and perioperative complications was performed. Frame-based lead placement took place in an operating room equipped with an MRI machine using stereotactic images to verify lead placement before removing the stereotactic frame. Immediate lead relocation was performed when necessary. Systematic analysis of the targeting error was calculated. RESULTS: Verification of 1201 DBS leads with stereotactic MRI was performed in 643 procedures and with stereotactic CT in 7. The mean ± SD of the final targeting error was 0.9 ± 0.3 mm (range 0.1-2.3 mm). Anatomically acceptable lead placement was achieved with a single brain pass for 97% (n = 1164) of leads; immediate intraoperative relocation was performed in 37 leads (3%) to obtain satisfactory anatomical placement. General anesthesia was used in 91% (n = 593) of the procedures. Hemorrhage was noted after 4 procedures (0.6%); 3 patients (0.4% of procedures) presented with transient neurological symptoms, and 1 experienced delayed cognitive decline. Two bleeds coincided with immediate relocation (2 of 37 leads, 5.4%), which contrasts with hemorrhage in 2 (0.2%) of 1164 leads implanted on the first pass (p = 0.0058). Three patients had transient seizures in the postoperative period. The seizures coincided with hemorrhage in 2 of these patients and with immediate lead relocation in the other. There were 21 infections (3.2% of procedures, 1.5% in 3 months) leading to hardware removal. Delayed (> 3 months) retargeting of 6 leads (0.5%) in 4 patients (0.6% of procedures) was performed because of suboptimal stimulation benefit. There were no MRI-related complications, no permanent motor deficits, and no deaths. CONCLUSIONS: To the authors' knowledge, this is the largest series reporting the use of iMRI to guide and verify lead location during DBS surgery. It demonstrates a high level of accuracy, precision, and safety. Significantly higher hemorrhage was encountered when multiple brain passes were required for lead implantation, although none led to permanent deficit. Meticulous audit and calibration can improve precision and maximize safety

Normative vs. patient-specific brain connectivity in deep brain stimulation

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, a number of 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 estimation of clinical improvement that they may generate. Data from 33 patients suffering from Parkinson's 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 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. In a data-driven approach that estimated optimal whole-brain connectivity profiles, out-of-sample predictions of clinical improvements were calculated. Using either patient-specific connectivity (R = 0.43 at p = 0.001), an age- and disease-matched group connectome (R = 0.25, p = 0.048) and a normative connectome based on healthy/young subjects (R = 0.31 at p = 0.028), significant predictions could be made and underlying optimal connectivity profiles were highly similar. Our results of patient-specific connectivity and normative connectomes lead to similar 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. Furthermore, use of normative connectomes involves datasets with high signal-to-noise acquired on specialized MRI hardware, while clinical datasets as the ones used here may not exactly match their quality. Our findings support the role of DBS electrode connectivity profiles as a promising method to investigate DBS effects and to potentially guide DBS programming

Modulation of limbic resting-state networks by subthalamic nucleus deep brain stimulation

Beyond the established effects of subthalamic nucleus deep brain stimulation (STN-DBS) in reducing motor symptoms in Parkinson’s disease, recent evidence has highlighted the effect on non-motor symptoms. However, the impact of STN-DBS on disseminated networks remains unclear. This study aimed to perform a quantitative evaluation of network-specific modulation induced by STN-DBS using Leading Eigenvector Dynamics Analysis (LEiDA). We calculated the occupancy of resting-state networks (RSNs) in functional MRI data from 10 patients with Parkinson’s disease implanted with STN-DBS and statistically compared between ON and OFF conditions. STN-DBS was found to specifically modulate the occupancy of networks overlapping with limbic RSNs. STN-DBS significantly increased the occupancy of an orbitofrontal limbic subsystem with respect to both DBS OFF (p = 0.0057) and 49 age-matched healthy controls (p = 0.0033). Occupancy of a diffuse limbic RSN was increased with STN-DBS OFF when compared with healthy controls (p = 0.021), but not when STN-DBS was ON, which indicates rebalancing of this network. These results highlight the modulatory effect of STN-DBS on components of the limbic system, particularly within the orbitofrontal cortex, a structure associated with reward processing. These results reinforce the value of quantitative biomarkers of RSN activity in evaluating the disseminated impact of brain stimulation techniques and the personalization of therapeutic strategies