Probabilistic versus deterministic tractography for delineation of the cortico-subthalamic hyperdirect pathway in patients with Parkinson disease selected for deep brain stimulation

Electrophysiological sweet spot mapping in deep brain stimulation for Parkinson's disease patients

BACKGROUND

Subthalamic deep brain stimulation (STN-DBS) is a well-established therapy to treat Parkinson's disease (PD). However, the STN-DBS sub-target remains debated. Recently, a white matter tract termed the hyperdirect pathway (HDP), directly connecting the motor cortex to STN, has gained interest as HDP stimulation is hypothesized to drive DBS therapeutic effects. Previously, we have investigated EEG-based evoked potentials (EPs) to better understand the neuroanatomical origins of the DBS clinical effect. We found a 3-millisecond peak (P3) relating to clinical benefit, and a 10-millisecond peak (P10) suggesting nigral side effects. Here, we aimed to investigate the neuroanatomical origins of DBS EPs using probabilistic mapping.

METHODS

EPs were recorded using EEG whilst low-frequency stimulation was delivered at all DBS-contacts individually. Next, EPs were mapped onto the patients' individual space and then transformed to MNI standard space. Using voxel-wise and fiber-wise probabilistic mapping, we determined hotspots/hottracts and coldspots/coldtracts for P3 and P10. Topography analysis was also performed to determine the spatial distribution of the DBS EPs.

RESULTS

In all 13 patients (18 hemispheres), voxel- and fiber-wise probabilistic mapping resulted in a P3-hotspot/hottract centered on the posterodorsomedial STN border indicative of HDP stimulation, while the P10-hotspot/hottract covered large parts of the substantia nigra.

CONCLUSION

This study investigated EP-based probabilistic mapping in PD patients during STN-DBS, revealing a P3-hotspot/hottract in line with HDP stimulation and P10-hotspot/hottract related to nigral stimulation. Results from this study provide key evidence for an electrophysiological measure of HDP and nigral stimulation.

Mapping dysfunctional circuits in the frontal cortex using deep brain stimulation

Frontal circuits play a critical role in motor, cognitive and affective processing, and their dysfunction may result in a variety of brain disorders. However, exactly which frontal domains mediate which (dys)functions remains largely elusive. We studied 534 deep brain stimulation electrodes implanted to treat four different brain disorders. By analyzing which connections were modulated for optimal therapeutic response across these disorders, we segregated the frontal cortex into circuits that had become dysfunctional in each of them. Dysfunctional circuits were topographically arranged from occipital to frontal, ranging from interconnections with sensorimotor cortices in dystonia, the primary motor cortex in Tourette's syndrome, the supplementary motor area in Parkinson's disease, to ventromedial prefrontal and anterior cingulate cortices in obsessive-compulsive disorder. Our findings highlight the integration of deep brain stimulation with brain connectomics as a powerful tool to explore couplings between brain structure and functional impairments in the human brain.

Connectivity-based segmentation of the thalamic motor region for deep brain stimulation in essential tremor: A comparison of deterministic and probabilistic tractography

OBJECTIVE

Deep brain stimulation (DBS) studies have shown that stimulation of the motor segment of the thalamus based on probabilistic tractography is predictive of improvement in essential tremor (ET). However, probabilistic methods are computationally demanding, requiring the need for alternative tractography methods for use in the clinical setting. The purpose of this study was to compare probabilistic vs deterministic tractography methods for connectivity-based targeting in patients with ET.

METHODS

Probabilistic and deterministic tractography methods were retrospectively applied to diffusion-weighted data sets in 36 patients with refractory ET. The thalamus and precentral gyrus were selected as regions of interest and fiber tracking was performed between these regions to produce connectivity-based thalamic segmentations, per prior methods. The resultant deterministic target maps were compared with those of thresholded probabilistic maps. The center of gravity (CG) of each connectivity map was determined and the differences in spatial distribution between the tractography methods were characterized. Furthermore, the intersection between the connectivity maps and CGs with the therapeutic volume of tissue activated (VTA) was calculated. A mixed linear model was then used to assess clinical improvement in tremor with volume of overlap.

RESULTS

Both tractography methods delineated the region of the thalamus with connectivity to the precentral gyrus to be within the posterolateral aspect of the thalamus. The average CG of deterministic maps was more medial-posterior in both the left (3.7 ± 1.3 mm3) and the right (3.5 ± 2.2 mm3) hemispheres when compared to 30 %-thresholded probabilistic maps. Mixed linear model showed that the volume of overlap between CGs of deterministic and probabilistic targeting maps and therapeutic VTAs were significant predictors of clinical improvement.

CONCLUSIONS

Deterministic tractography can reconstruct DBS thalamic target maps in approximately 5 min comparable to those produced by probabilistic methods that require > 12 h to generate. Despite differences in CG between the methods, both deterministic-based and probabilistic targeting were predictive of clinical improvement in ET.

Fibre orientation atlas guided rapid segmentation of white matter tracts

Fibre tract delineation from diffusion magnetic resonance imaging (MRI) is a valuable clinical tool for neurosurgical planning and navigation, as well as in research neuroimaging pipelines. Several popular methods are used for this task, each with different strengths and weaknesses making them more or less suited to different contexts. For neurosurgical imaging, priorities include ease of use, computational efficiency, robustness to pathology and ability to generalise to new tracts of interest. Many existing methods use streamline tractography, which may require expert neuroimaging operators for setting parameters and delineating anatomical regions of interest, or suffer from as a lack of generalisability to clinical scans involving deforming tumours and other pathologies. More recently, data-driven approaches including deep-learning segmentation models and streamline clustering methods have improved reproducibility and automation, although they can require large amounts of training data and/or computationally intensive image processing at the point of application. We describe an atlas-based direct tract mapping technique called 'tractfinder', utilising tract-specific location and orientation priors. Our aim was to develop a clinically practical method avoiding streamline tractography at the point of application while utilising prior anatomical knowledge derived from only 10-20 training samples. Requiring few training samples allows emphasis to be placed on producing high quality, neuro-anatomically accurate training data, and enables rapid adaptation to new tracts of interest. Avoiding streamline tractography at the point of application reduces computational time, false positives and vulnerabilities to pathology such as tumour deformations or oedema. Carefully filtered training streamlines and track orientation distribution mapping are used to construct tract specific orientation and spatial probability atlases in standard space. Atlases are then transformed to target subject space using affine registration and compared with the subject's voxel-wise fibre orientation distribution data using a mathematical measure of distribution overlap, resulting in a map of the tract's likely spatial distribution. This work includes extensive performance evaluation and comparison with benchmark techniques, including streamline tractography and the deep-learning method TractSeg, in two publicly available healthy diffusion MRI datasets (from TractoInferno and the Human Connectome Project) in addition to a clinical dataset comprising paediatric and adult brain tumour scans. Tract segmentation results display high agreement with established techniques while requiring less than 3 min on average when applied to a new subject. Results also display higher robustness than compared methods when faced with clinical scans featuring brain tumours and resections. As well as describing and evaluating a novel proposed tract delineation technique, this work continues the discussion on the challenges surrounding the white matter segmentation task, including issues of anatomical definitions and the use of quantitative segmentation comparison metrics.

Sensitivity analyses of probabilistic and deterministic DTI tractography methodologies for studying arm muscle architecture

PURPOSE

To determine the sensitivity profiles of probabilistic and deterministic DTI tractography methods in estimating geometric properties in arm muscle anatomy.

METHODS

Spin-echo diffusion-weighted MR images were acquired in the dominant arm of 10 participants. Both deterministic and probabilistic tractography were performed in two different muscle architectures of the parallel-structured biceps brachii (and the pennate-structured flexor carpi ulnaris. Muscle fascicle geometry estimates and number of fascicles were evaluated with respect to tractography turning angle, polynomial fitting order, and SNR. The DTI tractography estimated fascicle lengths were compared with measurements obtained from conventional cadaveric dissection and ultrasound modalities.

RESULTS

The probabilistic method generally estimated fascicle lengths closer to ranges reported by conventional methods than the deterministic method, most evident in the biceps brachii (p > 0.05), consisting of longer, arc-like fascicles. For both methods, a wide turning angle (50º-90°) generated fascicle lengths that were in close agreement with conventional methods, most evident in the flexor carpi ulnaris (p > 0.05), consisting of shorter, feather-like fascicles. The probabilistic approach produced at least two times more fascicles than the deterministic approach. For both approaches, second-order fitting yielded about double the complete tracts as third-order fitting. In both muscles, as SNR decreased, deterministic tractography produced less fascicles but consistent geometry (p > 0.05), whereas probabilistic tractography produced a consistent number but altered geometry of fascicles (p < 0.001).

CONCLUSION

Findings from this study provide best practice recommendations for implementing DTI tractography in skeletal muscle and will inform future in vivo studies of healthy and pathological muscle structure.

Advancements in Diffusion MRI Tractography for Neurosurgery

ABSTRACT

Diffusion magnetic resonance imaging tractography is a noninvasive technique that enables the visualization and quantification of white matter tracts within the brain. It is extensively used in preoperative planning for brain tumors, epilepsy, and functional neurosurgical procedures such as deep brain stimulation. Over the past 25 years, significant advancements have been made in imaging acquisition, fiber direction estimation, and tracking methods, resulting in considerable improvements in tractography accuracy. The technique enables the mapping of functionally critical pathways around surgical sites to avoid permanent functional disability. When the limitations are adequately acknowledged and considered, tractography can serve as a valuable tool to safeguard critical white matter tracts and provides insight regarding changes in normal white matter and structural connectivity of the whole brain beyond local lesions. In functional neurosurgical procedures such as deep brain stimulation, it plays a significant role in optimizing stimulation sites and parameters to maximize therapeutic efficacy and can be used as a direct target for therapy. These insights can aid in patient risk stratification and prognosis. This article aims to discuss state-of-the-art tractography methodologies and their applications in preoperative planning and highlight the challenges and new prospects for the use of tractography in daily clinical practice.

A Retrospective Comparison of Multiple Approaches to Anatomically Informed Contact Selection in Subthalamic Deep Brain Stimulation for Parkinson's Disease

Background

Conventional deep brain stimulation (DBS) programming via trial-and-error warrants improvement to ensure swift achievement of optimal outcomes. The definition of a sweet spot for subthalamic DBS in Parkinson's disease (PD-STN-DBS) may offer such advancement.

Objective

This investigation examines the association of long-term motor outcomes with contact selection during monopolar review and different strategies for anatomically informed contact selection in a retrospective real-life cohort of PD-STN-DBS.

Methods

We compared contact selection based on a monopolar review (MPR) to multiple anatomically informed contact selection strategies in a cohort of 28 PD patients with STN-DBS. We employed a commercial software package for contact selection based on visual assessment of individual anatomy following two predefined strategies and two algorithmic approaches with automatic targeting of either the sensorimotor STN or our previously published sweet spot. Similarity indices between chronic stimulation and contact selection strategies were correlated to motor outcomes at 12 months follow-up.

Results

Lateralized motor outcomes of chronic DBS were correlated to the similarity between chronic stimulation and visual contact selection targeting the dorsal part of the posterior STN (rho = 0.36, p = 0.007). Similar relationships could not be established for MPR or any of the other investigated strategies.

Conclusions

Our data demonstrates that a visual contact selection following a predefined strategy can be linked to beneficial long-term motor outcomes in PD-STN-DBS. Since similar correlations could not be observed for the other approaches to anatomically informed contact selection, we conclude that clear definitions and prospective validation of any approach to imaging-based DBS-programming is warranted.

Dorsal subthalamic nucleus targeting in deep brain stimulation: microelectrode recording versus 7-Tesla connectivity

Connectivity-derived 7-Tesla MRI segmentation and intraoperative microelectrode recording can both assist subthalamic nucleus targeting for deep brain stimulation in Parkinson's disease. It remains unclear whether deep brain stimulation electrodes placed in the 7-Tesla MRI segmented subdivision with predominant projections to cortical motor areas (hyperdirect pathway) achieve superior motor improvement and whether microelectrode recording can accurately distinguish the motor subdivision. In 25 patients with Parkinson's disease, deep brain stimulation electrodes were evaluated for being inside or outside the predominantly motor-connected subthalamic nucleus (motor-connected subthalamic nucleus or non-motor-connected subthalamic nucleus, respectively) based on 7-Tesla MRI connectivity segmentation. Hemi-body motor improvement (Movement Disorder Society Unified Parkinson's Disease Rating Scale, Part III) and microelectrode recording characteristics of multi- and single-unit activities were compared between groups. Deep brain stimulation electrodes placed in the motor-connected subthalamic nucleus resulted in higher hemi-body motor improvement, compared with electrodes placed in the non-motor-connected subthalamic nucleus (80% versus 52%, P < 0.0001). Multi-unit activity was found slightly higher in the motor-connected subthalamic nucleus versus the non-motor-connected subthalamic nucleus (P < 0.001, receiver operating characteristic 0.63); single-unit activity did not differ between groups. Deep brain stimulation in the connectivity-derived 7-Tesla MRI subthalamic nucleus motor segment produced a superior clinical outcome; however, microelectrode recording did not accurately distinguish this subdivision within the subthalamic nucleus.

Structural connections of the centromedian nucleus of thalamus and their relevance for neuromodulation in generalized drug-resistant epilepsy: insight from a tractography study

Background

Epilepsy is a widespread neurologic disorder and almost one-third of patients suffer from drug-resistant epilepsy (DRE). Neuromodulation targeting the centromediannucleus of the thalamus (CM) has been showing promising results for patients with generalized DRE who are not surgical candidates. Recently, the effect of CM- deep brain stimulation (DBS) in DRE patients was investigated in the Electrical Stimulation of Thalamus for Epilepsy of Lennox-Gastaut phenotype (ESTEL) trial, a monocentric randomized-controlled study. The same authors described a 'cold-spot' and a 'sweet-spot', which are defined as the volume of stimulation in the thalamus yielding the least and the best clinical response, respectively. However, it remains unclear which structural connections may contribute to the anti-seizure effect of the stimulation.

Objective

We investigated the differences in structural connectivity among CM, the sweet-spot and the cold-spot. Furthermore, we tried to validate our results in a cohort of DRE patients who underwent CM-DBS or CM-RNS (responsive neurostimulation). We hypothesized that the sweet-spot would share similar structural connectivity with responder patients.

Methods

By using the software FMRIB Software Library (FSL), probabilistic tractography was performed on 100 subjects from the Human Connectome Project to calculate the probability of connectivity of the whole CM, the sweet-spot and the cold-spot to 45 cortical and subcortical areas. Results among the three seeds were compared with multivariate analysis of variance (MANOVA). Similarly, the structural connectivity of volumes of tissue activated (VTAs) from eight DRE patients was investigated. Patients were divided into responders and non-responders based on the degree of reduction in seizure frequency, and the mean probabilities of connectivity were similarly compared between the two groups.

Results

The sweet-spot demonstrated a significantly higher probability of connectivity (p < 0.001) with the precentral gyrus, superior frontal gyrus, and the cerebellum than the whole CM and the cold-spot. Responder patients displayed a higher probability of connectivity with both ipsilateral (p = 0.011) and contralateral cerebellum (p = 0.04) than the non-responders.

Conclusion

Cerebellar connections seem to contribute to the beneficial effects of CM-neuromodulation in patients with drug-resistant generalized epilepsy.

Effect of Enlarged Perivascular Spaces in Reliable Distinction of Prospective Targeting During Deep Brain Stimulation in Patients With Advanced Parkinson's Disease: A Study of Deterministic and Probabilistic Tractography

BACKGROUND

Precise electrode position is vital for effective deep brain stimulation in treating motor symptoms in Parkinson's disease (PD). Enlarged perivascular spaces (PVSs) are associated with pathophysiology of neurodegenerative diseases including PD and may affect the microstructure of surrounding brain tissue.

OBJECTIVE

To quantify the clinical implications of enlarged PVS on tractography-based stereotactic targeting in patients with advanced PD selected to undergo deep brain stimulation.

METHODS

Twenty patients with PD underwent MRI scanning. The PVS areas were visualized and segmented. Based on the size of the PVS areas, the patient group was split into 2 categories of large vs small PVSs. Probabilistic and deterministic tractography methods were applied to a diffusion-weighted data set. Fiber assignment was performed using motor cortex as an initiation seed and the globus pallidus interna and subthalamic nucleus, separately, as inclusion masks. Two exclusion masks used consisted of cerebral peduncles and the PVS mask. The center of gravity of the tract density map was measured and compared between the tracts generated with and without consideration of the PVS mask.

RESULTS

The average differences between the center of gravity of the tracts made by excluding PVS and without excluding PVS using deterministic and probabilistic tractography methods were less than 1 mm. Statistical analysis showed nonsignificant differences between deterministic and probabilistic methods and differences between patients with large and small PVSs ( P > .05).

CONCLUSION

This study demonstrated that the presence of enlarged PVS is unlikely to affect targeting of basal ganglia nuclei based on tractography.

Local neuroanatomical and tract-based proxies of optimal subcallosal cingulate deep brain stimulation

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.

Connectivity Profile for Subthalamic Nucleus Deep Brain Stimulation in Early Stage Parkinson Disease

OBJECTIVE

This study was undertaken to describe relationships between electrode localization and motor outcomes from the subthalamic nucleus (STN) deep brain stimulation (DBS) in early stage Parkinson disease (PD) pilot clinical trial.

METHODS

To determine anatomical and network correlates associated with motor outcomes for subjects randomized to early DBS (n = 14), voxelwise sweet spot mapping and structural connectivity analyses were carried out using outcomes of motor progression (Unified Parkinson Disease Rating Scale Part III [UPDRS-III] 7-day OFF scores [∆baseline➔24 months, MedOFF/StimOFF]) and symptomatic motor improvement (UPDRS-III ON scores [%∆baseline➔24 months, MedON/StimON]).

RESULTS

Sweet spot mapping revealed a location associated with slower motor progression in the dorsolateral STN (anterior/posterior commissure coordinates: 11.07 ± 0.82mm lateral, 1.83 ± 0.61mm posterior, 3.53 ± 0.38mm inferior to the midcommissural point; Montreal Neurological Institute coordinates: +11.25, -13.56, -7.44mm). Modulating fiber tracts from supplementary motor area (SMA) and primary motor cortex (M1) to the STN correlated with slower motor progression across STN DBS subjects, whereas fiber tracts originating from pre-SMA and cerebellum were negatively associated with motor progression. Robustness of the fiber tract model was demonstrated in leave-one-patient-out (R = 0.56, p = 0.02), 5-fold (R = 0.50, p = 0.03), and 10-fold (R = 0.53, p = 0.03) cross-validation paradigms. The sweet spot and fiber tracts associated with motor progression revealed strong similarities to symptomatic motor improvement sweet spot and connectivity in this early stage PD cohort.

INTERPRETATION

These results suggest that stimulating the dorsolateral region of the STN receiving input from M1 and SMA (but not pre-SMA) is associated with slower motor progression across subjects receiving STN DBS in early stage PD. This finding is hypothesis-generating and must be prospectively tested in a larger study. ANN NEUROL 2023;94:271-284.

Comparison of Anatomical Pathway Models with Tractography Estimates of the Pallidothalamic, Cerebellothalamic, and Corticospinal Tracts

Introduction: Models of structural connectivity in the human brain are typically simulated using tractographic approaches. However, the nonlinear fitting of anatomical pathway atlases to de novo subject brains represents a simpler alternative that is hypothesized to provide more anatomically realistic results. Therefore, the goal of this study was to perform a side-by-side comparison of the streamline estimates generated by either pathway atlas fits or tractographic reconstructions in the same subjects. Methods: Our analyses focused on reconstruction of the corticospinal tract (CST), cerebellothalamic (CBT), and pallidothalamic (PT) pathways using example datasets from the Human Connectome Project (HCP). We used MRtrix3 to explore whole brain, as well as manual seed-to-target, tractography approaches. In parallel, we performed nonlinear fits of an axonal pathway atlas to each HCP dataset using Advanced Normalization Tools (ANTs). Results: The different methods produced notably different estimates for each pathway in each subject. The fitted atlas pathways were highly stereotyped and exhibited low variability in their streamline trajectories. Manual tractography resulted in pathway estimates that generally corresponded with the fitted atlas pathways, but with a higher degree of variability in the individual streamlines. Pathway reconstructions derived from whole-brain tractography exhibited the highest degree of variability and struggled to create anatomically realistic representations for either the CBT or PT pathways. Conclusion: The speed, simplicity, reproducibility, and realism of anatomical pathway model fits makes them an appealing option for some forms of structural connectivity modeling in the human brain. Impact statement Axonal pathway modeling is an important component of deep brain stimulation (DBS) research studies that seek to identify the brain connections that are directly activated by stimulation. The corticospinal tract, cerebellothalamic (CBT), and pallidothalamic (PT) pathways are specifically relevant to the study of subthalamic DBS for the treatment of Parkinson's disease. Our results suggest that anatomical pathway model fits of the CBT and PT pathways to de novo subject brains represent a more anatomically realistic option than tractographic approaches when studying subthalamic DBS.

Deep brain stimulation of the dentato-rubro-thalamic tract in a case of Holmes tremor: a constrained spherical deconvolution (CSD)-guided procedure

Deep brain stimulation (DBS) is an established treatment for movement disorders, including Holmes tremor (HT). HT is a rest and action tremor that occurs as a late symptom of brainstem lesions such as stroke. Unfortunately, it is frequently refractory to medical treatment, hence DBS surgery may be a good option. Due to variable results, the ideal target for DBS in HT still remains to be established, ranging from the thalamus to the globus pallidus internus, to the subthalamic nucleus. Pre-operative imaging also is very challenging, as the complexity of brain fiber architecture may prevent the correct positioning of the directional lead. Herein, we describe the case of a patient affected by a rubral tremor secondary to a brain hemorrhage, who had advanced pre-operative neuroimaging with constrained spherical deconvolution (CSD)-based tractography obtained from diffusion-weighted imaging (DWI) to identify the dentato-rubro-thalamic tract, involved in the pathophysiology of HT. The patient was then addressed to an awake DBS surgery, and with the help of intraoperative microelectrode recordings, a tailored DRTT-targeted procedure was performed. The stimulation determined an almost complete tremor suppression, with no significant side effects at a follow-up of 6 months, paving the way towards new effective techniques for the planning, i.e., CSD-based tractography and the treatment of refractory tremors.

Stimulation of the Presupplementary Motor Area Cluster of the Subthalamic Nucleus Predicts More Consistent Clinical Outcomes

BACKGROUND

The development of diffusion tensor imaging and tractography has raised increasing interest in the functional targeting of deep brain stimulation of the subthalamic nucleus (STN) in Parkinson disease.

OBJECTIVE

To study, using deterministic tractography, the functional subdivisions of the STN and hyperdirect white matter connections located between the STN and the medial frontal cortex, especially the presupplementary motor area (preSMA), SMA, primary motor area (M1), and dorsolateral premotor cortex, and to study retrospectively whether this information correlates with clinical outcome.

METHODS

Twenty-two patients with Parkinson disease who underwent STN deep brain stimulation were analyzed. Using 3 T MR images, the medial frontal cortex was manually segmented into preSMA, SMA, M1, and dorsolateral premotor cortex, which were then used to determine the functional subdivisions of the lateral border of the STN. The intersectional quantities of the volume of activated tissue (VAT) and the hyperdirect white matter connections were calculated. The results were combined with clinical data including unilateral 12-month postoperative motor outcome and levodopa equivalent daily dose.

RESULTS

Stimulated clusters of the STN were connected mostly to the cortical SMA and preSMA regions. Patients with primarily preSMA cluster stimulation (presmaVAT% ≥ 50%) had good responses to the treatment with unilateral motor improvement over 40% and levodopa equivalent daily dose reduction over 60%. Larger VAT was not found to correlate with better patient outcomes.

CONCLUSION

Our study is the first to suggest that stimulating, predominantly, the STN cluster where preSMA hyperdirect pathways are located, could be predictive of more consistent treatment results.

Imaging Modalities Used for Frameless and Fiducial-Less Deep Brain Stimulation: A Single Centre Exploratory Study among Parkinson's Disease Cases

Deep brain stimulation (DBS) is a beneficial procedure for treating idiopathic Parkinson's disease (PD), essential tremor, and dystonia. The authors describe their set of imaging modalities used for a frameless and fiducial-less method of DBS. CT and MRI scans are obtained preoperatively, and STN parcellation is done based on diffusion tractography. During the surgery, an intraoperative cone-beam computed tomography scan is obtained and merged with the preoperatively-acquired images to place electrodes using a frameless and fiducial-less system. Accuracy is evaluated prospectively. The described sequence of imaging methods shows excellent accuracy compared to the frame-based techniques.

The Role of Graph Theory in Evaluating Brain Network Alterations in Frontotemporal Dementia

Frontotemporal dementia (FTD) is a spectrum of clinical syndromes that affects personality, behavior, language, and cognition. The current diagnostic criteria recognize three main clinical subtypes: the behavioral variant of FTD (bvFTD), the semantic variant of primary progressive aphasia (svPPA), and the non-fluent/agrammatic variant of PPA (nfvPPA). Patients with FTD display heterogeneous clinical and neuropsychological features that highly overlap with those presented by psychiatric syndromes and other types of dementia. Moreover, up to now there are no reliable disease biomarkers, which makes the diagnosis of FTD particularly challenging. To overcome this issue, different studies have adopted metrics derived from magnetic resonance imaging (MRI) to characterize structural and functional brain abnormalities. Within this field, a growing body of scientific literature has shown that graph theory analysis applied to MRI data displays unique potentialities in unveiling brain network abnormalities of FTD subtypes. Here, we provide a critical overview of studies that adopted graph theory to examine the topological changes of large-scale brain networks in FTD. Moreover, we also discuss the possible role of information arising from brain network organization in the diagnostic algorithm of FTD-spectrum disorders and in investigating the neural correlates of clinical symptoms and cognitive deficits experienced by patients.

Tractography of supplementary motor area projections in progressive speech apraxia and aphasia

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Degeneration of SMA white matter tracts occurs in progressive apraxia of speech.

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SMA commissural, putamen and precentral tracts were associated with speech apraxia.

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Agrammatism was associated with SMA-prefrontal and frontal aslant tracts.

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Tract profile analysis suggests different disease epicenters across syndromes.

Progressive apraxia of speech (AOS) is a motor speech disorder affecting the ability to produce phonetically or prosodically normal speech. Progressive AOS can present in isolation or co-occur with agrammatic aphasia and is associated with degeneration of the supplementary motor area. We aimed to assess breakdowns in structural connectivity from the supplementary motor area in patients with any combination of progressive AOS and/or agrammatic aphasia to determine which supplementary motor area tracts are specifically related to these clinical symptoms. Eighty-four patients with progressive AOS or progressive agrammatic aphasia were recruited by the Neurodegenerative Research Group and underwent neurological, speech/language, and neuropsychological testing, as well as 3 T diffusion magnetic resonance imaging. Of the 84 patients, 36 had apraxia of speech in isolation (primary progressive apraxia of speech, PPAOS), 40 had apraxia of speech and agrammatic aphasia (AOS-PAA), and eight had agrammatic aphasia in isolation (progressive agrammatic aphasia, PAA). Tractography was performed to identify 5 distinct tracts connecting to the supplementary motor area. Fractional anisotropy and mean diffusivity were assessed at 10 positions along the length of the tracts to construct tract profiles, and median profiles were calculated for each tract. In a case-control comparison, decreased fractional anisotropy and increased mean diffusivity were observed along the supplementary motor area commissural fibers in all three groups compared to controls. PPAOS also had abnormal diffusion in tracts from the supplementary motor area to the putamen, prefrontal cortex, Broca’s area (frontal aslant tract) and motor cortex, with greatest abnormalities observed closest to the supplementary motor area. The AOS-PAA group showed abnormalities in the same set of tracts, but with greater involvement of the supplementary motor area to prefrontal tract compared to PPAOS. PAA showed abnormalities in the left prefrontal and frontal aslant tracts compared to both other groups, with PAA showing greatest abnormalities furthest from the supplementary motor area. Severity of AOS correlated with tract metrics in the supplementary motor area commissural and motor cortex tracts. Severity of aphasia correlated with the frontal aslant and prefrontal tracts. These findings provide insight into how AOS and agrammatism are differentially related to disrupted diffusivity, with progressive AOS associated with abnormalities close to the supplementary motor area, and the frontal aslant and prefrontal tracts being particularly associated with agrammatic aphasia.

Somatotopic Organization of Hyperdirect Pathway Projections From the Primary Motor Cortex in the Human Brain

Background

The subthalamic nucleus (STN) is an effective neurosurgical target to improve motor symptoms in Parkinson's Disease (PD) patients. MR-guided Focused Ultrasound (MRgFUS) subthalamotomy is being explored as a therapeutic alternative to Deep Brain Stimulation (DBS) of the STN. The hyperdirect pathway provides a direct connection between the cortex and the STN and is likely to play a key role in the therapeutic effects of MRgFUS intervention in PD patients.

Objective

This study aims to investigate the topography and somatotopy of hyperdirect pathway projections from the primary motor cortex (M1).

Methods

We used advanced multi-fiber tractography and high-resolution diffusion MRI data acquired on five subjects of the Human Connectome Project (HCP) to reconstruct hyperdirect pathway projections from M1. Two neuroanatomy experts reviewed the anatomical accuracy of the tracts. We extracted the fascicles arising from the trunk, arm, hand, face and tongue area from the reconstructed pathways. We assessed the variability among subjects based on the fractional anisotropy (FA) and mean diffusivity (MD) of the fibers. We evaluated the spatial arrangement of the different fascicles using the Dice Similarity Coefficient (DSC) of spatial overlap and the centroids of the bundles.

Results

We successfully reconstructed hyperdirect pathway projections from M1 in all five subjects. The tracts were in agreement with the expected anatomy. We identified hyperdirect pathway fascicles projecting from the trunk, arm, hand, face and tongue area in all subjects. Tract-derived measurements showed low variability among subjects, and similar distributions of FA and MD values among the fascicles projecting from different M1 areas. We found an anterolateral somatotopic arrangement of the fascicles in the corona radiata, and an average overlap of 0.63 in the internal capsule and 0.65 in the zona incerta.

Conclusion

Multi-fiber tractography combined with high-resolution diffusion MRI data enables the identification of the somatotopic organization of the hyperdirect pathway. Our preliminary results suggest that the subdivisions of the hyperdirect pathway projecting from the trunk, arm, hand, face, and tongue motor area are intermixed at the level of the zona incerta and posterior limb of the internal capsule, with a predominantly overlapping topographical organization in both regions. Subject-specific knowledge of the hyperdirect pathway somatotopy could help optimize target definition in MRgFUS intervention.

Personalizing Deep Brain Stimulation Using Advanced Imaging Sequences

OBJECTIVE

With a growing appreciation for interindividual anatomical variability and patient-specific brain connectivity, advanced imaging sequences offer the opportunity to directly visualize anatomical targets for deep brain stimulation (DBS). The lack of quantitative evidence demonstrating their clinical utility, however, has hindered their broad implementation in clinical practice.

METHODS

Using fast gray matter acquisition T1 inversion recovery (FGATIR) sequences, the present study identified a thalamic hypointensity that holds promise as a visual marker in DBS. To validate the clinical utility of the identified hypointensity, we retrospectively analyzed 65 patients (26 female, mean age = 69.1 ± 12.7 years) who underwent DBS in the treatment of essential tremor. We characterized its neuroanatomical substrates and evaluated the hypointensity's ability to predict clinical outcome using stimulation volume modeling and voxelwise mapping. Finally, we determined whether the hypointensity marker could predict symptom improvement on a patient-specific level.

RESULTS

Anatomical characterization suggested that the identified hypointensity constituted the terminal part of the dentatorubrothalamic tract. Overlap between DBS stimulation volumes and the hypointensity in standard space significantly correlated with tremor improvement (R²  = 0.16, p = 0.017) and distance to hotspots previously reported in the literature (R²  = 0.49, p = 7.9e-4). In contrast, the amount of variance explained by other anatomical atlas structures was reduced. When accounting for interindividual neuroanatomical variability, the predictive power of the hypointensity increased further (R²  = 0.37, p = 0.002).

INTERPRETATION

Our findings introduce and validate a novel imaging-based marker attainable from FGATIR sequences that has the potential to personalize and inform targeting and programming in DBS for essential tremor. ANN NEUROL 2022;91:613-628.

Use of probabilistic tractography to provide reliable distinction of the motor and sensory thalamus for prospective targeting during asleep deep brain stimulation

OBJECTIVE

Accurate electrode placement is key to effective deep brain stimulation (DBS). The ventral intermediate nucleus (VIM) of the thalamus is an established surgical target for the treatment of essential tremor (ET). Retrospective tractography-based analysis of electrode placement has associated successful outcomes with modulation of motor input to VIM, but no study has yet evaluated the feasibility and efficacy of prospective presurgical tractography-based targeting alone. Therefore, the authors sought to demonstrate the safety and efficacy of probabilistic tractography-based VIM targeting in ET patients and to perform a systematic comparison of probabilistic and deterministic tractography.

METHODS

Fourteen patients with ET underwent preoperative diffusion imaging. Probabilistic tractography was applied for preoperative targeting, and deterministic tractography was performed as a comparison between methods. Tractography was performed using the motor and sensory areas as initiation seeds, the ipsilateral thalamus as an inclusion mask, and the contralateral dentate nucleus as a termination mask. Tract-density maps consisted of voxels with 10% or less of the maximum intensity and were superimposed onto anatomical images for presurgical planning. Target planning was based on probabilistic tract-density images and indirect target coordinates. Patients underwent robotic image-guided, image-verified implantation of directional DBS systems. Postoperative tremor scores with and without DBS were recorded. The center of gravity and Dice similarity coefficients were calculated and compared between tracking methods.

RESULTS

Prospective probabilistic targeting of VIM was successful in all 14 patients. All patients experienced significant tremor reduction. Formal postoperative tremor scores were available for 9 patients, who demonstrated a mean 68.0% tremor reduction. Large differences between tracking methods were observed across patients. Probabilistic tractography-identified VIM fibers were more anterior, lateral, and superior than deterministic tractography-identified fibers, whereas probabilistic tractography-identified ventralis caudalis fibers were more posterior, lateral, and superior than deterministic tractography-identified fibers. Deterministic methods were unable to clearly distinguish between motor and sensory fibers in the majority of patients, but probabilistic methods produced distinct separation.

CONCLUSIONS

Probabilistic tractography-based VIM targeting is safe and effective for the treatment of ET. Probabilistic tractography is more precise than deterministic tractography for the delineation of VIM and the ventralis caudalis nucleus of the thalamus. Deterministic algorithms tended to underestimate separation between motor and sensory fibers, which may have been due to its limitations with crossing fibers. Larger studies across multiple centers are necessary to further validate this method.

Electrophysiological characterization of the hyperdirect pathway and its functional relevance for subthalamic deep brain stimulation

The subthalamic nucleus (STN) receives input from various cortical areas via hyperdirect pathway (HDP) which bypasses the basal-ganglia loop. Recently, the HDP has gained increasing interest, because of its relevance for STN deep brain stimulation (DBS). To understand the HDP's role cortical responses evoked by STN-DBS have been investigated. These responses have short (<2 ms), medium (2-15 ms), and long (20-70 ms) latencies. Medium-latency responses are supposed to represent antidromic cortical activations via HDP. Together with long-latency responses the medium responses can potentially be used as biomarker of DBS efficacy as well as side effects. We here propose that the activation sequence of the cortical evoked responses can be conceptualized as high frequency oscillations (HFO) for signal analysis. HFO might therefore serve as marker for antidromic activation. Using existing knowledge on HFO recordings, this approach allows data analyses and physiological modeling to advance the pathophysiological understanding of cortical DBS-evoked high-frequency activity.

Effects of diffusion signal modeling and segmentation approaches on subthalamic nucleus parcellation

The subthalamic nucleus (STN) is commonly used as a surgical target for deep brain stimulation in movement disorders such as Parkinson's Disease. Tractography-derived connectivity-based parcellation (CBP) has been recently proposed as a suitable tool for non-invasive in vivo identification and pre-operative targeting of specific functional territories within the human STN. However, a well-established, accurate and reproducible protocol for STN parcellation is still lacking. The present work aims at testing the effects of different tractography-based approaches for the reconstruction of STN functional territories. We reconstructed functional territories of the STN on the high-quality dataset of 100 unrelated healthy subjects and on the test-retest dataset of the Human Connectome Project (HCP) repository. Connectivity-based parcellation was performed with a hypothesis-driven approach according to cortico-subthalamic connectivity, after dividing cortical areas into three groups: associative, limbic and sensorimotor. Four parcellation pipelines were compared, combining different signal modeling techniques (single-fiber vs multi-fiber) and different parcellation approaches (winner takes all parcellation vs fiber density thresholding). We tested these procedures on STN regions of interest obtained from three different, commonly employed, subcortical atlases. We evaluated the pipelines both in terms of between-subject similarity, assessed on the cohort of 100 unrelated healthy subjects, and of within-subject similarity, using a second cohort of 44 subjects with available test-retest data. We found that each parcellation provides converging results in terms of location of the identified parcels, but with significative variations in size and shape. All pipelines obtained very high within-subject similarity, with tensor-based approaches outperforming multi-fiber pipelines. On the other hand, higher between-subject similarity was found with multi-fiber signal modeling techniques combined with fiber density thresholding. We suggest that a fine-tuning of tractography-based parcellation may lead to higher reproducibility and aid the development of an optimized surgical targeting protocol.

Connectome spatial smoothing (CSS): Concepts, methods, and evaluation

Structural connectomes are increasingly mapped at high spatial resolutions comprising many hundreds-if not thousands-of network nodes. However, high-resolution connectomes are particularly susceptible to image registration misalignment, tractography artifacts, and noise, all of which can lead to reductions in connectome accuracy and test-retest reliability. We investigate a network analogue of image smoothing to address these key challenges. Connectome Spatial Smoothing (CSS) involves jointly applying a carefully chosen smoothing kernel to the two endpoints of each tractography streamline, yielding a spatially smoothed connectivity matrix. We develop computationally efficient methods to perform CSS using a matrix congruence transformation and evaluate a range of different smoothing kernel choices on CSS performance. We find that smoothing substantially improves the identifiability, sensitivity, and test-retest reliability of high-resolution connectivity maps, though at a cost of increasing storage burden. For atlas-based connectomes (i.e. low-resolution connectivity maps), we show that CSS marginally improves the statistical power to detect associations between connectivity and cognitive performance, particularly for connectomes mapped using probabilistic tractography. CSS was also found to enable more reliable statistical inference compared to connectomes without any smoothing. We provide recommendations for optimal smoothing kernel parameters for connectomes mapped using both deterministic and probabilistic tractography. We conclude that spatial smoothing is particularly important for the reliability of high-resolution connectomes, but can also provide benefits at lower parcellation resolutions. We hope that our work enables computationally efficient integration of spatial smoothing into established structural connectome mapping pipelines.

Brain Connectivity Changes in Post-Concussion Syndrome as the Neural Substrate of a Heterogeneous Syndrome

BACKGROUND

Post-concussion syndrome (PCS) or persistent symptoms of concussion refers to a constellation of symptoms that persist for weeks and months after a concussion. To better capture the heterogeneity of the symptoms of patients with post-concussion syndrome, we aimed to separate patients into clinical subtypes based on brain connectivity changes.

METHODS

Subject-specific structural and functional connectomes were created based on Diffusion Weighted and Resting State Functional Magnetic Resonance Imaging, respectively. Following an informed dimensionality reduction, a gaussian mixture model was used on patient specific structural and functional connectivity matrices to find potential patient clusters. For validation, the resulting patient subtypes were compared in terms of cognitive, neuropsychiatric, and post-concussive symptom differences.

RESULTS

Multimodal analyses of brain connectivity were predictive of behavioural outcomes. Our modelling revealed 2 patient subtypes; mild and severe. The severe group showed significantly higher levels of depression, anxiety, aggression, and a greater number of symptoms than the mild patient subgroup.

CONCLUSION

This study suggests that structural and functional connectivity changes together can help us better understand the symptom severity and neuropsychiatric profiles of patients with post-concussion syndrome. This work allows us to move towards precision medicine in concussions and provides a novel machine learning approach that can be applicable to other heterogeneous conditions.

General additive models address statistical issues in diffusion MRI: An example with clinically anxious adolescents

Statistical models employed to test for group differences in quantized diffusion-weighted MRI white matter tracts often fail to account for the large number of data points per tract in addition to the distribution, type, and interdependence of the data. To address these issues, we propose the use of Generalized Additive Models (GAMs) and supply code and examples to aid in their implementation. Specifically, using diffusion data from 73 periadolescent clinically anxious and no-psychiatric-diagnosis control participants, we tested for group tract differences and show that a GAM allows for the identification of differences within a tract while accounting for the nature of the data as well as covariates and group factors. Further, we then used these tract differences to investigate their association with performance on a memory test. When comparing our high versus low anxiety groups, we observed a positive association between the left uncinate fasciculus and memory overgeneralization for negatively valenced stimuli. This same association was not evident in the right uncinate or anterior forceps. These findings illustrate that GAMs are well-suited for modeling diffusion data while accounting for various aspects of the data, and suggest that the adoption of GAMs will be a powerful investigatory tool for diffusion-weighted analyses.

Deterministic Tractography Analysis of Rat Brain Using SIGMA Atlas in 9.4T MRI

Preclinical studies using rodents have been the choice for many neuroscience researchers due totheir close reflection of human biology. In particular, research involving rodents has utilized MRI to accurately identify brain regions and characteristics by acquiring high resolution cavity images with different contrasts non-invasively, and this has resulted in high reproducibility and throughput. In addition, tractographic analysis using diffusion tensor imaging to obtain information on the neural structure of white matter has emerged as a major methodology in the field of neuroscience due to its contribution in discovering significant correlations between altered neural connections and various neurological and psychiatric diseases. However, unlike image analysis studies with human subjects where a myriad of human image analysis programs and procedures have been thoroughly developed and validated, methods for analyzing rat image data using MRI in preclinical research settings have seen significantly less developed. Therefore, in this study, we present a deterministic tractographic analysis pipeline using the SIGMA atlas for a detailed structural segmentation and structural connectivity analysis of the rat brain’s structural connectivity. In addition, the structural connectivity analysis pipeline presented in this study was preliminarily tested on normal and stroke rat models for initial observation.

Ventral intermediate nucleus structural connectivity-derived segmentation: anatomical reliability and variability

The Ventral intermediate nucleus (Vim) of thalamus is the most targeted structure for the treatment of drug-refractory tremors. Since methodological differences across existing studies are remarkable and no gold-standard pipeline is available, in this study, we tested different parcellation pipelines for tractography-derived putative Vim identification. Thalamic parcellation was performed on a high quality, multi-shell dataset and a downsampled, clinical-like dataset using two different diffusion signal modeling techniques and two different voxel classification criteria, thus implementing a total of four parcellation pipelines. The most reliable pipeline in terms of inter-subject variability has been picked and parcels putatively corresponding to motor thalamic nuclei have been selected by calculating similarity with a histology-based mask of Vim. Then, spatial relations with optimal stimulation points for the treatment of essential tremor have been quantified. Finally, effect of data quality and parcellation pipelines on a volumetric index of connectivity clusters has been assessed. We found that the pipeline characterized by higher-order signal modeling and threshold-based voxel classification criteria was the most reliable in terms of inter-subject variability regardless data quality. The maps putatively corresponding to Vim were those derived by precentral and dentate nucleus-thalamic connectivity. However, tractography-derived functional targets showed remarkable differences in shape and sizes when compared to a ground truth model based on histochemical staining on seriate sections of human brain. Thalamic voxels connected to contralateral dentate nucleus resulted to be the closest to literature-derived stimulation points for essential tremor but at the same time showing the most remarkable inter-subject variability. Finally, the volume of connectivity parcels resulted to be significantly influenced by data quality and parcellation pipelines. Hence, caution is warranted when performing thalamic connectivity-based segmentation for stereotactic targeting.

DTI for brain targeting: Diffusion weighted imaging fiber tractography-Assisted deep brain stimulation

Fiber tractography assisted Deep Brain Stimulation (DBS) has been performed by different groups for more than 10 years to now. Groups around the world have adapted initial approaches to currently embrace the fiber tractography technology mainly for treating tremor (DBS and lesions), psychiatric indications (OCD and major depression) and pain (DBS). Despite the advantages of directly visualizing the target structure, the technology is demanding and is vulnerable to inaccuracies especially since it is performed on individual level. In this contribution, we will focus on tremor and psychiatric indications, and will show future applications of sophisticated tractography applications for subthalamic nucleus (STN) DBS surgery and stimulation steering as an example.

Directed stimulation of the dentato-rubro-thalamic tract for deep brain stimulation in essential tremor: a blinded clinical trial

OBJECTIVE

Observational studies utilising diffusion tractography have suggested a common mechanism for tremor alleviation in deep brain stimulation for essential tremor: the decussating portion of the dentato-rubro-thalamic tract. We hypothesised that directional stimulation of the dentato-rubro-thalamic tract would result in greater tremor improvement compared to sham programming, as well as comparable improvement as more tedious standard-of-care programming.

METHODS

A prospective, blinded crossover trial was performed to assess the feasibility, safety and outcomes of programming based solely on dentato-rubro-thalamic tract anatomy. Using magnetic resonance imaging diffusion-tractography, the dentato-rubro-thalamic tract was identified and a connectivity-based treatment setting was derived by modelling a volume of tissue activated using directional current steering oriented towards the dentato-rubro-thalamic tract centre. A sham setting was created at approximately 180° opposite the connectivity-based treatment. Standard-of-care programming at 3 months was compared to connectivity-based treatment and sham settings that were blinded to the programmer. The primary outcome measure was percentage improvement in the Fahn-Tolosa-Marín tremor rating score compared to the preoperative baseline.

RESULTS

Among the six patients, tremor rating scores differed significantly among the three experimental conditions (P=0.030). The mean tremor rating score improvement was greater with the connectivity-based treatment settings (64.6% ± 14.3%) than with sham (44.8% ± 18.6%; P=0.031) and standard-of-care programming (50.7% ± 19.2%; P=0.062). The distance between the centre of the dentato-rubro-thalamic tract and the volume of tissue activated inversely correlated with the percentage improvement in the tremor rating score (R²=0.24; P=0.04). No significant adverse events were encountered.

CONCLUSIONS

Using a blinded, crossover trial design, we have shown the technical feasibility, safety and potential efficacy of connectivity-based stimulation settings in deep brain stimulation for treatment of essential tremor.

Increased structural connectivity of thalamic stimulation sites to motor cortex relates to tremor suppression

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Clinically weighted tractography reveals key patterns of therapeutic brain stimulation.

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Thalamic stimulation for tremor preferentially connects to precentral gyrus and cerebellum.

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Thalamic DBS of areas most connected to motor cortex results in superior outcomes.

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Acute and chronic therapeutic outcomes demonstrate converging connectivity patterns.

Deep brain stimulation (DBS) of the ventral intermediate nucleus (VIM-DBS) is a highly successful treatment for medication-refractory essential tremor (ET). Clinical outcomes are dependent on accurate targeting. Here, we aim to develop a framework for connectivity-guided DBS targeting by evaluating probabilistic tractography and clinical response at both initial programming (IP) and clinical follow-up (CF).

Magnetic resonance imaging and clinical outcomes were evaluated in 23 ET patients who were treated by VIM-DBS at the University of California Los Angeles (20 at IP, 18 at CF, 14 at both). Lead-DBS was used to model the volume of tissue activated tissue (VTA) based on programming configurations at both IP and CF. Probabilistic tractography, calculated in FSL, was used to evaluate 1) clinically weighted whole brain connectivity of VTA; 2) connectivity between VTA and freesurfer-derived target regions of interest (ROI) including primary motor, premotor, and prefrontal cortices, and cerebellum; and 3) volume of intersection between VTA and probabilistic tractography-based segmentation of the thalamus. At IP, individual contacts were scored as high or low efficacy based on acute tremor improvement. At CF, clinical response was measured by percent of change of the Clinical Rating Scale for Tremor (CRST) compared to preoperative scores. Contributions from each target ROI to clinical response was measured using logistic regression for IP and linear regression for CF.

The clinically weighted map of whole brain connectivity of VTA shows preferential connectivity to precentral gyrus and brainstem/cerebellum. The volume of intersection between VTA and thalamic segmentation map based on probabilistic connectivity to primary motor cortex was a significant predictor of contact efficacy at IP (OR = 2.26 per 100 mm³ of overlap, p = .04) and percent change in CRST at CF (β = 14.67 per 100 mm³ of overlap, p = .003).

Targeting DBS to the area of thalamus most connected to primary motor cortex based on probabilistic tractography is associated with superior outcomes, providing a potential guide not only for lead targeting but also therapeutic programming.

Detecting Corticospinal Tract Impairment in Tumor Patients With Fiber Density and Tensor-Based Metrics

Tumors infiltrating the motor system lead to significant disability, often caused by corticospinal tract injury. The delineation of the healthy-pathological white matter (WM) interface area, for which diffusion magnetic resonance imaging (dMRI) has shown promising potential, may improve treatment outcome. However, up to 90% of white matter (WM) voxels include multiple fiber populations, which cannot be correctly described with traditional metrics such as fractional anisotropy (FA) or apparent diffusion coefficient (ADC). Here, we used a novel fixel-based along-tract analysis consisting of constrained spherical deconvolution (CSD)-based probabilistic tractography and fixel-based apparent fiber density (FD), capable of identifying fiber orientation specific microstructural metrics. We addressed this novel methodology's capability to detect corticospinal tract impairment. We measured and compared tractogram-related FD and traditional microstructural metrics bihemispherically in 65 patients with WHO grade III and IV gliomas infiltrating the motor system. The cortical tractogram seeds were based on motor maps derived by transcranial magnetic stimulation. We extracted 100 equally distributed cross-sections along each streamline of corticospinal tract (CST) for along-tract statistical analysis. Cross-sections were then analyzed to detect differences between healthy and pathological hemispheres. All metrics showed significant differences between healthy and pathologic hemispheres over the entire tract and between peritumoral segments. Peritumoral values were lower for FA and FD, but higher for ADC within the entire cohort. FD was more specific to tumor-induced changes in CST than ADC or FA, whereas ADC and FA showed higher sensitivity. The bihemispheric along-tract analysis provides an approach to detect subject-specific structural changes in healthy and pathological WM. In the current clinical dataset, the more complex FD metrics did not outperform FA and ADC in terms of describing corticospinal tract impairment.

Variability of white matter anatomy in the subcallosal cingulate area

The subcallosal cingulate (SCC) area is a putative hub in the brain network underlying depression. Deep brain stimulation (DBS) targeting a particular subregion of SCC, identified as the intersection of forceps minor (FM), uncinate fasciculus (UCF), cingulum and fronto-striatal fiber bundles, may be critical to a therapeutic response in patients with severe, treatment-resistant forms of major depressive disorder (MDD). The pattern and variability of the white matter anatomy and organization within SCC has not been extensively characterized across individuals. The goal of this study is to investigate the variability of white matter bundles within the SCC that structurally connect this region with critical nodes in the depression network. Structural and diffusion data from 100 healthy subjects from the Human Connectome Project database were analyzed. Anatomically defined SCC regions were used as seeds to perform probabilistic tractography and to estimate the connectivity from the SCC to subject-specific target areas believed to be involved in the pathology of MDD including ventral striatum (VS), UCF, anterior cingulate cortex (ACC), and medial prefrontal cortex (mPFC). Four distinct areas of connectivity were identified within SCC across subjects: (a) postero-lateral SCC connectivity to medial temporal regions via UCF, (b) postero-medial connectivity to VS, (c) superior-medial connectivity to ACC via cingulum bundle, and (d) antero-lateral connectivity to mPFC regions via forceps minor. Assuming white matter connectivity is critical to therapeutic response, the improved anatomic understanding of SCC as well as an appreciation of the intersubject variability are critical to developing optimized therapeutic targeting for SCC DBS.

Effect of distortion corrections on the tractography quality in spinal cord diffusion-weighted imaging

PURPOSE

To assess the impact of a different distortion correction (DC) method and patient geometry (sagittal balance) on the quality of spinal cord tractography rendering according to different tractography approaches.

METHODS

Forty-four adults free of spinal cord diseases underwent cervical diffusion-weighted imaging. The phase-encoding direction was head→foot. Sequence with opposed polarities (foot→head) was acquired to perform DC. Eddy-current, motion effects, and susceptibility artifact correction methods were used for DC, and two deterministic and one probabilistic tractography approaches were evaluated using MRtrix and DSI Studio tractography software. Fiber length and number of fibers were extracted to evaluate the quality of the tractography rendering. For each subject, cervical lordosis was measured to assess patient geometry. The angle between the main direction of the spinal cord and the orientation of the acquisition box were computed at each spine level to assess acquisition geometry and define an angle threshold for which a tractography of good quality is no longer possible.

RESULTS

There was a significant improvement in tractography quality after performing DC with susceptibility artifact correction using a deterministic approach based on tensor. Before DC, the angle threshold was defined at C6 (15.2°) compared with C7 (21.9°) after corrections, demonstrating the importance of spinal cord angulation for DC.

CONCLUSION

The impact of DC on tractography quality is greatly impacted by acquisition geometry. To obtain a good-quality tractography, we propose as a future perspective to adapt the acquisition geometry to that of the patient by automatically adjusting the acquisition box.

The Use of Tractography-Based Targeting in Deep Brain Stimulation for Psychiatric Indications

Deep Brain Stimulation (DBS) has been investigated as a treatment option for patients with refractory psychiatric illness. Over the past two decades, neuroimaging developments have helped to advance the field, particularly the use of diffusion tensor imaging (DTI) and tractographic reconstruction of white-matter pathways. In this article, we review translational considerations and how DTI and tractography have been used to improve targeting during DBS surgery for depression, obsessive compulsive disorder (OCD) and post-traumatic stress disorder (PTSD).

Opportunities of connectomic neuromodulation

The process of altering neural activity - neuromodulation - has long been used to treat patients with brain disorders and answer scientific questions. Deep brain stimulation in particular has provided clinical benefit to over 150,000 patients. However, our understanding of how neuromodulation impacts the brain is evolving. Instead of focusing on the local impact at the stimulation site itself, we are considering the remote impact on brain regions connected to the stimulation site. Brain connectivity information derived from advanced magnetic resonance imaging data can be used to identify these connections and better understand clinical and behavioral effects of neuromodulation. In this article, we review studies combining neuromodulation and brain connectomics, highlighting opportunities where this approach may prove particularly valuable. We focus on deep brain stimulation, but show that the same principles can be applied to other forms of neuromodulation, such as transcranial magnetic stimulation and MRI-guided focused ultrasound. We outline future perspectives and provide testable hypotheses for future work.

Multimodal MRI for MRgFUS in essential tremor: post-treatment radiological markers of clinical outcome

BACKGROUND

MRI-guided focused ultrasound (MRgFUS) thalamotomy is a promising non-invasive treatment option for medication-resistant essential tremor. However, it has been associated with variable efficacy and a relatively high incidence of adverse effects.

OBJECTIVES

To assess the evolution of radiological findings after MRgFUS thalamotomy and to evaluate their significance for clinical outcomes.

METHODS

Ninety-four patients who underwent MRgFUS between 2012 and 2017 were retrospectively evaluated. Lesion characteristics were assessed on routine MRI sequences, as well as with tractography. Relationships between imaging appearance, extent of white matter tract lesioning (59/94, on a 4-point scale) and clinical outcome were investigated. Recurrence was defined as >33% loss of tremor suppression at 3 months relative to day 7.

RESULTS

Acute lesions demonstrated blood products, surrounding oedema and peripheral diffusion restriction. The extent of dentatorubrothalamic tract (DRTT) lesioning was significantly associated with clinical improvement at 1 year (t=4.32, p=0.001). Lesion size decreased over time (180.8±91.5 mm³ at day 1 vs 19.5±19.3 mm³ at 1-year post-treatment). Higher post-treatment oedema (t=3.59, p<0.001) was associated with larger lesions at 3 months. Patients with larger lesions at day 1 demonstrated reduced rates of tremor recurrence (t=2.67, p=0.019); however, lesions over 170 mm³ trended towards greater incidence of adverse effects (sensitivity=0.60, specificity=0.63). Lesion encroachment on the medial lemniscus (Sn=1.00, Sp=0.32) and pyramidal tract (Sn=1.00, Sp=0.12) were also associated with increased adverse effects incidence.

CONCLUSION

Lesion size at day 1 predicts symptom recurrence, with fewer recurrences seen with larger lesions. Greater DRTT lesioning is associated with treatment efficacy. These findings may have implications for lesion targeting and extent.

TRIAL REGISTRATION NUMBER

NCT02252380.

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 their ability to predict clinical improvement. 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 patient-specific diffusion-MRI data, age- and disease-matched or normative group connectome data (acquired in healthy young subjects). Based on these profiles, models of optimal connectivity were calculated and used to estimate 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 this present 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. 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 explaining slightly more variance than 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.

A unified connectomic target for deep brain stimulation in obsessive-compulsive disorder

Multiple surgical targets for treating obsessive-compulsive disorder with deep brain stimulation (DBS) have been proposed. However, different targets may modulate the same neural network responsible for clinical improvement. We analyzed data from four cohorts of patients (N = 50) that underwent DBS to the anterior limb of the internal capsule (ALIC), the nucleus accumbens or the subthalamic nucleus (STN). The same fiber bundle was associated with optimal clinical response in cohorts targeting either structure. This bundle connected frontal regions to the STN. When informing the tract target based on the first cohort, clinical improvements in the second could be significantly predicted, and vice versa. To further confirm results, clinical improvements in eight patients from a third center and six patients from a fourth center were significantly predicted based on their stimulation overlap with this tract. Our results show that connectivity-derived models may inform clinical improvements across DBS targets, surgeons and centers. The identified tract target is openly available in atlas form.

Li et al. analyzed structural connectivity of deep brain stimulation electrodes in 50 patients suffering from obsessive-compulsive disorder operated at four centers. Connectivity to a specific tract within the anterior limb of the internal capsule was associated with optimal treatment response across cohorts, surgeons and centers.

Modeling of Electric Fields in Individual Imaging Atlas for Capsular Threshold Prediction of Deep Brain Stimulation in Parkinson's Disease: A Pilot Study

Background: Modeling of deep brain stimulation electric fields and anatomy-based software might improve post-operative management of patients with Parkinson's disease (PD) who have benefitted from subthalamic nucleus deep brain stimulation (STN-DBS).

Objective: We compared clinical and software-guided determination of the thresholds for current diffusion to the pyramidal tract, the most frequent limiting side effect in post-operative management of STN-DBS PD patients.

Methods: We assessed monopolar reviews in 16 consecutive STN-DBS PD patients and retrospectively compared clinical capsular thresholds, which had been assessed according to standard clinical practice, to those predicted by volume of tissue activated (VTA) model software. All the modeling steps were performed blinded from patients' clinical evaluations.

Results: At the group level, we found a significant correlation (p = 0.0001) when performing statistical analysis on the z-scored capsular thresholds, but with a low regression coefficient (r = 0.2445). When considering intra-patient analysis, we found significant correlations (p < 0.05) between capsular threshold as modeled with the software and capsular threshold as determined clinically in five patients (31.2%).

Conclusions: In this pilot study, the VTA model software was of limited assistance in identifying capsular thresholds for the whole cohort due to a large inter-patient variability. Clinical testing remains the gold standard in selecting stimulation parameters for STN-DBS in PD.

Individual variations of the human corticospinal tract and its hand-related motor fibers using diffusion MRI tractography

The corticospinal tract (CST) is one of the most well studied tracts in human neuroanatomy. Its clinical significance can be demonstrated in many notable traumatic conditions and diseases such as stroke, spinal cord injury (SCI) or amyotrophic lateral sclerosis (ALS). With the advent of diffusion MRI and tractography the computational representation of the human CST in a 3D model became available. However, the representation of the entire CST and, specifically, the hand motor area has remained elusive. In this paper we propose a novel method, using manually drawn ROIs based on robustly identifiable neuroanatomic structures to delineate the entire CST and isolate its hand motor representation as well as to estimate their variability and generate a database of their volume, length and biophysical parameters. Using 37 healthy human subjects we performed a qualitative and quantitative analysis of the CST and the hand-related motor fiber tracts (HMFTs). Finally, we have created variability heat maps from 37 subjects for both the aforementioned tracts, which could be utilized as a reference for future studies with clinical focus to explore neuropathology in both trauma and disease states.

The dentato-rubro-thalamic tract as the potential common deep brain stimulation target for tremor of various origin: an observational case series

INTRODUCTION

Deep brain stimulation alleviates tremor of various origins. The dentato-rubro-thalamic tract (DRT) has been suspected as a common tremor-reducing structure. Statistical evidence has not been obtained. We here report the results of an uncontrolled case series of patients with refractory tremor who underwent deep brain stimulation under tractographic assistance.

METHODS

A total of 36 patients were enrolled (essential tremor (17), Parkinson's tremor (8), multiple sclerosis (7), dystonic head tremor (3), tardive dystonia (1)) and received 62 DBS electrodes (26 bilateral; 10 unilateral). Preoperatively, diffusion tensor magnetic resonance imaging sequences were acquired together with high-resolution anatomical T1W and T2W sequences. The DRT was individually tracked and used as a direct thalamic or subthalamic target. Intraoperative tremor reduction was graded on a 4-point scale (0 = no tremor reduction to 3 = full tremor control) and recorded together with the current amplitude, respectively. Stimulation point coordinates were recorded and compared to DRT. The relation of the current amplitude needed to reduce tremor was expressed as TiCR (tremor improvement per current ratio).

RESULTS

Stimulation points of 241 were available for analysis. A total of 68 trajectories were tested (62 dB leads, 1.1 trajectories tested per implanted lead). Tremor improvement was significantly decreasing (p < 0.01) if the distance to both the border and the center of the DRT was increasing. On the initial trajectory, 56 leads (90.3%) were finally placed. Long-term outcomes were not part of this analysis.

DISCUSSION

Tremor of various origins was acutely alleviated at different points along the DRT fiber tract (above and below the MCP plane) despite different tremor diseases. DRT is potentially a common tremor-reducing structure. Individual targeting helps to reduce brain penetrating tracts. TiCR characterizes stimulation efficacy and might help to identify an optimal stimulation point.

Anatomy and Connectivity of the Subthalamic Nucleus in Humans and Non-human Primates

The Subthalamic Nucleus (STh) is an oval-shaped diencephalic structure located ventrally to the thalamus, playing a fundamental role in the circuitry of the basal ganglia. In addition to being involved in the pathophysiology of several neurodegenerative disorders, such as Huntington’s and Parkinson’s disease, the STh is one of the target nuclei for deep brain stimulation. However, most of the anatomical evidence available derives from non-human primate studies. In this review, we will present the topographical and morphological organization of the nucleus and its connections to structurally and functionally related regions of the basal ganglia circuitry. We will also highlight the importance of additional research in humans focused on validating STh connectivity, cytoarchitectural organization, and its functional subdivision.

MR-guided focused ultrasound cerebellothalamic tractotomy for chronic therapy-resistant essential tremor: anatomical target reappraisal and clinical results

OBJECTIVE

In addition to the well-recognized ventral intermediate nucleus (Vim) thalamotomy for the treatment of chronic therapy-resistant essential tremor (ET), an alternative approach targeting the posterior part of the subthalamus was proposed in the 1960s and early 1970s and then was reactualized as cerebellothalamic tractotomy (CTT) with the advent of MR-guided focused ultrasound (MRgFUS) surgery. The goal of this study was to improve target coverage and thus efficacy (i.e., tremor control and its consistency). The authors undertook a histological reappraisal of the CTT target and proposed a targeting strategy of the MRgFUS CTT based on 1) the MR visualization of the center of the red nucleus and 2) the application of preplanned target subunits realized with short sonications under thermal dose control. This study was aimed at demonstrating the efficacy and risk profile of this approach against chronic therapy-resistant ET.

METHODS

Ten consecutive patients suffering from chronic therapy-resistant ET benefited from a unilateral MRgFUS CTT and were followed over the course of 1 year. Primary endpoints were subjective tremor relief, Clinical Rating Scale for Tremor (CRST) score, activities of daily living (ADL) score, and the hand function (HF) scores HF16 and HF32. Histological reappraisal of the target led the authors to propose a standardized targeting protocol for MRgFUS CTT. Thermal doses for 18 and 240 cumulative equivalent minutes at 43°C were calculated and correlated with intraoperative and 2 days postoperative T2-weighted MR images.

RESULTS

The mean ± SD for the baseline CRST score was 48 ± 12; the score was 16 ± 7 at 3 months, and 17 ± 8 at 1 year. The mean tremor relief rated by the patients for the operated side was 95% after 2 days, 96% at 3 months, and 93% at 1 year. The mean HF16 was 11.0 ± 2.1 at baseline, 0.7 ± 0.7 at 3 months, and 0.8 ± 0.9 at 1 year (93% mean reduction). The minimum reduction for the HF16 at 1 year was 78%. There was a 51% reduction of the mean ADL score at 1 year. There was no bleeding or infection. Gait difficulties, only detectable on tandem gait, were increased in 3 patients and reduced in 2 patients at 1 year. There was no dysarthria.

CONCLUSIONS

The authors' results suggest that MRgFUS CTT is a very effective treatment option for therapy-resistant ET.

Differences in topological progression profile among neurodegenerative diseases from imaging data

The spatial distribution of atrophy in neurodegenerative diseases suggests that brain connectivity mediates disease propagation. Different descriptors of the connectivity graph potentially relate to different underlying mechanisms of propagation. Previous approaches for evaluating the influence of connectivity on neurodegeneration consider each descriptor in isolation and match predictions against late-stage atrophy patterns. We introduce the notion of a topological profile - a characteristic combination of topological descriptors that best describes the propagation of pathology in a particular disease. By drawing on recent advances in disease progression modeling, we estimate topological profiles from the full course of pathology accumulation, at both cohort and individual levels. Experimental results comparing topological profiles for Alzheimer's disease, multiple sclerosis and normal ageing show that topological profiles explain the observed data better than single descriptors. Within each condition, most individual profiles cluster around the cohort-level profile, and individuals whose profiles align more closely with other cohort-level profiles show features of that cohort. The cohort-level profiles suggest new insights into the biological mechanisms underlying pathology propagation in each disease.

White matter tracts involved by deep brain stimulation of the subthalamic nucleus in Parkinson's disease: a connectivity study based on preoperative diffusion tensor imaging tractography

Purpose: To depict the specific brain networks that are modulated by deep brain stimulation (DBS) of the subthalamic nucleus (STN) in Parkinson's disease (PD), using diffusion tensor imaging-based fibre tractography (DTI-FT).Materials and methods: Nine patients who received bilateral STN-DBS for PD were included. Electrodes were localized by co-registering preoperative magnetic resonance imaging and postoperative computed tomography. The volume of tissue activated (VTA) was estimated as an isotropic, spherical electric field distribution centred at each effective electrode contact's centroid coordinates, taking into account individual stimulation parameters (i.e. voltage, impedance). Brain connectivity analysis was undertaken using a deterministic DTI-FT method, seeded from a single region of interest corresponding to the VTA. The labelling of the reconstructed white matter fibre tracts relied on their path and (sub)cortical termination territories.Results: Six months after surgery, we observed a statistically significant reduction in both the Unified Parkinson Disease Rating Scale part III and L-dopa equivalent daily dose. Areas consistently connected to the VTA included the brainstem (100%), cerebellum (94%), dorsal (i.e. supplementary motor area) and lateral premotor cortex (94%), and primary motor cortex (72%). An involvement of the hyperdirect pathway (HDP) connecting the STN and the (pre)motor cortex was demonstrated.Conclusions: The connectivity patterns observed in this study suggest that the therapeutic effects of STN-DBS are mediated through the modulation of distributed, large-scale motor networks. Specifically, the depiction of projection neurons connecting the stimulated area/STN to the (pre)motor cortex, reinforce the growing evidence that the HDP might be a potential therapeutic target in PD. If further replicated, these findings could raise the possibility that DTI-FT reconstruction of the HDP may critically improve DBS targeting and stimulation parameters selection, through the development of programming tools that incorporate VTA modelling and patient-specific DTI-FT data.