Enlarging and shrinking focal perivascular spaces.

BACKGROUND AND PURPOSE: Perivascular spaces (PVS) are interstitial fluid-filled spaces surrounding blood vessels traversing the deep gray nuclei and white matter of the brain. These are commonly encountered on CT and MR imaging and are generally asymptomatic and of no clinical significance. However, occasional changes in the size of focal PVS, for example, when enlarging, may mimic pathologies including neoplasms and infections, hence potentially confounding radiological interpretation. Given these potential diagnostic issues, we sought to better characterize common clinical and imaging features of focal PVS demonstrating size fluctuations. MATERIALS AND METHODS: Upon institutional approval, we retrospectively identified 4 cases demonstrating PVS with size changes at our institution. To supplement our cases, we also performed a literature review, which identified an additional 14 cases. Their clinical and imaging data were analyzed to identify characteristic features. RESULTS: Of the 18 total cases (including the 4 institutional cases), 10 cases increased and 8 decreased in size. These focal PVS ranged from 0.4-4.5 cm in size. Whereas a decrease in size did not represent a diagnostic issue, focal increase in size of PVS led to concerning differential diagnoses in at least 30% of the radiology reports. These enlarging PVS were most found in the basal ganglia and temporal lobe, and in patients with previous brain radiation treatment. CONCLUSION: Focal size change of PVS can occur, especially years after brain radiation treatment. Being cognizant of this benign finding is important to consider in the differential diagnosis to avoid undue patient anxiety or unnecessary medical intervention.

A large normative connectome for exploring the tractographic correlates of focal brain interventions.

Diffusion-weighted MRI (dMRI) is a widely used neuroimaging modality that permits the in vivo exploration of white matter connections in the human brain. Normative structural connectomics - the application of large-scale, group-derived dMRI datasets to out-of-sample cohorts - have increasingly been leveraged to study the network correlates of focal brain interventions, insults, and other regions-of-interest (ROIs). Here, we provide a normative, whole-brain connectome in MNI space that enables researchers to interrogate fiber streamlines that are likely perturbed by given ROIs, even in the absence of subject-specific dMRI data. Assembled from multi-shell dMRI data of 985 healthy Human Connectome Project subjects using generalized Q-sampling imaging and multispectral normalization techniques, this connectome comprises ~12 million unique streamlines, the largest to date. It has already been utilized in at least 18 peer-reviewed publications, most frequently in the context of neuromodulatory interventions like deep brain stimulation and focused ultrasound. Now publicly available, this connectome will constitute a useful tool for understanding the wider impact of focal brain perturbations on white matter architecture going forward.

Neural signatures of indirect pathway activity during subthalamic stimulation in Parkinson's disease.

Deep brain stimulation (DBS) of the subthalamic nucleus (STN) produces an electrophysiological signature called evoked resonant neural activity (ERNA); a high-frequency oscillation that has been linked to treatment efficacy. However, the single-neuron and synaptic bases of ERNA are unsubstantiated. This study proposes that ERNA is a subcortical neuronal circuit signature of DBS-mediated engagement of the basal ganglia indirect pathway network. In people with Parkinson's disease, we: (i) showed that each peak of the ERNA waveform is associated with temporally-locked neuronal inhibition in the STN; (ii) characterized the temporal dynamics of ERNA; (iii) identified a putative mesocircuit architecture, embedded with empirically-derived synaptic dynamics, that is necessary for the emergence of ERNA in silico; (iv) localized ERNA to the dorsal STN in electrophysiological and normative anatomical space; (v) used patient-wise hotspot locations to assess spatial relevance of ERNA with respect to DBS outcome; and (vi) characterized the local fiber activation profile associated with the derived group-level ERNA hotspot.

Assessing the Emergence and Evolution of Artificial Intelligence and Machine Learning Research in Neuroradiology.

BACKGROUND AND PURPOSE: Interest in artificial intelligence (AI) and machine learning (ML) has been growing in neuroradiology, but there is limited knowledge on how this interest has manifested into research and specifically, its qualities and characteristics. This study aims to characterize the emergence and evolution of AI/ML articles within neuroradiology and provide a comprehensive overview of the trends, challenges, and future directions of the field. MATERIALS AND METHODS: We performed a bibliometric analysis of the American Journal of Neuroradiology (AJNR): the journal was queried for original research articles published since inception (Jan. 1, 1980) to Dec. 3, 2022 that contained any of the following key terms: "machine learning", "artificial intelligence", "radiomics", "deep learning", "neural network", "generative adversarial network", "object detection", or "natural language processing". Articles were screened by two independent reviewers, and categorized into Statistical Modelling (Type 1), AI/ML Development (Type 2), both representing developmental research work but without a direct clinical integration, or End-user Application (Type 3) which is the closest surrogate of potential AI/ML integration into day-to-day practice. To better understand the limiting factors to Type 3 articles being published, we analyzed Type 2 articles as they should represent the precursor work leading to Type 3. RESULTS: A total of 182 articles were identified with 79% being non-integration focused (Type 1 n = 53, Type 2 n = 90) and 21% (n = 39) being Type 3. The total number of articles published grew roughly five-fold in the last five years, with the non-integration focused articles mainly driving this growth. Additionally, a minority of Type 2 articles addressed bias (22%) and explainability (16%). These articles were primarily led by radiologists (63%), with most of them (60%) having additional postgraduate degrees. CONCLUSIONS: AI/ML publications have been rapidly increasing in neuroradiology with only a minority of this growth being attributable to end-user application. Areas identified for improvement include enhancing the quality of Type 2 articles, namely external validation, and addressing both bias and explainability. These results ultimately provide authors, editors, clinicians, and policymakers important insights to promote a shift towards integrating practical AI/ML solutions in neuroradiology. ABBREVIATIONS: AI = artificial intelligence; ML = machine learning.

Comparative neural correlates of DBS and MRgFUS lesioning for tremor control in essential tremor.

BACKGROUND: Given high rates of early complications and non-reversibility, refined targeting is necessitated for magnetic resonance-guided focused ultrasound (MRgFUS) thalamotomy for essential tremor (ET). Selection of lesion location can be informed by considering optimal stimulation area from deep brain stimulation (DBS). METHODS: 118 patients with ET who received DBS (39) or MRgFUS (79) of the ventral intermediate nucleus (VIM) underwent stimulation/lesion mapping, probabilistic mapping of clinical efficacy and normative structural connectivity analysis. The efficacy maps were compared, which depict the relationship between stimulation/lesion location and clinical outcome. RESULTS: Efficacy maps overlap around the VIM ventral border and encompass the dentato-rubro-thalamic tract. While the MRgFUS map extends inferiorly into the posterior subthalamic area, the DBS map spreads inside the VIM antero-superiorly. CONCLUSION: Comparing the efficacy maps of DBS and MRgFUS suggests a potential alternative location for lesioning, more antero-superiorly. This may reduce complications, without sacrificing efficacy, and individualise targeting. TRIAL REGISTRATION NUMBER: NCT02252380.

Uncovering neuroanatomical correlates of impaired coordinated movement after pallidal deep brain stimulation.

BACKGROUND: The loss of the ability to swim following deep brain stimulation (DBS), although rare, poses a worrisome risk of drowning. It is unclear what anatomic substrate and neural circuitry underlie this phenomenon. We report a case of cervical dystonia with lost ability to swim and dance during active stimulation of globus pallidus internus. We investigated the anatomical underpinning of this phenomenon using unique functional and structural imaging analysis. METHODS: Tesla (3T) functional MRI (fMRI) of the patient was used during active DBS and compared with a cohort of four matched patients without this side effect. Structural connectivity mapping was used to identify brain network engagement by stimulation. RESULTS: fMRI during stimulation revealed significant (Pbonferroni<0.0001) stimulation-evoked responses (DBS ON

Successful magnetic resonance-guided focused ultrasound treatment of tremor in patients with a skull density ratio of 0.4 or less.

OBJECTIVE: The use of magnetic resonance-guided focused ultrasound (MRgFUS) for the treatment of tremor-related disorders and other novel indications has been limited by guidelines advocating treatment of patients with a skull density ratio (SDR) above 0.45 ± 0.05 despite reports of successful outcomes in patients with a low SDR (LSDR). The authors' goal was to retrospectively analyze the sonication strategies, adverse effects, and clinical and imaging outcomes in patients with SDR ≤ 0.4 treated for tremor using MRgFUS. METHODS: Clinical outcomes and adverse effects were assessed at 3 and 12 months after MRgFUS. Outcomes and lesion location, volume, and shape characteristics (elongation and eccentricity) were compared between the SDR groups. RESULTS: A total of 102 consecutive patients were included in the analysis, of whom 39 had SDRs ≤ 0.4. No patient was excluded from treatment because of an LSDR, with the lowest being 0.22. Lesioning temperatures (> 52°C) and therapeutic ablations were achieved in all patients. There were no significant differences in clinical outcome, adverse effects, lesion location, and volume between the high SDR group and the LSDR group. SDR was significantly associated with total energy (rho = -0.459, p < 0.001), heating efficiency (rho = 0.605, p < 0.001), and peak temperature (rho = 0.222, p = 0.025). CONCLUSIONS: The authors' results show that treatment of tremor in patients with an LSDR using MRgFUS is technically possible, leading to a safe and lasting therapeutic effect. Limiting the number of sonications and adjusting the energy and duration to achieve the required temperature early during the treatment are suitable strategies in LSDR patients.

WarpDrive: Improving spatial normalization using manual refinements.

Spatial normalization-the process of mapping subject brain images to an average template brain-has evolved over the last 20+ years into a reliable method that facilitates the comparison of brain imaging results across patients, centers & modalities. While overall successful, sometimes, this automatic process yields suboptimal results, especially when dealing with brains with extensive neurodegeneration and atrophy patterns, or when high accuracy in specific regions is needed. Here we introduce WarpDrive, a novel tool for manual refinements of image alignment after automated registration. We show that the tool applied in a cohort of patients with Alzheimer's disease who underwent deep brain stimulation surgery helps create more accurate representations of the data as well as meaningful models to explain patient outcomes. The tool is built to handle any type of 3D imaging data, also allowing refinements in high-resolution imaging, including histology and multiple modalities to precisely aggregate multiple data sources together.

Postoperative cerebellar mutism syndrome is an acquired Autism-like network disturbance.

BACKGROUND: Cerebellar mutism syndrome (CMS) is a common and debilitating complication of posterior fossa tumour surgery in children. Affected children exhibit communication and social impairments that overlap phenomenologically with subsets of deficits exhibited by children with Autism spectrum disorder (ASD). Although both CMS and ASD are thought to involve disrupted cerebro-cerebellar circuitry, they are considered independent conditions due to an incomplete understanding of their shared neural substrates. METHODS: In this study, we analyzed post-operative cerebellar lesions from 90 children undergoing posterior fossa resection of medulloblastoma, 30 of whom developed CMS. Lesion locations were mapped to a standard atlas, and the networks functionally connected to each lesion were computed in normative adult and paediatric datasets. Generalizability to ASD was assessed using an independent cohort of children with ASD and matched controls (n=427). RESULTS: Lesions in children who developed CMS involved the vermis and inferomedial cerebellar lobules. They engaged large-scale cerebellothalamocortical circuits with a preponderance for the prefrontal and parietal cortices in the paediatric and adult connectomes, respectively. Moreover, with increasing connectomic age, CMS-associated lesions demonstrated stronger connectivity to the midbrain/red nuclei, thalami and inferior parietal lobules and weaker connectivity to prefrontal cortex. Importantly, the CMS-associated lesion network was independently reproduced in ASD and correlated with communication and social deficits, but not repetitive behaviours. CONCLUSIONS: Our findings indicate that CMS-associated lesions result in an ASD-like network disturbance that occurs during sensitive windows of brain development. A common network disturbance between CMS and ASD may inform improved treatment strategies for affected children.

Dissociable default-mode subnetworks subserve childhood attention and cognitive flexibility: Evidence from deep learning and stereotactic electroencephalography.

Cognitive flexibility encompasses the ability to efficiently shift focus and forms a critical component of goal-directed attention. The neural substrates of this process are incompletely understood in part due to difficulties in sampling the involved circuitry. We leverage stereotactic intracranial recordings to directly resolve local-field potentials from otherwise inaccessible structures to study moment-to-moment attentional activity in children with epilepsy performing a flexible attentional task. On an individual subject level, we employed deep learning to decode neural features predictive of task performance indexed by single-trial reaction time. These models were subsequently aggregated across participants to identify predictive brain regions based on AAL atlas and FIND functional network parcellations. Through this approach, we show that fluctuations in beta (12-30 Hz) and gamma (30-80 Hz) power reflective of increased top-down attentional control and local neuronal processing within relevant large-scale networks can accurately predict single-trial task performance. We next performed connectomic profiling of these highly predictive nodes to examine task-related engagement of distributed functional networks, revealing exclusive recruitment of the dorsal default mode network during shifts in attention. The identification of distinct substreams within the default mode system supports a key role for this network in cognitive flexibility and attention in children. Furthermore, convergence of our results onto consistent functional networks despite significant inter-subject variability in electrode implantations supports a broader role for deep learning applied to intracranial electrodes in the study of human attention.

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.

Deep Brain Stimulation of the Globus Pallidus Internus and Externus in Multiple System Atrophy.

BACKGROUND: Multiple system atrophy with parkinsonism (MSA-P) is a progressive condition with no effective treatment. OBJECTIVE: The aim of this study was to describe the safety and efficacy of deep brain stimulation (DBS) of globus pallidus pars interna and externa in a cohort of patients with MSA-P. METHODS: Six patients were included. Changes in Movement Disorders Society Unified Parkinson's Disease Rating Scale Part III (MDS-UPDRS III), Parkinson's Disease Questionnaire (PDQ-39) scores, and levodopa equivalent daily dose were compared before and after DBS. Electrode localization and volume tissue activation were calculated. RESULTS: DBS surgery did not result in any major adverse events or intraoperative complications. Overall, no differences in MDS-UPDRS III scores were demonstrated (55.2 ± 17.6 preoperatively compared with 67.3 ± 19.2 at 1 year after surgery), although transient improvement in mobility and dyskinesia was reported in some subjects. CONCLUSIONS: Globus pallidus pars interna and externa DBS for patients with MSA-P did not result in major complications, although it did not provide significant clinical benefit as measured by MDS-UPDRS III. © 2023 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

Multi-centre analysis of networks and genes modulated by hypothalamic stimulation in patients with aggressive behaviours.

Deep brain stimulation targeting the posterior hypothalamus (pHyp-DBS) is being investigated as a treatment for refractory aggressive behavior, but its mechanisms of action remain elusive. We conducted an integrated imaging analysis of a large multi-centre dataset, incorporating volume of activated tissue modeling, probabilistic mapping, normative connectomics, and atlas-derived transcriptomics. Ninety-one percent of the patients responded positively to treatment, with a more striking improvement recorded in the pediatric population. Probabilistic mapping revealed an optimized surgical target within the posterior-inferior-lateral region of the posterior hypothalamic area. Normative connectomic analyses identified fiber tracts and functionally connected with brain areas associated with sensorimotor function, emotional regulation, and monoamine production. Functional connectivity between the target, periaqueductal gray and key limbic areas - together with patient age - were highly predictive of treatment outcome. Transcriptomic analysis showed that genes involved in mechanisms of aggressive behavior, neuronal communication, plasticity and neuroinflammation might underlie this functional network.

Advances in Technical Aspects of Deep Brain Stimulation Surgery.

BACKGROUND: Deep brain stimulation has become an established technology for the treatment of patients with a wide variety of conditions, including movement disorders, psychiatric disorders, epilepsy, and pain. Surgery for implantation of DBS devices has enhanced our understanding of human physiology, which in turn has led to advances in DBS technology. Our group has previously published on these advances, proposed future developments, and examined evolving indications for DBS. SUMMARY: The crucial roles of structural MR imaging pre-, intra-, and post-DBS procedure in target visualization and confirmation of targeting are described, with discussion of new MR sequences and higher field strength MRI enabling direct visualization of brain targets. The incorporation of functional and connectivity imaging in procedural workup and their contribution to anatomical modelling is reviewed. Various tools for targeting and implanting electrodes, including frame-based, frameless, and robot-assisted, are surveyed, and their pros and cons are described. Updates on brain atlases and various software used for planning target coordinates and trajectories are presented. The pros and cons of asleep versus awake surgery are discussed. The role and value of microelectrode recording and local field potentials are described, as well as the role of intraoperative stimulation. Technical aspects of novel electrode designs and implantable pulse generators are presented and compared.

Optimal deep brain stimulation sites and networks for stimulation of the fornix in Alzheimer's disease.

Deep brain stimulation (DBS) to the fornix is an investigational treatment for patients with mild Alzheimer's Disease. Outcomes from randomized clinical trials have shown that cognitive function improved in some patients but deteriorated in others. This could be explained by variance in electrode placement leading to differential engagement of neural circuits. To investigate this, we performed a post-hoc analysis on a multi-center cohort of 46 patients with DBS to the fornix (NCT00658125, NCT01608061). Using normative structural and functional connectivity data, we found that stimulation of the circuit of Papez and stria terminalis robustly associated with cognitive improvement (R = 0.53, p < 0.001). On a local level, the optimal stimulation site resided at the direct interface between these structures (R = 0.48, p < 0.001). Finally, modulating specific distributed brain networks related to memory accounted for optimal outcomes (R = 0.48, p < 0.001). Findings were robust to multiple cross-validation designs and may define an optimal network target that could refine DBS surgery and programming.

Magnetic resonance-guided focused ultrasound for the treatment of tremor.

INTRODUCTION: Magnetic resonance-guided focused ultrasound (MRgFUS) is an emerging treatment for tremor and other movement disorders. An incisionless therapy, it is becoming increasingly common worldwide. However, given MRgFUS' relative novelty, there remain limited data on its benefits and adverse effects. AREAS COVERED: We review the current state of evidence of MRgFUS for tremor, highlight its challenges, and discuss future perspectives. EXPERT OPINION: Essential tremor (ET) has been the major indication for MRgFUS since a milestone randomized controlled trial (RCT) in 2016, with substantial evidence attesting to the efficacy and acceptable safety profile of this treatment. Patients with other tremor etiologies are also being treated with MRgFUS, with studies - including an RCT - suggesting parkinsonian tremor in particular responds well to this intervention. Additionally, targets other than the ventral intermediate nucleus, such as the subthalamic nucleus and internal segment of the globus pallidus, have been reported to improve parkinsonian symptoms beyond tremor, including rigidity and bradykinesia. Although MRgFUS is encumbered by certain unique technical challenges, it nevertheless offers significant advantages compared to alternative neurosurgical interventions for tremor. The fast-growing interest in this treatment modality will likely lead to further scientific and technological advancements that could optimize and expand its therapeutic potential.

Lesion network mapping of ectopic craniopharyngioma identifies potential cause of psychosis: a case report.

We report the case of a patient with craniopharyngioma who demonstrated ectopic spread to the right temporal lobe and concurrent local recurrence, 10 years after her initial diagnosis. The patient additionally demonstrated new-onset psychotic symptoms of uncertain etiology during her admission. Lesion network mapping identified the ectopic lesion as a putative cause for her psychosis. These findings were substantiated after the resection of the ectopic lesion and subsequent resolution of her psychiatric symptoms. This report adds to the rare accounts of ectopic craniopharyngioma, while highlighting the utility of network-based analyses in peri-operative tumor evaluation and the assessment of atypical neuropsychiatric phenomena.