Resting-State Functional Connectivity Predicts STN DBS Clinical Response

Individualized Structural Perturbations on Normative Brain Connectome Restrict Deep Brain Stimulation Outcomes in Parkinson's Disease

BACKGROUND

Patients with Parkinson's disease (PD) respond to deep brain stimulation (DBS) variably. However, how brain substrates restrict DBS outcomes remains unclear.

OBJECTIVE

In this article, we aim to identify prognostic brain signatures for explaining the response variability.

METHODS

We retrospectively investigated a cohort of patients with PD (n = 141) between 2017 and 2022, and defined DBS outcomes as the improvement ratio of clinical motor scores. We used a deviation index to quantify individual perturbations on a reference structural covariance network acquired with preoperative T1-weighted magnetic resonance imaging. The neurobiological perturbations of patients were represented as z scored indices based on the chronological perturbations measured on a group of normal aging adults.

RESULTS

After applying stringent statistical tests (z > 2.5) and correcting for false discoveries (P < 0.01), we found that accelerated deviations mainly affected the prefrontal cortex, motor strip, limbic system, and cerebellum in PD. Particularly, a negative network within the accelerated deviations, expressed as "more preoperative deviations, less postoperative improvements," could predict DBS outcomes (mean absolute error = 0.09, R2 = 0.15). Moreover, a fusion of personal brain predictors and medical responses significantly improved traditional evaluations of DBS outcomes. Notably, the most important brain predictor, a pathway connecting the cognitive unit (prefrontal cortex) and motor control unit (cerebellum and motor strip), partially mediates DBS outcomes with the age at surgery.

CONCLUSIONS

Our findings suggest that individual structural perturbations on the cognitive motor control circuit are critical for modulating DBS outcomes. Interventions toward the circuit have the potential for additional clinical improvements. © 2024 The Author(s). Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

New Perspectives of Deep Brain Stimulation Indications for Parkinson's Disease: A Critical Review

Deep Brain Stimulation (DBS) is an effective treatment option for patients with dopaminergic complications of Parkinson's disease (PD) and drug-refractory PD tremor. However, DBS and its indications can be challenging, and they are not often debated in the medical community. Through a critical narrative review, the objective of this paper is to improve the comprehension of DBS indications and help to solve the puzzle that this process can be. Proper patient selection is the first step for a good surgical outcome. In this review, then, relevant considerations are discussed, involving PD genes, PD phenotypes, indications of early stages, non-motor symptoms, neuroimaging predictors, comorbidities, and age. Individualized approaches are encouraged, including clinical and radiological factors. Social support during the whole follow-up and expectations alignment are necessary through this process and are also debated.

Profiles of resting state functional connectivity in temporal lobe epilepsy associated with post-laser interstitial thermal therapy seizure outcomes and semiologies

Introduction

It is now understood that in focal epilepsy, impacted neural regions are not limited to the epileptogenic zone. As such, further investigation into the underlying functional connectivity (FC) patterns in those enduring Temporal Lobe Epilepsy (TLE) with Mesial Temporal Sclerosis (MTS) is imperative to understanding the intricacies of the disease.

Methods

The rsfMRIs of 17 healthy participants, 10 left-sided TLE-MTS patients with a pre-operative history of focal impaired awareness seizures (FIA), and 13 left-sided TLE-MTS patients with a pre-operative history of focal aware seizures (FA) were compared to determine the existence of distinct FC patterns with respect to seizure types. Similarly, the rsfMRIs of the above-mentioned healthy participants, 16 left-sided TLE-MTS individuals who were seizure-free (SF) 12 months postoperatively, and 16 left-sided TLE-MTS persons without seizure freedom (nSF) were interrogated. The ROI-to-ROI connectivity analysis included a total of 175 regions of interest (ROIs) and accounted for both age and duration of epileptic activity. Significant correlations were determined via two-sample t-tests and Bonferroni correction (α = 0.05).

Results

Comparisons of FA and FIA groups depicted significant correlations between the contralateral anterior cingulate gyrus, subgenual region, and the contralateral cerebellum, lobule III (p-value = 2.26e-4, mean z-score = -0.05 ± 0.28, T = -4.23). Comparisons of SF with nSF depicted two significantly paired-ROIs; the contralateral amygdala and the contralateral precuneus (p-value = 2.9e-5, mean z-score = -0.12 ± 0.19, T = 4.98), as well as the contralateral locus coeruleus and the ipsilateral intralaminar nucleus (p-value= 1.37e-4, mean z-score = 0.06 ± 0.17, T = -4.41).

Significance

FC analysis proves to be a lucrative modality for exploring unique signatures with respect to seizure types and postoperative outcomes. By furthering our understanding of the differences between epileptic phenotypes, we can achieve improvement in future treatment modalities not limited to targeting advancements.

The Role of Levodopa Challenge in Predicting the Outcome of Subthalamic Deep Brain Stimulation

Background

Deep brain stimulation of the subthalamic nucleus (STN-DBS) is an effective and evidence-based treatment for idiopathic Parkinson's disease (iPD). A minority of patients does not sufficiently benefit from STN-DBS.

Objective

The predictive validity of the levodopa challenge for individual patients is analyzed.

Methods

Data from patients assessed with a preoperative Levodopa-test and a follow-up examination (mean ± standard deviation: 9.15 months ±3.39) from Kiel (n = 253), Berlin (n = 78) and Toronto (n = 98) were studied. Insufficient DBS outcome was defined as an overall UPDRS-III reduction <33% compared to UPDRS-III in med-off at baseline or alternatively if the minimal clinically important improvement of 5 points was not reached. Single UPDRS-items and sub-scores were dichotomized. Following exploratory analysis, we trained supervised regression- and classification models for outcome prediction.

Results

Data analysis confirmed significant correlation between the absolute UPDRS-III reduction during Levodopa challenge and after stimulation. But individual improvement was inaccurately predicted with a large range of up to 30 UPDRS III points. Further analysis identified preoperative UPDRS-III/med-off-scores and preoperative Levodopa-improvement as most influential factors. The models for UPDRS-III and sub-scores improvement achieved comparably low accuracy.

Conclusions

With large prediction intervals, the Levodopa challenge use for patient counseling is limited, though remains important for excluding non-responders to Levodopa. Despite these deficiencies, the current practice of patient selection is highly successful and builds not only on the Levodopa challenge. However, more specific motor tasks and further paraclinical tools for prediction need to be developed.

Parkinson's disease may disrupt overlapping subthalamic nucleus and pallidal motor networks

There is an ongoing debate about differential clinical outcome and associated adverse effects of deep brain stimulation (DBS) in Parkinson's disease (PD) targeting the subthalamic nucleus (STN) or the globus pallidus pars interna (GPi). Given that functional connectivity profiles suggest beneficial DBS effects within a common network, the empirical evidence about the underlying anatomical circuitry is still scarce. Therefore, we investigate the STN and GPi-associated structural covariance brain patterns in PD patients and healthy controls. We estimate GPi's and STN's whole-brain structural covariance from magnetic resonance imaging (MRI) in a normative mid- to old-age community-dwelling cohort (n = 1184) across maps of grey matter volume, magnetization transfer (MT) saturation, longitudinal relaxation rate (R1), effective transversal relaxation rate (R2*) and effective proton density (PD*). We compare these with the structural covariance estimates in patients with idiopathic PD (n = 32) followed by validation using a reduced size controls' cohort (n = 32). In the normative data set, we observed overlapping spatially distributed cortical and subcortical covariance patterns across maps confined to basal ganglia, thalamus, motor, and premotor cortical areas. Only the subcortical and midline motor cortical areas were confirmed in the reduced size cohort. These findings contrasted with the absence of structural covariance with cortical areas in the PD cohort. We interpret with caution the differential covariance maps of overlapping STN and GPi networks in patients with PD and healthy controls as correlates of motor network disruption. Our study provides face validity to the proposed extension of the currently existing structural covariance methods based on morphometry features to multiparameter MRI sensitive to brain tissue microstructure.

The altered spontaneous neural activity in patients with Parkinson's disease and its predictive value for the motor improvement of deep brain stimulation

BACKGROUND

This study aims to investigate the altered spontaneous neural activity in patients with Parkinson's disease (PD) revealed by amplitudes of low-frequency fluctuations (ALFF) of resting-state fMRI, and the feasibility of using ALFF as neuroimaging predictors for motor improvement after bilateral subthalamic nucleus (STN) deep brain stimulation (DBS).

METHODS

Fourty-four patients and 44 healthy controls were included in this study. First, the ALFF of patients with PD was compared with that of controls; then significant clusters were correlated with motor improvement after DBS (unified Parkinson's disease rating scale (UPDRS-III)) and other clinical variables. Second, regression and classification of the machine learning models were conducted to predict motor improvement after DBS. Receiver operating characteristic (ROC) analysis was used to evaluate the performance of the classification model.

RESULTS

Compared with healthy controls, patients with PD showed increased ALFF in the bilateral motor area and decreased ALFF in the bilateral temporal cortex and cerebellum. The Hoehn-Yahr stages correlated with ALFF within the bilateral cerebellum (p = 0.021), and UPDRS-III improvement correlated with ALFF in the left (p < 0.001) and right (p = 0.005) motor areas. The regression model showed a significant correlation between the predicted and observed UPDRS-III changes (R = 0.65, p < 0.001). The ROC analysis revealed an area under the curve (AUC) of 0.94 which differentiated moderate and superior DBS responders.

CONCLUSION

The results revealed altered ALFF patterns in patients with PD and their correlations with clinical variables. Both binary and continuous ALFF can potentially serve as predictive biomarkers for DBS response.

The effect of deep brain stimulation in Parkinson's disease reflected in EEG microstates

Mechanisms of deep brain stimulation (DBS) on cortical networks were explored mainly by fMRI. Advanced analysis of high-density EEG is a source of additional information and may provide clinically useful biomarkers. The presented study evaluates EEG microstates in Parkinson's disease and the effect of DBS of the subthalamic nucleus (STN). The association between revealed spatiotemporal dynamics of brain networks and changes in oscillatory activity and clinical examination were assessed. Thirty-seven patients with Parkinson's disease treated by STN-DBS underwent two sessions (OFF and ON stimulation conditions) of resting-state EEG. EEG microstates were analyzed in patient recordings and in a matched healthy control dataset. Microstate parameters were then compared across groups and were correlated with clinical and neuropsychological scores. Of the five revealed microstates, two differed between Parkinson's disease patients and healthy controls. Another microstate differed between ON and OFF stimulation conditions in the patient group and restored parameters in the ON stimulation state toward to healthy values. The mean beta power of that microstate was the highest in patients during the OFF stimulation condition and the lowest in healthy controls; sources were localized mainly in the supplementary motor area. Changes in microstate parameters correlated with UPDRS and neuropsychological scores. Disease specific alterations in the spatiotemporal dynamics of large-scale brain networks can be described by EEG microstates. The approach can reveal changes reflecting the effect of DBS on PD motor symptoms as well as changes probably related to non-motor symptoms not influenced by DBS.

Value of functional connectivity in outcome prediction for pallidal stimulation in Parkinson disease

OBJECTIVE

Functional connectivity shows the ability to predict the outcome of subthalamic nucleus deep brain stimulation (DBS) in Parkinson disease (PD). However, evidence supporting its value in predicting the outcome of globus pallidus internus (GPi) DBS remains scarce. In this study the authors investigated patient-specific functional connectivity related to GPi DBS outcome in PD and established connectivity models for outcome prediction.

METHODS

The authors reviewed the outcomes of 21 patients with PD who received bilateral GPi DBS and presurgical functional MRI at the Ruijin Hospital. The connectivity profiles within cortical areas identified as relevant to DBS outcome in the literature were calculated using the intersection of the volume of tissue activated (VTA) and the local structures as the seeds. Combined with the leave-one-out cross-validation strategy, models of the optimal connectivity profile were constructed to predict outcome.

RESULTS

Connectivity between the pallidal areas and primary motor area, supplementary motor area (SMA), and premotor cortex was identified through the literature as related to GPi DBS outcome. The similarity between the connectivity profile within the primary motor area, SMA, pre-SMA, and premotor cortex seeding from the VTA-GPi intersection from an out-of-sample patient and the constructed in-sample optimal connectivity profile predicts GPi DBS outcome (R = 0.58, p = 0.006). The predictions on average deviated by 13.1% ± 11.3% from actual improvements. On the contrary, connectivity profiles seeding from the GPi (R = -0.12, p = 0.603), the VTA (R = 0.23, p = 0.308), the VTA outside the GPi (R = 0.12, p = 0.617), or other local structures were found not to be predictive.

CONCLUSIONS

The results showed that patient-specific functional connectivity seeding from the VTA-GPi intersection could help in GPi DBS outcome prediction. Reproducibility remains to be determined across centers in larger cohorts stratified by PD motor subtype.

Altered Functional Connectivity of the Subthalamic Nucleus in Parkinson's Disease: Focus on Candidates for Deep Brain Stimulation

BACKGROUND

The hypothesis that the effectiveness of deep brain stimulation (DBS) in Parkinson's disease (PD) would be related to connectivity dysfunctions between the site of stimulation and other brain regions is growing.

OBJECTIVE

To investigate how the subthalamic nucleus (STN), the most frequently used DBS target for PD, is functionally linked to other brain regions in PD patients according to DBS eligibility.

METHODS

Clinical data and resting-state functional MRI were acquired from 60 PD patients and 60 age- and sex-matched healthy subjects within an ongoing longitudinal project. PD patients were divided into 19 patients eligible for DBS and 41 non-candidates. Bilateral STN were selected as regions of interest and a seed-based functional MRI connectivity analysis was performed.

RESULTS

A decreased functional connectivity between STN and sensorimotor cortex in both PD patient groups compared to controls was found. Whereas an increased functional connectivity between STN and thalamus was found in PD patient groups relative to controls. Candidates for DBS showed a decreased functional connectivity between bilateral STN and bilateral sensorimotor areas relative to non-candidates. In patients eligible for DBS, a weaker STN functional connectivity with left supramarginal and angular gyri was related with a more severe rigidity and bradykinesia whereas a higher connectivity between STN and cerebellum/pons was related to poorer tremor score.

CONCLUSION

Our results suggest that functional connectivity of STN varies among PD patients eligible or not for DBS. Future studies would confirm whether DBS modulates and restores functional connectivity between STN and sensorimotor areas in treated patients.

Risk Factors for Hiccups after Deep Brain Stimulation of Subthalamic Nucleus for Parkinson's Disease

Background: After deep brain stimulation (DBS), hiccups as a complication may lead to extreme fatigue, sleep deprivation, or affected prognosis. Currently, the causes and risk factors of postoperative hiccups are unclear. In this study, we investigated the risk factors for hiccups after DBS of the subthalamic nucleus (STN) for Parkinson’s disease (PD) under general anesthesia. Methods: We retrospectively included patients who underwent STN DBS in the study, and collected data of demographic characteristics, clinical evaluations, and medications. According to the occurrence of hiccups within seven days after operation, the patients were divided into a hiccups group and non-hiccups group. The potentially involved risk factors for postoperative hiccups were statistically analyzed by logistic regression analysis. Results: A total of 191 patients were included in the study, of which 34 (17.80%) had postoperative transient persistent hiccups. Binary univariate logistic regression analysis showed that male, higher body mass index (BMI), smoker, Hoehn and Yahr stage (off), preoperative use of amantadine, hypnotic, Hamilton anxiety scale and Hamilton depression scale scores, and postoperative limited noninfectious peri-electrode edema in deep white matter were suspected risk factors for postoperative hiccups (p < 0.1). In binary multivariate logistic regression analysis, male (compared to female, OR 14.00; 95% CI, 1.74−112.43), postoperative limited noninfectious peri-electrode edema in deep white matter (OR, 7.63; 95% CI, 1.37−42.37), preoperative use of amantadine (OR, 3.64; 95% CI, 1.08−12.28), and higher BMI (OR, 3.50; 95% CI, 1.46−8.36) were independent risk factors for postoperative hiccups. Conclusions: This study is the first report about the risk factors of hiccups after STN DBS under general anesthesia for PD patients. The study suggests that male, higher BMI, preoperative use of amantadine, and postoperative limited noninfectious peri-electrode edema in deep white matter are independent risk factors for postoperative hiccups of STN-DBS for PD patients. Most hiccups after STN-DBS for PD patients were transient and self-limiting.

Deep brain-machine interfaces: sensing and modulating the human deep brain

Different from conventional brain-machine interfaces that focus more on decoding the cerebral cortex, deep brain-machine interfaces enable interactions between external machines and deep brain structures. They sense and modulate deep brain neural activities, aiming at function restoration, device control and therapeutic improvements. In this article, we provide an overview of multiple deep brain recording and stimulation techniques that can serve as deep brain-machine interfaces. We highlight two widely used interface technologies, namely deep brain stimulation and stereotactic electroencephalography, for technical trends, clinical applications and brain connectivity research. We discuss the potential to develop closed-loop deep brain-machine interfaces and achieve more effective and applicable systems for the treatment of neurological and psychiatric disorders.

Pretherapeutic functional connectivity of tractography-based targeting of the ventral intermediate nucleus for predicting tremor response in patients with Parkinson's disease after thalamotomy with MRI-guided focused ultrasound

OBJECTIVE

Tractography-based direct targeting of the ventral intermediate nucleus (T-VIM) is a novel method that provides patient-specific VIM coordinates. This study aimed to explore the accuracy and predictive value of using T-VIM in combination with tractography and resting-state functional connectivity techniques to perform magnetic resonance imaging-guided focused ultrasound (MRgFUS) thalamotomy as a treatment of Parkinson's disease (PD).

METHODS

PD patients underwent MRgFUS thalamotomy and were recruited for functional MRI scanning. A subscore of the Clinical Rating Scale for Tremor was used to evaluate tremor improvement. T-VIM and surgical VIM (S-VIM) were defined on preoperative diffusion tensor MRI and 24-hour postoperative T1-weighted imaging, respectively. The overlapping volume and center distance between S-VIM and T-VIM were measured to determine their correlations with 12-month postoperative tremor improvement. Moreover, pretherapeutic functional connectivity of T-VIM or S-VIM, based on region-of-interest connectivity and whole-brain seed-to-voxel connectivity, was measured with the resting-state functional connectivity technique to investigate their correlations with tremor improvement.

RESULTS

All patients had excellent tremor improvement (mean [range] tremor improvement 74.82% [50.00%-94.44%]). The authors found that both overlapping volume and center distance between T-VIM and S-VIM were significantly correlated with tremor improvement (r = 0.788 and p = 0.012 for overlapping volume; r = -0.696 and p = 0.037 for center distance). Pretherapeutic functional connectivity of T-VIM with the ipsilateral sensorimotor cortex (r = 0.876 and p = 0.002), subthalamic nucleus (r = 0.700 and p = 0.036), and visual area (r = 0.911 and p = 0.001) was significantly and positively correlated with tremor improvement.

CONCLUSIONS

T-VIM may improve the clinical application of MRgFUS thalamotomy as a treatment of PD. Pretherapeutic functional connectivity of T-VIM with the ipsilateral sensorimotor cortex, subthalamic nucleus, and visual area may predict PD tremor responses after MRgFUS thalamotomy.

Neurobiological effects of deep brain stimulation: A systematic review of molecular brain imaging studies

Deep brain stimulation (DBS) is an established treatment for several brain disorders, including Parkinson's disease, essential tremor, dystonia and epilepsy, and an emerging therapeutic tool in many other neurological and psychiatric disorders. The therapeutic efficacy of DBS is dependent on the stimulation target, but its mechanisms of action are still relatively poorly understood. Investigating these mechanisms is challenging, partly because the stimulation devices and electrodes have limited the use of functional MRI in these patients. Molecular brain imaging techniques, such as positron emission tomography (PET) and single photon emission tomography (SPET), offer a unique opportunity to characterize the whole brain effects of DBS. Here, we investigated the direct effects of DBS by systematically reviewing studies performing an `on' vs `off' contrast during PET or SPET imaging. We identified 62 studies (56 PET and 6 SPET studies; 531 subjects). Approximately half of the studies focused on cerebral blood flow or glucose metabolism in patients Parkinson's disease undergoing subthalamic DBS (25 studies, n = 289), therefore Activation Likelihood Estimation analysis was performed on these studies. Across disorders and stimulation targets, DBS was associated with a robust local increase in ligand uptake at the stimulation site and target-specific remote network effects. Subthalamic nucleus stimulation in Parkinson's disease showed a specific pattern of changes in the motor circuit, including increased ligand uptake in the basal ganglia, and decreased ligand uptake in the primary motor cortex, supplementary motor area and cerebellum. However, there was only a handful of studies investigating other brain disorder and stimulation site combinations (1-3 studies each), or specific neurotransmitter systems, preventing definitive conclusions of the detailed molecular effects of the stimulation in these cases.

Deep brain stimulation in dystonia: factors contributing to variability in outcome in short and long term follow-up

PURPOSE OF REVIEW

Deep brain stimulation (DBS) is currently the most effective treatment for medically refractory dystonia with globus pallidus internus (GPi) usually the preferred target. Despite the overall success of DBS in dystonia, there remains variability in treatment outcome in both short and long-term follow-up, due to various factors. Factors contributing to variability in outcome comprise 'Dystonia Related' including dystonia classification, semiology, duration, body distribution, orthopaedic deformity, aetiology and genetic cause. The majority of these factors are identifiable from clinical assessment, brain MRI and genetic testing, and therefore merit careful preoperative consideration. 'DBS related' factors include brain target, accuracy of lead placement, stimulation parameters, time allowed for response, neurostimulation technology employed and DBS induced side-effects. In this review, factors contributing to variability in short and long-term dystonia DBS outcome are reviewed and discussed.

RECENT FINDINGS

The recognition of differential DBS benefit in monogenic dystonia, increasing experience with subthalamic nucleus (STN) DBS and in DBS for Meige syndrome, elucidation of DBS side effects and novel neurophysiological and imaging techniques to assist in predicting clinical outcome.

SUMMARY

Improved understanding of factors contributing to variability of DBS outcome in dystonia may assist in patient selection and predicting surgical outcomes.

Network structure mediates functional reorganization induced by optogenetic stimulation of non-human primate sensorimotor cortex

Because aberrant network-level functional connectivity underlies a variety of neural disorders, the ability to induce targeted functional reorganization would be a profound development toward therapies for neural disorders. Brain stimulation has been shown to induce large-scale network-wide functional connectivity changes (FCC), but the mapping from stimulation to the induced changes is unclear. Here, we develop a model which jointly considers the stimulation protocol and the cortical network structure to accurately predict network-wide FCC in response to optogenetic stimulation of non-human primate primary sensorimotor cortex. We observe that the network structure has a much stronger effect than the stimulation protocol on the resulting FCC. We also observe that the mappings from these input features to the FCC diverge over frequency bands and successive stimulations. Our framework represents a paradigm shift for targeted neural stimulation and can be used to interrogate, improve, and develop stimulation-based interventions for neural disorders.

Is Resting State Functional MRI Effective Connectivity in Movement Disorders Helpful? A Focused Review Across Lifespan and Disease

In the evolving modern era of neuromodulation for movement disorders in adults and children, much progress has been made recently characterizing the human motor network (MN) with potentially important treatment implications. Herein is a focused review of relevant resting state fMRI functional and effective connectivity of the human motor network across the lifespan in health and disease. The goal is to examine how the transition from functional connectivity to dynamic effective connectivity may be especially informative of network-targeted movement disorder therapies, with hopeful implications for children.

Use of Functional MRI in Deep Brain Stimulation in Parkinson's Diseases: A Systematic Review

Deep brain stimulation (DBS) has been used to modulate aberrant circuits associated with Parkinson's disease (PD) for decades and has shown robust therapeutic benefits. However, the mechanism of action of DBS remains incompletely understood. With technological advances, there is an emerging use of functional magnetic resonance imaging (fMRI) after DBS implantation to explore the effects of stimulation on brain networks in PD. This systematic review was designed following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines to summarize peer-reviewed articles published within the past 10 years in which fMRI was employed on patients with PD-DBS. Search in PubMed database provided 353 references, and screenings resulted in a total of 19 studies for qualitative synthesis regarding study designs (fMRI scan timepoints and paradigm), methodology, and PD subtypes. This review concluded that fMRI may be used in patients with PD-DBS after proper safety test; resting-state and block-based fMRI designs have been employed to explore the effects of DBS on brain networks and the mechanism of action of the DBS, respectively. With further validation of safety use of fMRI and advances in imaging techniques, fMRI may play an increasingly important role in better understanding of the mechanism of stimulation as well as in improving clinical care to provide subject-specific neuromodulation treatments.

Functional connectivity in Parkinson's disease candidates for deep brain stimulation

This study aimed to identify functional neuroimaging patterns anticipating the clinical indication for deep brain stimulation (DBS) in patients with Parkinson’s disease (PD). A cohort of prospectively recruited patients with PD underwent neurological evaluations and resting-state functional MRI (RS-fMRI) at baseline and annually for 4 years. Patients were divided into two groups: 19 patients eligible for DBS over the follow-up and 41 patients who did not meet the criteria to undergo DBS. Patients selected as candidates for DBS did not undergo surgery at this stage. Sixty age- and sex-matched healthy controls performed baseline evaluations. Graph analysis and connectomics assessed global and local topological network properties and regional functional connectivity at baseline and at each time point. At baseline, network analysis showed a higher mean nodal strength, local efficiency, and clustering coefficient of the occipital areas in candidates for DBS over time relative to controls and patients not eligible for DBS. The occipital hyperconnectivity pattern was confirmed by regional analysis. At baseline, a decreased functional connectivity between basal ganglia and sensorimotor/frontal networks was found in candidates for DBS compared to patients not eligible for surgery. In the longitudinal analysis, patient candidate for DBS showed a progressively decreased topological brain organization and functional connectivity, mainly in the posterior brain networks, and a progressively increased connectivity of basal ganglia network compared to non-candidates for DBS. RS-fMRI may support the clinical indication to DBS and could be useful in predicting which patients would be eligible for DBS in the earlier stages of PD.

Factors correlated with therapeutic effects of globus pallidus deep brain stimulation on freezing of gait in advanced Parkinson's disease: A pilot study

INTRODUCTION

Deep brain stimulation (DBS) has showed variable therapeutic effect on freezing of gait (FOG) in Parkinson's disease (PD). It is unclear which factors associated with the effect of DBS on FOG in patients with advanced PD. In this study, we investigated the correlation of pre and postoperative factors with the therapeutic effect of globus pallidus interna (GPi) DBS on FOG in PD patients.

METHODS

We retrospectively analyzed PD patients with FOG (N = 20) who underwent GPi DBS surgery. Postoperatively, video-based analysis for FOG severity was performed at the first DBS programming and patients were categorized into two groups according to DBS effect on FOG (11 FOG responders and 9 FOG non-responders) at medication-off state. We analyzed preoperative clinical characteristics, cognitive function, striatal dopamine transporter availability, postoperative DBS programming parameters, lead locations, and volume of tissue activated in functional subregions of GPi. Bootstrap enhanced Elastic-Net logistic regression was used to select pre and postoperative factors associated with the effect of GPi DBS.

RESULTS

Therapeutic effect of GPi DBS on FOG were correlated with the disease duration of PD before DBS surgery, preoperative improvement in FOG severity by levodopa medication, and the distance from active contact of DBS electrode to the prefrontal region of GPi anatomical site.

CONCLUSIONS

Our study results suggest that the effect of GPi DBS on FOG is correlated with disease duration, levodopa responsiveness on FOG before DBS surgery and DBS electrode location, providing useful information to predict FOG outcome after GPi DBS in PD patients.

Clinical applications of magnetic resonance imaging based functional and structural connectivity

Advances in computational neuroimaging techniques have expanded the armamentarium of imaging tools available for clinical applications in clinical neuroscience. Non-invasive, in vivo brain MRI structural and functional network mapping has been used to identify therapeutic targets, define eloquent brain regions to preserve, and gain insight into pathological processes and treatments as well as prognostic biomarkers. These tools have the real potential to inform patient-specific treatment strategies. Nevertheless, a realistic appraisal of clinical utility is needed that balances the growing excitement and interest in the field with important limitations associated with these techniques. Quality of the raw data, minutiae of the processing methodology, and the statistical models applied can all impact on the results and their interpretation. A lack of standardization in data acquisition and processing has also resulted in issues with reproducibility. This limitation has had a direct impact on the reliability of these tools and ultimately, confidence in their clinical use. Advances in MRI technology and computational power as well as automation and standardization of processing methods, including machine learning approaches, may help address some of these issues and make these tools more reliable in clinical use. In this review, we will highlight the current clinical uses of MRI connectomics in the diagnosis and treatment of neurological disorders; balancing emerging applications and technologies with limitations of connectivity analytic approaches to present an encompassing and appropriate perspective.

Predicting Motor Outcome of Subthalamic Nucleus Deep Brain Stimulation for Parkinson's Disease Using Quantitative Susceptibility Mapping and Radiomics: A Pilot Study

Background

Emerging evidence indicates that iron distribution is heterogeneous within the substantia nigra (SN) and it may reflect patient-specific trait of Parkinson’s Disease (PD). We assume it could account for variability in motor outcome of subthalamic nucleus deep brain stimulation (STN-DBS) in PD.

Objective

To investigate whether SN susceptibility features derived from radiomics with machine learning (RA-ML) can predict motor outcome of STN-DBS in PD.

Methods

Thirty-three PD patients underwent bilateral STN-DBS were recruited. The bilateral SN were segmented based on preoperative quantitative susceptibility mapping to extract susceptibility features using RA-ML. MDS-UPDRS III scores were recorded 1–3 days before and 6 months after STN-DBS surgery. Finally, we constructed three predictive models using logistic regression analyses: (1) the RA-ML model based on radiomics features, (2) the RA-ML+LCT (levodopa challenge test) response model which combined radiomics features with preoperative LCT response, (3) the LCT response model alone.

Results

For the predictive performances of global motor outcome, the RA-ML model had 82% accuracy (AUC = 0.85), while the RA-ML+LCT response model had 74% accuracy (AUC = 0.83), and the LCT response model alone had 58% accuracy (AUC = 0.55). For the predictive performance of rigidity outcome, the accuracy of the RA-ML model was 80% (AUC = 0.85), superior to those of the RA-ML+LCT response model (76% accuracy, AUC = 0.82), and the LCT response model alone (58% accuracy, AUC = 0.42).

Conclusion

Our findings demonstrated that SN susceptibility features from radiomics could predict global motor and rigidity outcomes of STN-DBS in PD. This RA-ML predictive model might provide a novel approach to counsel candidates for STN-DBS.