Iron concentration linked to structural connectivity in the subthalamic nucleus: implications for deep brain stimulation

2020 ◽  
Vol 132 (1) ◽  
pp. 197-204 ◽  
Author(s):  
Alexey Dimov ◽  
Wahaj Patel ◽  
Yihao Yao ◽  
Yi Wang ◽  
Rafael O’Halloran ◽  
...  
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Deep Brain Stimulation ◽  
Subthalamic Nucleus ◽  
Brain Stimulation ◽  
Iron Concentration ◽  
Susceptibility Mapping ◽  
Strong Positive Correlation ◽  
Quantitative Susceptibility Mapping ◽  
Deep Brain

OBJECTIVEThe objective of this study was to investigate the relationship between iron and white matter connectivity in the subthalamic nucleus (STN) in patients undergoing deep brain stimulation (DBS) of the STN for treatment of Parkinson’s disease.METHODSNine Parkinson’s disease patients underwent preoperative 3T MRI imaging which included acquisition of T1-weighted anatomical images along with diffusion tensor imaging (DTI) and quantitative susceptibility mapping (QSM). MR tractography was performed for the seed voxels located within the STN, and the correlations between normalized QSM values and the STN’s connectivity to a set of a priori chosen regions of interest were assessed.RESULTSA strong negative correlation was found between STN connectivity and QSM intensity for the thalamus, premotor, motor, and sensory regions, while a strong positive correlation was found for frontal, putamen, and brain stem areas.CONCLUSIONSQuantitative susceptibility mapping not only accurately delineates the STN borders but is also able to provide functional information about the STN functional subdivisions. The observed iron-to-connectivity correlation patterns may aid in planning DBS surgery to avoid unwanted side effects associated with DBS.

Utilization of Quantitative Susceptibility Mapping for Direct Targeting of the Subthalamic Nucleus During Deep Brain Stimulation Surgery

2017 ◽  
Vol 14 (4) ◽  
pp. 412-419 ◽  
Author(s):  
Jonathan Rasouli ◽  
Ritesh Ramdhani ◽  
Fedor E Panov ◽  
Alexey Dimov ◽  
Yan Zhang ◽  
...  
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Deep Brain Stimulation ◽  
Clinical Response ◽  
Subthalamic Nucleus ◽  
Brain Stimulation ◽  
Quantitative Susceptibility Mapping ◽  
Direct Targeting ◽  
Satisfactory Clinical Response ◽  
Deep Brain

AbstractBACKGROUNDDeep brain stimulation of the subthalamic nucleus (STN) has demonstrated efficacy in improving motor disability in Parkinson's disease. The recently developed quantitative susceptibility mapping (QSM) technique, which can accurately map iron deposits in deep brain nuclei, promises precise targeting of the STN.OBJECTIVETo demonstrate the use of QSM to target STN effectively by correlating with classical physiological-based targeting measures in a prospective study.METHODSThe precision and accuracy of direct targeting with QSM was examined in a total of 25 Parkinson's disease patients between 2013 and 2015 at our institution. QSM was utilized as the primary magnetic resonance imaging (MRI) method to perform direct STN targeting on a stereotactic planning station utilizing computed tomography/MR fusion. Intraoperative microelectrode recordings (MER) were obtained to confirm appropriate trajectory through the sensorimotor STN.RESULTSEstimations of STN thickness between the MER and QSM methods appeared to be correlated. Mean STN thickness was 5.3 mm. Kinesthetic responsive cells were found in > 90% of electrode runs. The mean radial error (±SEM) was 0.54 ± 0.1 mm. Satisfactory clinical response as determined by Unified Parkinson's Disease Rating Scale (UPDRS III) was seen at 12 mo after surgery.CONCLUSIONDirect targeting of the sensorimotor STN using QSM demonstrates MER correlation and can be safely used for deep brain stimulation lead placement with satisfactory clinical response. These results imply that targeting based on QSM signaling alone is sufficient to obtain reliable and reproducible outcomes in the absence of physiological recordings.

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

2021 ◽  
Vol 15 ◽  
Author(s):  
Yu Liu ◽  
Bin Xiao ◽  
Chencheng Zhang ◽  
Junchen Li ◽  
Yijie Lai ◽  
...  
Keyword(s):  
Parkinson’S Disease ◽  
Deep Brain Stimulation ◽  
Subthalamic Nucleus ◽  
Brain Stimulation ◽  
Susceptibility Mapping ◽  
Response Model ◽  
Quantitative Susceptibility Mapping ◽  
Motor Outcome ◽  
Stn Dbs ◽  
Deep Brain

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

Precise targeting of the globus pallidus internus with quantitative susceptibility mapping for deep brain stimulation surgery

2020 ◽  
Vol 133 (5) ◽  
pp. 1605-1611 ◽  
Author(s):  
Hongjiang Wei ◽  
Chencheng Zhang ◽  
Tao Wang ◽  
Naying He ◽  
Dianyou Li ◽  
...  
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Deep Brain Stimulation ◽  
Globus Pallidus ◽  
Brain Stimulation ◽  
Susceptibility Mapping ◽  
Globus Pallidus Internus ◽  
Quantitative Susceptibility Mapping ◽  
Lead Position ◽  
Deep Brain

OBJECTIVEThe goal of this study was to demonstrate the use of quantitative susceptibility mapping (QSM)–based images to precisely localize the globus pallidus internus (GPi) for deep brain stimulation (DBS) planning and to enhance postsurgical visualization of the DBS lead positions.METHODSPresurgical T1-weighted (T1w), T2-weighted (T2w), and QSM images as well as postsurgical CT images were obtained in 29 patients with Parkinson’s disease. To enhance the contrast within the GP, a hybrid contrast was created by linearly combining T1w and QSM images. Contrast-to-noise ratios (CNRs) of the GPi on T1w, T2w, QSM, and hybrid images were compared. The CNR differences were tested using the 1-way ANOVA method. The visualization of the DBS lead position was demonstrated by merging the postsurgical CT with presurgical MR images.RESULTSThe hybrid images yield the best CNRs for GPi depiction and the visualization of the postsurgical DBS lead position was significantly improved.CONCLUSIONSQSM-based images allow for confident localization of borders of the GPi that is superior to T1w and T2w images. High-contrast hybrid images can be used for precisely directed DBS targeting, e.g., GPi DBS for the treatment of advanced Parkinson’s disease.

Coronal Gradient Echo MRI to Visualize the Zona Incerta for Deep Brain Stimulation Targeting in Parkinson’s Disease

2021 ◽  
pp. 1-8
Author(s):  
Ashesh A. Thaker ◽  
Kartik M. Reddy ◽  
John A. Thompson ◽  
Pamela David Gerecht ◽  
Mark S. Brown ◽  
...  
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Deep Brain Stimulation ◽  
Subthalamic Nucleus ◽  
Brain Stimulation ◽  
Regions Of Interest ◽  
Zona Incerta ◽  
Gradient Echo ◽  
Noise Ratio ◽  
Deep Brain

<b><i>Introduction:</i></b> Deep brain stimulation of the zona incerta is effective at treating tremor and other forms of parkinsonism. However, the structure is not well visualized with standard MRI protocols making direct surgical targeting unfeasible and contributing to inconsistent clinical outcomes. In this study, we applied coronal gradient echo MRI to directly visualize the rostral zona incerta in Parkinson’s disease patients to improve targeting for deep brain stimulation. <b><i>Methods:</i></b> We conducted a prospective study to optimize and evaluate an MRI sequence to visualize the rostral zona incerta in patients with Parkinson’s disease (<i>n</i> = 31) and other movement disorders (<i>n</i> = 13). We performed a contrast-to-noise ratio analysis of specific regions of interest to quantitatively assess visual discrimination of relevant deep brain structures in the optimized MRI sequence. Regions of interest were independently assessed by 2 neuroradiologists, and interrater reliability was assessed. <b><i>Results:</i></b> Rostral zona incerta and subthalamic nucleus were well delineated in our 5.5-min MRI sequence, indicated by excellent interrater agreement between neuroradiologists for region-of-interest measurements (&#x3e;0.90 intraclass coefficient). Mean contrast-to-noise ratio was high for both rostral zona incerta (6.39 ± 3.37) and subthalamic nucleus (17.27 ± 5.61) relative to adjacent white matter. There was no significant difference between mean signal intensities or contrast-to-noise ratio for Parkinson’s and non-Parkinson’s patients for either structure. <b><i>Discussion/Conclusion:</i></b> Our optimized coronal gradient echo MRI sequence delineates subcortical structures relevant to traditional and novel deep brain stimulation targets, including the zona incerta, with high contrast-to-noise. Future studies will prospectively apply this sequence to surgical planning and postimplantation outcomes.

scholarly journals Electrode Location in a Microelectrode Recording-Based Model of the Subthalamic Nucleus Can Predict Motor Improvement After Deep Brain Stimulation for Parkinson’s Disease

2019 ◽  
Vol 9 (3) ◽  
pp. 51 ◽  
Author(s):  
Rens Verhagen ◽  
Lo Bour ◽  
Vincent Odekerken ◽  
Pepijn van den Munckhof ◽  
P. Schuurman ◽  
...  
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Deep Brain Stimulation ◽  
Subthalamic Nucleus ◽  
Brain Stimulation ◽  
Anatomical Variation ◽  
Patient Specific ◽  
One Year ◽  
Motor Improvement ◽  
Deep Brain

Motor improvement after deep brain stimulation (DBS) in the subthalamic nucleus (STN) may vary substantially between Parkinson’s disease (PD) patients. Research into the relation between improvement and active contact location requires a correction for anatomical variation. We studied the relation between active contact location relative to the neurophysiological STN, estimated by the intraoperative microelectrode recordings (MER-based STN), and contralateral motor improvement after one year. A generic STN shape was transformed to fit onto the stereotactically defined MER sites. The location of 43 electrodes (26 patients), derived from MRI-fused CT images, was expressed relative to this patient-specific MER-based STN. Using regression analyses, the relation between contact location and motor improvement was studied. The regression model that predicts motor improvement based on levodopa effect alone was significantly improved by adding the one-year active contact coordinates (R2 change = 0.176, p = 0.014). In the combined prediction model (adjusted R2 = 0.389, p < 0.001), the largest contribution was made by the mediolateral location of the active contact (standardized beta = 0.490, p = 0.002). With the MER-based STN as a reference, we were able to find a significant relation between active contact location and motor improvement. MER-based STN modeling can be used to complement imaging-based STN models in the application of DBS.

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