Opicapone to Treat Early Wearing-off in Parkinson's Disease Patients: The Korean ADOPTION Trial.

BACKGROUND: Increasing levodopa (L-dopa)/dopa decarboxylase inhibitor (DDCI) daily dose or adding a catechol-O-methyltransferase (COMT) inhibitor to levodopa/DDCI therapy are strategies used to manage wearing-off symptoms in Parkinson's disease (PD) patients. OBJECTIVES: To evaluate the COMT inhibitor opicapone versus an additional dose of levodopa to treat early wearing-off in PD patients. METHODS: ADOPTION was a randomized, parallel-group, open-label, Phase 4 study conducted in Korea. At baseline, eligible patients were randomized (1:1) to opicapone 50 mg (n = 87) or L-dopa 100 mg (n = 81) (added to current L-dopa/DDCI therapy) for 4 weeks. The main efficacy endpoint was change from baseline to end of study in absolute off time. Other endpoints included changes in on time, in Movement Disorder Society-Unified Parkinson's Disease Rating Scale and 8-item PD Questionnaire scores, and the Clinical and Patient Global Impression of Improvement/Change. RESULTS: The adjusted mean in absolute off time was significantly greater for opicapone 50 mg than for L-dopa 100 mg (-62.1 vs. -16.7 minutes; P = 0.0015). Opicapone-treated patients also reported a greater reduction in the percentage of off time (P = 0.0015), a greater increase in absolute on time (P = 0.0338) and a greater increase in the percentage of on time (P = 0.0015). There were no significant differences in other secondary endpoints. The L-dopa equivalent daily dose was significantly higher in the opicapone group (750.9 vs. 690.0 mg; P = 0.0247), when a 0.5 conversion factor is applied. CONCLUSIONS: Opicapone 50 mg was more effective than an additional 100 mg L-dopa dose at decreasing off time in patients with PD and early wearing-off.

Predicting cognitive decline in Parkinson's disease using FDG-PET-based supervised learning.

BackgroundCognitive impairment is a common symptom of Parkinson's disease (PD) that increases in risk and severity as the disease progresses. An accurate prediction of the risk of progression from the mild cognitive impairment (MCI) stage to the dementia (PDD) stage is an unmet clinical need.MethodsWe investigated the use of a supervised learning algorithm called the support vector machine (SVM) to retrospectively stratify patients on the basis of brain fluorodeoxyglucose-PET (FDG-PET) scans. Of 43 patients with PD-MCI according to the baseline scan, 23 progressed to PDD within a 5-year period, whereas 20 maintained stable MCI. The baseline scans were used to train a model, which separated patients identified as PDD converters versus those with stable MCI with 95% sensitivity and 91% specificity.ResultsIn an independent validation data set of 19 patients, the AUC was 0.73, with 67% sensitivity and 80% specificity. The SVM model was topographically characterized by hypometabolism in the temporal and parietal lobes and hypermetabolism in the anterior cingulum and putamen and the insular, mesiotemporal, and postcentral gyri. The performance of the SVM model was further tested on 2 additional data sets, which confirmed that the model was also sensitive to later-stage PDD (17 of 19 patients; 89% sensitivity) and dementia with Lewy bodies (DLB) (16 of 17 patients; 94% sensitivity), but not to normal cognition PD (2 of 17 patients). Finally, anti-PD medication status did not change the SVM classification of the other set of 10 patients with PD who were scanned twice, ON and OFF medication.ConclusionsThese results potentially indicate that the proposed FDG-PET-based SVM classifier has utility for providing an accurate prognosis of dementia development in patients with PD-MCI.

Evaluation of low-pass genome sequencing in polygenic risk score calculation for Parkinson's disease.

BACKGROUND: Low-pass sequencing (LPS) has been extensively investigated for applicability to various genetic studies due to its advantages over genotype array data including cost-effectiveness. Predicting the risk of complex diseases such as Parkinson's disease (PD) using polygenic risk score (PRS) based on the genetic variations has shown decent prediction accuracy. Although ultra-LPS has been shown to be effective in PRS calculation, array data has been favored to the majority of PRS analysis, especially for PD. RESULTS: Using eight high-coverage WGS, we assessed imputation approaches for downsampled LPS data ranging from 0.5 × to 7.0 × . We demonstrated that uncertain genotype calls of LPS diminished imputation accuracy, and an imputation approach using genotype likelihoods was plausible for LPS. Additionally, comparing imputation accuracies between LPS and simulated array illustrated that LPS had higher accuracies particularly at rare frequencies. To evaluate ultra-low coverage data in PRS calculation for PD, we prepared low-coverage WGS and genotype array of 87 PD cases and 101 controls. Genotype imputation of array and downsampled LPS were conducted using a population-specific reference panel, and we calculated risk scores based on the PD-associated SNPs from an East Asian meta-GWAS. The PRS models discriminated cases and controls as previously reported when both LPS and genotype array were used. Also strong correlations in PRS models for PD between LPS and genotype array were discovered. CONCLUSIONS: Overall, this study highlights the potentials of LPS under 1.0 × followed by genotype imputation in PRS calculation and suggests LPS as attractive alternatives to genotype array in the area of precision medicine for PD.

Diagnostic accuracy of dual-phase 18F-FP-CIT PET imaging for detection and differential diagnosis of Parkinsonism.

Delayed phase 18F-FP-CIT PET (dCIT) can assess the striatal dopamine transporter binding to detect degenerative parkinsonism (DP). Early phase 18F-FP-CIT (eCIT) can assess the regional brain activity for differential diagnosis among parkinsonism similar with 18F-FDG PET. We evaluated the diagnostic performance of dual phase 18F-FP-CIT PET (dual CIT) and 18F-FDG PET compared with clinical diagnosis in 141 subjects [36 with idiopathic Parkinson's disease (IPD), 77 with multiple system atrophy (MSA), 18 with progressive supranuclear palsy (PSP), and 10 with non-DP)]. Visual assessment of eCIT, dCIT, dual CIT, 18F-FDG and 18F-FDG PET with dCIT was in agreement with the clinical diagnosis in 61.7%, 69.5%, 95.7%, 81.6%, and 97.2% of cases, respectively. ECIT showed about 90% concordance with non-DP and MSA, and 8.3% and 27.8% with IPD and PSP, respectively. DCIT showed ≥ 88% concordance with non-DP, IPD, and PSP, and 49.4% concordance with MSA. Dual CIT showed ≥ 90% concordance in all groups. 18F-FDG PET showed ≥ 90% concordance with non-DP, MSA, and PSP, but only 33.3% concordance with IPD. The combination of 18F-FDG and dCIT yielded ≥ 90% concordance in all groups. Dual CIT may represent a powerful alternative to the combination of 18F-FDG PET and dCIT for differential diagnosis of parkinsonian disorders.

Pretreatment brain volumes can affect the effectiveness of deep brain stimulation in Parkinson's disease patients.

We aimed to assess whether brain volumes may affect the results of deep brain stimulation (DBS) in patients with Parkinson's disease (PD). Eighty-one consecutive patients with PD (male:female 40:41), treated with DBS between June 2012 and December 2017, were enrolled. Total and regional brain volumes were measured using automated brain volumetry (NeuroQuant). The Unified Parkinson Disease Rating Scale motor score quotient was used to assess changes in clinical outcome and compare the preoperative regional brain volume in patients categorized into the higher motor improvement and lower motor improvement groups based on changes in the postoperative scores. The study groups showed significant volume differences in multiple brain areas. In the higher motor improvement group, the anterior cingulate and right thalamus showed high volumes after false discovery rate (FDR) correction. In the lower motor improvement group, the left caudate, paracentral, right primary sensory and left primary motor cortex showed high volume, but no area showed high volumes after FDR correction. Our data suggest that the effectiveness of DBS in patients with PD may be affected by decreased brain volume in different areas, including the cingulate gyrus and thalamus. Preoperative volumetry could help predict outcomes in patients with PD undergoing DBS.

Clinical Evaluation of 18F-PI-2620 as a Potent PET Radiotracer Imaging Tau Protein in Alzheimer Disease and Other Neurodegenerative Diseases Compared With 18F-THK-5351.

PURPOSE: PET is a useful tool for detecting the presence and extent of brain tau accumulation. However, most first-generation tau PET tracers are limited for high off-target binding and detection of tau in non-Alzheimer disease (AD). This study evaluated potential clinical applications of F-PI-2620 as a novel PET tracer with a high binding affinity for tau deposition in AD and non-AD tauopathies. METHODS: Twenty-six participants diagnosed with either mild cognitive impairment, probable AD, frontotemporal dementia, or parkinsonism, as well as healthy controls underwent a 60- to 90-minute brain PET scan after 7 mci (259 MBq) injection of F-PI-2620. Some participants had previous PET scans using F-THK-5351 or F-FP-CIT for dopamine transporter imaging. RESULTS: All participants showed no increase in off-target binding in basal ganglia on F-PI-2620 PET images, as noted for first-generation tau tracers. Aß+ mild cognitive impairment or AD patients showed diverse cortical F-PI-2620 uptake in frontotemporoparietal cortex that correlated with Mini-Mental Status Examination (ρ = -0.692, P = 0.013). Aß+ Parkinson disease with dementia and (Aß unknown) primary progressive aphasia patients also showed increased F-PI-2620 uptakes in the frontotemporoparietal cortex. Patients with parkinsonism showed increased uptakes in the pallidum compared with Aß- healthy controls (left: 1.41 ± 0.14 vs 1.04 ± 0.13, P = 0.014; right: 1.18 ± 0.16 vs 0.95 ± 0.07, P = 0.014). CONCLUSIONS: F-PI-2620 PET might be a sensitive tool to detect cortical tau deposits in patients with Aß+ AD and Aß+ non-AD tauopathies. Furthermore, this study showed that "off-target" binding in the basal ganglia does not affect F-PI-2620.

Deep Learning-Based Deep Brain Stimulation Targeting and Clinical Applications.

BACKGROUND: The purpose of the present study was to evaluate deep learning-based image-guided surgical planning for deep brain stimulation (DBS). We developed deep learning semantic segmentation-based DBS targeting and prospectively applied the method clinically. METHODS: T2∗ fast gradient-echo images from 102 patients were used for training and validation. Manually drawn ground truth information was prepared for the subthalamic and red nuclei with an axial cut ∼4 mm below the anterior-posterior commissure line. A fully convolutional neural network (FCN-VGG-16) was used to ensure margin identification by semantic segmentation. Image contrast augmentation was performed nine times. Up to 102 original images and 918 augmented images were used for training and validation. The accuracy of semantic segmentation was measured in terms of mean accuracy and mean intersection over the union. Targets were calculated based on their relative distance from these segmented anatomical structures considering the Bejjani target. RESULTS: Mean accuracies and mean intersection over the union values were high: 0.904 and 0.813, respectively, for the 62 training images, and 0.911 and 0.821, respectively, for the 558 augmented training images when 360 augmented validation images were used. The Dice coefficient converted from the intersection over the union was 0.902 when 720 training and 198 validation images were used. Semantic segmentation was adaptive to high anatomical variations in size, shape, and asymmetry. For clinical application, two patients were assessed: one with essential tremor and another with bradykinesia and gait disturbance due to Parkinson's disease. Both improved without complications after surgery, and microelectrode recordings showed subthalamic nuclei signals in the latter patient. CONCLUSION: The accuracy of deep learning-based semantic segmentation may surpass that of previous methods. DBS targeting and its clinical application were made possible using accurate deep learning-based semantic segmentation, which is adaptive to anatomical variations.

Association of striatal dopaminergic neuronal integrity with cognitive dysfunction and cerebral cortical metabolism in Parkinson's disease with mild cognitive impairment.

OBJECTIVES: Cognitive impairment is a common non-motor feature of Parkinson's disease (PD). However, the underlying pathophysiology of cognitive decline is unclear. We investigated the association of striatal dopamine transporter (DAT) loss with cognitive function and cerebral cortical metabolism in PD. METHODS: Twenty-eight patients (63.1 ± 7.1 yrs, M:F = 15:13) with advanced stage of PD were enrolled, including 15 (53.6%) diagnosed with mild cognitive impairment (MCI). All patients underwent FP-CIT PET/CT, neuropsychological tests, and FDG PET/CT within a 2-week interval. We calculated the specific to non-specific binding ratio on FP-CIT PET images in 12 striatal subregional VOIs, using one occipital VOI template as a reference. Age-adjusted normalized specific to non-specific binding ratios (%BRs) of striatal subregions were compared in two groups: PD with MCI versus PD (without cognitive impairment). RESULTS: There were no statistical differences in age, age at onset, disease duration, motor symptoms, or level of education between the two groups. The PD with MCI had lower %BRs in all striatal subregions (P < 0.05) except the posterior putamen, compared with the PD. Striatal DAT availability correlated with frontal/executive function (r = 0.567, P = 0.003) and visuospatial function (r = 0.614, P = 0.001) but not with memory function. Dopamine transporter binding of striatal subregions also correlated with posterior cortical metabolism. CONCLUSION: This study suggest that DAT loss in the striatum, except in the posterior putamen, is associated with cognitive dysfunction, specifically frontal/executive function and visuospatial function in PD subjects.

Magnetic Resonance Imaging Distortion and Targeting Errors from Strong Rare Earth Metal Magnetic Dental Implant Requiring Revision.

Recently, the use of magnetic dental implants has been re-popularized with the introduction of strong rare earth metal, for example, neodymium, magnets. Unrecognized magnetic dental implants can cause critical magnetic resonance image distortions. We report a case involving surgical failure caused by a magnetic dental implant. A 62-year-old man underwent deep brain stimulation for medically insufficiently controlled Parkinson"s disease. Stereotactic magnetic resonance imaging performed for the first deep brain stimulation showed that the overdenture was removed. However, a dental implant remained and contained a neodymium magnet, which was unrecognized at the time of imaging; the magnet caused localized non-linear distortions that were the largest around the dental magnets. In the magnetic field, the subthalamic area was distorted by a 4.6 mm right shift and counter clockwise rotation. However, distortions were visually subtle in the operation field and small for distant stereotactic markers, with approximately 1-2 mm distortions. The surgeon considered the distortion to be normal asymmetry or variation. Stereotactic marker distortion was calculated to be in the acceptable range in the surgical planning software. Targeting errors, approximately 5 mm on the right side and 2 mm on the left side, occurred postoperatively. Both leads were revised after the removal of dental magnets. Dental magnets may cause surgical failures and should be checked and removed before stereotactic surgery. Our findings should be considered when reviewing surgical precautions and making distortion-detection algorithm improvements.

Machine learning identified an Alzheimer's disease-related FDG-PET pattern which is also expressed in Lewy body dementia and Parkinson's disease dementia.

Utilizing the publicly available neuroimaging database enabled by Alzheimer's disease Neuroimaging Initiative (ADNI; http://adni.loni.usc.edu/ ), we have compared the performance of automated classification algorithms that differentiate AD vs. normal subjects using Positron Emission Tomography (PET) with fluorodeoxyglucose (FDG). General linear model, scaled subprofile modeling and support vector machines were examined. Among the tested classification methods, support vector machine with Iterative Single Data Algorithm produced the best performance, i.e., sensitivity (0.84) × specificity (0.95), by 10-fold cross-validation. We have applied the same classification algorithm to four different datasets from ADNI, Health Science Centre (Winnipeg, Canada), Dong-A University Hospital (Busan, S. Korea) and Asan Medical Centre (Seoul, S. Korea). Our data analyses confirmed that the support vector machine with Iterative Single Data Algorithm showed the best performance in prediction of future development of AD from the prodromal stage (mild cognitive impairment), and that it was also sensitive to other types of dementia such as Parkinson's Disease Dementia and Dementia with Lewy Bodies, and that perfusion imaging using single photon emission computed tomography may achieve a similar accuracy to that of FDG-PET.

Systematic Stereotactic Error Reduction Using a Calibration Technique in Single-Brain-Pass and Multitrack Deep Brain Stimulations.

BACKGROUND: A calibration technique that shifts the frame coordinates from the intended coordinates to correct a systematic stereotactic error has been reported for single-brain-pass deep brain stimulation. OBJECTIVE: To analyze the intercenter reproducibility of this method for deep brain stimulation. METHODS: A total of 310 leads from 166 patients undergoing surgery were analyzed, including 220 multitrack (primarily 3-track) subthalamic nucleus leads, 17 single-brain-pass subthalamic nucleus leads, and 73 single-brain-pass globus pallidus interna leads. We adopted the previously reported calibration factors. Calibration shifts the frame coordinates from the target coordinates to the left, anterior, and inferior directions by 0, 0.5, or 1 mm, respectively, according to the arc angles in each axis. We analyzed 9 subgroups of single-brain-pass, multitracks, operated sides, technical, and instrumental variations. RESULTS: In total, the stereotactic error decreased from 1.5 ± 0.8 mm in the distance to the frame coordinates (error calculation before using the calibration technique) to 1.1 ± 0.6 mm in the distance to the intended target coordinates (error after using the calibration technique, 28% reduction, P < .000001). Frame-related errors were 0.1 to 0.3 mm when measured with the stereotactic simulator. The reduction of stereotactic errors by the calibration technique (median 0.4 mm, 0.1-0.7 mm, median 28%, 7%-45% in each subgroup) was significant in 8 of the 9 subgroups (P < .05). CONCLUSION: Calibration is an effective and reproducible method for reducing systematic stereotactic errors both in single-brain-pass and multitrack deep brain stimulations, as well as in both sides using various instrumental and technical conditions.

Longitudinal Decline of Striatal Subregional [18F]FP-CIT Uptake in Parkinson's Disease.

PURPOSE: Dopamine transporter imaging is suggested to be a useful imaging biomarker for Parkinson's disease (PD) progression and monitoring drug effects. We investigated the longitudinal decline characteristics of striatal [18F]FP-CIT uptake in PD. METHODS: We retrospectively reviewed 35 PD patients and 9 non-PD patients. All patients underwent [18F]FP-CIT PET at the initial diagnosis and follow-up. PET images were spatially normalized and analyzed with eight striatal and one occipital VOI templates. We measured the specific to non-specific binding ratio (SNBR) of the striatal subregions and calculated the absolute annual reduction (AAR) and relative annual reduction (%RAR) of the SNBRs. RESULTS: Total striatal SNBRs in PD patients were significantly lower than those in non-PD patients, with the most significant difference in the posterior putamen. Both AAR (0.26 ± 0.14 vs. 0.09 ± 0.19, p < 0.05) and %RAR (6.9 ± 3.5 vs. 1.2 ± 2.7, p < 0.001) of total striatal SNBRs were significantly greater in PD than non-PD patients. There were no significant differences in the AAR and %RAR of total striatal SNBRs between elderly and young onset PD. The AARs of the posterior putamen were higher in early PD than in advanced PD. Conversely, the %RARs were not significantly different between early and more advanced PD. The disease duration was significantly negatively correlated with the AAR but not with the %RAR of the posterior putamen. CONCLUSIONS: The longitudinal decline of striatal [18F]FP-CIT uptake in PD was nonlinear and significantly faster than that in non-PD, with a different rate of decline among the striatal subregions.

Distinct brain metabolic patterns separately associated with cognition, motor function, and aging in Parkinson's disease dementia.

We explored whether patients with Parkinson's disease dementia (PDD) show a distinct spatial metabolic pattern that characterizes cognitive deficits in addition to motor dysfunction. Eighteen patients with PDD underwent 3 separate positron emission tomography sessions with [18F]fluorodeoxyglucose (for glucose metabolism), fluorinated N-3-fluoropropyl-2-beta-carboxymethoxy-3-beta-(4-iodophenyl) nortropane (for dopamine transporter density) and Pittsburgh compound-B (for beta-amyloid load). We confirmed in PDD versus normal controls, overall hypometabolism in the posterior and prefrontal brain regions accompanied with hypermetabolism in subcortical structures and the cerebellar vermis. A multivariate network analysis then revealed 3 metabolic patterns that are separately associated with cognitive performance (p = 0.042), age (p = 0.042), and motor symptom severity (p = 0.039). The age-related pattern's association with aging was replicated in healthy controls (p = 0.047) and patients with Alzheimer's disease (p = 0.002). The cognition-related pattern's association with cognitive performance was observed, with a trend-level of correlation, in patients with dementia with Lewy bodies (p = 0.084) but not in patients with Alzheimer's disease (p = 0.974). We found no association with fluorinated N-3-fluoropropyl-2-beta-carboxymethoxy-3-beta-(4-iodophenyl) nortropane and Pittsburgh compound-B positron emission tomography with patients' cognitive performance.

Erratum to: The KMDS-NATION Study: Korean Movement Disorders Society Multicenter Assessment of Non-Motor Symptoms and Quality of Life in Parkinson's Disease NATION Study Group.

This corrects the article on p. 393 in vol. 12, PMID: 27819413.

Different subregional metabolism patterns in patients with cerebellar ataxia by 18F-fluorodeoxyglucose positron emission tomography.

We evaluated cerebellar subregional metabolic alterations in patients with cerebellar ataxia, a representative disease involving the spinocerebellum. We retrospectively analyzed 18F-fluorodeoxyglucose positron emission tomography (18F-FDG PET) images in 44 patients with multiple system atrophy of the cerebellar type (MSA-C), 9 patients with spinocerebellar ataxia (SCA) type 2, and 14 patients with SCA type 6 and compared with 15 patients with crossed cerebellar diaschisis (CCD) and 89 normal controls. Cerebellar subregional metabolism was assessed using 13 cerebellar subregions (bilateral anterior lobes [ANT], superior/mid/inferior posterior lobes [SUPP/MIDP/INFP], dentate nucleus [DN], anterior vermis [ANTV], and superior/inferior posterior vermis [SUPV/INFV]) to determine FDG uptake ratios. MSA-C and SCA type 2 showed severely decreased metabolic ratios in all cerebellar subregions compared to normal controls (ANT, 0.58 ± 0.08 and 0.50 ± 0.06 vs. 0.82 ± 0.07, respectively, p < 0.001). SCA type 6 showed lower metabolic ratios in almost all cerebellar subregions (ANT, 0.57 ± 0.06, p < 0.001) except INFV. Anterior-posterior lobe ratio measurements revealed that SCA type 2 (Right, 0.81 ± 0.05 vs. 0.88 ± 0.04, p < 0.001; Left, 0.83 ± 0.05 vs. 0.88 ± 0.04, p = 0.003) and SCA type 6 (Right, 0.72 ± 0.05 vs. 0.88 ± 0.04, p < 0.001; Left, 0.72 ± 0.05 vs. 0.88 ± 0.04, p < 0.001) showed preferential hypometabolism in the anterior lobe compared to normal controls, which was not observed in CCD and MSA-C. Asymmetric indices were higher in CCD and MSA-C than in normal controls (p < 0.001), whereas such differences were not found in SCA types 2 and 6. In summary, quantitative analysis of cerebellar subregional metabolism ratios revealed preferential involvement of the anterior lobe, corresponding to the spinocerebellum, in patients with cerebellar ataxia, whereas patients with CCD and MSA-C exhibited more asymmetric hypometabolism in the posterior lobe.

Family Functioning and Communication in Spouses of Patients with Parkinsonism.

BACKGROUND: Patients with parkinsonism exhibit motor symptoms, cognitive impairment, and neuropsychiatric changes, and these symptoms increase caregiver burden. Family dynamics can be influenced by the presence of comorbidities, which is especially important in diseases causing caregiver burden. We investigated the effects of spousal parkinsonism on family functioning and communication. METHODS: Couples without parkinsonism, who visited hospital-based family practices, were recruited by 28 family physicians from 22 hospitals between April 2009 and June 2011; patients with parkinsonism and their spouses were recruited from a single institution. The participants completed questionnaires on demographic characteristics, lifestyle factors, family functioning (the Korean version of the Family Adaptation and Cohesion Evaluation Scale [FACES] III), and family communication (the Family Communication Scale of the FACES-IV). We compared family functioning and communication between spouses of the patients with and without parkinsonism. RESULTS: The mean family adaptability and cohesion scores of the spouses of the patients with parkinsonism were 23.09±6.48 and 32.40±8.43, respectively, whereas those of the control group were 23.84±5.88 and 34.89±7.59, respectively. Family functioning and family communication were significantly different between the spouses of individuals with and without parkinsonism. After adjusting for age, sex, income, and cardiovascular disease in the logistic regression analysis, family functioning was found to significantly deteriorate in the spouses of patients with parkinsonism but not the control group. Family communication decreased significantly in spouses of patients with parkinsonism. CONCLUSION: Family functioning and family communication significantly deteriorated in spouses of patients with parkinsonism.

Metabolic network expression in parkinsonism: Clinical and dopaminergic correlations.

Little is known of the precise relationship between the expression of disease-related metabolic patterns and nigrostriatal dopaminergic dysfunction in parkinsonism. We studied 51 subjects with Parkinson's disease (PD) (18 non-demented, 24 demented, and 9 dementia with Lewy bodies) and 127 with atypical parkinsonian syndromes (47 multiple system atrophy (MSA), 38 progressive supranuclear palsy (PSP), and 42 corticobasal syndrome (CBS)) with 18F-fluorodeoxyglucose PET to quantify the expression of previously validated disease-related patterns for PD, MSA, PSP, and CBS and 18F-fluoropropyl-ß-CIT PET to quantify caudate and putamen dopamine transporter (DAT) binding. The patients in each group exhibited significant elevations in the expression of the corresponding disease-related pattern ( p < 0.001), relative to 16 healthy subjects. With the exception of cerebellar MSA (MSA-C), all groups displayed significant reductions in putamen DAT binding relative to healthy subjects ( p < 0.05). Correlations between the dopaminergic and metabolic measures were significant in PD and CBS but not in MSA and PSP. In all patient groups with the exception of MSA-C and CBS, pattern expression values and DAT binding correlated with disease duration and severity measures. The findings suggest that in these parkinsonian disorders, metabolic network expression and DAT binding provide complementary information regarding the underlying disease process.

Comparison of the Stereotactic Accuracies of Function-Guided Deep Brain Stimulation, Calculated Using Multitrack Target Locations Geometrically Inferred from Three-Dimensional Trajectory Rotations, and of Magnetic Resonance Imaging-Guided Deep Brain Stimulation and Outcomes.

OBJECTIVE: In previous studies, multitrack trajectories in deep brain stimulation (DBS) have usually been approximated. Using a geometrically more accurate method, we compared the stereotactic accuracy of DBS with multitrack microelectrode recording and awake stimulation (function group) and MRI-guided DBS (MRI group). METHODS: One hundred and seventy-two leads used in DBS between April 2014 and January 2016 were evaluated for stereotactic errors. Targets were the subthalamic nucleus (STN, 139 leads) or globus pallidus interna (GPi, 33 leads). We geometrically calculated shifted-track targets by considering the three-dimensional stereotactic ring and arc rotations. Stereotactic errors were calculated using Euclidean distances perpendicular to trajectories. Motor outcomes according to the Unified Parkinson's Disease Rating Scale (UPDRS) part III, improvement percentages by stimulations, were analyzed in 24 patients with 1 year follow-ups. RESULTS: Functional evaluation tended to increase stereotactic errors in the STN function group (n = 129; 1.4 ± 0.7 mm) more than in the STN MRI group (n = 10; 1.0 ± 0.6 mm; P = 0.06). Leads with higher stereotactic errors (n = 65; 1.6 ± 0.7 mm; P < 0.001) than the center-track leads (n = 64; 1.2 ± 0.7 mm) were selectively track shifted. Track-shifted leads approached MRI targets in 86% (56/65 leads). Lower stereotactic errors tended to correlate with a better outcome (P = 0.095). Distances to MRI targets >2.5 mm tended to relate to a worse outcome (P = 0.087). Stereotactic errors were lower (n = 33; 0.9 ± 0.5 mm) in the GPi MRI group. CONCLUSIONS: Multitrack DBS using intraoperative functional evaluation resulted in worse stereotactic accuracy than did MRI-guided DBS. However, track shifts in function-guided DBS can approach MRI targets effectively.

The KMDS-NATION Study: Korean Movement Disorders Society Multicenter Assessment of Non-Motor Symptoms and Quality of Life in Parkinson's Disease NATION Study Group.

BACKGROUND AND PURPOSE: Nonmotor symptoms (NMS) in Parkinson's disease (PD) have multisystem origins with heterogeneous manifestations that develop throughout the course of PD. NMS are increasingly recognized as having a significant impact on the health-related quality of life (HrQoL). We aimed to determine the NMS presentation according to PD status, and the associations of NMS with other clinical variables and the HrQoL of Korean PD patients. METHODS: We surveyed patients in 37 movement-disorders clinics throughout Korea. In total, 323 PD patients were recruited for assessment of disease severity and duration, NMS, HrQoL, and other clinical variables including demographics, cognition, sleep scale, fatigability, and symptoms. RESULTS: In total, 98.1% of enrolled PD subjects suffered from various kinds of NMS. The prevalence of NMS and scores in each NMS domain were significantly higher in the PD group, and the NMS worsened as the disease progressed. Among clinical variables, disease duration and depressive mood showed significant correlations with all NMS domains (p<0.001). NMS status impacted HrQoL in PD (rS=0.329, p<0.01), and the association patterns differed with the disease stage. CONCLUSIONS: The results of our survey suggest that NMS in PD are not simply isolated symptoms of degenerative disease, but rather exert significant influences throughout the disease course. A novel clinical approach focused on NMS to develop tailored management strategies is warranted to improve the HrQoL in PD patients.