PD-related Pattern Research Articles

FDG PET Parkinson's disease-related pattern as a biomarker for clinical trials in early stage disease.

BackgroundThe development of therapeutic interventions for Parkinson disease (PD) is challenged by disease complexity and subjectivity of symptom evaluation. A Parkinson's Disease Related Pattern (PDRP) of glucose metabolism via fluorodeoxyglucose positron emission tomography (FDG-PET) has been reported to correlate with motor symptom scores and may aid the detection of disease-modifying therapeutic effects.ObjectivesWe sought to independently evaluate the potential utility of the PDRP as a biomarker for clinical trials of early-stage PD.MethodsTwo machine learning approaches (Scaled Subprofile Model (SSM) and NPAIRS with Canonical Variates Analysis) were performed on FDG-PET scans from 17 healthy controls (HC) and 23 PD patients. The approaches were compared regarding discrimination of HC from PD and relationship to motor symptoms.ResultsBoth classifiers discriminated HC from PD (p < 0.01, p < 0.03), and classifier scores for age- and gender- matched HC and PD correlated with Hoehn & Yahr stage (R2 = 0.24, p < 0.015) and UPDRS (R2 = 0.23, p < 0.018). Metabolic patterns were highly similar, with hypometabolism in parieto-occipital and prefrontal regions and hypermetabolism in cerebellum, pons, thalamus, paracentral gyrus, and lentiform nucleus relative to whole brain, consistent with the PDRP. An additional classifier was developed using only PD subjects, resulting in scores that correlated with UPDRS (R2 = 0.25, p < 0.02) and Hoehn & Yahr stage (R2 = 0.16, p < 0.06).ConclusionsTwo independent analyses performed in a cohort of mild PD patients replicated key features of the PDRP, confirming that FDG-PET and multivariate classification can provide an objective, sensitive biomarker of disease stage with the potential to detect treatment effects on PD progression.

FDG PET, dopamine transporter SPECT, and olfaction: Combining biomarkers in REM sleep behavior disorder.

ABSTRACTBackgroundIdiopathic REM sleep behavior disorder is a prodromal stage of Parkinson's disease and dementia with Lewy bodies. Hyposmia, reduced dopamine transporter binding, and expression of the brain metabolic PD‐related pattern were each associated with increased risk of conversion to PD. The objective of this study was to study the relationship between the PD‐related pattern, dopamine transporter binding, and olfaction in idiopathic REM sleep behavior disorder.MethodsIn this cross‐sectional study, 21 idiopathic REM sleep behavior disorder subjects underwent 18F‐fluorodeoxyglucose PET, dopamine transporter imaging, and olfactory testing. For reference, we included 18F‐fluorodeoxyglucose PET data of 19 controls, 20 PD patients, and 22 patients with dementia with Lewy bodies. PD‐related pattern expression z‐scores were computed from all PET scans.ResultsPD‐related pattern expression was higher in idiopathic REM sleep behavior disorder subjects compared with controls (P = 0.048), but lower compared with PD (P = 0.001) and dementia with Lewy bodies (P < 0.0001). PD‐related pattern expression was higher in idiopathic REM sleep behavior disorder subjects with hyposmia and in subjects with an abnormal dopamine transporter scan (P < 0.05, uncorrected).ConclusionPD‐related pattern expression, dopamine transporter binding, and olfaction may provide complementary information for predicting phenoconversion. © 2017 The Authors. Movement Disorders published by Wiley Periodicals, Inc. on behalf of International Parkinson and Movement Disorder Society.

Abnormal metabolic brain network associated with Parkinson's disease: replication on a new European sample.

The purpose of this study was to identify the specific metabolic brain pattern characteristic for Parkinson's disease (PD): Parkinson's disease-related pattern (PDRP), using network analysis of [18F]-fluorodeoxyglucose positron emission tomography (FDG-PET) brain images in a cohort of Slovenian PD patients. Twenty PD patients (age 70.1±7.8years, Movement Disorder Society Unified Parkinson's Disease Motor Rating Scale (MDS-UPDRS-III) 38.3±12.2; disease duration 4.3±4.1years) and 20 age-matched normal controls (NCs) underwent FDG-PET brain imaging. An automatic voxel-based scaled subprofile model/principal component analysis (SSM/PCA) was applied to these scans for PDRP-Slovenia identification. The pattern was characterized by relative hypermetabolism in pallidum, putamen, thalamus, brain stem, and cerebellum associated with hypometabolism in sensorimotor cortex, posterior parietal, occipital, and frontal cortices. The expression of PDRP-Slovenia discriminated PD patients from NCs (p<0.0001) and correlated positively with patients' clinical score (MDS-UPDRS-III, p=0.03). Additionally, its topography agrees well with the original PDRP (p<0.001) identified in American cohort of PD patients. We validated the PDRP-Slovenia expression on additional FDG-PET scans of 20 PD patients, 20 NCs, and 25 patients with atypical parkinsonism (AP). We confirmed that the expression of PDRP-Slovenia manifests good diagnostic accuracy with specificity and sensitivity of 85-90% at optimal pattern expression cutoff for discrimination of PD patients and NCs and is not expressed in AP. PDRP-Slovenia proves to be a robust and reproducible functional imaging biomarker independent of patient population. It accurately differentiates PD patients from NCs and AP and correlates well with the clinical measure of PD progression.

Parkinson's disease-related network topographies characterized with resting state functional MRI.

Spatial covariance mapping can be used to identify and measure the activity of disease-related functional brain networks. While this approach has been widely used in the analysis of cerebral blood flow and metabolic PET scans, it is not clear whether it can be reliably applied to resting state functional MRI (rs-fMRI) data. In this study, we present a novel method based on independent component analysis (ICA) to characterize specific network topographies associated with Parkinson's disease (PD). Using rs-fMRI data from PD and healthy subjects, we used ICA with bootstrap resampling to identify a PD-related pattern that reliably discriminated the two groups. This topography, termed rs-MRI PD-related pattern (fPDRP), was similar to previously characterized disease-related patterns identified using metabolic PET imaging. Following pattern identification, we validated the fPDRP by computing its expression in rs-fMRI testing data on a prospective case basis. Indeed, significant increases in fPDRP expression were found in separate sets of PD and control subjects. In addition to providing a similar degree of group separation as PET, fPDRP values correlated with motor disability and declined toward normal with levodopa administration. Finally, we used this approach in conjunction with neuropsychological performance measures to identify a separate PD cognition-related pattern in the patients. This pattern, termed rs-fMRI PD cognition-related pattern (fPDCP), was topographically similar to its PET-derived counterpart. Subject scores for the fPDCP correlated with executive function in both training and testing data. These findings suggest that ICA can be used in conjunction with bootstrap resampling to identify and validate stable disease-related network topographies in rs-fMRI. Hum Brain Mapp 38:617-630, 2017. © 2016 Wiley Periodicals, Inc.

Metabolic brain networks in patients with Parkinson's disease based on 18F-FDG PET imaging

Objective To validate PD-related pattern (PDRP) network as a measure of PD by 18F-FDG PET imaging.Methods Thirty-two PD patients with different severities and 32 healthy controls matched by age and gender were recruited in studies of resting-state brain 18F-FDG PET imaging.To obtain the PDRP,principal component analysis (PCA) was used.The correlations between PDRP expression and the severities of PD (classified by unified PD rating scale (UPDRS) motor scores and Hoehn & Yahr stages) were investigated.The two-sample t test and Pearson correlation analysis were used for statistical analysis.Results PDRP was characterized by relative metabolic increases in the putamen,globus pallidus (GP),thalamus,pons,cerebellum and primary motor cortex,and was associated with decreases in the premotor and posterior parietal areas.The value of PDRP expression in PD group (1.605±0.655) was significantly higher than that of healthy controls (0.000±0.523 ; t =10.829,P＜0.001).The value of PDRP expression also correlated significantly with UPDRS motor scores (r=0.760,P＜0.001) and Hoehn & Yahr stages in PD group (r=0.736,P＜0.001).Conclusion The PDRP based on 18F-FDG PET imaging can be useful for identification of PD patients from healthy controls and correlates well with the severity of the disease. Key words: Parkinson disease; Brain; Metabolism; Tomography, emission-computed; Deoxyglucose

Metabolic brain network in the Chinese patients with Parkinson's disease based on 18F-FDG PET imaging

The objective of this study was to validate Parkinson's disease-related pattern (PDRP) as a measure of network biomarker of Parkinson's disease (PD) in Chinese population by using 18F-fluorodeoxyglucose (FDG) and Positron Emission Tomography (PET). Resting-state brain FDG PET imaging was performed in a cohort of 33 PD patients and 33 age/gender-matched healthy controls to identify a PDRP. PDRP expression was then computed in a new cohort of 30 PD patients and 30 healthy controls using a voxel-based network quantification algorithm. Differences in PDRP expression were compared across groups and correlations with severities of PD were investigated. As a result, we identified a PDRP characterized by relative increases in pallidothalamic, pontine, and cerebellar metabolism, associated with concurrent metabolic decreases in the premotor and posterior parietal areas. PDRP expression in each of the two PD groups was significantly elevated relative to that of the healthy controls (P < 0.001). Receiver operating characteristic (ROC) analysis revealed that the PDRP-based discrimination for PD patients and controls had high sensitivity and specificity (both = 93.9%) in the derivation cohort, which declined slightly in the validation cohort (both = 90.0%) at the same diagnostic threshold. Moreover, PDRP scores correlated positively with Hoehn and Yahr scores (r ≥ 0.590, P ≤ 0.001) and Unified Parkinson's Disease Rating Scale motor scores (r ≥ 0.646, P < 0.001) in both patient groups. In conclusion, PDRP is highly reproducible in Chinese cohorts based on FDG PET imaging. Network activity of PDRP can differentiate PD patients from healthy controls and correlates with the severities of the disease.

18F-FDG PET imaging in early diagnosis of multiple system atrophy

Objective To evaluate the feasibility of 18F-FDG PET/CT imaging in the early diagnosis of multiple system atrophy (MSA) and differentiation from early PD.Methods Five patients with MSA were included in this study.These patients had a disease duration of less than 2 years,predominantly with cerebellar dysfunction (MSA-C).Ten clinically confirmed PD patients with disease duration less than 3 years were also enrolled.All patients underwent 18F-FDG PET/CT imaging.To compare the metabolic features of these two diseases,SPM 5 software and t-test were used for image data analysis.The PD related pattern (PDRP) expression was calculated in all patients and the efficacy of the PDRP score in distinguishing early MSA from PD was evaluated.Results At the t-test level of P =0.01,all the 5 MSA patients displayed cerebellar hypometabolism ( t:-13.04 to -3.75 ) and 3 of them also had decreased metabolism in the putamen (t:-5.14 to -3.21 ).On the contrary,all PD patients showed cerebellar hypermetabolism (t:4.16 to 11.72) and normal metabolism in putamen.The PDRP scores in the PD group were significantly higher than those in the MSA group(ll.9±4.96vs -6.25±5.97,t=6.27,P＜0.01).Conclusions Cerebellar hypometabolism is the predominant FDG-PET feature of MSA-C,which may be used to distinguish it from early PD.Striatum may be involved in the early phase of MSA-C,displaying hypometabolism in putamen.The PDRP scores are also helpful in differentiating early phase MSA-C from early PD. Key words: Multiple system atrophy; Tomography, emission-computed ; Tomography,X-ray computed; Diagnosis, differential; Deoxyglucose

Patterns of cortical thickness and surface area in early Parkinson's disease

Idiopathic Parkinson's disease (PD) is a neurodegenerative disorder diagnosed on the basis of motor symptoms, but that also includes cognitive and visuo-spatial deficits. Though PD is known to initially affect subcortical regions, the cortex also exhibits neuronal loss in the course of the disease as post mortem studies have shown. So far, PD-related pattern of cortical damage remains unclear, because of disease-caused heterogeneity, and also in part because of methodological issues such as the limitations of Voxel Based Morphometry. Here corticometry was used, a technique that decouples local surface from thickness, to obtain a better picture of PD corticomorphometric patterns.We acquired MRI volumes for 33 healthy controls (HC) and 49 PD patients, extracted local cortical thickness and surface area and modeled both of them as a function of group and age for each participant. Cortical thickness averaged on the whole cortex did not differ between the two groups while mean surface area was significantly larger in the PD group. The bilateral parietal lobule, the right superior frontal gyrus, the left cingulate cortex and the left insular cortex exhibited larger local surface area in the PD group. The right precuneus exhibited cortical thinning associated with age in the PD group and not in the HC group. Furthermore, cortical thinning was observed in the PD group compared with the control group in the left medial supplementary motor area (SMA) and in the right dorsal pre-SMA. Finally, we found the left temporal pole thickness to correlate with disease duration, as well as the bilateral occipital cortex and Broca's area.These results suggest that PD etiology is associated with specific cortical alterations, which could account for cognitive deficits that arise as the disease evolves. Finally, our results observed in the occipital cortex as a function of disease duration may indicate the increase in PD-related visuo-spatial deficits, which can sometimes result in hallucinations later on in the disease. In the future, MRI-generated corticometry, combined with additional behavioral markers, may prove to be a useful diagnosis tool to characterize the evolution of motor and cognitive deficits in PD.

Subcortical elevation of metabolism in Parkinson's disease — A critical reappraisal in the context of global mean normalization

In a recent issue of NeuroImage, we presented evidence that biased global mean (GM) normalization of brain PET data can generate the appearance of subcortical foci with relative hypermetabolism in patients with Parkinson's disease (PD), and other degenerative disorders. In a commentary to our article, Ma and colleagues presented a study seeking to establish that a pattern of widespread hypermetabolism, known as the Parkinson's disease related pattern (PDRP) is a genuine metabolic feature of PD. In the present paper, we respond to the arguments presented by Ma et al., and we provide a critical reappraisal of the evidence for the existence of the PDRP. To this end, we present new analyses of PET data sets, which demonstrate that very similar patterns of relative subcortical increases are seen in PD, Alzheimer's disease, hepatic encephalopathy, healthy aging, and simulation data. Furthermore, longitudinal studies of PD previously reported relative hypermetabolism in very small anatomical structures such as the subthalamic nucleus. We now demonstrate how focal hypermetabolism attributed to small nuclei can similarly arise as a consequence of GM normalization. Finally, we give a comprehensive summary of the entire deoxyglucose autoradiography literature on acquired parkinsonism in experimental animals. Based on this evidence, we conclude that (1) there is no quantitative evidence for widespread subcortical hypermetabolism in PD, (2) very similar patterns of subcortical hyperactivity are evident in various other brain disorders whenever GM normalization is utilized, and (3) the PDRP is not evident in animal models of PD. In the absence of quantitative evidence for the PDRP, our alternative interpretation of normalization bias seems the more parsimonious explanation for the reports of relative hypermetabolism in PD.

Tolerability and efficacy of oral loading of levetiracetam

Nonsedating antiepileptic drugs (AEDs) that can be initiated rapidly are desirable in a variety of clinical situations. Levetiracetam (LEV) is a newer AED, with a recently approved parenteral formulation, that can be initiated at doses effective in controlling seizures. We investigated whether oral loading of levetiracetam is well tolerated and facilitates stabilization and discharge of patients in epilepsy monitoring units (EMU). Adult patients in the EMU at two centers were identified who received 1,500 mg of LEV in a single dose. This was an observational study of these patients where LEV was thought to be an appropriate component of the therapeutic regimen. Patients were either LEV naive or had been off all LEV for at least 3 days. LEV maintenance was begun 12 hours later at doses of 500 to 1,000 mg twice a day. A total of 37 adult patients (20 female) were identified. There were no spontaneous complaints of side effects. Upon questioning, 33 patients (89%) denied side effects. The remaining 4 patients (11%) reported transient irritability, imbalance, tiredness, or lightheadedness. Eleven patients (mean weight = 85.0 Kg) had mean LEV serum concentration of 31.5 microg/mL after 1 hour, 23 (mean weight 85.7 Kg) had mean concentration of 30.77 microg/mL after 2 hours, five (mean weight 84.3 Kg) had mean concentration of 12.1 microg/mL after 12 hours, and two (mean weight 94 Kg) had mean concentration of 7.4 microg/mL after 14 hours. No seizures occurred within 24 hours of loading. All patients were able to be discharged 3 to 30 hours after loading. In the population surveyed, oral loading with levetiracetam was well-tolerated and rapidly yielded serum concentrations thought to decrease seizure frequency. This regimen facilitated discharge from the epilepsy monitoring units.

Abnormal metabolic networks in atypical parkinsonism

Spatial covariance analysis has been used with (18)F-fluorodeoxyglucose (FDG) PET to detect and quantify specific metabolic patterns associated with Parkinson's disease (PD). However, PD-related patterns cannot necessarily serve as biomarkers of the processes that underlie the atypical parkinsonian syndromes. In this FDG PET study, we used strictly defined statistical criteria to identify disease-related metabolic patterns in the imaging data from patients with multiple system atrophy (MSA) and progressive supranuclear palsy (PSP), the two most common of these atypical conditions. We found that MSA and PSP were each associated with a specific, highly stable metabolic brain network (P < 0.0001, bootstrap estimation). The MSA-related pattern was characterized by decreased metabolism in the putamen and cerebellum. The PSP-related pattern was characterized by metabolic decreases in the brainstem and medial frontal cortex. For both conditions, pattern expression was significantly elevated in patients relative to age-matched healthy control subjects (P < 0.001). For each condition, we validated the associated disease-related metabolic pattern by computing its expression on an individual scan basis in two independent patient cohorts, and in one subsequent healthy volunteer cohort. We found that for both MSA and PSP, prospective assessments of pattern expression accurately discriminated patients from controls (P < 0.001). These findings suggest that the major atypical parkinsonian syndromes are associated with distinct patterns of abnormal regional metabolic activity. These disease-related networks can potentially be used in conjunction with functional brain imaging as quantifiable biomarkers for the assessment of these pathological conditions.

Regional metabolic changes in Parkinsonian patients with normal dopaminergic imaging

Dopaminergic imaging has been found to be normal in approximately 15% of parkinsonian patients enrolled in neuroprotective trials. We used (18)F-fluorodeoxyglucose positron emission tomography (FDG PET) to determine the metabolic basis for this finding. We reviewed scans from 185 patients with clinical signs of Parkinson's disease (PD) who underwent (18)F-fluorodopa PET imaging for diagnostic confirmation. Of this group, 27 patients (14.6%) had quantitatively normal scans; 8 of these patients were additionally scanned with FDG PET. Pattern analysis was performed on an individual scan basis to determine whether the metabolic changes were consistent with classic PD. Computer-assisted single-case assessments of the FDG PET scans of these 8 patients did not disclose patterns of regional metabolic change compatible with classical PD or an atypical parkinsonian variant. Similarly, network quantification revealed that PD-related pattern expression was not elevated in these patients as it was in an age- and duration-matched cohort with classical PD (P < 0.0001). None of these patients developed clinical signs of classical PD or of an atypical parkinsonian syndrome at a follow-up visit conducted 3 years after imaging. The results suggest that parkinsonian subjects with normal dopaminergic imaging do not have evidence of classical PD or an atypical parkinsonian syndrome.

Corticostriatal covariance patterns of 6–[18F]fluoro–L–dopa and [18F]fluorodeoxyglucose PET in Parkinson's disease

6-[18F]fluoro-L-dopa (FDOPA) is a common presynaptic dopaminergic tracer used in examinations by positron emission tomography (PET) for patients with Parkinson's disease (PD). The distinct metabolic covariance pattern in the uptake of [18F]fluorodeoxyglucose (FDG) can also be used to investigate PD pathology. Although the two tracers are widely used in PD research and clinical assessment, no thorough comparative studies of the tracers have been made. In this study, 25 PD patients were examined with FDOPA and FDG to investigate relationships and clinical correlates of metabolic and monoaminergic function in the Parkinsonian brain. A VOI (volume-of-interest) analysis was achieved by 3D spatial normalisation and fixed VOI-sets. The hemisphere ipsi- and contralateral to the predominant symptoms of PD was identified in each data set, and data across subjects were related using that laterality, rather than body side. Regional covariance patterns for FDOPA and FDG were derived from principal component analysis (PCA). The results demonstrated hemispheric asymmetries and sex-differences in the striatal FDOPA uptake, which were not seen with FDG. In addition, the PCA analysis identified a positive relationship between a major component in FDOPA uptake (associated with the striatal uptake) and an FDG component, which had positive loadings in the thalamus and the cerebellum. The subject scores for these components correlated positively, and both had a negative association with the clinical severity of the disease. The specific extrastriatal FDG covariance pattern contained the thalamus and the cerebellum, components of the previously reported PD related pattern, but not the striatum. The network correlated with both the severity of clinical symptoms of PD and the severity of nigrostriatal dopaminergic hypofunction. The results indicate that FDG PET, when combined with multivariate network analysis at group-level, can be used as an indicator of PD severity.

Metabolic correlates of levodopa response in Parkinson's disease.

To assess the effects of levodopa on resting-state brain metabolism in PD. In previous studies the authors used [18F] fluorodeoxyglucose (FDG) and PET to quantify regional metabolic abnormalities in PD. They found that this disease is characterized reproducibly by a specific abnormal PD-related pattern (PDRP). In this study the authors used IV levodopa infusion to quantify the effects of dopamine replacement on regional metabolism and PDRP network activity. They tested the hypothesis that clinical response to dopaminergic therapy correlates with these metabolic changes. The authors used FDG/PET to measure resting-state regional brain metabolism in seven patients with PD (age, 59.4 +/- 4.2 years; Hoehn and Yahr stage, 1.9 +/- 0.7, mean +/- SD); subjects were scanned both off levodopa and during an individually titrated constant-rate IV levodopa infusion. The authors used statistical parametric mapping to identify significant changes in regional brain metabolism that occurred with this intervention. They also quantified levodopa-induced changes in PDRP expression. Metabolic changes with levodopa correlated with clinical improvement as measured by changes in Unified PD Rating Scale (UPDRS) motor scores. Levodopa infusion improved UPDRS motor ratings (30.6% +/- 12.0%, p < 0.002) and significantly decreased regional glucose metabolism in the left putamen, right thalamus, bilateral cerebellum, and left primary motor cortex (p < 0.001). Changes in pallidal metabolism correlated significantly with clinical improvement in UPDRS motor ratings (p < 0.01). Levodopa infusion also resulted in a significant (p = 0.01) decline in PDRP expression. The changes in PDRP activity mediated by levodopa correlated significantly with clinical improvement in UPDRS motor ratings (r = -0.78, p < 0.04). Levodopa reduces brain metabolism in the putamen, thalamus, and cerebellum in patients with PD. Additionally, levodopa reduces PD-related pattern activity, and the degree of network suppression correlates with clinical improvement. The response to dopaminergic therapy in Patients with PD may be determined by the modulation of cortico-striato-pallido-thalamocortical pathways.

Networks mediating the clinical effects of pallidal brain stimulation for Parkinson's disease: a PET study of resting-state glucose metabolism.

Employing [(18)F]fluorodeoxyglucose (FDG) and PET, we have found previously that stereotaxic ablation of the internal globus pallidus (GPi) for Parkinson's disease causes resting metabolic changes in brain regions remote from the lesion site. In this study we determined whether similar metabolic changes occur in Parkinson's disease patients treated with deep brain stimulation (DBS) of the GPi. We studied seven Parkinson's disease patients with FDG-PET to measure resting regional cerebral glucose utilization on and off GPi stimulation. We used statistical parametric mapping to identify significant changes in regional brain metabolism that occurred with this intervention. We also quantified stimulation-related changes in the expression of a specific abnormal Parkinson's disease-related pattern of metabolic covariation (PDRP) that had been identified in earlier FDG-PET studies. Metabolic changes with DBS were correlated with clinical improvement as measured by changes in Unified Parkinson's Disease Rating Scale (UPDRS) motor ratings off medication. GPi DBS improved UPDRS motor ratings (36%, P < 0.001) and significantly increased regional glucose metabolism in the premotor cortex ipsilateral to stimulation and in the cerebellum bilaterally. GPi DBS also resulted in a significant (P < 0.01) decline in PDRP activity ipsilateral to stimulation, which correlated significantly with clinical improvement in UPDRS motor ratings (P < 0.03). Clinical improvement with GPi DBS is associated with reduced expression of an abnormal Parkinson's disease-related metabolic network involving elements of the cortico-striato-pallido-thalamocortical and the cerebello-cortical motor loops.

The metabolic anatomy of tremor in Parkinson's disease.

To identify regional metabolic brain networks related specifically to the presence of tremor in PD. The pathophysiology of parkinsonian tremor is unknown. Because tremor in PD occurs mainly in repose, we used resting state PET with 18F-fluorodeoxyglucose (FDG) to identify specific metabolic brain networks associated with this clinical manifestation. We studied two discrete groups of eight PD patients with and without tremor using FDG/PET. Both patient groups were matched for gender, age, and Unified Parkinson Disease Rating Scale ratings for akinesia and rigidity. Ten normal volunteer subjects served as controls. Network analysis with the Scaled Subprofile Model was performed in two steps. 1) We computed the expression of the PD-related pattern (PDRP) identified by us previously in each of the PD patients and control subjects. Although PDRP subject scores were abnormally elevated in the combined PD cohort (p < 0.005), these values did not differ in the PD patient groups with and without tremor (p = 0.36). 2) We used SSM to analyze the data from the combined PD cohort comprising both patient groups. We found that PD patients with tremor were characterized by increased expression of a metabolic network comprising the thalamus, pons, and premotor cortical regions. Subject scores for this pattern were elevated in the tremor group compared with the atremulous patient group and the normal control group (p < 0.005). The findings suggest that PD patients with tremor are characterized by distinct increases in the functional activity of thalamo-motor cortical projections. Modulation of this functional anatomic pathway is likely to be the mechanism for successful interventions for the relief of parkinsonian tremor.