Jingjie Ge

Consistent abnormalities in metabolic network activity in idiopathic rapid eye movement sleep behaviour disorder

Rapid eye movement sleep behaviour disorder has been evaluated using Parkinsons disease-related metabolic network. It is unknown whether this disorder is itself associated with a unique metabolic network. 18F-fluorodeoxyglucose positron emission tomography was performed in 21 patients (age 65.0±5.6 years) with idiopathic rapid eye movement sleep behaviour disorder and 21 age/gender-matched healthy control subjects (age 62.5±7.5 years) to identify a disease-related pattern and examine its evolution in 21 hemi-parkinsonian patients (age 62.6±5.0 years) and 16 moderate parkinsonian patients (age 56.9±12.2 years). We identified a rapid eye movement sleep behaviour disorder-related metabolic network characterized by increased activity in pons, thalamus, medial frontal and sensorimotor areas, hippocampus, supramarginal and inferior temporal gyri, and posterior cerebellum, with decreased activity in occipital and superior temporal regions. Compared to the healthy control subjects, network expressions were elevated (P<0.0001) in the patients with this disorder and in the parkinsonian cohorts but decreased with disease progression. Parkinsons disease-related network activity was also elevated (P<0.0001) in the patients with rapid eye movement sleep behaviour disorder but lower than in the hemi-parkinsonian cohort. Abnormal metabolic networks may provide markers of idiopathic rapid eye movement sleep behaviour disorder to identify those at higher risk to develop neurodegenerative parkinsonism.

Cerebral Metabolic Differences Associated with Cognitive Impairment in Parkinson’s Disease

Purpose To characterize cerebral glucose metabolism associated with different cognitive states in Parkinson’s disease (PD) using 18F-fluorodeoxyglucose (FDG) and Positron Emission Tomography (PET). Methods Three groups of patients were recruited in this study including PD patients with dementia (PDD; n = 10), with mild cognitive impairment (PD-MCI; n = 20), and with no cognitive impairment (PD-NC; n = 30). The groups were matched for age, sex, education, disease duration, motor disability, levodopa equivalent dose and Geriatric Depression Rating Scale (GDS) score. All subjects underwent a FDG-PET study. Maps of regional metabolism in the three groups were compared using statistical parametric mapping (SPM5). Results PD-MCI patients exhibited limited areas of hypometabolism in the frontal, temporal and parahippocampal gyrus compared with the PD-NC patients (p < 0.01). PDD patients had bilateral areas of hypometabolism in the frontal and posterior parietal-occipital lobes compared with PD-MCI patients (p < 0.01), and exhibited greater metabolic reductions in comparison with PD-NC patients (p < 0.01). Conclusions Compared with PD-NC patients, hypometabolism was much higher in the PDD patients than in PD-MCI patients, mainly in the posterior cortical areas. The result might suggest an association between posterior cortical hypometabolism and more severe cognitive impairment. PD-MCI might be important for early targeted therapeutic intervention and disease modification.

Onset-related subtypes of Parkinson's disease differ in the patterns of striatal dopaminergic dysfunction: A positron emission tomography study

PURPOSE The young-onset subtype of Parkinsons disease (YOPD) differs from the late-onset subtype (LOPD) in drug responsiveness, incidence of motor complications, and prognosis. The pathophysiology underlying these differences remains largely unknown. This study investigated whether the two subtypes differ in the pattern of dysfunction in striatal (caudate and putamen) dopaminergic system and if the dopamine transporter (DAT) imaging patterns are associated with the clinical features of corresponding PD subtype. METHODS We assessed the spatial pattern of striatal dopaminergic dysfunction in 40 YOPD and 47 LOPD with early to mid-stage PD with DAT imaging by positron emission tomography. Two sub-regional parameters (caudate/putamen ratio and asymmetry index) were calculated to measure the spatial pattern of striatal dopaminergic dysfunction. RESULTS The caudate/anterior putamen ratios were significantly higher in YOPD than that in the LOPD (P = 0.03 contralateral to the most affected side of the body and P = 0.004 ipsilateral), which was supported by significantly inverse correlations between age of onset and caudate/anterior putamen ratios (r = -0.428, P < 0.001 for the contralateral and r = -0.576, P < 0.001 for the ipsilateral). Sub-regional DAT binding in caudate ipsilateral to affected limbs was significantly correlated with age, while DAT bindings in putamen were significantly inversely correlated with disease duration and UPDRS motor scores. CONCLUSION The YOPD subtype suffers from an uneven pattern of dopaminergic dysfunction: more sparing of the caudate compared with the putamen, while the LOPD patients is with a relatively uniform pattern.

Data-driven identification of intensity normalization region based on longitudinal coherency of (18)F-FDG metabolism in the healthy brain.

Objectives In brain 18F‐FDG PET data intensity normalization is usually applied to control for unwanted factors confounding brain metabolism. However, it can be difficult to determine a proper intensity normalization region as a reference for the identification of abnormal metabolism in diseased brains. In neurodegenerative disorders, differentiating disease‐related changes in brain metabolism from age‐associated natural changes remains challenging. This study proposes a new data‐driven method to identify proper intensity normalization regions in order to improve separation of age‐associated natural changes from disease related changes in brain metabolism. Methods 127 female and 128 male healthy subjects (age: 20 to 79) with brain18F‐FDG PET/CT in the course of a whole body cancer screening were included. Brain PET images were processed using SPM8 and were parcellated into 116 anatomical regions according to the AAL template. It is assumed that normal brain 18F‐FDG metabolism has longitudinal coherency and this coherency leads to better model fitting. The coefficient of determination R2 was proposed as the coherence coefficient, and the total coherence coefficient (overall fitting quality) was employed as an index to assess proper intensity normalization strategies on single subjects and age‐cohort averaged data. Age‐associated longitudinal changes of normal subjects were derived using the identified intensity normalization method correspondingly. In addition, 15 subjects with clinically diagnosed Parkinsons disease were assessed to evaluate the clinical potential of the proposed new method. Results Intensity normalizations by paracentral lobule and cerebellar tonsil, both regions derived from the new data‐driven coherency method, showed significantly better coherence coefficients than other intensity normalization regions, and especially better than the most widely used global mean normalization. Intensity normalization by paracentral lobule was the most consistent method within both analysis strategies (subject‐based and age‐cohort averaging). In addition, the proposed new intensity normalization method using the paracentral lobule generates significantly higher differentiation from the age‐associated changes than other intensity normalization methods. Conclusion Proper intensity normalization can enhance the longitudinal coherency of normal brain glucose metabolism. The paracentral lobule followed by the cerebellar tonsil are shown to be the two most stable intensity normalization regions concerning age‐dependent brain metabolism. This may provide the potential to better differentiate disease‐related changes from age‐related changes in brain metabolism, which is of relevance in the diagnosis of neurodegenerative disorders. HighlightsA method to differentiate disease‐related metabolic changes from age‐associated natural changes.A concept of longitudinal coherency to identify proper age‐associated metabolic changes.A data‐driven method to find out optimal intensity normalization enhancing longitudinal coherency.Normalization using paracentral lobule can best describe age‐dependent brain metabolism.Development on normal subjects and preliminary verification on PD patients.

Reproducible network and regional topographies of abnormal glucose metabolism associated with progressive supranuclear palsy: Multivariate and univariate analyses in American and Chinese patient cohorts

Progressive supranuclear palsy (PSP) is a rare movement disorder and often difficult to distinguish clinically from Parkinsons disease (PD) and multiple system atrophy (MSA) in early phases. In this study, we report reproducible disease‐related topographies of brain network and regional glucose metabolism associated with PSP in clinically‐confirmed independent cohorts of PSP, MSA, and PD patients and healthy controls in the USA and China. Using 18F‐FDG PET images from PSP and healthy subjects, we applied spatial covariance analysis with bootstrapping to identify a PSP‐related pattern (PSPRP) and estimate its reliability, and evaluated the ability of network scores for differential diagnosis. We also detected regional metabolic differences using statistical parametric mapping analysis. We produced a highly reliable PSPRP characterized by relative metabolic decreases in the middle prefrontal cortex/cingulate, ventrolateral prefrontal cortex, striatum, thalamus and midbrain, covarying with relative metabolic increases in the hippocampus, insula and parieto‐temporal regions. PSPRP network scores correlated positively with PSP duration and accurately discriminated between healthy, PSP, MSA and PD groups in two separate cohorts of parkinsonian patients at both early and advanced stages. Moreover, PSP patients shared many overlapping areas with abnormal metabolism in the same cortical and subcortical regions as in the PSPRP. With rigorous cross‐validation, this study demonstrated highly comparable and reproducible PSP‐related metabolic topographies at network and regional levels across different patient populations and PET scanners. Metabolic brain network activity may serve as a reliable and objective marker of PSP, although cross‐validation applying recent diagnostic criteria and classification is warranted.

The metabolic brain network in patients with Parkinson's disease based on 18 F-FDG PET imaging: evaluation of neuronal injury and regeneration

Over the past two decades, the development of functional imaging methods has greatly promoted our understanding on the changes of neurons following neurodegenerative disorders, such as Parkinsons disease (PD). The application of a spatial covariance analysis on 18F-FDG PET imaging has led to the identification of a distinctive disease-related metabolic pattern. This pattern has proven to be useful in clinical diagnosis, disease progression monitoring as well as assessment of the neuronal changes before and after clinical treatment. It may potentially serve as an objective biomarker on disease progression monitoring, assessment, histological and functional evaluation of related diseases. PD is one of the most common neurodegenerative disorders in the elderly. It is characterized by progressive loss of dopamine neurons in the substantia nigra pars compacta. Throughout the course of disease, the most obvious symptoms are movement-related, such as resting tremor, muscle rigidity, hypokinesia and postural instability (Worth, 2013). Currently, a definite diagnosis of PD is made by clinical evaluation with at least 2 years of follow-up (Hughes et al., 2002; Bhidayasiri and Reichmann, 2013), due to the overlap of motor symptoms between early PD and atypical parkinsonism including multiple system atrophy (MSA) and progressive supranuclear palsy (PSP). However, this classic diagnostic criterion does not benefit the early diagnosis of disease. The prognostic outcome and treatment option are substantially different between PD and atypical parkinsonism. Thus it is critical to develop biomarkers for earlier and more accurate diagnosis of PD. Generally, appropriate diagnostic biomarker for PD ought to cover several key characteristics: (i) minimal invasiveness to detect the biomarker in easily accessible body tissue or fluids, (ii) excellent sensitivity to explore the patients with PD, (iii) high specificity to prevent false-positive results in PD-free individuals, and (iv) robustness against potential affecting factors. A PD-related spatial covariance pattern (PDRP) with quantifiable expression on 18F-FDG PET imaging has been gradually detected using a spatial covariance method during the last two decades and it has been demonstrated to be the right diagnostic biomarker for PD (Eidelberg et al., 1994). PDRP has proven not only to be effective in early discrimination of PD from atypical parkinsonian disorders, but also to be able to assess the disease progression and treatment response. Thus it is considered as a multifunctional biomarker. In this review, we aim to provide an overview of the development in pattern-based biomarker for PD.

Validation of abnormal glucose metabolism associated with Parkinson’s disease in Chinese participants based on 18F-fluorodeoxyglucose positron emission tomography imaging

Purpose We previously identified disease-related cerebral metabolic characteristics associated with Parkinson’s disease (PD) in the Chinese population using 18F-fluorodeoxyglucose (FDG) positron emission tomography (PET)/computed tomography (CT) imaging. The present study aims to assess data reproducibility and robustness of the metabolic activity characteristics across independent cohorts. Patients and methods Forty-eight patients with PD and 48 healthy controls from Chongqing district, in addition to 33 patients with PD and 33 healthy controls from Shanghai district were recruited. Each subject underwent brain 18F-FDG PET/CT imaging in a resting state. Based on the brain images, differences between the groups and PD-related cerebral metabolic activities were graphically and quantitatively evaluated. Results Both PD patient cohorts exhibited analogous cerebral patterns characterized by metabolic increase in the putamen, globus pallidus, thalamus, pons, sensorimotor cortex and cerebellum, along with metabolic decrease in parieto-occipital areas. Additionally, the metabolic pattern was highly indicative of the disease, with a significant elevation in PD patients compared with healthy controls (p<0.001) in both the derivation (Shanghai) and validation (Chongqing) cohorts. Conclusion This dual-center study demonstrated the high comparability and reproducibility of PD-related cerebral metabolic activity patterns across independent Chinese cohorts and may serve as an objective diagnostic marker for the disease.

Clinical characteristics of cognitive impairment in patients with Parkinson's disease and its related pattern in 18F-FDG PET imaging

This study aimed to characterize the clinical features and the related cerebral glucose metabolism pattern of cognitive impairments in Parkinsons disease (PD) with positron emission tomography (PET) imaging. We recruited 168 PD patients and 100 age‐matched healthy controls of similar education and gender distribution. All of those enrolled underwent clinical assessment including the unified Parkinsons disease rating scale motor score, Hoehn and Yahr scale, and comprehensive neuropsychological tests including domains of executive function, attention, memory, visuospatial function, and language. Demographics and the results of cognitive measures were compared between patients and healthy controls. Cognition status was classified as PD patients with dementia (PD‐D), PD patients with mild cognitive impairment (PD‐MCI), or PD patients with normal cognition (PD‐NC). In 53 PD patients who underwent 18F‐fluorodeoxyglucose (18F‐FDG) PET imaging, correlations between Z‐score values of the different cognitive domains and cerebral 18F‐FDG uptake were assessed using statistical parametric mapping (SPM8) corrected for age and motor severity. A total of 23.2% of PD patients were PD‐MCI and 8.9% were PD‐D. In the group of PD‐MCI, 96.3% showed multiple‐domain deficits, with executive function and attention impairment most predominantly involved. All the cognitive domain scores with the exception of language correlated with 18F‐FDG metabolisms, primarily in posterior temporo‐parieto‐occipital association cortical areas. This study found that cognitive impairment in PD particularly encompasses frontal/executive deficits. Posterior cortical areas, containing multiple neurotransmitters and neural circuits, may play an important role in the pathogenesis of cognitive impairment in PD.

Glucose Metabolic Brain Network Differences between Chinese Patients with Lewy Body Dementia and Healthy Control

Dementia with Lewy bodies (DLB) is the second most common degenerative dementia of the central nervous system. The technique 18F-fluorodeoxyglucose positron emission tomography (18F FDG PET) was used to investigate brain metabolism patterns in DLB patients. Conventional statistical methods did not consider intern metabolism transforming connections between various brain regions; therefore, most physicians do not understand the underlying neuropathology of DLB patients. In this study, 18F FDG-PET images and graph-theoretical methods were used to investigate alterations in whole-brain intrinsic functional connectivity in a Chinese DLB group and healthy control (HC) group. This experimental study was performed on 22 DLB patients and 22 HC subjects in Huashan Hospital, Shanghai, China. Experimental results indicate that compared with the HC group, the DLB group has severely impaired small-world network. Compared to those of the HC group, the clustering coefficients of the DLB group were higher and characteristic path lengths were longer, and in terms of global efficiencies, those of the DLB group was also lower. Moreover, four significantly altered regions were observed in the DLB group: Inferior frontal gyrus, opercular part (IFG.R), olfactory cortex (OLF.R), hippocampus (HIP.R), and fusiform gyrus (FFG.L). Amongst them, in the DLB group, betweenness centrality became strong in OLF.R, HIP.R, and FFG.L, whereas betweenness centrality became weaker in IFG.R. Finally, IFGoperc.R was selected as a seed and a voxel-wise correlation analysis was performed. Compared to the HC group, the DLB group showed several regions of strengthened connection with IFGoperc.R; these regions were located in the prefrontal cortex and regions of weakened connection were located in the occipital cortex. The results of this paper may help physicians to better understand and characterize DLB patients.