Search

Background: To date, studies on positron emission tomography (PET) with 18F‐fluorodeoxyglucose (FDG) in progressive supranuclear palsy (PSP) usually included PSP cohorts overrepresenting patients with Richardson's syndrome (PSP‐RS). Objectives: To evaluate FDG‐PET in a patient sample representing the broad phenotypic PSP spectrum typically encountered in routine clinical practice. Methods: This retrospective, multicenter study included 41 PSP patients, 21 (51%) with RS and 20 (49%) with non‐RS variants of PSP (vPSP), and 46 age‐matched healthy controls. Two state‐of‐the art methods for the interpretation of FDG‐PET were compared: visual analysis supported by voxel‐based statistical testing (five readers) and automatic covariance pattern analysis using a predefined PSP‐related pattern. Results: Sensitivity and specificity of the majority visual read for the detection of PSP in the whole cohort were 74% and 72%, respectively. The percentage of false‐negative cases was 10% in the PSP‐RS subsample and 43% in the vPSP subsample. Automatic covariance pattern analysis provided sensitivity and specificity of 93% and 83% in the whole cohort. The percentage of false‐negative cases was 0% in the PSP‐RS subsample and 15% in the vPSP subsample. Conclusions: Visual interpretation of FDG‐PET supported by voxel‐based testing provides good accuracy for the detection of PSP‐RS, but only fair sensitivity for vPSP. Automatic covariance pattern analysis outperforms visual interpretation in the detection of PSP‐RS, provides clinically useful sensitivity for vPSP, and reduces the rate of false‐positive findings. Thus, pattern expression analysis is clinically useful to complement visual reading and voxel‐based testing of FDG‐PET in suspected PSP. © 2023 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society. [ABSTRACT FROM AUTHOR]

Parkinson's disease (PD) is associated with an abnormal pattern of regional brain function. The expression of this PD-related covariance pattern (PDRP) has been used to assess disease progression and the response to treatment. In this study, we validated the PDRP network as a measure of parkinsonism by prospectively computing its expression (PDRP scores) in 15O-water (H215O) and 18F-fluorodeoxyglucose (FDG) positron emission tomography (PET) scans from PD patients and healthy volunteers. The reliability of this measure was also assessed within subjects using a test–retest design in mildly affected and advanced PD patients scanned at baseline and during treatment with levodopa or deep brain stimulation (DBS). We found that PDRP expression was significantly elevated in PD patients (P<0.001) relative to controls in a prospective analysis of brain scans obtained with either H215O or FDG PET. A significant correlation (R2=0.61; P<0.001) was evident between PDRP scores computed from H215O and FDG images in PD subjects scanned with both tracers. Test–retest reproducibility was very high (intraclass correlation coefficient (ICC)>0.92) for PDRP scores measured both within PET session and between sessions separated by up to 2 months. This high reproducibility was observed in both early stage and advanced PD patients scanned at baseline and during treatment. The within-subject variability of this measure was less than 10% for both unmedicated and treated conditions. These findings suggest that the PDRP network is a reproducible and stable descriptor of regional functional abnormalities in parkinsonism. The quantification of PDRP expression in PD patients can serve as a potential biomarker in PET intervention studies for this disorder.Journal of Cerebral Blood Flow & Metabolism (2007) 27, 597–605. doi:10.1038/sj.jcbfm.9600358; published online 28 June 2006 [ABSTRACT FROM AUTHOR]

Background: Diagnostic criteria for progressive supranuclear palsy (PSP) include midbrain atrophy in MRI and hypometabolism in [ 18 F]fluorodeoxyglucose (FDG)-positron emission tomography (PET) as supportive features. Due to limited data regarding their relative and sequential value, there is no recommendation for an algorithm to combine both modalities to increase diagnostic accuracy. This study evaluated the added value of sequential imaging using state-of-the-art methods to analyse the images regarding PSP features., Methods: The retrospective study included 41 PSP patients, 21 with Richardson's syndrome (PSP-RS), 20 with variant PSP phenotypes (vPSP) and 46 sex- and age-matched healthy controls. A pretrained support vector machine (SVM) for the classification of atrophy profiles from automatic MRI volumetry was used to analyse T1w-MRI (output: MRI-SVM-PSP score). Covariance pattern analysis was applied to compute the expression of a predefined PSP-related pattern in FDG-PET (output: PET-PSPRP expression score)., Results: The area under the receiver operating characteristic curve for the detection of PSP did not differ between MRI-SVM-PSP and PET-PSPRP expression score (p≥0.63): about 0.90, 0.95 and 0.85 for detection of all PSP, PSP-RS and vPSP. The MRI-SVM-PSP score achieved about 13% higher specificity and about 15% lower sensitivity than the PET-PSPRP expression score. Decision tree models selected the MRI-SVM-PSP score for the first branching and the PET-PSPRP expression score for a second split of the subgroup with normal MRI-SVM-PSP score, both in the whole sample and when restricted to PSP-RS or vPSP., Conclusions: FDG-PET provides added value for PSP-suspected patients with normal/inconclusive T1w-MRI, regardless of PSP phenotype and the methods to analyse the images for PSP-typical features., Competing Interests: Competing interests: H-JH has used atlas-based volumetric MRI analysis in industry-sponsored research projects. CB received a grant from the Hilde-Ulrichs-Stiftung, served as a consultant for Bial, Hormosan Pharma, Merz Pharmaceuticals and Zambon and received honoraria for scientific presentations from Abbvie, Bial, Stada Pharma, TAD Pharma, UCB Pharma and Zambon. MP-N received lecture fees from Abbott, Abbvie, Boston Scientific and served as consultant for Medtronic, Boston Scientific, Abbott, Zambon and Abbvie. SK was funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) under Germany’s Excellence Strategy within the framework of the Munich Cluster for Systems Neurology (EXC 2145 SyNergy–ID 390857198), the Ehrmann Foundation and the Lüneburg Heritage. SK receives research funding from CurePSP and reports travel support from Life Molecular Imaging outside the submitted work. MK received honoraria for scientific presentations from Abbvie and Ever Pharma. JL reports speaker fees from Bayer Vital, Biogen, EISAI, TEVA and Roche, consulting fees from Axon Neuroscience and Biogen, author fees from Thieme medical publishers and W. Kohlhammer medical publishers and is inventor in a patent 'Oral Phenylbutyrate for Treatment of Human 4-Repeat Tauopathies' (EP 23 156 122.6) filed by LMU Munich. In addition, he reports compensation for serving as chief medical officer for MODAG, is beneficiary of the phantom share program of MODAG and is inventor in a patent 'Pharmaceutical Composition and Methods of Use' (EP 22 159 408.8) filed by MODAG, all activities outside the submitted work. J-JR received speaker honoraria from GE Healthcare. OS received research support from Life Molecular Imaging. HB received reader honoraria from Life Molecular Imaging and speaker honoraria from Novartis/AAA. MPW received speaker or consultancy honoraria from Alexion, Bayer Healthcare, Biogen, Biologix, Bristol Myers Squibb, Celgene, Genilac, Imcyse, IXICO, Icometrix, Medison, Merck-Serono, Novartis, Roche, Sanofi-Genzyme. Publication royalties from Springer and Elsevier. GH was funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) under Germany’s Excellence Strategy within the framework of the Munich Cluster for Systems Neurology (EXC 2145 SyNergy–ID 390857198) and within the Hannover Cluster RESIST (EXC 2155–project number 39087428), the EU/EFPIA/Innovative Medicines Initiative (2) Joint Undertaking (IMPRIND grant no 116060), the European Joint Programme on Rare Diseases (Improve-PSP), Deutsche Forschungsgemeinschaft (DFG, HO2402/6-2 Heisenberg Program, HO2402/18-1 MSAomics), the VolkswagenStiftung (Niedersächsisches Vorab), the Petermax-Müller Foundation (Etiology and Therapy of Synucleinopathies and Tauopathies); participated in indurtry-sponsored research projects from Abbvie, Biogen, Biohaven, Novartis, Roche, Sanofi, UCB; served as a consultant for Abbvie, Alzprotect, Aprineua, Asceneuron, Bial, Biogen, Biohaven, Kyowa Kirin, Lundbeck, Novartis, Retrotope, Roche, Sanofi, UCB; received honoraria for scientific presentations from Abbvie, Bayer Vital, Bial, Biogen, Bristol Myers Squibb, Kyowa Kirin, Roche, Teva, UCB, Zambon; received publication royalties from Academic Press, Kohlhammer and Thieme. All other authors declare that they have no potential conflicts of interest., (© Author(s) (or their employer(s)) 2024. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.)

Background: To date, studies on positron emission tomography (PET) with 18 F-fluorodeoxyglucose (FDG) in progressive supranuclear palsy (PSP) usually included PSP cohorts overrepresenting patients with Richardson's syndrome (PSP-RS)., Objectives: To evaluate FDG-PET in a patient sample representing the broad phenotypic PSP spectrum typically encountered in routine clinical practice., Methods: This retrospective, multicenter study included 41 PSP patients, 21 (51%) with RS and 20 (49%) with non-RS variants of PSP (vPSP), and 46 age-matched healthy controls. Two state-of-the art methods for the interpretation of FDG-PET were compared: visual analysis supported by voxel-based statistical testing (five readers) and automatic covariance pattern analysis using a predefined PSP-related pattern., Results: Sensitivity and specificity of the majority visual read for the detection of PSP in the whole cohort were 74% and 72%, respectively. The percentage of false-negative cases was 10% in the PSP-RS subsample and 43% in the vPSP subsample. Automatic covariance pattern analysis provided sensitivity and specificity of 93% and 83% in the whole cohort. The percentage of false-negative cases was 0% in the PSP-RS subsample and 15% in the vPSP subsample., Conclusions: Visual interpretation of FDG-PET supported by voxel-based testing provides good accuracy for the detection of PSP-RS, but only fair sensitivity for vPSP. Automatic covariance pattern analysis outperforms visual interpretation in the detection of PSP-RS, provides clinically useful sensitivity for vPSP, and reduces the rate of false-positive findings. Thus, pattern expression analysis is clinically useful to complement visual reading and voxel-based testing of FDG-PET in suspected PSP. © 2023 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society., (© 2023 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.)

Previous multi-center imaging studies with 18 F-FDG PET have established the presence of Parkinson's disease motor- and cognition-related metabolic patterns termed PDRP and PDCP in patients with this disorder. Given that in PD cerebral perfusion and glucose metabolism are typically coupled in the absence of medication, we determined whether subject expression of these disease networks can be quantified in early-phase images from dynamic 18 F-FPCIT PET scans acquired to assess striatal dopamine transporter (DAT) binding. Methods: We studied a cohort of early-stage PD patients and age-matched healthy control subjects who underwent 18 F-FPCIT at baseline; scans were repeated 4 years later in a smaller subset of patients. The early 18 F-FPCIT frames, which reflect cerebral perfusion, were used to compute PDRP and PDCP expression (subject scores) in each subject, and compared to analogous measures computed based on 18 F-FDG PET scan when additionally available. The late 18 F-FPCIT frames were used to measure caudate and putamen DAT binding in the same individuals. Results: PDRP subject scores from early-phase 18 F-FPCIT and 18 F-FDG scans were elevated and striatal DAT binding reduced in PD versus healthy subjects. The PDRP scores from 18 F-FPCIT correlated with clinical motor ratings, disease duration, and with corresponding measures from 18 F-FDG PET. In addition to correlating with disease duration and analogous 18 F-FDG PET values, PDCP scores correlated with DAT binding in the caudate/anterior putamen. PDRP and PDCP subject scores using either method rose over 4 years whereas striatal DAT binding declined over the same time period. Conclusion: Early-phase images obtained with 18 F-FPCIT PET can provide an alternative to 18 F-FDG PET for PD network quantification. This technique therefore allows PDRP/PDCP expression and caudate/putamen DAT binding to be evaluated with a single tracer in one scanning session., (Copyright © 2021 by the Society of Nuclear Medicine and Molecular Imaging, Inc.)

Abnormal physiological networks of brain areas in disease can be identified by applying specialized multivariate computational algorithms based on principal component analysis to functional image data. Here we demonstrate the reproducibility of network patterns derived using positron emission tomography (PET) data in independent populations of parkinsonian patients for a large, clinically validated data set comprised of subjects with idiopathic Parkinson's disease (iPD), multiple system atrophy (MSA) and progressive supranuclear palsy (PSP). Correlation of voxel values of network patterns derived for the same condition in different data sets was high. To further illustrate the validity of these networks, we performed single subject differential diagnosis of prospective test subjects to determine the most probable case based on a subject's network scores expressed for each of these distinct parkinsonian syndromes. Three-fold cross-validation was performed to determine accuracy and positive predictive rates based on networks derived in separate folds of the composite data set. A logistic regression based classification algorithm was used to train in each fold and test in the remaining two folds. Combined accuracy for each of the three folds ranged from 82% to 93% in the training set and was approximately 81% for prospective test subjects.

New strategies are considered for automated, single-subject differential diagnosis of independent degenerative brain disorders characterized by similar clinical symptoms using functional imaging. The methodology of these strategies is described and its application in parkinsonian movement disorders is illustrated for PET data. Using an automated diagnostic Topographic Profile Rating (TPR) technique based on the Scaled Subprofile Model (SSM-PCA), single-subject score values for different conditions are compared with reference values to predict diagnosis. The discriminatory parameters of reference score sets associated with significant SSM principal components referred to as group invariant subprofiles (GIS networks) are examined. It is shown that the extraction of exclusive sub-networks that stem from contrasting image features between conditions can be an effective tool for optimization that does not require expert knowledge.