Recent progress in the applications of presynaptic dopaminergic positron emission tomography imaging in parkinsonism.

Nowadays, presynaptic dopaminergic positron emission tomography, which assesses deficiencies in dopamine synthesis, storage, and transport, is widely utilized for early diagnosis and differential diagnosis of parkinsonism. This review provides a comprehensive summary of the latest developments in the application of presynaptic dopaminergic positron emission tomography imaging in disorders that manifest parkinsonism. We conducted a thorough literature search using reputable databases such as PubMed and Web of Science. Selection criteria involved identifying peer-reviewed articles published within the last 5 years, with emphasis on their relevance to clinical applications. The findings from these studies highlight that presynaptic dopaminergic positron emission tomography has demonstrated potential not only in diagnosing and differentiating various Parkinsonian conditions but also in assessing disease severity and predicting prognosis. Moreover, when employed in conjunction with other imaging modalities and advanced analytical methods, presynaptic dopaminergic positron emission tomography has been validated as a reliable in vivo biomarker. This validation extends to screening and exploring potential neuropathological mechanisms associated with dopaminergic depletion. In summary, the insights gained from interpreting these studies are crucial for enhancing the effectiveness of preclinical investigations and clinical trials, ultimately advancing toward the goals of neuroregeneration in parkinsonian disorders.

Visual reading for [18F]Florzolotau Tau PET scans in progressive supranuclear palsy.

PURPOSE: The identification of tau accumulation within living brains holds significant potential in facilitating accurate diagnosis of progressive supranuclear palsy (PSP). While visual assessment is frequently employed, standardized methods for tau positron emission tomography (PET) specifically in PSP are absent. We aimed to develop a visual reading algorithm dedicated to the evaluation of [18F]Florzolotau PET in PSP. METHODS: 148 PSP and 30 healthy volunteers were divided into a development set (for the establishment of the reading rules; n = 89) and a testing set (for the validation of the reading rules; n = 89). For differential diagnosis, 55 α-synucleinopathies were additionally included into the testing set. The visual reading method was established by an experienced assessor (Reader 0) and was then validated by Reader 0 and two additional readers on regional and overall binary manners. A positive binding in both midbrain and globus pallidus/putamen regions was characterized as a PSP-like pattern, whereas any other pattern was classified as non-PSP-like. RESULTS: Reader 1 (94.4%) and Reader 2 (93.8%) showed excellent agreement for the overall binary determination against Reader 0. The regional binary determinations of midbrain and globus pallidus/putamen showed excellent agreement among readers (kappa > 0.80). The overall binary evaluation demonstrated reproducibility of 86.1%, 94.4% and 77.8% for three readers. The visual reading algorithm showed high agreement with regional standardized uptake value ratios and clinical diagnoses. CONCLUSION: Through the application of the suggested visual reading algorithm, [18F]Florzorotau PET imaging demonstrated a robust performance for the imaging diagnosis of PSP.

Impact of excessive daytime sleepiness on the progression of freezing of gait in de novo Parkinson's disease: a cohort study.

BACKGROUND: Excessive daytime sleepiness (EDS) and freezing of gait (FOG) are prevalent non-motor and motor symptoms in patients with Parkinson's disease (PD), significantly impacting their quality of life. However, the correlation between EDS and FOG progression in de novo PD patients remains controversial. METHODS: A total of 328 participants from the Parkinson's Progression Markers Initiative (PPMI) were divided into two groups: 43 with EDS (EDS group) and 285 without EDS (nEDS group). The cumulative incidence of FOG was assessed at the 5-year follow-up using Kaplan-Meier and log-rank tests. Multivariate Cox proportional hazards models were used to assess the impact of EDS on FOG progression in PD patients, with validation for robustness through sensitivity and subgroup analyses. RESULTS: The EDS group experienced a higher incidence of FOG throughout the 5-year follow-up than did the nEDS group. Multivariate Cox proportional hazards models showed significantly association between EDS severity and enhanced risk of developing FOG (HR = 1.076, 95% CI:1.007 ~ 1.149, P = 0.031). For sensitivity analysis, parallel analyses were performed by substituting the independent variable with categorical variables, which yielded analogous outcomes (HR = 1.837, 95% CI:1.063 ~ 3.174, P = 0.029). Furthermore, subgroup analyses based on sex, age, TD/PIGD classification, depressive symptoms, cognitive impairment, mean caudate nucleus uptake level, mean putamen nucleus uptake level and CSF Aß-42 level revealed no significant interactions between subgroups (all P values for interaction were > 0.05). CONCLUSION: EDS is a potential prognosis factor for the progression of FOG in patients with PD.

Comparing shear wave elastography of breast tumors and axillary nodes in the axillary assessment after neoadjuvant chemotherapy in patients with node-positive breast cancer.

BACKGROUND: Accurately identifying patients with axillary pathologic complete response (pCR) after neoadjuvant chemotherapy (NAC) in breast cancer patients remains challenging. PURPOSE: To compare the feasibility of shear wave elastography (SWE) performed on breast tumors and axillary lymph nodes (LNs) in predicting the axillary status after NAC. MATERIALS AND METHODS: This prospective study included a total of 319 breast cancer patients with biopsy-proven positive node who received NAC followed by axillary lymph node dissection from 2019 to 2022. The correlations between shear wave velocity (SWV) and pathologic characteristics were analyzed separately for both breast tumors and LNs after NAC. We compared the performance of SWV between breast tumors and LNs in predicting the axillary status after NAC. Additionally, we evaluated the performance of the most significantly correlated pathologic characteristic in breast tumors and LNs to investigate the pathologic evidence supporting the use of breast or axilla SWE. RESULTS: Axillary pCR was achieved in 51.41% of patients with node-positive breast cancer. In breast tumors, there is a stronger correlation between SWV and collagen volume fraction (CVF) (r = 0.52, p < 0.001) compared to tumor cell density (TCD) (r = 0.37, p < 0.001). In axillary LNs, SWV was weakly correlated with CVF (r = 0.31, p = 0.177) and TCD (r = 0.29, p = 0.213). No significant correlation was found between SWV and necrosis proportion in breast tumors or axillary LNs. The predictive performances of both SWV and CVF for axillary pCR were found to be superior in breast tumors (AUC = 0.87 and 0.85, respectively) compared to axillary LNs (AUC = 0.70 and 0.74, respectively). CONCLUSION: SWE has the ability to characterize the extracellular matrix, and serves as a promising modality for evaluating axillary LNs after NAC. Notably, breast SWE outperform axilla SWE in determining the axillary status in breast cancer patients after NAC.

Disease progression in proposed brain-first and body-first Parkinson's disease subtypes.

A new Parkinson's disease (PD) subtyping model has been recently proposed based on the initial location of α-synuclein inclusions, which divides PD patients into the brain-first subtype and the body-first subtype. Premotor RBD has proven to be a predictive marker of the body-first subtype. We found compared to PD patients without possible RBD (PDpRBD-, representing the brain-first subtype), PD patients with possible premotor RBD (PDpRBD+, representing the body-first subtype) had lower Movement Disorders Society Unified Parkinson's Disease Rating Scale part III (MDS UPDRS-III) score (p = 0.022) at baseline but presented a faster progression rate (p = 0.009) in MDS UPDRS-III score longitudinally. The above finding indicates the body-first subtype exhibited a faster disease progression in motor impairments compared to the brain-first subtype and further validates the proposed subtyping model.

Bidirectional regulation of levodopa-induced dyskinesia by a specific neural ensemble in globus pallidus external segment.

Levodopa-induced dyskinesia (LID) is an intractable motor complication arising in Parkinson's disease with the progression of disease and chronic treatment of levodopa. However, the specific cell assemblies mediating dyskinesia have not been fully elucidated. Here, we utilize the activity-dependent tool to identify three brain regions (globus pallidus external segment [GPe], parafascicular thalamic nucleus, and subthalamic nucleus) that specifically contain dyskinesia-activated ensembles. An intensity-dependent hyperactivity in the dyskinesia-activated subpopulation in GPe (GPeTRAPed in LID) is observed during dyskinesia. Optogenetic inhibition of GPeTRAPed in LID significantly ameliorates LID, whereas reactivation of GPeTRAPed in LID evokes dyskinetic behavior in the levodopa-off state. Simultaneous chemogenetic reactivation of GPeTRAPed in LID and another previously reported ensemble in striatum fully reproduces the dyskinesia induced by high-dose levodopa. Finally, we characterize GPeTRAPed in LID as a subset of prototypic neurons in GPe. These findings provide theoretical foundations for precision medication and modulation of LID in the future.

Deep learning combining mammography and ultrasound images to predict the malignancy of BI-RADS US 4A lesions in women with dense breasts: a diagnostic study.

OBJECTIVES: The authors aimed to assess the performance of a deep learning (DL) model, based on a combination of ultrasound (US) and mammography (MG) images, for predicting malignancy in breast lesions categorized as Breast Imaging Reporting and Data System (BI-RADS) US 4A in diagnostic patients with dense breasts. METHODS: A total of 992 patients were randomly allocated into the training cohort and the test cohort at a proportion of 4:1. Another, 218 patients were enrolled to form a prospective validation cohort. The DL model was developed by incorporating both US and MG images. The predictive performance of the combined DL model for malignancy was evaluated by sensitivity, specificity, and area under the receiver operating characteristic curve (AUC). The combined DL model was then compared to a clinical nomogram model and to the DL model trained using US image only and to that trained MG image only. RESULTS: The combined DL model showed satisfactory diagnostic performance for predicting malignancy in breast lesions, with an AUC of 0.940 (95% CI: 0.874-1.000) in the test cohort, and an AUC of 0.906 (95% CI: 0.817-0.995) in the validation cohort, which was significantly higher than the clinical nomogram model, and the DL model for US or MG alone ( P <0.05). CONCLUSIONS: The study developed an objective DL model combining both US and MG imaging features, which was proven to be more accurate for predicting malignancy in the BI-RADS US 4A breast lesions of patients with dense breasts. This model may then be used to more accurately guide clinicians' choices about whether performing biopsies in breast cancer diagnosis.

Clinical features, disease progression, and nuclear imaging in ATXN2-related parkinsonism in a longitudinal cohort.

BACKGROUND: Spinocerebellar ataxia 2 (SCA2) with a low range of CAG repeat expansion of ATXN2 gene can present with predominant or isolated parkinsonism that closely resembles Parkinson's disease (PD). This study is aimed at comparing clinical features, disease progression, and nuclear imaging between ATXN2-related parkinsonism (ATXN2-P) and PD. METHODS: Three hundred and seventy-seven clinically diagnosed PD with family history were screened by multiplex ligation-dependent probe amplification, whole-exome sequencing or target sequencing, and dynamic mutation testing of 10 SCA subtypes. The baseline and longitudinal clinical features as well as the dual-tracer positron emission tomography (PET) imaging were compared between ATXN2-P and genetically undefined familial PD (GU-fPD). RESULTS: Fifteen ATXN2-P patients from 7 families and 50 randomly selected GU-fPD patients were evaluated. Significantly less resting tremor and more symmetric signs were observed in ATXN2-P than GU-fPD. No significant difference was found in motor progression and duration from onset to occurrence of fluctuation, dyskinesia, and recurrent falls between the two groups. Cognitive impairment and rapid-eye-movement sleep behavior disorder were more common in ATXN2-P. During follow-up, olfaction was relatively spared, and no obvious progression of cognition dysfunction evaluated by Mini-Mental State Examination scores was found in ATXN2-P. PET results of ATXN2-P demonstrated a symmetric, diffuse, and homogenous dopamine transporter loss of bilateral striatum and a glucose metabolism pattern inconsistent with that in PD. CONCLUSIONS: Symmetric motor signs and unique nuclear imaging might be the clues to distinguish ATXN2-P from GU-fPD.

Diagnostic performance of artificial intelligence-assisted PET imaging for Parkinson's disease: a systematic review and meta-analysis.

Artificial intelligence (AI)-assisted PET imaging is emerging as a promising tool for the diagnosis of Parkinson's disease (PD). We aim to systematically review the diagnostic accuracy of AI-assisted PET in detecting PD. The Ovid MEDLINE, Ovid Embase, Web of Science, and IEEE Xplore databases were systematically searched for related studies that developed an AI algorithm in PET imaging for diagnostic performance from PD and were published by August 17, 2023. Binary diagnostic accuracy data were extracted for meta-analysis to derive outcomes of interest: area under the curve (AUC). 23 eligible studies provided sufficient data to construct contingency tables that allowed the calculation of diagnostic accuracy. Specifically, 11 studies were identified that distinguished PD from normal control, with a pooled AUC of 0.96 (95% CI: 0.94-0.97) for presynaptic dopamine (DA) and 0.90 (95% CI: 0.87-0.93) for glucose metabolism (18F-FDG). 13 studies were identified that distinguished PD from the atypical parkinsonism (AP), with a pooled AUC of 0.93 (95% CI: 0.91 - 0.95) for presynaptic DA, 0.79 (95% CI: 0.75-0.82) for postsynaptic DA, and 0.97 (95% CI: 0.96-0.99) for 18F-FDG. Acceptable diagnostic performance of PD with AI algorithms-assisted PET imaging was highlighted across the subgroups. More rigorous reporting standards that take into account the unique challenges of AI research could improve future studies.

International consensus on clinical use of presynaptic dopaminergic positron emission tomography imaging in parkinsonism.

PURPOSE: Presynaptic dopaminergic positron emission tomography (PET) imaging serves as an essential tool in diagnosing and differentiating patients with suspected parkinsonism, including idiopathic Parkinson's disease (PD) and other neurodegenerative and non-neurodegenerative diseases. The PET tracers most commonly used at the present time mainly target dopamine transporters (DAT), aromatic amino acid decarboxylase (AADC), and vesicular monoamine type 2 (VMAT2). However, established standards for the imaging procedure and interpretation of presynaptic dopaminergic PET imaging are still lacking. The goal of this international consensus is to help nuclear medicine practitioners procedurally perform presynaptic dopaminergic PET imaging. METHOD: A multidisciplinary task group formed by experts from various countries discussed and approved the consensus for presynaptic dopaminergic PET imaging in parkinsonism, focusing on standardized recommendations, procedures, interpretation, and reporting. CONCLUSION: This international consensus and practice guideline will help to promote the standardized use of presynaptic dopaminergic PET imaging in parkinsonism. It will become an international standard for this purpose in clinical practice.

Uncovering distinct progression patterns of tau deposition in progressive supranuclear palsy using [18F]Florzolotau PET imaging and subtype/stage inference algorithm.

BACKGROUND: Progressive supranuclear palsy (PSP) is a primary 4-repeat tauopathy with diverse clinical phenotypes. Previous post-mortem studies examined tau deposition sequences in PSP, but in vivo scrutiny is lacking. METHODS: We conducted [18F]Florzolotau tau positron emission tomography (PET) scans on 148 patients who were clinically diagnosed with PSP and 20 healthy controls. We employed the Subtype and Stage Inference (SuStaIn) algorithm to identify PSP subtype/stage and related tau patterns, comparing clinical features across subtypes and assessing PSP stage-clinical severity association. We also evaluated functional connectivity differences among subtypes through resting-state functional magnetic resonance imaging. FINDINGS: We identified two distinct subtypes of PSP: Subtype1 and Subtype2. Subtype1 typically exhibits a sequential progression of the disease, starting from subcortical and gradually moving to cortical regions. Conversely, Subtype2 is characterized by an early, simultaneous onset in both regions. Interestingly, once the disease is initiated, Subtype1 tends to spread more rapidly within each region compared to Subtype2. Individuals categorized as Subtype2 are generally older and exhibit less severe dysfunctions in areas such as cognition, bulbar, limb motor, and general motor functions compared to those with Subtype1. Moreover, they have a more favorable prognosis in terms of limb motor function. We found significant correlations between several clinical variables and the identified PSP SuStaIn stages. Furthermore, Subtype2 displayed a remarkable reduction in functional connectivity compared to Subtype1. INTERPRETATION: We present the evidence of distinct in vivo spatiotemporal tau trajectories in PSP. Our findings can contribute to precision medicine advancements for PSP. FUNDING: This work was supported by grants from the National Natural Science Foundation of China (number 82272039, 81971641, 82021002, and 92249302); Swiss National Science Foundation (number 188350); the STI2030-Major Project of China (number 2022ZD0211600); the Clinical Research Plan of Shanghai Hospital Development Center of China (number SHDC2020CR1038B); and the National Key R&D Program of China (number 2022YFC2009902, 2022YFC2009900), the China Scholarship Council (number 202006100181); the Deutsche Forschungsgemeinschaft (DFG) under Germany's Excellence Strategy within the framework of the Munich Cluster for Systems Neurology (EXC 2145 SyNergy, ID 390857198).

Improved interpretation of 18F-florzolotau PET in progressive supranuclear palsy using a normalization-free deep-learning classifier.

While 18F-florzolotau tau PET is an emerging biomarker for progressive supranuclear palsy (PSP), its interpretation has been hindered by a lack of consensus on visual reading and potential biases in conventional semi-quantitative analysis. As clinical manifestations and regions of elevated 18F-florzolotau binding are highly overlapping in PSP and the Parkinsonian type of multiple system atrophy (MSA-P), developing a reliable discriminative classifier for 18F-florzolotau PET is urgently needed. Herein, we developed a normalization-free deep-learning (NFDL) model for 18F-florzolotau PET, which achieved significantly higher accuracy for both PSP and MSA-P compared to semi-quantitative classifiers. Regions driving the NFDL classifier's decision were consistent with disease-specific topographies. NFDL-guided radiomic features correlated with clinical severity of PSP. This suggests that the NFDL model has the potential for early and accurate differentiation of atypical parkinsonism and that it can be applied in various scenarios due to not requiring subjective interpretation, MR-dependent, and reference-based preprocessing.

The genetic spectrum of a cohort of patients clinically diagnosed as Parkinson's disease in mainland China.

So far, over 20 causative genes of monogenic Parkinson's disease (PD) have been identified. Some causative genes of non-parkinsonian entities may also manifest with parkinsonism mimicking PD. This study aimed to investigate the genetic characteristics of clinically diagnosed PD with early onset age or family history. A total of 832 patients initially diagnosed with PD were enrolled, of which, 636 were classified into the early-onset group and 196 were classified into the familial late-onset group. The genetic testing included the multiplex ligation-dependent probe amplification and next generation sequencing (target sequencing or whole-exome sequencing). The dynamic variants of spinocerebellar ataxia were tested in probands with family history. In the early-onset group, 30.03% of patients (191/636) harbored pathogenic/likely pathogenic (P/LP) variants in known PD-related genes (CHCHD2, DJ-1, GBA (heterozygous), LRRK2, PINK1, PRKN, PLA2G6, SNCA and VPS35). Variants in PRKN were the most prevalent, accounting for 15.72% of the early-onset patients, followed by GBA (10.22%), and PLA2G6 (1.89%). And 2.52% (16/636) had P/LP variants in causative genes of other diseases (ATXN3, ATXN2, GCH1, TH, MAPT, GBA (homozygous)). In the familial late-onset group, 8.67% of patients (17/196) carried P/LP variants in known PD-related genes (GBA (heterozygous), HTRA2, SNCA) and 2.04% (4/196) had P/LP variants in other genes (ATXN2, PSEN1, DCTN1). Heterozygous GBA variants (7.14%) were the most common genetic cause found in familial late-onset patients. Genetic testing is of vital importance in differential diagnosis especially in early-onset and familial PD. Our findings may also provide some clues to the nomenclature of genetic movement disorders.

Autosomal dominant Parkinson's disease caused by the recently identified LRRK2 N1437D mutation in a Chinese family: Clinical features, imaging findings, and functional impact.

INTRODUCTION: Mutations in leucine-rich repeat kinase 2 (LRRK2) are the most common genetic cause of autosomal dominantly inherited Parkinson's disease (PD). Recently, a novel pathogenic variant (N1437D; c.4309A > G; NM_98578) in the LRRK2 gene has been identified in three Chinese families with PD. In this study, we describe a Chinese family with autosomal dominant PD that segregated with the N1437D mutation. A detailed clinical and neuroimaging characterization of the affected family members is reported. We also sought to investigate the functional mechanisms by which the detected mutation could cause PD. METHODS: We characterized the clinical and imaging phenotype of a Chinese pedigree with autosomal dominant PD. We searched for a disease-causing mutation by targeted sequencing and multiple ligation-dependent probe amplification. The functional impact of the mutation was investigated in terms of LRRK2 kinase activity, guanosine triphosphate (GTP) binding, and guanosine triphosphatase (GTPase) activity. RESULTS: The disease was found to co-segregate with the LRRK2 N1437D mutation. Patients in the pedigree exhibited typical parkinsonism (age at onset: 54.0 ± 5.9 years). One affected family member - who had evidence of abnormal tau accumulation in the occipital lobe on tau PET imaging - developed PD dementia at follow-up. The mutation markedly increased LRRK2 kinase activity and promoted GTP binding, without affecting GTPase activity. CONCLUSIONS: This study describes the functional impact of a recently identified LRRK2 mutation, N1437D, that causes autosomal dominant PD in the Chinese population. Further research is necessary to investigate the contribution of this mutation to PD in multiple Asian populations.

Adjustment for the Age- and Gender-Related Metabolic Changes Improves the Differential Diagnosis of Parkinsonism.

Age and gender are the important factors for brain metabolic declines in both normal aging and neurodegeneration, and the confounding effects may influence early and differential diagnosis of neurodegenerative diseases based on the [18F]fluorodeoxyglucose positron emission tomography ([18F]FDG PET). We aimed to explore the potential of the adjustment of age- and gender-related confounding factors on [18F]FDG PET images in differentiation of Parkinson's disease (PD), multiple system atrophy (MSA) and progressive supra-nuclear palsy (PSP). Eight hundred and seventy-seven clinically definitely diagnosed Parkinsonian patients from a benchmark Huashan Parkinsonian PET imaging database were included. An age- and gender-adjusted Z (AGAZ) score was established based on the gender-specific longitudinal metabolic changes on healthy subjects. AGAZ scores and standardized uptake value ratio (SUVR) values were quantified at regional-level and support vector machine-based error-correcting output codes method was applied for classification. Additional references of the classifications based on metabolic pattern scores were included. The feature-based AGAZ score showed the best performance in classification (accuracy for PD, MSA, PSP: 93.1%, 96.3%, 94.8%). In both genders, the AGAZ score consistently achieved the best efficiency, and the improvements compared to the conventional SUVR value for PD, MSA, and PSP mainly laid in specificity (Male: 5.7%; Female: 11.1%), sensitivity (Male: 7.2%; Female: 7.3%), and sensitivity (Male: 7.3%; Female: 17.2%). Female patients benefited more from the adjustment on [18F]FDG PET in MSA and PSP groups (absolute net reclassification index, p < 0.001). Collectively, the adjustment of age- and gender-related confounding factors may improve the differential diagnosis of Parkinsonism. Particularly, the diagnosis of female Parkinsonian population has the best improvement from this correction. Supplementary Information: The online version contains supplementary material available at 10.1007/s43657-022-00079-6.

Dopaminergic Dysfunction and Glucose Metabolism Characteristics in Parkin-Induced Early-Onset Parkinson's Disease Compared to Genetically Undetermined Early-Onset Parkinson's Disease.

While early-onset Parkinson's disease (EOPD) caused by mutations in the parkin gene (PRKN) tends to have a relatively benign course compared to genetically undetermined (GU)-EOPD, the exact underlying mechanisms remain elusive. We aimed to search for the differences between PRKN-EOPD and GU-EOPD by dopamine transporter (DAT) and glucose metabolism positron-emission-tomography (PET) imaging. Twelve patients with PRKN-EOPD and 16 with GU-EOPD who accepted both 11C-2b-carbomethoxy-3b-(4-trimethylstannylphenyl) tropane (11C-CFT) and 18F-fluorodeoxyglucose PET were enrolled. The 11C-CFT uptake was analyzed on both regional and voxel levels, whereas glucose metabolism was assessed in a voxel-wise fashion. Correlations between DAT and glucose metabolism imaging, DAT imaging and clinical severity, as well as glucose metabolism imaging and clinical severity were explored. Both clinical symptoms and DAT-binding patterns in the posterior putamen were highly symmetrical in patients with PRKN-EOPD, and dopaminergic dysfunction in the ipsilateral putamen was severer in patients with PRKN-EOPD than GU-EOPD. Meanwhile, the DAT binding was associated with the severity of motor dysfunction in  patients with GU-EOPD only. Patients with PRKN-EOPD showed increased glucose metabolism in the contralateral medial frontal gyrus (supplementary motor area (SMA)), contralateral substantia nigra, contralateral thalamus, and contralateral cerebellum. Notably, glucose metabolic activity in the contralateral medial frontal gyrus was inversely associated with regional DAT binding in the bilateral putamen. Patients with PRKN-EOPD showed enhanced metabolic connectivity within the bilateral putamen, ipsilateral paracentral and precentral lobules, and the ipsilateral SMA. Collectively, compared to GU-EOPD, PRKN-EOPD is characterized by symmetrical, more severe dopaminergic dysfunction and relative increased glucose metabolism. Meanwhile, SMA with elevated glucose metabolism and enhanced connectivity may act as compensatory mechanisms in PRKN-EOPD. Supplementary Information: The online version contains supplementary material available at 10.1007/s43657-022-00077-8.

Optimized Cingulate Island Sign in Discriminating Dementia With Lewy Bodies From Alzheimer Disease.

PURPOSE: This study aimed to optimize the analysis of cingulate island sign (CIS) to improve its diagnostic accuracy in discriminating dementia with Lewy bodies (DLB) from Alzheimer disease (AD). PATIENTS AND METHODS: Patients with DLB (n = 80), AD (n = 75), and normal controls (n = 22) with 18 F-FDG PET imaging were enrolled in this study. Sixty-two DLB patients also underwent dopaminergic PET scans. The optimized/conventional CIS ratios and metabolism in associated brain regions were evaluated by diagnostic accuracy among groups and correlation with cognitive/dopaminergic dysfunction. RESULTS: In discriminating DLB from AD, the optimized CIS ratio calculated by dorsal posterior cingulate cortex (PCC)/lateral occipital lobe metabolism achieved the highest specificity, sensitivity, and accuracy at 0.907, 0.750, and 0.825, respectively. The metabolism of dorsal-PCC positively correlated with cognitive impairment in DLB patients cross-sectionally and longitudinally ( P < 0.001, r = 0.601; P = 0.044, r = 0.645), and also correlated with dopaminergic impairment in the caudate ( P = 0.048, r = 0.315). CONCLUSIONS: Optimized CIS ratios of incorporated metabolic activity of dorsal-PCC and occipital subregions are clinically useful for differentiating DLB from AD, in which dorsal-PCC metabolism may provide an objective biomarker to reflect the severity of cognitive impairment in DLB.

18 F-Florzolotau Positron Emission Tomography Imaging of Tau Pathology in the Living Brains of Patients with Corticobasal Syndrome.

BACKGROUND: Recent development in tau-sensitive tracers has sparkled significant interest in tracking tauopathies using positron emission tomography (PET) biomarkers. However, the ability of 18 F-florzolotau PET imaging to topographically characterize tau pathology in corticobasal syndrome (CBS) remains unclear. Further, the question as to whether disease-level differences exist with other neurodegenerative tauopathies is still unanswered. OBJECTIVE: To analyze the topographical patterns of tau pathology in the living brains of patients with CBS using 18 F-florzolotau PET imaging and to examine whether differences with other tauopathies exist. METHODS: 18 F-florzolotau PET imaging was performed in 20 consecutive patients with CBS, 20 cognitively healthy controls (HCs), 20 patients with Alzheimer's disease (AD), and 16 patients with progressive supranuclear palsy-Richardson's syndrome (PSP-RS). Cerebrospinal fluid (CSF) levels of ß-amyloid biomarkers were quantified in all patients with CBS. 18 F-florzolotau uptake was quantitatively assessed using standardized uptake value ratios. RESULTS: Of the 20 patients with CBS, 19 (95%) were negative for CSF biomarkers of amyloid pathology; of them, three had negative 18 F-florzolotau PET findings. Compared with HCs, patients with CBS showed increased 18 F-florzolotau signals in both cortical and subcortical regions. In addition, patients with CBS were characterized by higher tracer retentions in subcortical regions compared with those with AD and showed a trend toward higher signals in cortical areas compared with PSP-RS. An asymmetric pattern of 18 F-florzolotau uptake was associated with an asymmetry of motor severity in patients with CBS. CONCLUSIONS: In vivo 18 F-florzolotau PET imaging holds promise for distinguishing CBS in the spectrum of neurodegenerative tauopathies. © 2023 International Parkinson and Movement Disorder Society.

PDQ-8: A Simplified and Effective Tool Measuring Life Quality in Progressive Supranuclear Palsy.

BACKGROUND: The self-reported quality of life (QoL) should be carefully listened to in progressive supranuclear palsy (PSP) from the patient-centered perspective. However, there was still a lack of short QoL measurement tool in atypical parkinsonism. OBJECTIVE: We aimed to test whether the short Parkinson's Disease Questionnaire-8 (PDQ-8) was effective in assessing QoL in PSP, comparing with Progressive Supranuclear Palsy Quality of Life Scale (PSP-QoL) and Parkinson's Disease Questionnaire-39 (PDQ-39). METHODS: 132 patients with clinical diagnosed PSP, including PSP-Richardson syndrome (RS) subtype (n = 71) and PSP-non-RS subtype (n = 61) were recruited for clinical evaluation including QoL assessment. The detailed QoL profiles and possibility of using PDQ-8 were systemically analyzed. The determinants to the QoL were then calculated by multivariate linear regression analysis. RESULTS: The PSP-QoL total score summary index (SI) was 22.8 (10.1, 41.1), while the PDQ-8 and PDQ-39 total SI score were 28.1 (12.5, 46.9) and 29.5 (15.4, 49.4). Mobility, activities of daily life, cognition and communication were the main affected QoL subdomains (median SI: 40.0, 31.3, 25.0 and 25.0 respectively). PSP-RS subtype showed more severe damage physically (p<0.001) and mentally (p = 0.002) compared to other subtypes. More importantly, the strong relevance of PDQ-8 and recommended PSP QoL tools were confirmed (p<0.001). In addition, disease severity, depression and daytime sleepiness were proved to be critical determinants for QoL in PSP. CONCLUSIONS: PDQ-8 could be an easy, reliable, and valid tool to evaluate QoL in patients with PSP. Besides motor symptoms, more attention should be paid to non-motor impairment such as depression in PSP.