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.

Dopaminergic damage pattern predicts phenoconversion time in isolated rapid eye movement sleep behavior disorder.

PURPOSE: The exact phenoconversion time from isolated rapid eye movement (REM) sleep behavior disorder (iRBD) to synucleinopathies remains unpredictable. This study investigated whole-brain dopaminergic damage pattern (DDP) with disease progression and predicted phenoconversion time in individual patients. METHODS: Age-matched 33 iRBD patients and 20 healthy controls with 11C-CFT-PET scans were enrolled. The patients were followed up 2-10 (6.7 ± 2.0) years. The phenoconversion year was defined as the base year, and every 2 years before conversion was defined as a stage. Support vector machine with leave-one-out cross-validation strategy was used to perform prediction. RESULTS: Dopaminergic degeneration of iRBD was found to occur about 6 years before conversion and then abnormal brain regions gradually expanded. Using DDP, area under curve (AUC) was 0.879 (90% sensitivity and 88.3% specificity) for predicting conversion in 0-2 years, 0.807 (72.7% sensitivity and 83.3% specificity) in 2-4 years, 0.940 (100% sensitivity and 84.6% specificity) in 4-6 years, and 0.879 (100% sensitivity and 80.7% specificity) over 6 years. In individual patients, predicted stages correlated with whole-brain dopaminergic levels (r = - 0.740, p < 0.001). CONCLUSION: Our findings suggest that DDP could accurately predict phenoconversion time of individual iRBD patients, which may help to screen patients for early intervention.

Metabolic Asymmetry Relates to Clinical Characteristics and Brain Network Abnormalities in Alzheimer's Disease.

BACKGROUND: Metabolic asymmetry has been observed in Alzheimer's disease (AD), but different studies have inconsistent viewpoints. OBJECTIVE: To analyze the asymmetry of cerebral glucose metabolism in AD and investigate its clinical significance and potential metabolic network abnormalities. METHODS: Standardized uptake value ratios (SUVRs) were obtained from 18F-FDG positron emission tomography (PET) images of all participants, and the asymmetry indices (AIs) were calculated according to the SUVRs. AD group was divided into left/right-dominant or bilateral symmetric hypometabolism (AD-L/AD-R or AD-BI) when more than half of the AIs of the 20 regions of interest (ROIs) were < -2SD, >2SD, or between±1SD. Differences in clinical features among the three AD groups were compared, and the abnormal network characteristics underlying metabolic asymmetry were explored. RESULTS: In AD group, the proportions of AD-L, AD-R, and AD-BI were 28.4%, 17.9%, and 18.5%, respectively. AD-L/AD-R groups had younger age of onset and faster rate of cognitive decline than AD-BI group (p < 0.05). The absolute values of AIs in half of the 20 ROIs became higher at follow-up than at baseline (p < 0.05). Compared with those in AD-BI group, metabolic connection strength of network, global efficiency, cluster coefficient, degree centrality and local efficiency were lower, but shortest path length was longer in AD-L and AD-R groups (p < 0.05). CONCLUSION: Asymmetric and symmetric hypometabolism may represent different clinical subtypes of AD, which may provide a clue for future studies on the heterogeneity of AD and help to optimize the design of clinical trials.

Feasibility of 18F-florzolotau quantification in patients with Alzheimer's disease based on an MRI-free tau PET template.

OBJECTIVES: Quantification of tau accumulation using positron emission tomography (PET) is critical for the diagnosis of Alzheimer's disease (AD). This study aimed to evaluate the feasibility of 18F-florzolotau quantification in patients with AD using a magnetic resonance imaging (MRI)-free tau PET template, since individual high-resolution MRI is costly and not always available in practice. METHODS: 18F-florzolotau PET and MRI scans were obtained in a discovery cohort including (1) patients within the AD continuum (n = 87), (2) cognitively impaired patients with non-AD (n = 32), and (3) cognitively unimpaired subjects (n = 26). The validation cohort comprised 24 patients with AD. Following MRI-dependent spatial normalization (standard approach) in randomly selected subjects (n = 40) to cover the entire spectrum of cognitive function, selected PET images were averaged to create the 18F-florzolotau-specific template. Standardized uptake value ratios (SUVRs) were calculated in five predefined regions of interest (ROIs). MRI-free and MRI-dependent methods were compared in terms of continuous and dichotomous agreement, diagnostic performances, and associations with specific cognitive domains. RESULTS: MRI-free SUVRs had a high continuous and dichotomous agreement with MRI-dependent measures for all ROIs (intraclass correlation coefficient ≥ 0.980; agreement ≥ 94.5%). Similar findings were observed for AD-related effect sizes, diagnostic performances with respect to categorization across the cognitive spectrum, and associations with cognitive domains. The robustness of the MRI-free approach was confirmed in the validation cohort. CONCLUSIONS: The use of an 18F-florzolotau-specific template is a valid alternative to MRI-dependent spatial normalization, improving the clinical generalizability of this second-generation tau tracer. KEY POINTS: • Regional 18F-florzolotau SUVRs reflecting tau accumulation in the living brains are reliable biomarkers for the diagnosis, differential diagnosis, and assessment of disease severity in patients with AD. • The 18F-florzolotau-specific template is a valid alternative to MRI-dependent spatial normalization, improving the clinical generalizability of this second-generation tau tracer.

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.

In Vivo Tau Burden Is Associated with Abnormal Brain Functional Connectivity in Alzheimer's Disease: A 18F-Florzolotau Study.

PURPOSE: 18F-Florzolotau is a novel second-generation tau radiotracer that shows higher binding affinity and selectivity and no off-target binding. The proportion loss of functional connectivity strength (PLFCS) is a new indicator for representing brain functional connectivity (FC) alteration. This study aims to estimate the relationship between the regional tau accumulation and brain FC abnormality in Alzheimer's disease (AD) and mild cognitive impairment (MCI) patients based on Florzolotau PET and fMRI. METHODS: 22 NC (normal control), 31 MCI and 42 AD patients who have already been scanned with 18F-Florzolotau PET were recruited in this study. (We calculated the PLFCS and standardized uptake value ratio (SUVR) of each node based on the Brainnetome atlas (BNA) template. The SUVR of 246 brain regions was calculated with the cerebellum as the reference region. Further functional connection strength (FCs), PLFCS and SUVR of each brain region were obtained in three groups for comparison.) For each patient, PLFCS and standardized uptake value ratio (SUVR) were calculated based on the Brainnetome atlas (BNA) template. These results, as well as functional connection strength (FCs), were then compared between different groups. Multiple permutation tests were used to determine the target nodes between NC and cognitive impairment (CI) groups (MCI and AD). The relationship between PLFCS and neuropsychological scores or cortical tau deposit was investigated via Pearson correlation analysis. RESULTS: Higher PLFCS and FCs in AD and MCI groups were found compared to the NC group. The PLFCS of 129 brain regions were found to be different between NC and CI groups, and 8 of them were correlated with tau SUVR, including superior parietal lobule (MCI: r = 0.4360, p = 0.0260, AD: r = -0.3663, p = 0.0280), middle frontal gyrus (AD: MFG_R_7_2: r = 0.4106, p = 0.0129; MFG_R_7_5: r = 0.4239, p = 0.0100), inferior frontal gyrus (AD: IFG_R_6_2: r = 0.3589, p = 0.0316), precentral gyrus (AD: PrG_R_6_6: r = 0.3493, p = 0.0368), insular gyrus (AD: INS_R_6_3: r = 0.3496, p = 0.0366) and lateral occipital cortex (AD: LOcC _L_4_3: r = -0.3433, p = 0.0404). Noteworthily, the opposing relationship was found in the superior parietal lobule in the MCI and AD groups. CONCLUSIONS: Brain functional connectivity abnormality is correlated with tau pathology in AD and MCI.

Consistent Abnormalities in Metabolic Patterns of Lewy Body Dementias.

BACKGROUND: Whether dementia with Lewy bodies (DLB) and Parkinson's disease (PD) dementia (PDD) represent the same disease, distinct entities, or conditions within the same spectrum remains controversial. OBJECTIVE: The objective of this study was to provide new insight into this debate by separately identifying disease-specific metabolic patterns and comparing them with each other and with previously established PD-related pattern (PDRP). METHODS: Patients with DLB (n = 67), patients with PDD (n = 50), and healthy control subjects (HCs; n = 15) with brain 18 F-fluorodeoxyglucose positron emission tomography were enrolled as cohorts A and B for pattern identification and validation, respectively. Patients with PD (n = 30) were included for discrimination. Twenty-one participants had two scans. The principal component analysis was applied for pattern identification (DLB-related pattern [DLBRP], PDD-related pattern [PDDRP]). Similarities and differences among three patterns were assessed by pattern topography, pattern expression, clinical correlations cross-sectionally, and pattern expression changes longitudinally. RESULTS: DLBRP and PDDRP shared highly similar topographies, with relative hypometabolism mainly in the middle temporal gyrus, middle occipital gyrus, lingual gyrus, precuneus, cuneus, angular gyrus, superior and inferior parietal gyrus, middle and inferior frontal gyrus, cingulate, and caudate, and relative hypermetabolism in the cerebellum, putamen, thalamus, precentral/postcentral gyrus, and paracentral lobule, which were more extensive than the PDRP. Patients with DLB and PDD could not be distinguished successfully by any pattern, but patients with PD were easily recognized, especially by DLBRP and PDDRP. The pattern expression of DLBRP and PDDRP showed similar efficacy in cross-sectional disease severity assessment and longitudinal progression monitoring. CONCLUSIONS: The consistent abnormalities in metabolic patterns of DLB and PDD might underline the potential continuum across the clinical spectrum from PD to DLB. © 2022 International Parkinson and Movement Disorder Society.

Decoding the dopamine transporter imaging for the differential diagnosis of parkinsonism using deep learning.

PURPOSE: This work attempts to decode the discriminative information in dopamine transporter (DAT) imaging using deep learning for the differential diagnosis of parkinsonism. METHODS: This study involved 1017 subjects who underwent DAT PET imaging ([11C]CFT) including 43 healthy subjects and 974 parkinsonian patients with idiopathic Parkinson's disease (IPD), multiple system atrophy (MSA) or progressive supranuclear palsy (PSP). We developed a 3D deep convolutional neural network to learn distinguishable DAT features for the differential diagnosis of parkinsonism. A full-gradient saliency map approach was employed to investigate the functional basis related to the decision mechanism of the network. Furthermore, deep-learning-guided radiomics features and quantitative analysis were compared with their conventional counterparts to further interpret the performance of deep learning. RESULTS: The proposed network achieved area under the curve of 0.953 (sensitivity 87.7%, specificity 93.2%), 0.948 (sensitivity 93.7%, specificity 97.5%), and 0.900 (sensitivity 81.5%, specificity 93.7%) in the cross-validation, together with sensitivity of 90.7%, 84.1%, 78.6% and specificity of 88.4%, 97.5% 93.3% in the blind test for the differential diagnosis of IPD, MSA and PSP, respectively. The saliency map demonstrated the most contributed areas determining the diagnosis located at parkinsonism-related regions, e.g., putamen, caudate and midbrain. The deep-learning-guided binding ratios showed significant differences among IPD, MSA and PSP groups (P < 0.001), while the conventional putamen and caudate binding ratios had no significant difference between IPD and MSA (P = 0.24 and P = 0.30). Furthermore, compared to conventional radiomics features, there existed average above 78.1% more deep-learning-guided radiomics features that had significant differences among IPD, MSA and PSP. CONCLUSION: This study suggested the developed deep neural network can decode in-depth information from DAT and showed potential to assist the differential diagnosis of parkinsonism. The functional regions supporting the diagnosis decision were generally consistent with known parkinsonian pathology but provided more specific guidance for feature selection and quantitative analysis.

Knockdown of Annexin A2 Enhances Radiosensitivity by Increasing G2/M-Phase Arrest, Apoptosis and Activating the p38 MAPK-HSP27 Pathway in Nasopharyngeal Carcinoma.

Annexin A2 (ANXA2) has been found to be involved in cancer proliferation, metastasis and prognosis; however, its exact role in nasopharyngeal carcinoma (NPC) radioresistance remains unknown. We found that ANXA2 expression was correlated with prognosis in NPC patients, and longer overall survival in NPC patients with low ANXA2 expression than those with high ANXA2 expression. ANXA2 knockdown increased the radiosensitivity in radioresistant NPC cells, and ANXA2 overexpression decreased the radiosensitivity in NPC cells. Knocking-down ANXA2 expression increased the irradiation-induced apoptosis of radioresistant NPC cells, and ANXA2 overexpression decreased the irradiation-induced apoptosis of NPC cells. ANXA2 knockdown induced G2/M phase arrest in NPC cells post-irradiation, and ANXA2 overexpression abrogated G2/M phase arrest in NPC cells post-irradiation. ANXA2 overexpression resulted in inhibition of the p38 MAPK-HSP27 pathway, while ANXA2 knockdown resulted in activation of the p38 MAPK-HSP27 pathway. In addition, ANXA2 knockdown increased the radiosensitivity of the xenografted tumors in nude mice. Our data demonstrate that knockdown of Annexin A2 enhanced radiosensitivity in NPC by increasing G2/M-phase arrest, apoptosis and activating the p38 MAPK-HSP27 pathway. ANXA2 may be a promising target used to overcome radioresistance in NPC.

In Vivo 18 F-APN-1607 Tau Positron Emission Tomography Imaging in MAPT Mutations: Cross-Sectional and Longitudinal Findings.

BACKGROUND: Frontotemporal lobar degeneration with tauopathy caused by MAPT (microtubule-associated protein tau) mutations is a highly heterogenous disorder. The ability to visualize and longitudinally monitor tau deposits may be beneficial to understand disease pathophysiology and predict clinical trajectories. OBJECTIVE: The aim of this study was to investigate the cross-sectional and longitudinal 18 F-APN-1607 positron emission tomography/computed tomography (PET/CT) imaging findings in MAPT mutation carriers. METHODS: Seven carriers of MAPT mutations (six within exon 10 and one outside of exon 10) and 15 healthy control subjects were included. All participants underwent 18 F-APN-1607 PET/CT at baseline. Three carriers of exon 10 mutations received follow-up 18 F-APN-1607 PET/CT scans. Standardized uptake value ratio (SUVR) maps were obtained using the cerebellar gray matter as the reference region. SUVR values observed in MAPT mutation carriers were normalized to data from healthy control subjects. A regional SUVR z score ≥ 2 was used as the criterion to define positive 18 F-APN-1607 PET/CT findings. RESULTS: Although the seven study patients had heterogenous clinical phenotypes, all showed a significant 18 F-APN-1607 uptake characterized by high-contrast signals. However, the anatomical localization of tau deposits differed in patients with distinct clinical symptoms. Follow-up imaging data, which were available for three patients, demonstrated worsening trends in patterns of tau accumulation over time, which were paralleled by a significant clinical deterioration. CONCLUSIONS: Our data represent a promising step in understanding the usefulness of 18 F-APN-1607 PET/CT imaging for detecting tau accumulation in MAPT mutation carriers. Our preliminary follow-up data also suggest the potential value of 18 F-APN-1607 PET/CT for monitoring the longitudinal trajectories of frontotemporal lobar degeneration caused by MAPT mutations. © 2021 International Parkinson and Movement Disorder Society.

SNHG8 Promotes the Progression of Epstein-Barr Virus-Associated Gastric Cancer via Sponging miR-512-5p and Targeting TRIM28.

SNHG8, a family member of small nucleolar RNA host genes (SNHG), has been reported to act as an oncogene in gastric carcinoma (GC). However, its biological function in Epstein-Barr virus (EBV)-associated gastric cancer (EBVaGC) remains unclear. This study investigated the role of SNHG8 in EBVaGC. Sixty-one cases of EBVaGC, 20 cases of non-EBV-infected gastric cancer (EBVnGC), and relative cell lines were studied for the expression of SNHG8 and BHRF1 (BCL2 homolog reading frame 1) encoded by EBV with Western blot and qRT-PCR assays. The relationship between the expression levels of SNHG8 and the clinical outcome in 61 EBVaGC cases was analyzed. Effects of overexpression or knockdown of BHRF1, SNHG8, or TRIM28 on cell proliferation, migration, invasion, and cell cycle and the related molecules were determined by several assays, including cell proliferation, colony assay, wound healing assay, transwell invasion assay, cell circle with flow cytometry, qRT-PCR, and Western blot for expression levels. The interactions among SNHG8, miR-512-5p, and TRIM28 were determined with Luciferase reporter assay, RNA immunoprecipitation (RIP), pull-down assays, and Western blot assay. The in vivo activity of SNHG8 was assessed with SNHG8 knockdown tumor xenografts in zebrafish. Results demonstrated that the following. (1) BHRF1 and SNHG8 were overexpressed in EBV-encoded RNA 1-positive EBVaGC tissues and cell lines. BHRF1 upregulated the expressions of SNHG8 and TRIM28 in AGS. (2) SNHG8 overexpression had a significant correlation with tumor size and vascular tumor thrombus. Patients with high SNHG8 expression had poorer overall survival (OS) compared to those with low SNHG8 expression. (3) SNHG8 overexpression promoted EBVaGC cell proliferation, migration, and invasion in vitro and in vivo, cell cycle arrested at the G2/M phase via the activation of BCL-2, CCND1, PCNA, PARP1, CDH1, CDH2 VIM, and Snail. (4) Results of dual-luciferase reporter assay, RNA immunoprecipitation, and pull-down assays indicated that SNHG8 sponged miR-512-5p, which targeted on TRIM28 and promoted cancer malignant behaviors of EBVaGC cells. Our data suggest that BHRF1 triggered the expression of SNHG8, which sponged miR-512-5p and upregulated TRIM28 and a set of effectors (such as BCL-2, CCND1, CDH1, CDH2 Snail, and VIM) to promote EBVaGC tumorigenesis and invasion. SNHG8 could be an independent prognostic factor for EBVaGC and sever as target for EBVaGC therapy.