Effects of medication on dopamine transporter imaging using [123I]I-FP-CIT SPECT in routine practice.

PURPOSE: Dopamine transporter (DAT) imaging is used to support the diagnosis of neurodegenerative parkinsonian disorders. Specific medications have been reported to confound the interpretation of [123I]I-FP-CIT SPECT scans, but there is limited data. The aim of the current study is to identify potential medication effects on the interpretation of [123I]I-FP-CIT SPECT scans in routine practice. MATERIALS AND METHODS: Consecutive patients undergoing a [123I]I-FP-CIT SPECT/CT scan on a 360° CZT camera between September 2019 and December 2022 were included. An exhaustive review of patient medications (antidepressants, antipsychotics, anti-epileptics, anti-parkinsonians, benzodiazepines, lithium, opioids, and stimulants) was performed. Two experienced nuclear physicians, blinded to the medication reports, interpreted the [123I]I-FP-CIT SPECT scans visually and a semi-quantitative analysis was performed using a local normal database. RESULTS: The study included 305 patients (71.0 ± 10.4, 135 women) and 145 (47.5%) visually interpreted normal scans. In normal scans, the striatum/occiput radioligand uptake ratio was decreased by noradrenergic and specific serotonergic antidepressants (NASSAs) (n = 15, z-score of - 0.93) and opioid medication (tramadol, n = 6, z-score of - 0.85) and was associated with a younger age in the multivariate analysis. In the overall population, the striatum/occiput ratio was influenced by NASSAs and associated with consensual visual analysis, age, sex, and anti-parkinsonian medications related to the status of the disease. CONCLUSION: Our study confirms the potential impact of antidepressant (NASSA) and opioid (tramadol) medications on the semi-quantitative analysis of [123I]I-FP-CIT SPECT scans. However, when performing a visual analysis, only NASSAs significantly impacted the interpretation of [123I]I-FP-CIT SPECT scans.

Metabolic brain connectivity reorganization in Alzheimer's disease patients: a systematic review.

INTRODUCTION: Metabolic connectivity has been studied in various neurodegenerative diseases, particularly Alzheimer's disease (AD), but there is a wealth of accumulated evidence and sometimes conflicting results, depending on the methodology applied. Therefore, the aim of this systematic review was to summarize the results obtained regarding metabolic brain connectivity using [18F]-FDG-PET in AD patients compared to cognitively normal subjects. EVIDENCE ACQUISITION: A systematic and exhaustive search of data available in the literature was carried out by querying the PubMed and Web of Science databases. Studies had to meet the following criteria: 1) a metabolic connectivity study with [18F]-FDG-PET in AD patients; 2) the inclusion of a control group of healthy subjects or cognitively normal controls; and 3) use of seed-based, independent/principal component analyses or methods derived from graph theory. This systematic review followed the PRISMA method. EVIDENCE SYNTHESIS: A total of 49 full-text publications were included, involving 3589 AD patients, 3272 prodromal AD patients and 3898 cognitively normal subjects. These results show that AD patients have a reorganization of metabolic connectivity on a global scale, with a decrease in or even the loss of networks seen in the healthy brain and an increase in more local, less efficient connectivity. This reorganization affects not only areas commonly affected in AD but also remote regions known to be usually spared in this pathology. CONCLUSIONS: Changes in metabolic connectivity in AD patients do not simply constitute a decrease in global connectivity but rather more complex local and global changes ultimately affecting all brain regions.

Brain 18F-FDG PET imaging in outpatients with post-COVID-19 conditions: findings and associations with clinical characteristics.

BACKGROUND: Brain 18F-FDG PET imaging has the potential to provide an objective assessment of brain involvement in post-COVID-19 conditions but previous studies of heterogeneous patient series yield inconsistent results. The current study aimed to investigate brain 18F-FDG PET findings in a homogeneous series of outpatients with post-COVID-19 conditions and to identify associations with clinical patient characteristics. METHODS: We retrospectively included 28 consecutive outpatients who presented with post-COVID-19 conditions between September 2020 and May 2022 and who satisfied the WHO definition, and had a brain 18F-FDG PET for suspected brain involvement but had not been hospitalized for COVID-19. A voxel-based group comparison with 28 age- and sex-matched healthy controls was performed (p-voxel at 0.005 uncorrected, p-cluster at 0.05 FWE corrected) and identified clusters were correlated with clinical characteristics. RESULTS: Outpatients with post-COVID-19 conditions exhibited diffuse hypometabolism predominantly involving right frontal and temporal lobes including the orbito-frontal cortex and internal temporal areas. Metabolism in these clusters was inversely correlated with the number of symptoms during the initial infection (r = - 0.44, p = 0.02) and with the duration of symptoms (r = - 0.39, p = 0.04). Asthenia and cardiovascular, digestive, and neurological disorders during the acute phase and asthenia and language disorders during the chronic phase (p ≤ 0.04) were associated with these hypometabolic clusters. CONCLUSION: Outpatients with post-COVID-19 conditions exhibited extensive hypometabolic right fronto-temporal clusters. Patients with more numerous symptoms during the initial phase and with a longer duration of symptoms were at higher risk of persistent brain involvement.

18F-FDG PET can effectively rule out conversion to dementia and the presence of CSF biomarker of neurodegeneration: a real-world data analysis.

BACKGROUND: Precisely defining the delay in onset of dementia is a particular challenge for early diagnosis. Brain [18F] fluoro-2-deoxy-2-D-glucose (18F-FDG) Positron Emission Tomography (PET) is a particularly interesting tool for the early diagnosis of neurodegenerative diseases, through the measurement of the cerebral glucose metabolic rate. There is currently a lack of longitudinal studies under real-life conditions, with sufficient patients, to accurately evaluate the predictive values of brain 18F-FDG PET scans. Here, we aimed to estimate the value of brain 18F-FDG PET for predicting the risk of dementia conversion and the risk of occurrence of a neurodegenerative pathology. METHODS: Longitudinal data for a cohort of patients with no diagnosis of dementia at the time of recruitment referred by a tertiary memory clinic for brain 18F-FDG PET were matched with (Prince M, Wimo A, Guerchet Maëlenn, Ali G-C, Wu Y-T et al. World Alzheimer Report 2015. The Global Impact of Dementia: An analysis of prevalence, incidence, cost and trends. [Research Report] Alzheimer's Disease International. 2015. 2015.) data from the French National Health Data System (NHDS), (Jack CR, Bennett DA, Blennow K, Carrillo MC, Dunn B, Haeberlein SB, et al. NIA-AA Research Framework: Toward a biological definition of Alzheimer's disease. Alzheimers Dement. 2018;14(4):535-62.) data from the National Alzheimer Bank (NAB), and (Davis M, O`Connell T, Johnson S, Cline S, Merikle E, Martenyi F, et al. Estimating Alzheimer's Disease Progression Rates from Normal Cognition Through Mild Cognitive Impairment and Stages of Dementia. CAR. 2018;15(8):777-88.) lumbar puncture (LP) biomarker data. The criteria for dementia conversion were the designation, within the three years after the brain 18F-FDG PET scan, of a long-term condition for dementia in the NHDS and a dementia stage of cognitive impairment in the NAB. The criterion for the identification of a neurodegenerative disease in the medical records was the determination of LP biomarker levels. RESULTS: Among the 403 patients (69.9 ± 11.4 years old, 177 women) from the initial cohort with data matched with the NHDS data, 137 were matched with the NAB data, and 61 were matched with LP biomarker data. Within three years of the scan, a 18F-FDG PET had negative predictive values of 85% for dementia conversion (according to the NHDS and NAB datasets) and 95% for the presence of LP neurodegeneration biomarkers. CONCLUSION: A normal brain 18F-FDG PET scan can help rule out the risk of dementia conversion and the presence of cerebrospinal fluid (CSF) biomarker of neurodegeneration early with high certainty, allowing modifications to patient management regimens in the short term. TRIAL REGISTRATION: Clinical Trials database (NCT04804722). March 18, 2021. Retrospectively registered.

Identification of resting-state networks using dynamic brain perfusion SPECT imaging: A fSPECT case report.

Connectivity studies with nuclear medicine systems are scarce in literature. They mainly employ PET imaging and group level analyses due to the low temporal resolution of PET and especially SPECT imaging. Our current study analyses connectivity at an individual level using dynamic SPECT imaging, which has been enabled by the improved temporal resolution performances provided by the 360°CZT cameras. We present the case of an 80-year-old man referred for brain perfusion SPECT imaging for cognitive disorders for whom a dynamic SPECT acquisition was performed utilizing a 360°CZT camera (temporal sampling of 15 frames × 3 s, 10 frames × 15 s, 14 frames × 30 s), followed by a conventional static acquisition of 15 m. Functional SPECT connectivity (fSPECT) was assessed through a seed correlation analysis and 5 well-known resting-state networks were identified: the executive, the default mode, the sensory motor, the salience, and the visual networks. This case report supports the feasibility of fSPECT imaging to identify well known resting-state networks, thanks to the novel properties of a 360°CZT camera, and opens the way to the development of more dedicated functional connectivity studies using brain perfusion SPECT imaging.

Metabolic connectivity is associated with seizure outcome in surgically treated temporal lobe epilepsies: A 18F-FDG PET seed correlation analysis.

18F-FDG PET provides high sensitivity for the pre-surgical assessment of drug-resistant temporal lobe epilepsy (TLE). However, little is known about the metabolic connectivity of epileptogenic networks involved. This study therefore aimed to evaluate the association between metabolic connectivity and seizure outcome in surgically treated TLE. METHODS: The study included 107 right-handed patients that had undergone a presurgical interictal 18F-FDG PET assessment followed by an anterior temporal lobectomy and were classified according to seizure outcome 2 years after surgery. Metabolic connectivity was evaluated by seed correlation analysis in left and right epilepsy patients with a Class Engel IA or > IA outcome and compared to age-, sex- and handedness-matched healthy controls. RESULTS: Increased metabolic connectivity was observed in the >IA compared to the IA group within the operated temporal lobe (respective clusters of 7.5 vs 3.3 cm3 and 2.6 cm3 vs 2.2 cm3 in left and right TLE), and to a lower extent with the contralateral temporal lobe (1.2 vs 0.7 cm3 and 1.7 cm3 vs 0.7 cm3 in left and right TLE). Seed correlations provided added value for the estimated individual performance of seizure outcome over the group comparisons in left TLE (AUC of 0.74 vs 0.67). CONCLUSION: Metabolic connectivity is associated with outcome in surgically treated TLE with a strengthened epileptogenic connectome in patients with non-free-seizure outcomes. The added value of seed correlation analysis in left TLE underlines the importance of evaluating metabolic connectivity in network related diseases.