Dataset Information

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

ABSTRACT:

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.

SUBMITTER: Goehringer F

PROVIDER: S-EPMC9628394 | biostudies-literature | 2022 Nov

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

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

Goehringer François F Bruyere Alexandra A Doyen Matthieu M Bevilacqua Sibylle S Charmillon Alexandre A Heyer Sebastien S Verger Antoine A

European journal of nuclear medicine and molecular imaging 20221102 4

<h4>Background</h4>Brain <sup>18</sup>F-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 <sup>18</sup>F-FDG PET findings in a homogeneous series of outpatients with post-COVID-19 conditions and to identify associations with clinical patient characteristics.<h4>Methods</h4>We retrospectively included 28 c ...[more]

PMID: 36322190

Similar Datasets

Project description:Knowledge of the within-subject variability of 18F-FDG PET/MRI measurements is necessary for proper interpretation of quantitative PET or MRI metrics in the context of therapeutic efficacy assessments with integrated PET/MRI scanners. The goal of this study was to determine the test-retest repeatability of these metrics on PET/MRI, with comparison to similar metrics acquired by PET/CT. Methods: This prospective study enrolled subjects with pathology-proven pelvic malignancies. Baseline imaging consisted of PET/CT immediately followed by PET/MRI, using a single 370-MBq 18F-FDG dose. Repeat imaging was performed within 7 d using an identical imaging protocol, with no oncologic therapy between sessions. PET imaging on both scanners consisted of a list-mode acquisition at a single pelvic station. The MRI consisted of 2-point Dixon imaging for attenuation correction, standard sequences for anatomic correlation, and diffusion-weighted imaging. PET data were statically reconstructed using various frame durations and minimizing uptake time differences between sessions. SUV metrics were extracted for both PET/CT and PET/MRI in each imaging session. Apparent diffusion coefficient (ADC) metrics were extracted for both PET/MRI sessions. Results: The study cohort consisted of 14 subjects (13 female, 1 male) with various pelvic cancers (11 cervical, 2 rectal, 1 endometrial). For SUVmax, the within-subject coefficient of variation (wCV) appeared higher for PET/CT (8.5%-12.8%) than PET/MRI (6.6%-8.7%) across all PET reconstructions, though with no significant repeatability differences (all P values ≥ 0.08) between modalities. For lean body mass-adjusted SUVpeak, the wCVs appeared similar for PET/CT (9.9%-11.5%) and PET/MRI (9.2%-11.3%) across all PET reconstructions, again with no significant repeatability differences (all P values ≥ 0.14) between modalities. For PET/MRI, the wCV for ADCmedian of 3.5% appeared lower than the wCVs for SUVmax (6.6%-8.7%) and SULpeak (9.2%-11.3%), though without significant repeatability differences (all P values ≥ 0.23). Conclusion: For solid tumors of the pelvis, the repeatability of the evaluated SUV and ADC metrics on 18F-FDG PET/MRI is both acceptably high and similar to previously published values for 18F-FDG PET/CT and MRI, supporting the use of 18F-FDG PET/MRI for quantitative oncologic treatment response assessments.

Project description:PurposeA general glucose metabolism pattern is observed in patients with anti-leucine-rich glioma-inactivated 1 (LGI1) antibody encephalitis; however, it is unclear whether further subregional metabolic differences exist. Therefore, the present study aimed to conduct an in-depth exploration of the features of glucose metabolism within specific brain areas using 18F-fluorodeoxyglucose positron emission tomography (18F-FDG PET).Materials and methodsThis retrospective study enrolled thirteen patients confirmed with LGI1 antibody encephalitis who were admitted to Beijing Tiantan Hospital from June 2021 to September 2022. All patients underwent 18F-FDG PET before initiating clinical treatment. Changes in glucose metabolism in specific brain areas were analyzed using Cortex ID software. The laterality of 18F-FDG uptake was assessed, and differences in specific brain areas were compared using paired t-tests.ResultsSignificant metabolic changes in at least one brain region in 11 out of 13 patients (84.6%) were revealed by semi-quantitative analysis (z-score > 2). A bilateral decrease in the 18F-FDG metabolic pattern was revealed in almost all brain regions of interest; in contrast, a hypermetabolic pattern was observed in the medial temporal region, with mean z-scores of 1.75 ± 3.27 and 2.36 ± 5.90 on the left and right sides, respectively (p = 0.497). In the prefrontal and temporal lobes, 18F-FDG metabolism was significantly lower in the lateral region than in the medial region on both sides. For the cingulate cortex, significant hypometabolism was also observed in the posterior part compared to the anterior counterpart on both the left (z-score: -1.20 ± 1.93 vs. -0.42 ± 1.18, respectively; p = 0.047) and right (z-score: -1.56 ± 1.96 vs. -0.33 ± 1.63, respectively; p = 0.001) sides. However, a significant difference in regional metabolism was observed only on the left side (p = 0.041).ConclusionAn asymmetric 18F-FDG metabolic pattern exists in patients with anti-LGI1 encephalitis. Meanwhile, varied regional metabolic differences were revealed bilaterally in specific cerebral areas, which could be associated with the clinical manifestations.

Project description:Knowledge of the intrinsic variability of radiomic features is essential to the proper interpretation of changes in these features over time. The primary aim of this study was to assess the test-retest repeatability of radiomic features extracted from 18F-FDG PET images of cervical tumors. The impact of different image preprocessing methods was also explored. Methods: Patients with cervical cancer underwent baseline and repeat 18F-FDG PET/CT imaging within 7 d. PET images were reconstructed using 2 methods: ordered-subset expectation maximization (PETOSEM) or ordered-subset expectation maximization with point-spread function (PETPSF). Tumors were segmented to produce whole-tumor volumes of interest (VOIWT) and 40% isocontours (VOI40). Voxels were either left at the default size or resampled to 3-mm isotropic voxels. SUV was discretized to a fixed number of bins (32, 64, or 128). Radiomic features were extracted from both VOIs, and repeatability was then assessed using the Lin concordance correlation coefficient (CCC). Results: Eleven patients were enrolled and completed the test-retest PET/CT imaging protocol. Shape, neighborhood gray-level difference matrix, and gray-level cooccurrence matrix features were repeatable, with a mean CCC value of 0.81. Radiomic features extracted from PETOSEM images showed significantly better repeatability than features extracted from PETPSF images (P < 0.001). Radiomic features extracted from VOI40 were more repeatable than features extracted from VOIWT (P < 0.001). For most features (78.4%), a change in bin number or voxel size resulted in less than a 10% change in feature value. All gray-level emphasis and gray-level run emphasis features showed poor repeatability (CCC values < 0.52) when extracted from VOIWT but were highly repeatable (mean CCC values > 0.96) when extracted from VOI40 Conclusion: Shape, gray-level cooccurrence matrix, and neighborhood gray-level difference matrix radiomic features were consistently repeatable, whereas gray-level run length matrix and gray-level zone length matrix features were highly variable. Radiomic features extracted from VOI40 were more repeatable than features extracted from VOIWT Changes in voxel size or SUV discretization parameters typically resulted in relatively small differences in feature value, though several features were highly sensitive to these changes.

Dataset Information

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

Background

Methods

Results

Conclusion

Publications

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

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets

Dataset Information

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

Background

Methods

Results

Conclusion

Publications

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

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets

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