Dataset Information

Difference in F-18 FDG Uptake After Esophagogastroduodenoscopy and Colonoscopy in Healthy Sedated Subjects.

ABSTRACT:

Purpose

We aimed to evaluate the difference in fluorodeoxyglucose (FDG) uptake in sedated healthy subjects after they underwent esophagogastroduodenoscopy (EGD) and colonoscopy procedures.

Methods

The endoscopy group (n?=?29) included healthy subjects who underwent screening via F-18 FDG positron emission tomography/computed tomography (PET/CT) after an EGD and/or colonoscopy under sedation on the same day. The control group (n?=?35) included healthy subjects who underwent screening via PET/CT only. FDG uptake in the tongue, uvula, epiglottis, vocal cords, esophagus, stomach, duodenum, liver, cecum, colon, anus, and muscle were compared between the two groups.

Results

Maximum standardized uptake value (SUVmax) in the tongue, pharynx, larynx, and esophagus did not significantly differ between the endoscopy and control groups. In contrast, mean SUVmax in the whole stomach was 18 % higher in the endoscopy group than in the control group (SUVmax: 2.96 vs. 2.51, P?=?0.010). In the lower gastrointestinal track, SUVmax from the cecum to the rectum was not significantly different between the two groups, whereas SUVmax in the anus was 20 % higher in the endoscopy group than in the control group (SUVmax: 4.21 vs. 3.50, P?=?0.002). SUVmax in the liver and muscle was not significantly different between the two groups. Mean volume of the stomach and mean cross section of the colon was significantly higher in the endoscopy group than in the control group (stomach: 313.28 cm³ vs. 209.93 cm³, P?2 vs. 5.98 cm², P?=?0.001).

Conclusions

EGD and colonoscopy under sedation does not lead to significant differences in SUVmax in most parts of the body. Only gastric FDG uptake in the EGD subjects and anal FDG uptake in the colonoscopy subjects was higher than uptake in those regions in the control subjects.

SUBMITTER: Oh JR

PROVIDER: S-EPMC5567618 | biostudies-literature | 2017 Sep

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Difference in F-18 FDG Uptake After Esophagogastroduodenoscopy and Colonoscopy in Healthy Sedated Subjects.

Oh Jong-Ryool JR Seo Ji-Hyoung JH Chang Woo-Jin WJ Bae Seung-Il SI Song In-Wook IW Bong Jin-Gu JG Jeong Hye-Yeon HY Park So-Young SY Bae Jeongyup J Yoon Hyundae H

Nuclear medicine and molecular imaging 20161121 3

<h4>Purpose</h4>We aimed to evaluate the difference in fluorodeoxyglucose (FDG) uptake in sedated healthy subjects after they underwent esophagogastroduodenoscopy (EGD) and colonoscopy procedures.<h4>Methods</h4>The endoscopy group (<i>n</i> = 29) included healthy subjects who underwent screening via F-18 FDG positron emission tomography/computed tomography (PET/CT) after an EGD and/or colonoscopy under sedation on the same day. The control group (<i>n</i> = 35) included healthy subjects who und ...[more]

PMID: 28878850

Similar Datasets

Project description:ObjectiveThis Phase 2 study assessed the performance of positron emission tomography (PET) brain images made with Flutemetamol F 18 Injection in detecting β-amyloid neuritic plaques in Japanese subjects.MethodsSeventy subjects (25 with probable Alzheimer's disease (pAD), 20 with amnestic mild cognitive impairment (aMCI), and 25 cognitively normal healthy volunteers[HVs]) underwent PET brain imaging after intravenous Flutemetamol F 18 Injection (185 MBq). Images were interpreted as normal or abnormal for neuritic plaque density by each of five non-Japanese and five Japanese readers who were blinded to clinical data. The primary efficacy analysis (based on HV and pAD data) was the agreement of the non-Japanese readers' image interpretations with the clinical diagnosis, resulting in estimates of positive percent agreement (PPA; based on AD subjects; similar to sensitivity) and negative percent agreement (NPA; based on HVs; similar to specificity). Secondary analyses included PPA and NPA for the Japanese readers; inter-reader agreement (IRA); intra-reader reproducibility (IRR); quantitative image interpretations (standardized uptake value ratios [SUVRs]) by diagnostic subgroup; test-retest variability in five pAD subjects; and safety.ResultsPPA was 92% for all non-Japanese readers and ranged from 88 to 92% for the Japanese readers. NPA ranged from 96 to 100% for both the non-Japanese readers and the Japanese readers. The majority image interpretations (the interpretations made independently by ≥3 of 5 readers) resulted in PPA values of 92 and 92% and NPA values of 100 and 96% for the non-Japanese and Japanese readers, respectively. IRA and IRR were strong. Composite SUVR values (mean of multiple regional values) allowed clear differentiation between pAD subjects and HVs. Test-retest variability ranged from 1.14 to 2.27%, and test-retest agreement of the blinded visual interpretations was 100% for all readers. Flutemetamol F 18 Injection was generally well tolerated.ConclusionsThe detection of brain neuritic plaques in Japanese subjects using [18F]Flutemetamol PET images gave results highly consistent with clinical diagnosis, with non-Japanese and Japanese readers giving similar results. Inter-reader agreement and intra-reader reproducibility were high for both sets of readers. Visual delineation of abnormal and normal scans was corroborated by quantitative assessment, with low test-retest variability.Trial registrationClinicaltrials.gov registration number NCT02813070.

Project description:BackgroundThere is evidence that metabolic disease burden in lymphoma influences patient outcome. However, the impact of disease severity on the cardiovascular system is unknown.ObjectivesThe aim of this study was to examine whether lymphoma is associated with arterial inflammation by investigating the relationship between disease metabolic burden and arterial fluorodeoxyglucose (FDG) uptake.MethodsSixty-two chemotherapy-naïve patients with active Hodgkin's or non-Hodgkin's lymphoma were matched (2:1) to individual control groups of lymphoma patients previously treated and free of active disease. All groups underwent 18F-FDG position emission tomography-computed tomography imaging. Disease severity was quantified by metabolic tumor volume (MTV) and total lesion glycolysis corresponding to standardized uptake values (SUVs) ≥41% or ≥2.5 of the maximum SUV within lymphoma regions, and aortic FDG uptake was quantified through the target-to-background ratio (TBR). Inflammatory and disease severity biomarkers were also measured.ResultsMTV and total lesion glycolysis measurements were significantly correlated with inflammatory and disease biomarkers. Aortic TBR was higher in patients with active non-Hodgkin's lymphoma compared with control subjects (median difference 0.51; 95% confidence interval [CI]: 0.28 to 0.78; p < 0.001). Similarly, patients with active Hodgkin's lymphoma had higher values of aortic TBR compared with control subjects (median difference 0.31; 95% CI: 0.15 to 0.49; p < 0.001). In addition, aortic TBR was modestly increased in patients with stage III to IV disease compared with those with stage I to II disease (median aortic TBR: 2.23 [interquartile range: 2.01 to 2.54] vs. 2.06 [interquartile range: 1.83 to 2.27; p = 0.050). In multivariable analysis, aortic FDG uptake and MTV≥2.5 values were independently associated (β = 0.425; 95% CI: 0.189 to 0.662; p = 0.001; R2 = 0.208), as were aortic FDG uptake and MTV≥41% (β = 0.407; 95% CI: 0.167 to 0.649, p = 0.001; R2 = 0.191).ConclusionsAortic wall FDG uptake is related with disease severity indicative of a possible vascular effect of lymphoma. This work highlights a new potential role of molecular imaging in cardio-oncology for evaluating disease severity and its consequences on the vasculature.

Project description:Purpose: Building a universal genomic signature predicting the intensity of FDG uptake in diverse metastatic tumors may allow us to understand better the biological processes underlying this phenomenon and their requirements of glucose uptake. Methods: A balanced training set (n=71) of metastatic tumors including some of the most frequent histologies, with matched PET/CT quantification measurements and whole human genome gene expression microarrays, was used to build the signature. Selection of microarray features was carried out exclusively on the basis of their strong association with FDG uptake (as measured by SUVmean35) by means of univariate linear regression. A thorough bioinformatics study of these genes was performed and multivariable models were built by fitting several state of the art regression techniques to the training set for comparison. Results: The 909 probes with the strongest association with the SUVmean35 (comprising 742 identifiable genes and 62 probes not matched to a symbol) were used to build the signature. Partial Least Squares using 3 components (PLS-3) was the best performing model in the training dataset cross-validation (Root Mean Square Error, RMSE=0.443) and was validated further in an independent validation dataset (n=13) obtaining a performance within the 95% CI of that obtained in the training dataset (RMSE=0.645). Significantly overrepresented biological processes correlating with the SUVmean35 were identified beyond glycolysis, such as ribosome biogenesis and DNA replication (correlating with a higher SUVmean35), and cytoskeleton reorganization and autophagy (correlating with a lower SUVmean35), among others. Conclusions: PLS-3 is a signature predicting accurately the intensity of FDG uptake in diverse metastatic tumors. FDG-PET might help in the design of specific targeted therapies directed to counteract the identified malignant biological processes more likely activated in a tumor as inferred from the SUVmean35 and also from its variations in response to antineoplastic treatments.

Dataset Information

Difference in F-18 FDG Uptake After Esophagogastroduodenoscopy and Colonoscopy in Healthy Sedated Subjects.

Purpose

Methods

Results

Conclusions

Publications

Difference in F-18 FDG Uptake After Esophagogastroduodenoscopy and Colonoscopy in Healthy Sedated Subjects.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets