Human Organotypic Lung Tumor Models: Suitable For Preclinical 18F-FDG PET-Imaging.
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ABSTRACT:
SUBMITTER: Fecher D
PROVIDER: S-EPMC4976941 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Early diagnosis of low grade glioma has been a challenge to clinicians. Positron Emission Tomography (PET) using 18F-FDG as a radio-tracer has limited utility in this area because of the high background in normal brain tissue. Other radiotracers such as 18F-Fluorocholine (18F-FCH) could provide better contrast between tumor and normal brain tissue but with high incidence of false positives. In this study, the potential application of a dual tracer 18F-FCH/18F-FDG-PET is investigated in order to improve the sensitivity of PET imaging for low grade glioma diagnosis based on a mouse orthotopic xenograft model. BALB/c nude mice with and without orthotopic glioma xenografts from U87 MG-luc2 glioma cell line are used for the study. The animals are subjected to 18F-FCH and 18F-FDG PET imaging, and images acquired from two separate scans are superimposed for analysis. The 18F-FCH counts are subtracted from the merged images to identify the tumor. Micro-CT, bioluminescence imaging (BLI), histology and measurement of the tumor diameter are also conducted for comparison. Results show that there is a significant contrast in 18F-FCH uptake between tumor and normal brain tissue (2.65 ± 0.98), but with a high false positive rate of 28.6%. The difficulty of identifying the tumor by 18F-FDG only is also proved in this study. All the tumors can be detected based on the dual tracer technique of 18F-FCH/18F-FDG-PET imaging in this study, while the false-positive caused by 18F-FCH can be eliminated. Dual tracer 18F-FCH/18F-FDG PET imaging has the potential to improve the visualization of low grade glioma. 18F-FCH delineates tumor areas and the tumor can be identified by subtracting the 18F-FCH counts. The sensitivity was over 95%. Further studies are required to evaluate the possibility of applying this technique in clinical trials.
| S-EPMC4741524 | biostudies-literature
Project description:Background: This study investigated the performance of ensemble learning holomic models for the detection of breast cancer, receptor status, proliferation rate, and molecular subtypes from [18F]FDG-PET/CT images with and without incorporating data pre-processing algorithms. Additionally, machine learning (ML) models were compared with conventional data analysis using standard uptake value lesion classification. Methods: A cohort of 170 patients with 173 breast cancer tumors (132 malignant, 38 benign) was examined with [18F]FDG-PET/CT. Breast tumors were segmented and radiomic features were extracted following the imaging biomarker standardization initiative (IBSI) guidelines combined with optimized feature extraction. Ensemble learning including five supervised ML algorithms was utilized in a 100-fold Monte Carlo (MC) cross-validation scheme. Data pre-processing methods were incorporated prior to machine learning, including outlier and borderline noisy sample detection, feature selection, and class imbalance correction. Feature importance in each model was assessed by calculating feature occurrence by the R-squared method across MC folds. Results: Cross validation demonstrated high performance of the cancer detection model (80% sensitivity, 78% specificity, 80% accuracy, 0.81 area under the curve (AUC)), and of the triple negative tumor identification model (85% sensitivity, 78% specificity, 82% accuracy, 0.82 AUC). The individual receptor status and luminal A/B subtype models yielded low performance (0.46-0.68 AUC). SUVmax model yielded 0.76 AUC in cancer detection and 0.70 AUC in predicting triple negative subtype. Conclusions: Predictive models based on [18F]FDG-PET/CT images in combination with advanced data pre-processing steps aid in breast cancer diagnosis and in ML-based prediction of the aggressive triple negative breast cancer subtype.
| S-EPMC8000810 | biostudies-literature
Project description:We evaluated the relationship between pre-treatment positron emission tomography (PET) using the hypoxic tracer 18F-[2-(2-nitro-1-H-imidazol-1-yl)-N-(2,2,3,3,3- pentafluoropropyl) acetamide] (18F-EF5) and the response of preclinical tumor models to a range of fractionated radiotherapies. Subcutaneous HT29, A549 and RKO tumors grown in nude mice were imaged using 18F-EF5 positron emission tomography (PET) in order to characterize the extent and heterogeneity of hypoxia in these systems. Based on these results, 80 A549 tumors were subsequently grown and imaged using 18F-EF5 PET, and then treated with one, two, or four fraction radiation treatments to a total dose of 10-40 Gy. Response was monitored by serial caliper measurements of tumor volume. Longitudinal post-treatment 18F-EF5 PET imaging was performed on a subset of tumors. Terminal histologic analysis was performed to validate 18F-EF5 PET measures of hypoxia. EF5-positive tumors responded more poorly to low dose single fraction irradiation relative to EF5-negative tumors, however both groups responded similarly to larger single fraction doses. Irradiated tumors exhibited reduced 18F-EF5 uptake one month after treatment compared to control tumors. These findings indicate that pre- treatment 18F-EF5 PET can predict the response of tumors to single fraction radiation treatment. However, increasing the number of fractions delivered abrogates the difference in response between tumors with high and low EF5 uptake pre-treatment, in agreement with traditional radiobiology.
| S-EPMC4592127 | biostudies-literature
Project description:Dynamic early-phase PET images acquired with radiotracers binding to fibrillar amyloid-beta (Aβ) have shown to correlate with [18F]fluorodeoxyglucose (FDG) PET images and provide perfusion-like information. Perfusion information of static PET scans acquired during the first minute after radiotracer injection (FMF, first-minute-frame) is compared to [18F]FDG PET images. FMFs of 60 patients acquired with [18F]florbetapir (FBP), [18F]flutemetamol (FMM), and [18F]florbetaben (FBB) are compared to [18F]FDG PET images. Regional standardized uptake value ratios (SUVR) are directly compared and intrapatient Pearson's correlation coefficients are calculated to evaluate the correlation of FMFs to their corresponding [18F]FDG PET images. Additionally, regional interpatient correlations are calculated. The intensity profiles of mean SUVRs among the study cohort (r = 0.98, p < 0.001) and intrapatient analyses show strong correlations between FMFs and [18F]FDG PET images (r = 0.93 ± 0.05). Regional VOI-based analyses also result in high correlation coefficients. The FMF shows similar information to the cerebral metabolic patterns obtained by [18F]FDG PET imaging. Therefore, it could be an alternative to the dynamic imaging of early phase amyloid PET and be used as an additional neurodegeneration biomarker in amyloid PET studies in routine clinical practice while being acquired at the same time as amyloid PET images.
| S-EPMC8348394 | biostudies-literature
Project description:UnlabelledThe natural phytoestrogen genistein is known as protein kinase inhibitor and tumor suppressor in various types of cancers. We studied its antitumor effect in two different xenograft models using positron emission tomography (PET) in vivo combined with ex vivo histology and nuclear magnetic resonance (NMR) metabolic fingerprinting.ProceduresA431 and Colo205 tumor-bearing mice were treated with vehicle or genistein (500 mg/kg/d) over a period of 12 days. Imaging was performed with 2-deoxy-2-[18F]fluoro-D-glucose ([18F]FDG) and 3'-deoxy-3'-[18F]fluorothymidine ([18F] FLT). In a second study A431 tumor-bearing mice were treated with vehicle, genistein (500 mg/kg/d), cetuximab (1 mg/3d) or a combination of the compounds and imaged using [18F]FDG, [18F]FLT and [64Cu]NODAGA-cetuximab. Data were compared to histology and principal components analysis (PCA) of NMR fingerprinting data.ResultsGenistein reduced tumor growth significantly in both xenografts. [18F] FLT uptake was consistent in both models and corresponded to histological findings and also PCA whereas [18F]FDG and [64Cu]NODAGA-cetuximab were not suitable for therapy monitoring.ConclusionsAs mono-therapy the natural isoflavone genistein has a powerful therapeutic effect in vivo on A431 and Colo205 tumors. [18F]FLT has superior consistency compared to the other tested tracers in therapy monitoring, while the treatment effect could be shown on the molecular level by histology and metabolic fingerprinting.
| S-EPMC5053724 | biostudies-literature
Project description:Radiomic studies link quantitative imaging features to patient outcomes in an effort to personalise treatment in oncology. To be clinically useful, a radiomic feature must be robust to image processing steps, which has made robustness testing a necessity for many technical aspects of feature extraction. We assessed the stability of radiomic features to interpolation processing and categorised features based on stable, systematic, or unstable responses. Here, 18F-fluorodeoxyglucose (18F-FDG) PET images for 441 oesophageal cancer patients (split: testing?=?353, validation?=?88) were resampled to 6 isotropic voxel sizes (1.5?mm, 1.8?mm, 2.0?mm, 2.2?mm, 2.5?mm, 2.7?mm) and 141 features were extracted from each volume of interest (VOI). Features were categorised into four groups with two statistical tests. Feature reliability was analysed using an intraclass correlation coefficient (ICC) and patient ranking consistency was assessed using a Spearman's rank correlation coefficient (?). We categorised 93 features robust and 6 limited robustness (stable responses), 34 potentially correctable (systematic responses), and 8 not robust (unstable responses). We developed a correction technique for features with potential systematic variation that used surface fits to link voxel size and percentage change in feature value. Twenty-nine potentially correctable features were re-categorised to robust for the validation dataset, after applying corrections defined by surface fits generated on the testing dataset. Furthermore, we found the choice of interpolation algorithm alone (spline vs trilinear) resulted in large variation in values for a number of features but the response categorisations remained constant. This study attempted to quantify the diverse response of radiomics features commonly found in 18F-FDG PET clinical modelling to isotropic voxel size interpolation.
| S-EPMC6609613 | biostudies-literature
Project description:IntroductionMetabolic brain network analysis based on graph theory using FDG PET imaging is potentially useful for investigating brain activity alternation due to metabolism changes in different stages of Alzheimer's disease (AD). Most studies on metabolic network construction have been based on group data. Here a novel approach in building an individual metabolic network was proposed to investigate individual metabolic network abnormalities.MethodFirst, a weighting matrix was calculated based on the interregional effect size difference of mean uptake between a single subject and average normal controls (NCs). Then the weighting matrix for a single subject was multiplied by a group-based connectivity matrix from an NC cohort. To study the performance of the proposed individual metabolic network, inter- and intra-hemispheric connectivity patterns in the groups of NC, sMCI (stable mild cognitive impairment), pMCI (progressive mild cognitive impairment), and AD using the proposed individual metabolic network were constructed and compared with those from the group-based results. The network parameters of global efficiency and clustering coefficient and the network density score (NDS) in the default-mode network (DMN) of generated individual metabolic networks were estimated and compared among the disease groups in AD.ResultsOur results show that the intra- and inter-hemispheric connectivity patterns estimated from our individual metabolic network are similar to those from the group-based method. In particular, the key patterns of occipital-parietal and occipital-temporal inter-regional connectivity deficits detected in the groupwise network study for differentiating different disease groups in AD were also found in the individual network. A reduction trend was observed for network parameters of global efficiency and clustering coefficient, and also for the NDS from NC, sMCI, pMCI, and AD. There was no significant difference between NC and sMCI for all network parameters.ConclusionWe proposed a novel method in constructing the individual metabolic network using a single-subject FDG PET image and a group-based NC connectivity matrix. The result has shown the effectiveness and feasibility of the proposed individual metabolic network in differentiating disease groups in AD. Future studies should include investigation of inter-individual variability and the correlation of individual network features to disease severities and clinical performance.
| S-EPMC7235322 | biostudies-literature
Project description:IntroductionAutoimmune lymphoproliferative syndrome (ALPS) is a rare immune dysregulatory condition, usually presenting in childhood with massive lymphadenopathy, splenomegaly, and an increased incidence of lymphoma. Methods to differentiate between benign ALPS adenopathy and lymphoma are needed. To this end, we evaluated the usefulness of FDG PET.MethodsWe prospectively evaluated 76 ALPS/ALPS-like patients including FS-7-associated surface antigen (FAS) germline mutation with (n = 4) and without lymphoma (n = 50), FAS-somatic (n = 6), ALPS-unknown (n = 6), and others (n = 10) who underwent FDG PET. Uptakes in 14 nodal sites, liver, and spleen were determined.ResultsIn 76 ALPS patients, FDG PET showed uptake in multiple nodal sites in all but 1 patient. The highest SUVmax values in FAS mutation without lymphoma, FAS mutation with lymphoma, FAS somatic, ALPS-unknown, and other genetic mutations were a median (range) 9.2 (4.3-25), 16.2 (10.7-37.2), 7.6 (4.6-18.1), 11.5 (4.8-17.2), and 5.5 (0-15.3), respectively. Differences between uptake in the FAS group with and without lymphoma were statistically significant, but overlapped, making discrimination between individuals with/without lymphoma impossible. The spleen:liver uptake ratio was greater than 1 in 82% of patients.ConclusionsWhile statistically significant differences were observed in FAS mutation ALPS with and without lymphoma, the significant overlap in FDG uptake and visual appearance in many patients prevents discrimination between patients with and without lymphoma. Similar patterns of FDG biodistribution were noted between the various ALPS subgroups.
| S-EPMC8189160 | biostudies-literature
Project description:PurposeTo investigate the possibility of reducing the injected activity for whole-body [18F]FDG-PET/CT studies of paediatric oncology patients and to assess the usefulness of time-of-flight (TOF) acquisition on PET image quality at reduced count levels.ProceduresTwenty-nine paediatric oncology patients (12F/17M, 3-18 years old (median age 13y), weight 45±20 kg, BMI 19±4 kg/m2), who underwent routine whole-body PET/CT examinations on a Siemens Biograph mCT TrueV system with TOF capability (555ps) were included in this study. The mean injected activity was 156 ± 45 MBq (3.8 ± 0.8 kg/MBq) and scaled to patient weight. The raw data was collected in listmode (LM) format and pre-processed to simulate reduced levels of [18F]FDG activity (75, 50, 35, 20 and 10% of the original counts) by randomly removing events from the original LM data. All data were reconstructed using the vendor-specific e7-tools with standard OSEM only, with OSEM plus resolution recovery (PSF). The reconstructions were repeated with added TOF (TOF) and PSF+TOF. The benefit of TOF together with the reduced count levels was evaluated by calculating the gains in signal-to-noise ratio (SNR) in the liver and contrast-to-noise ratio (CNR) in all PET-positive lesions before and after TOF employed at every simulated reduced count level. Finally, the PSF+TOF images at 50, 75 and 100% of counts were evaluated clinically on a 5-point scale by three nuclear medicine physicians.ResultsThe visual inspection of the reconstructed images did not reveal significant differences in image quality between 75 and 100% count levels for PSF+TOF. The improvements in SNR and CNR were the greatest for TOF reconstruction and PSF combined. Both SNR and CNR gains did increase linearly with the patients BMI for both OSEM only and PSF reconstruction. These benefits were observed until reducing the counts to 50 and 35% for SNR and CNR, respectively.ConclusionsThe benefit of using TOF was noticeable when using 50% or greater of the counts when evaluating the CNR and SNR. For [18F]FDG-PET/CT, whole-body paediatric imaging the injected activity can be reduced to 75% of the original dose without compromising PET image quality.
| S-EPMC8410733 | biostudies-literature
Project description: Not available
| S-EPMC11345444 | biostudies-literature