Do TSH, FT3, and FT4 Impact BAT Visualization of Clinical FDG-PET/CT Images?
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ABSTRACT:
SUBMITTER: Nishii R
PROVIDER: S-EPMC5831944 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:The current guidelines for 2-deoxy-2-[18F]fluoro-d-glucose PET/CT scanning do not address potential inaccuracies that may arise due to patients with renal failure. We report a retrospective analysis of standard uptake values (SUVs) in patients with and without renal failure in order to warrant a protocol adjustment.Patients were matched based on age, gender, and BMI all of which are potential effectors on observed SUV. Thirty patients were selected with clinically diagnosed renal failure, of which 12 were on dialysis. All 30 patients had age, gender, and BMI control matches. Blood urea nitrogen and creatinine levels were measured within 1 month of the scan to assess renal failure. PET/CT scans for both the renal failure patients and controls were performed 60 min after FDG injection. SUVs were measured by placing circular regions of interest in the right hepatic lobe (LSUV) and left psoas muscle (PSUV).For the 30 renal failure patients, the mean LSUV was 2.77 (SD = 0.57) and PSUV was 1.43 (SD = 0.30) while the controls had mean LSUV 2.74 (SD = 0.50) and PSUV 1.42 (SD = 0.37). The SUVs from both the liver and psoas muscle were not significantly different between the renal failure patients and the normal controls with p values >0.05. In addition, dialysis and gender also had no effect on SUVs.Our data suggest that renal failure patients do not require an adjustment in protocol and the standard protocol times should remain.
| S-EPMC5519567 | biostudies-other
Project description:PurposeFor pediatric lymphoma, quantitative FDG PET/CT imaging features such as metabolic tumor volume (MTV) are important for prognosis and risk stratification strategies. However, feature extraction is difficult and time-consuming in cases of high disease burden. The purpose of this study was to fully automate the measurement of PET imaging features in PET/CT images of pediatric lymphoma.Methods18F-FDG PET/CT baseline images of 100 pediatric Hodgkin lymphoma patients were retrospectively analyzed. Two nuclear medicine physicians identified and segmented FDG avid disease using PET thresholding methods. Both PET and CT images were used as inputs to a three-dimensional patch-based, multi-resolution pathway convolutional neural network architecture, DeepMedic. The model was trained to replicate physician segmentations using an ensemble of three networks trained with 5-fold cross-validation. The maximum SUV (SUVmax), MTV, total lesion glycolysis (TLG), surface-area-to-volume ratio (SA/MTV), and a measure of disease spread (Dmaxpatient) were extracted from the model output. Pearson's correlation coefficient and relative percent differences were calculated between automated and physician-extracted features.ResultsMedian Dice similarity coefficient of patient contours between automated and physician contours was 0.86 (IQR 0.78-0.91). Automated SUVmax values matched exactly the physician determined values in 81/100 cases, with Pearson's correlation coefficient (R) of 0.95. Automated MTV was strongly correlated with physician MTV (R = 0.88), though it was slightly underestimated with a median (IQR) relative difference of - 4.3% (- 10.0-5.7%). Agreement of TLG was excellent (R = 0.94), with median (IQR) relative difference of - 0.4% (- 5.2-7.0%). Median relative percent differences were 6.8% (R = 0.91; IQR 1.6-4.3%) for SA/MTV, and 4.5% (R = 0.51; IQR - 7.5-40.9%) for Dmaxpatient, which was the most difficult feature to quantify automatically.ConclusionsAn automated method using an ensemble of multi-resolution pathway 3D CNNs was able to quantify PET imaging features of lymphoma on baseline FDG PET/CT images with excellent agreement to reference physician PET segmentation. Automated methods with faster throughput for PET quantitation, such as MTV and TLG, show promise in more accessible clinical and research applications.
| S-EPMC7736382 | biostudies-literature
Project description: Not available
| S-EPMC5368524 | biostudies-literature
Project description:Circulating tumor DNA (ctDNA) as a biomarker of disease activity in classic Hodgkin lymphoma (cHL) patients are still not well-defined. By profiling primary tumors and ctDNA, we identified common variants between primary tumors and longitudinal plasma samples in most of the cases, confirming high PBatial and temporal heterogeneity. Though ctDNA analyses mirrored HRS cell genetics overall, the prevalence of variants shows that none of them can be used as a single biomarker. Conversely, the estimation of hGE/mL, based in total ctDNA quantification, reflects disease activity and is almost perfectly correlated with standard parameters such as PET/CT that are associated with refractoriness.
2023-12-18 | GSE244989 | GEO
Project description:ObjectiveFDG-PET/CT (fluorodeoxyglucose-positron emission tomography/computed tomography) is effective to assess for occult neck nodal disease. We report risks and patterns of nodal disease based on primary site and nodal level from data on the dissected cN0 per the results from ACRIN 6685.Study designProspective nonrandomized enrollment included participants with first-time head and neck squamous cell carcinoma and at least 1 cN0 neck side to be dissected.SettingTwenty-four ACRIN-certified centers internationally (American College of Radiology Imaging Network).MethodsA total of 287 participants were enrolled. Preoperative FDG-PET/CT findings were centrally reviewed and compared with pathology. Incidence, relative risk, pattern of lymph node involvement, and impact upon neck dissection were reported.ResultsAn overall 983 nodal levels were dissected (n = 261 necks, n = 203 participants). The highest percentages of ipsilateral positive nodes by primary location and nodal level were oral cavity (level I, 17/110, 15.5%), pharynx (level II, 6/30, 20.0%), and larynx (level VI, 1/3, 33.3%).ConclusionLevels at greatest risk for nodal disease in cN0 in terms of ipsilateral neck dissection are level I (oral cavity), II (pharynx), and VI (larynx). These data should be considered when treating patients presenting with cN0. This is the first study to comprehensively report the incidence, location, and risk of metastases in cN0 in the FDG-PET/CT era.
| S-EPMC8342266 | biostudies-literature
Project description:Aim: Several series have already demonstrated that intratumoral subvolumes with high tracer avidity (hotspots) in 18F-flurodesoxyglucose positron-emission tomography (FDG-PET/CT) are preferential sites of local recurrence (LR) in various solid cancers after radiotherapy (RT), becoming potential targets for dose escalation. However, studies conducted on head and neck squamous cell carcinoma (HNSCC) found only a moderate overlap between pre- and post-treatment subvolumes. A limitation of these studies was that scans were not performed in RT treatment position (TP) and were coregistred using a rigid registration (RR) method. We sought to study (i) the influence of FDG-PET/CT acquisition in TP and (ii) the impact of using an elastic registration (ER) method to improve the localization of hotpots in HNSCC. Methods: Consecutive patients with HNSCC treated by RT between March 2015 and September 2017 who underwent FDG-PET/CT in TP at initial staging (PETA) and during follow-up (PETR) were prospectively included. We utilized a control group scanned in non treatment position (NTP) from our previous retrospective study. Scans were registered with both RR and ER methods. Various sub-volumes (AX; x = 30, 40, 50, 60, 70, 80, and 90%SUVmax) within the initial tumor and in the subsequent LR (RX; x = 40 and 70%SUVmax) were overlaid on the initial PET/CT for comparison [Dice, Jaccard, overlap fraction = OF, common volume/baseline volume = AXnRX/AX, common volume/recurrent volume = AXnRX/RX]. Results: Of 199 patients included, 43 (21.6%) had LR (TP = 15; NTP = 28). The overlap between A30, A40, and A50 sub-volumes on PETA and the whole metabolic volume of recurrence R40 and R70 on PETR showed moderate to good agreements (0.41-0.64) with OF and AXnRX/RX index, regardless of registration method or patient position. Comparison of registration method demonstrated OF and AXnRX/RX indices (x = 30% to 50%SUVmax) were significantly higher with ER vs. RR in NTP (p < 0.03), but not in TP. For patient position, the OF and AXnRX/RX indices were higher in TP than in NTP when RR was used with a trend toward significance, particularly for x=40%SUVmax (0.50±0.22 vs. 0.31 ± 0.13, p = 0.094). Conclusion: Our study suggested that PET/CT acquired in TP improves results in the localization of FDG hotspots in HNSCC. If TP is not possible, using an ER method is significantly more accurate than RR for overlap estimation.
| S-EPMC7287148 | biostudies-literature
Project description:It has been shown that [(18)F]fluorodeoxyglucose (FDG)-positron emission tomography (PET) provides robust and reproducible data for early metabolic response assessment in various malignancies. This led to the initiation of several prospective multicenter trials in malignant lymphoma and adenocarcinoma of the esophagogastric junction, in order to investigate whether the use of PET-guided treatment individualization results in a survival benefit. In Hodgkin lymphoma and aggressive non-Hodgkin lymphoma, several trials are ongoing. Some studies aim to investigate the use of PET in early identification of metabolic non-responders in order to intensify treatment to improve survival. Other studies aim at reducing toxicity without adversely affecting cure rates by safely de-escalating therapy in metabolic responders. In solid tumors the first PET response-adjusted treatment trials have been realized in adenocarcinoma of the esophagogastric junction. These trials showed that patients with an early metabolic response to neoadjuvant chemotherapy benefit from this treatment, whereas metabolic non-responders should switch early to surgery, thus reducing the risk of tumor progression during chemotherapy and the risk of toxic death. The trials provide a model for designing response-guided treatment algorithms in other malignancies. PET-guided treatment algorithms are the promise of the near future; the choice of therapy, its intensity, and its duration will become better adjusted to the biology of the individual patient. Today's major challenge is to investigate the impact on patient outcome of personalized response-adapted treatment concepts.
| S-EPMC3460598 | biostudies-literature
Project description:PurposeThe purpose of this study was to explore the application of 18F-fluorodeoxyglucose positron emission tomography/computed tomography (18F-FDG PET/CT) image radiomics in the identification of spine multiple myeloma (MM) and bone metastasis (BM), and whether this method could improve the classification diagnosis performance compared with traditional methods.MethodsThis retrospective study collected a total of 184 lesions from 131 patients between January 2017 and January 2021. All images were visually evaluated independently by two physicians with 20 years of experience through the double-blind method, while the maximum standardized uptake value (SUVmax) of each lesion was recorded. A total of 279 radiomics features were extracted from the region of interest (ROI) of CT and PET images of each lesion separately by manual method. After the reliability test, the least absolute shrinkage and selection operator (LASSO) regression and 10-fold cross-validation were used to perform dimensionality reduction and screening of features. Two classification models of CT and PET were derived from CT images and PET images, respectively and constructed using the multivariate logistic regression algorithm. In addition, the ComModel was constructed by combining the PET model and the conventional parameter SUVmax. The performance of the three classification diagnostic models, as well as the human experts and SUVmax, were evaluated and compared, respectively.ResultsA total of 8 and 10 features were selected from CT and PET images for the construction of radiomics models, respectively. Satisfactory performance of the three radiomics models was achieved in both the training and the validation groups (Training: AUC: CT: 0.909, PET: 0.949, ComModel: 0.973; Validation: AUC: CT: 0.897, PET: 0.929, ComModel: 0.948). Moreover, the PET model and ComModel showed significant improvement in diagnostic performance between the two groups compared to the human expert (Training: P = 0.01 and P = 0.001; Validation: P = 0.018 and P = 0.033), and no statistical difference was observed between the CT model and human experts (P = 0.187 and P = 0.229, respectively).ConclusionThe radiomics model constructed based on 18F-FDG PET/CT images achieved satisfactory diagnostic performance for the classification of MM and bone metastases. In addition, the radiomics model showed significant improvement in diagnostic performance compared to human experts and PET conventional parameter SUVmax.
| S-EPMC9058063 | biostudies-literature
Project description:To compare the interobserver agreement and degree of confidence in anatomical localisation of lesions using 2-[fluorine-18]fluoro-2-deoxy-D-glucose ((18)F-FDG) positron emission tomography (PET)/computed tomography (CT) and (18)F-FDG PET alone in patients with head and neck tumours. A prospective study of 24 patients (16 male, eight female, median age 59 years) with head and neck tumours was undertaken. (18)F-FDG PET/CT was performed for staging purposes. 2D images were acquired over the head and neck area using a GE Discovery LS PET/CT scanner. (18)F-FDG PET images were interpreted by three independent observers. The observers were asked to localise abnormal (18)F-FDG activity to an anatomical territory and score the degree of confidence in localisation on a scale from 1 to 3 (1=exact region unknown; 2=probable; 3=definite). For all (18)F-FDG-avid lesions, standardised uptake values (SUVs) were also calculated. After 3 weeks, the same exercise was carried out using (18)F-FDG PET/CT images, where CT and fused volume data were made available to observers. The degree of interobserver agreement was measured in both instances. A total of six primary lesions with abnormal (18)F-FDG uptake (SUV range 7.2-22) were identified on (18)F-FDG PET alone and on (18)F-FDG PET/CT. In all, 15 nonprimary tumour sites were identified with (18)F-FDG PET only (SUV range 4.5-11.7), while 17 were identified on (18)F-FDG PET/CT. Using (18)F-FDG PET only, correct localisation was documented in three of six primary lesions, while (18)F-FDG PET/CT correctly identified all primary sites. In nonprimary tumour sites, (18)F-FDG PET/CT improved the degree of confidence in anatomical localisation by 51%. Interobserver agreement in assigning primary and nonprimary lesions to anatomical territories was moderate using (18)F-FDG PET alone (kappa coefficients of 0.45 and 0.54, respectively), but almost perfect with (18)F-FDG PET/CT (kappa coefficients of 0.90 and 0.93, respectively). We conclude that (18)F-FDG PET/CT significantly increases interobserver agreement and confidence in disease localisation of (18)F-FDG-avid lesions in patients with head and neck cancers.
| S-EPMC2361926 | biostudies-other
Project description:Radiomics has become an area of interest for tumor characterization in 18F-Fluorodeoxyglucose positron emission tomography/computed tomography (18F-FDG PET/CT) imaging. The aim of the present study was to demonstrate how imaging phenotypes was connected to somatic mutations through an integrated analysis of 115 non-small cell lung cancer (NSCLC) patients with somatic mutation testings and engineered computed PET/CT image analytics. A total of 38 radiomic features quantifying tumor morphological, grayscale statistic, and texture features were extracted from the segmented entire-tumor region of interest (ROI) of the primary PET/CT images. The ensembles for boosting machine learning scheme were employed for classification, and the least absolute shrink age and selection operator (LASSO) method was used to select the most predictive radiomic features for the classifiers. A radiomic signature based on both PET and CT radiomic features outperformed individual radiomic features, the PET or CT radiomic signature, and the conventional PET parameters including the maximum standardized uptake value (SUVmax), SUVmean, SUVpeak, metabolic tumor volume (MTV), and total lesion glycolysis (TLG), in discriminating between mutant-type of epidermal growth factor receptor (EGFR) and wild-type of EGFR- cases with an AUC of 0.805, an accuracy of 80.798%, a sensitivity of 0.826 and a specificity of 0.783. Consistently, a combined radiomic signature with clinical factors exhibited a further improved performance in EGFR mutation differentiation in NSCLC. In conclusion, tumor imaging phenotypes that are driven by somatic mutations may be predicted by radiomics based on PET/CT images.
| S-EPMC6803612 | biostudies-literature