scholarly journals Effects of New Bayesian Penalized Likelihood Reconstruction Algorithm on Visualization and Quantification of Upper Abdominal Malignant Tumors in Clinical FDG PET/CT Examinations

2021 ◽  
Vol 11 ◽  
Author(s):  
Mitsuaki Tatsumi ◽  
Fumihiko Soeda ◽  
Takashi Kamiya ◽  
Junpei Ueda ◽  
Daisuke Katayama ◽  
...  
Keyword(s):  
Fdg Pet ◽  
Malignant Tumors ◽  
Reconstruction Algorithm ◽  
Lesion Group ◽  
Small Lesion ◽  
Gray Level ◽  
Quantitative Metrics ◽  
Pet Ct ◽  
Upper Abdominal ◽  
Fdg Pet Ct

PurposeThis study evaluated the effects of new Bayesian penalized likelihood (BPL) reconstruction algorithm on visualization and quantification of upper abdominal malignant tumors in clinical FDG PET/CT examinations, comparing the results to those obtained by an ordered subset expectation maximization (OSEM) reconstruction algorithm. Metabolic tumor volume (MTV) and texture features (TFs), as well as SUV-related metrics, were evaluated to clarify the BPL effects on quantification.Materials and MethodsA total of 153 upper abdominal lesions (82 liver metastatic and 71 pancreatic cancers) were included in this study. FDG PET/CT images were acquired with a GE Discovery 710 scanner equipped with a time-of-flight system. Images were reconstructed using OSEM and BPL (beta 700) algorithms. In 58 lesions <1.5 cm in greatest diameter (small-lesion group), visual image quality of each lesion was evaluated using a four-point scale. SUVmax was obtained for quantitative metrics. Visual scores and SUVmax were compared between OSEM and BPL images. In 95 lesions >2.0 cm in greatest diameter (larger-lesion group), SUVmax, SUVpeak, MTV, and six TFs were compared between OSEM and BPL images. In addition to the size-based analyses, an increase of SUVmax with BPL was evaluated according to the original SUVmax in OSEM images.ResultsIn the small-lesion group, both visual score and SUVmax were significantly higher in the BPL than OSEM images. The increase in visual score was observed in 20 (34%) of all 58 lesions. In the larger-lesion group, no statistical difference was observed in SUVmax, SUVpeak, or MTV between OSEM and BPL images. BPL increased high gray-level zone emphasis and decreased low gray-level zone emphasis among six TFs compared to OSEM with statistical significance. No statistical differences were observed in other TFs. SUVmax-based analysis demonstrated that BPL increased and decreased SUVmax in lesions with low (<5) and high (>10) SUVmax in original OSEM images, respectively.ConclusionThis study demonstrated that BPL improved conspicuity of small or low-count upper abdominal malignant lesions in clinical FDG PET/CT examinations. Only two TFs represented significant differences between OSEM and BPL images of all quantitative metrics in larger lesions.

scholarly journals Use of F-18 FDG PET/CT Through Delayed Diuretic Imaging for Preoperative Evaluation of Upper Urinary Tract-Occupying Lesions

2021 ◽  
Vol 11 ◽  
Author(s):  
Jun Wang ◽  
Liang Zhang ◽  
Jian Guo Wu ◽  
Ruohua Chen ◽  
Jia lin Shen
Keyword(s):  
Urinary Tract ◽  
Fdg Pet ◽  
Malignant Tumors ◽  
Upper Urinary Tract ◽  
Characteristic Analysis ◽  
Patient Age ◽  
Patient Âgé ◽  
Pet Ct ◽  
Significant Difference ◽  
Fdg Pet Ct

PurposeTo evaluate the value of F-18 FDG PET/CT in the differentiation of malignant and benign upper urinary tract-occupying lesions.Patients and Methods64 patients with upper urinary tract-occupying lesions underwent F-18 FDG PET/CT at RenJi Hospital from January 2015 to February 2019 in this retrospective study. Of the 64 patients, 50 patients received nephroureterectomy or partial ureterectomy; 14 patients received ureteroscopy and biopsy. The comparisons of PET/CT parameters and clinical characteristics between malignant and benign upper urinary tract-occupying lesions were investigated.ResultsOf the 64 patients, 49 were found to have malignant tumors. Receiver operating characteristic analysis determined the lesion SUVmax value of 6.75 as the threshold for predicting malignant tumors. There were significant associations between malignant and benign upper urinary tract-occupying lesions and SUVmax of lesion (P<0.001), lesion size (P<0.001), and patient age (P=0.011). Multivariate analysis showed that SUVmax of lesion (P=0.042) and patient age (P=0.009) as independent predictors for differentiation of malignant from benign upper urinary tract-occupying lesions. There was a significant difference in tumor size between the positive (SUVmax >6.75) and negative (SUVmax ≤6.75) PET groups in 38 of the 49 patients with malignant tumors.ConclusionThe SUVmax of lesion and patient age is associated with the nature of upper urinary tract-occupying lesions. F-18 FDG PET/CT may be useful to distinguish between malignant and benign upper urinary tract-occupying lesions and determine a suitable therapeutic strategy.

scholarly journals Value of 18-F-FDG PET/CT and CT in the Diagnosis of Indeterminate Adrenal Masses

2015 ◽  
Vol 2015 ◽  
pp. 1-8 ◽  
Author(s):  
Nathalie Launay ◽  
Stéphane Silvera ◽  
Florence Tenenbaum ◽  
Lionel Groussin ◽  
Frédérique Tissier ◽  
...  
Keyword(s):  
Fdg Pet ◽  
Malignant Tumors ◽  
Apparent Diffusion Coefficient Values ◽  
Standardized Uptake Values ◽  
Pet Ct ◽  
Adrenal Masses ◽  
18F Fdg ◽  
Ct Data ◽  
Adrenocortical Carcinomas ◽  
Fdg Pet Ct

The purpose of this paper was to study the value of 18-FDG PET/CT and reassess the value of CT for the characterization of indeterminate adrenal masses. 66 patients with 67 indeterminate adrenal masses were included in our study. CT/MRI images and 18F-FDG PET/CT data were evaluated blindly for tumor morphology, enhancement features, apparent diffusion coefficient values, maximum standardized uptake values, and adrenal-to-liver maxSUV ratio. The study population comprised pathologically confirmed 16 adenomas, 19 metastases, and 32 adrenocortical carcinomas. Macroscopic fat was observed in 62.5% of the atypical adenomas at CT but not in malignant masses. On 18F-FDG PET/CT, SUVmax and adrenal-to-liver maxSUV ratio were significantly lower in adenomas than in malignant tumors. An SUVmax value of less than 3.7 or an adrenal-to-liver maxSUV ratio of less than 1.29 is highly predictive of benignity.

scholarly journals Application of Community Detection Algorithm to Investigate the Correlation between Imaging Biomarkers of Tumor Metabolism, Hypoxia, Cellularity, and Perfusion for Precision Radiotherapy in Head and Neck Squamous Cell Carcinomas

Cancers ◽  
2021 ◽  
Vol 13 (15) ◽  
pp. 3908
Author(s):  
Ramesh Paudyal ◽  
Milan Grkovski ◽  
Jung Hun Oh ◽  
Heiko Schöder ◽  
David Aramburu Nunez ◽  
...  
Keyword(s):  
Head And Neck ◽  
Community Detection ◽  
Squamous Cell ◽  
Fdg Pet ◽  
Detection Algorithm ◽  
Dce Mri ◽  
Quantitative Metrics ◽  
Pet Ct ◽  
Community Detection Algorithm ◽  
Fdg Pet Ct

The present study aimed to investigate the correlation at pre-treatment (TX) between quantitative metrics derived from multimodality imaging (MMI), including 18F-FDG-PET/CT, 18F-FMISO-PET/CT, DW- and DCE-MRI, using a community detection algorithm (CDA) in head and neck squamous cell carcinoma (HNSCC) patients. Twenty-three HNSCC patients with 27 metastatic lymph nodes underwent a total of 69 MMI exams at pre-TX. Correlations among quantitative metrics derived from FDG-PET/CT (SUL), FMSIO-PET/CT (K1, k3, TBR, and DV), DW-MRI (ADC, IVIM [D, D*, and f]), and FXR DCE-MRI [Ktrans, ve, and τi]) were investigated using the CDA based on a “spin-glass model” coupled with the Spearman’s rank, ρ, analysis. Mean MRI T2 weighted tumor volumes and SULmean values were moderately positively correlated (ρ = 0.48, p = 0.01). ADC and D exhibited a moderate negative correlation with SULmean (ρ ≤ −0.42, p < 0.03 for both). K1 and Ktrans were positively correlated (ρ = 0.48, p = 0.01). In contrast, Ktrans and k3max were negatively correlated (ρ = −0.41, p = 0.03). CDA revealed four communities for 16 metrics interconnected with 33 edges in the network. DV, Ktrans, and K1 had 8, 7, and 6 edges in the network, respectively. After validation in a larger population, the CDA approach may aid in identifying useful biomarkers for developing individual patient care in HNSCC.

scholarly journals Predicting Model for Tumor Budding Status using Radiomics Features of 18F-PET/CT and in Cervical Cancer

2021 ◽  
Author(s):  
Gun Oh Chong ◽  
Shin-Hyung Park ◽  
Shin Young Jeong ◽  
Su Jeong Kim ◽  
Jee Young Park ◽  
...  
Keyword(s):  
Cervical Cancer ◽  
Cancer Patients ◽  
Fdg Pet ◽  
Univariate Analysis ◽  
Metabolic Parameters ◽  
Tumor Budding ◽  
Gray Level ◽  
Predicting Model ◽  
Pet Ct ◽  
Fdg Pet Ct

Abstract ObjectiveThe aim of this study was to compare radiomics feature on 18F-FDG PET/CT and intratumoral heterogeneity according to tumor budding (TB) status and to develop predicting model for TB status using radiomics feature of 18F-FDG PET/CT in patients with cervical cancer.Materials and methodsA total of 76 cervical cancer patients who performed radical hysterectomy and preoperative 18F-FDG PET/CT were included. We assessed the status of intratumoral budding (ITP) and peritumoral budding (PTB) in all available hematoxylin and eosin-stained specimens. Three conventional metabolic parameters and a total of 59 features were extracted and analyzed. Univariate analysis was used to identify significant metabolic parameters and radiomics findings for TB status. Predicting model for TB status was built by the LASSO regularization.ResultsThe univariate analysis lead to the identification of 2 significant metabolic parameters and 12 significant radiomic features according to ITB status. Among these parameters, only compacity was remained in multivariate analysis for ITB status (odds ratio. 5.0047; 95% confidence interval, 1.1636 – 21.5253; p = 0.0305). Five radiomics features (Kurtosis, Compacity, Short-Zone Low Gray-level Emphasis, Coarseness, Low Gray-level Run Emphasis) were selected by the LASSO regularization and the predicting model for ITB status had a mean area under curve of 0.810 in training dataset and 0.794 in validation dataset.ConclusionRadiomics features on 18F-FDG PET/CT was associated with ITB status. The predicting model using radiomics features successfully predicted TB status in cervical cancer. The predicting models for ITB status may contribute to personalized medicine in the management of cervical cancer patients.

scholarly journals The diagnostic performance of 18F-FDG PET/CT and MRI in differentiating benign and malignant ovarian tumors: an indirect comparative analysis

2021 ◽  
Author(s):  
Xianwen Hu ◽  
Dandan Li ◽  
Zhigang Liang ◽  
Yan Liao ◽  
Ling Yang ◽  
...  
Keyword(s):  
Sensitivity And Specificity ◽  
Fdg Pet ◽  
Diagnostic Performance ◽  
Malignant Tumors ◽  
Meta Analysis ◽  
Ovarian Tumors ◽  
Scanning Time ◽  
Pet Ct ◽  
Fdg Pet Ct ◽  
Ct And Mri

Abstract Objective: To compare the value of Fluorodeoxyglucose positron emission tomography (FDG-PET)/computed tomography (CT) and magnetic resonance imaging(MRI) in differentiating benign and malignant ovarian tumors.Material and Methods: Retrieved the research on the diagnostic performance of MRI or 18F-FDG PET/CT in identifying benign and malignant ovarian tumors published in PubMed and Embase from January 2000 to January 2021. Two authors independently extracted the data of the characteristics of each study. If the data of the study report can be used to construct a 2X2 contingency table comparing 18F-FDG PET/CT and MRI, these studies were selected. The Quality Assessment of Diagnostic Accuracy Studies were used to evaluate the quality of the studies. According to the sensitivity and specificity of 18F-FDG PET/CT and MRI, forest plots is generated.Results：A total of 27 articles including 1118F-FDG PET/CT studies and 17 MRI studies on the differentiation of benign and malignant ovarian or accessory tumors were included for this meta-analysis. The pooled sensitivity and specificity for 18F-FDG PET/CT in differentiating benign and malignant ovarian tumors were 0.92 (95% CI, 0.86-0.96) and 0.86 (95% CI, 0.79-0.91), respectively, and the pooled sensitivity and specificity for MRI were 0.92 (95% CI: 0.89-0.95) and 0.85 (95% CI: 0.79-0.89), respectively.Conclusion：MRI and 18F-FDG PET/CT have the same diagnostic performance in the differential diagnosis of ovarian benign and malignant tumors. However, MRI is more worthy of clinical application because of its lack of radiation, shorter scanning time, and lower medical costs.

scholarly journals Usefulness of Respiratory-Gated 18F-FDG PET/CT in Detecting Upper Abdominal Fever Focus

2018 ◽  
Vol 52 (5) ◽  
pp. 380-383 ◽  
Author(s):  
Sungwoo Bae ◽  
Ji-In Bang ◽  
Yoo Sung Song ◽  
Won Woo Lee
Keyword(s):  
Fdg Pet ◽  
Pet Ct ◽  
18F Fdg ◽  
Upper Abdominal ◽  
Fdg Pet Ct

scholarly journals Clinical evaluation of a block sequential regularized expectation maximization reconstruction algorithm in 18F-FDG PET/CT studies

2017 ◽  
Vol 38 (1) ◽  
pp. 57-66 ◽  
Author(s):  
Bert-Ram Sah ◽  
Paul Stolzmann ◽  
Gaspar Delso ◽  
Scott D. Wollenweber ◽  
Martin Hüllner ◽  
...  
Keyword(s):  
Clinical Evaluation ◽  
Expectation Maximization ◽  
Fdg Pet ◽  
Reconstruction Algorithm ◽  
Pet Ct ◽  
18F Fdg ◽  
Fdg Pet Ct ◽  
Ct Studies

Whole-body MR-DWIBS vs. [18F]-FDG-PET/CT in the study of malignant tumors: a retrospective study

2011 ◽  
Vol 117 (2) ◽  
pp. 293-311 ◽  
Author(s):  
D. Cafagna ◽  
G. Rubini ◽  
F. Iuele ◽  
N. Maggialetti ◽  
A. Notaristefano ◽  
...  
Keyword(s):  
Retrospective Study ◽  
Fdg Pet ◽  
Malignant Tumors ◽  
Whole Body ◽  
Pet Ct ◽  
18F Fdg ◽  
Fdg Pet Ct

scholarly journals AI-based detection of lung lesions in [18F]FDG PET-CT from lung cancer patients

2021 ◽  
Vol 8 (1) ◽  
Author(s):  
Pablo Borrelli ◽  
John Ly ◽  
Reza Kaboteh ◽  
Johannes Ulén ◽  
Olof Enqvist ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Fdg Pet ◽  
Test Group ◽  
Added Value ◽  
Small Lesion ◽  
Predictive Values ◽  
Lung Lesions ◽  
Pet Ct ◽  
Medicine Physician ◽  
Fdg Pet Ct

Abstract Background [18F]-fluorodeoxyglucose (FDG) positron emission tomography with computed tomography (PET-CT) is a well-established modality in the work-up of patients with suspected or confirmed diagnosis of lung cancer. Recent research efforts have focused on extracting theragnostic and textural information from manually indicated lung lesions. Both semi-automatic and fully automatic use of artificial intelligence (AI) to localise and classify FDG-avid foci has been demonstrated. To fully harness AI’s usefulness, we have developed a method which both automatically detects abnormal lung lesions and calculates the total lesion glycolysis (TLG) on FDG PET-CT. Methods One hundred twelve patients (59 females and 53 males) who underwent FDG PET-CT due to suspected or for the management of known lung cancer were studied retrospectively. These patients were divided into a training group (59%; n = 66), a validation group (20.5%; n = 23) and a test group (20.5%; n = 23). A nuclear medicine physician manually segmented abnormal lung lesions with increased FDG-uptake in all PET-CT studies. The AI-based method was trained to segment the lesions based on the manual segmentations. TLG was then calculated from manual and AI-based measurements, respectively and analysed with Bland-Altman plots. Results The AI-tool’s performance in detecting lesions had a sensitivity of 90%. One small lesion was missed in two patients, respectively, where both had a larger lesion which was correctly detected. The positive and negative predictive values were 88% and 100%, respectively. The correlation between manual and AI TLG measurements was strong (R2 = 0.74). Bias was 42 g and 95% limits of agreement ranged from − 736 to 819 g. Agreement was particularly high in smaller lesions. Conclusions The AI-based method is suitable for the detection of lung lesions and automatic calculation of TLG in small- to medium-sized tumours. In a clinical setting, it will have an added value due to its capability to sort out negative examinations resulting in prioritised and focused care on patients with potentially malignant lesions.

FDG PET/CT differentiating two malignant tumors in the same patient

2011 ◽  
Vol 51 (1) ◽  
pp. 142-144 ◽  
Author(s):  
Ayelet Shai ◽  
Larisa Leitzin ◽  
Mariana Steiner ◽  
Avivit Peer ◽  
Saher Srour ◽  
...  
Keyword(s):  
Fdg Pet ◽  
Malignant Tumors ◽  
Pet Ct ◽  
Fdg Pet Ct
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