scholarly journals Preoperative Texture Analysis Using 11C-Methionine Positron Emission Tomography Predicts Survival after Surgery for Glioma

Diagnostics ◽  
2021 ◽  
Vol 11 (2) ◽  
pp. 189
Author(s):  
Osamu Manabe ◽  
Shigeru Yamaguchi ◽  
Kenji Hirata ◽  
Kentaro Kobayashi ◽  
Hiroyuki Kobayashi ◽  
...  
Keyword(s):  
Positron Emission Tomography ◽  
Texture Analysis ◽  
Standardized Uptake Value ◽  
Texture Features ◽  
Tumor Grade ◽  
Emission Tomography ◽  
World Health ◽  
Metabolic Imaging ◽  
Gray Level ◽  
Positron Emission

Background: Positron emission tomography with 11C-methionine (MET) is well established in the diagnostic work-up of malignant brain tumors. Texture analysis is a novel technique for extracting information regarding relationships among surrounding voxels, in order to quantify their inhomogeneity. This study evaluated whether the texture analysis of MET uptake has prognostic value for patients with glioma. Methods: We retrospectively analyzed adults with glioma who had undergone preoperative metabolic imaging at a single center. Tumors were delineated using a threshold of 1.3-fold of the mean standardized uptake value for the contralateral cortex, and then processed to calculate the texture features in glioma. Results: The study included 42 patients (median age: 56 years). The World Health Organization classifications were grade II (7 patients), grade III (17 patients), and grade IV (18 patients). Sixteen (16.1%) all-cause deaths were recorded during the median follow-up of 18.8 months. The univariate analyses revealed that overall survival (OS) was associated with age (hazard ratio (HR) 1.04, 95% confidence interval (CI) 1.01–1.08, p = 0.0093), tumor grade (HR 3.64, 95% CI 1.63–9.63, p = 0.0010), genetic status (p < 0.0001), low gray-level run emphasis (LGRE, calculated from the gray-level run-length matrix) (HR 2.30 × 1011, 95% CI 737.11–4.23 × 1019, p = 0.0096), and correlation (calculated from the gray-level co-occurrence matrix) (HR 5.17, 95% CI 1.07–20.93, p = 0.041). The multivariate analyses revealed OS was independently associated with LGRE and correlation. The survival curves were also significantly different (both log-rank p < 0.05). Conclusion: Textural features obtained using preoperative MET positron emission tomography may compliment the semi-quantitative assessment for prognostication in glioma cases.

Usefulness of positron emission tomography for differentiating gliomas according to the 2016 World Health Organization classification of tumors of the central nervous system

2020 ◽  
Vol 133 (4) ◽  
pp. 1010-1019 ◽  
Author(s):  
Hiroaki Takei ◽  
Jun Shinoda ◽  
Soko Ikuta ◽  
Takashi Maruyama ◽  
Yoshihiro Muragaki ◽  
...  
Keyword(s):  
Positron Emission Tomography ◽  
Pet Imaging ◽  
Who Classification ◽  
Standardized Uptake Value ◽  
Emission Tomography ◽  
World Health ◽  
Pet Tracers ◽  
Positron Emission ◽  
Significant Difference ◽  
The Mean

OBJECTIVEPositron emission tomography (PET) is important in the noninvasive diagnostic imaging of gliomas. There are many PET studies on glioma diagnosis based on the 2007 WHO classification; however, there are no studies on glioma diagnosis using the new classification (the 2016 WHO classification). Here, the authors investigated the relationship between uptake of 11C-methionine (MET), 11C-choline (CHO), and 18F-fluorodeoxyglucose (FDG) on PET imaging and isocitrate dehydrogenase (IDH) status (wild-type [IDH-wt] or mutant [IDH-mut]) in astrocytic and oligodendroglial tumors according to the 2016 WHO classification.METHODSIn total, 105 patients with newly diagnosed cerebral gliomas (6 diffuse astrocytomas [DAs] with IDH-wt, 6 DAs with IDH-mut, 7 anaplastic astrocytomas [AAs] with IDH-wt, 24 AAs with IDH-mut, 26 glioblastomas [GBMs] with IDH-wt, 5 GBMs with IDH-mut, 19 oligodendrogliomas [ODs], and 12 anaplastic oligodendrogliomas [AOs]) were included. All OD and AO patients had both IDH-mut and 1p/19q codeletion. The maximum standardized uptake value (SUV) of the tumor/mean SUV of normal cortex (T/N) ratios for MET, CHO, and FDG were calculated, and the mean T/N ratios of DA, AA, and GBM with IDH-wt and IDH-mut were compared. The diagnostic accuracy for distinguishing gliomas with IDH-wt from those with IDH-mut was assessed using receiver operating characteristic (ROC) curve analysis of the mean T/N ratios for the 3 PET tracers.RESULTSThere were significant differences in the mean T/N ratios for all 3 PET tracers between the IDH-wt and IDH-mut groups of all histological classifications (p < 0.001). Among the 27 gliomas with mean T/N ratios higher than the cutoff values for all 3 PET tracers, 23 (85.2%) were classified into the IDH-wt group using ROC analysis. In DA, there were no significant differences in the T/N ratios for MET, CHO, and FDG between the IDH-wt and IDH-mut groups. In AA, the mean T/N ratios of all 3 PET tracers in the IDH-wt group were significantly higher than those in the IDH-mut group (p < 0.01). In GBM, the mean T/N ratio in the IDH-wt group was significantly higher than that in the IDH-mut group for both MET (p = 0.034) and CHO (p = 0.01). However, there was no significant difference in the ratio for FDG.CONCLUSIONSPET imaging using MET, CHO, and FDG was suggested to be informative for preoperatively differentiating gliomas according to the 2016 WHO classification, particularly for differentiating IDH-wt and IDH-mut tumors.

scholarly journals Texture Analysis in the Diagnosis of Primary Breast Cancer: Comparison of High-Resolution Dedicated Breast Positron Emission Tomography (dbPET) and Whole-Body PET/CT

2020 ◽  
Vol 7 ◽  
Author(s):  
Yoko Satoh ◽  
Kenji Hirata ◽  
Daiki Tamada ◽  
Satoshi Funayama ◽  
Hiroshi Onishi
Keyword(s):  
Breast Cancer ◽  
Positron Emission Tomography ◽  
High Resolution ◽  
Texture Analysis ◽  
Texture Features ◽  
Emission Tomography ◽  
Whole Body ◽  
Tumor Characteristics ◽  
Positron Emission ◽  
Pet Ct

Objective: This retrospective study aimed to compare the ability to classify tumor characteristics of breast cancer (BC) of positron emission tomography (PET)-derived texture features between dedicated breast PET (dbPET) and whole-body PET/computed tomography (CT).Methods: Forty-four BCs scanned by both high-resolution ring-shaped dbPET and whole-body PET/CT were analyzed. The primary BC was extracted with a standardized uptake value (SUV) threshold segmentation method. On both dbPET and PET/CT images, 38 texture features were computed; their ability to classify tumor characteristics such as tumor (T)-category, lymph node (N)-category, molecular subtype, and Ki67 levels was compared. The texture features were evaluated using univariate and multivariate analyses following principal component analysis (PCA). AUC values were used to evaluate the diagnostic power of the computed texture features to classify BC characteristics.Results: Some texture features of dbPET and PET/CT were different between Tis-1 and T2-4 and between Luminal A and other groups, respectively. No association with texture features was found in the N-category or Ki67 level. In contrast, receiver-operating characteristic analysis using texture features' principal components showed that the AUC for classification of any BC characteristics were equally good for both dbPET and whole-body PET/CT.Conclusions: PET-based texture analysis of dbPET and whole-body PET/CT may have equally good classification power for BC.

scholarly journals Impact of metabolic indices of 18F-fluorodeoxyglucose positron emission tomography/computed tomography on post transplantation recurrence of hepatocellular carcinoma.

2021 ◽  
Author(s):  
Astrid Bauschke ◽  
Annelore Altendorf-Hofmann ◽  
Lukas Brückner ◽  
Robert Drescher ◽  
Martin Freesmeyer ◽  
...  
Keyword(s):  
Computed Tomography ◽  
Hepatocellular Carcinoma ◽  
Positron Emission Tomography ◽  
Overall Survival ◽  
Standardized Uptake Value ◽  
Emission Tomography ◽  
Fluorodeoxyglucose Positron Emission Tomography ◽  
Recurrence Rates ◽  
Positron Emission ◽  
Fluorodeoxyglucose Positron Emission

Abstract Background Tumor recurrence is the leading cause of death after liver transplantation in patients with hepatocellular carcinoma. There is an ongoing debate as to whether metabolic indices such as tumor to liver standardized uptake value ratio in 18 F-fluorodeoxyglucose positron emission tomography/computed tomography of the primary tumor can identify patients outside the Milan criteria with as low recurrence rates as patients inside Milan and thus should be added to the established prognostic factors. Methods This retrospective study analyzes 103 consecutive patients who underwent 18 F fluorodeoxyglucose positron emission tomography/computed tomography before liver transplantation for hepatocellular carcinoma using data of clinical tumor registry. Primary endpoints were overall survival and 10-year cumulative recurrence rates. Results Tumor to liver standardized uptake value ratio of the primary tumor was statistically significant higher in Milan out tumors, “up-to-seven” out tumors, grade 3 tumors, alpha-fetoprotein level >400 ng/ml and lesions upwarts 5cm in diameter. Factors with statistically significant influence on the 10-year overall survival in the univariate analysis were Milan, up-to-seven” criteria, number of lesions and pT-category. COX regression analysis did not show independently statistically significant factors for 10-year overall survival. Milan, “up-to-seven” criteria, grade, pV, number of lesions, size of lesion, pT-category, tumor to liver standardized uptake value ratio influenced 10-year cumulative recurrence rates statistically significantly. Tumor to liver standardized uptake value ratio, grade and pT-category proved to be independently statistically significant factors for 10-year cumulative recurrence rates. Conclusions Our study suggests that tumor to liver standardized uptake value standardized uptake value ratio in 18 F-fluorodeoxyglucose positron emission tomography/computed tomography is an independent prognostic factor in transplanted patients with hepatocellular carcinoma and might be helpful in estimating the risk of recurrence for patients scheduled for liver transplantation.

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