scholarly journals Application of Haralick texture features in brain [18F]-florbetapir positron emission tomography without reference region normalization

2017 ◽  
Vol Volume 12 ◽  
pp. 2077-2086 ◽  
Author(s):  
Desmond L Campbell ◽  
Hakmook Kang ◽  
Sepideh Shokouhi
Keyword(s):  
Positron Emission Tomography ◽  
Texture Features ◽  
Emission Tomography ◽  
Reference Region ◽  
Positron Emission

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 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.

scholarly journals The Simplified Reference Tissue Model with 18 F-Fallypride Positron Emission Tomography: Choice of Reference Region

2013 ◽  
Vol 12 (8) ◽  
pp. 7290.2013.00065 ◽  
Author(s):  
Kenji Ishibashi ◽  
Chelsea L. Robertson ◽  
Mark A. Mandelkern ◽  
Andrew T. Morgan ◽  
Edythe D. London
Keyword(s):  
Positron Emission Tomography ◽  
Emission Tomography ◽  
Reference Region ◽  
Reference Tissue ◽  
Tissue Model ◽  
Positron Emission ◽  
Reference Tissue Model ◽  
Simplified Reference Tissue Model

scholarly journals Positron Emission Tomography Quantification of [11C]-DASB Binding to the Human Serotonin Transporter: Modeling Strategies

2001 ◽  
Vol 21 (11) ◽  
pp. 1342-1353 ◽  
Author(s):  
Nathalie Ginovart ◽  
Alan A. Wilson ◽  
Jeffrey H. Meyer ◽  
Doug Hussey ◽  
Sylvain Houle
Keyword(s):  
Positron Emission Tomography ◽  
Serotonin Transporter ◽  
Quantitative Methods ◽  
Goodness Of Fit ◽  
Emission Tomography ◽  
Binding Potential ◽  
Reference Region ◽  
Time Activity ◽  
Healthy Humans ◽  
Positron Emission

[11C]-DASB, namely [11C]-3-amino-4-(2-dimethylaminomethyl-phenylsulfanyl)-benzonitrile, is a new highly selective radioligand for the in vivo visualization of the serotonin transporter (SERT) using positron emission tomography (PET). The current study evaluates different kinetic modeling strategies for quantification of [11C]-DASB binding in five healthy humans. Kinetic analyses of tissue data were performed with a one-tissue (1CM) and a two-tissue (2CM) compartment model. Time-activity curves were well described by a 1CM for all regions. A 2CM model with four parameters failed to converge reliably. Reliable fits of the data were obtained only if no more than three parameters were allowed to vary. However, even then, the rate constants k3 and k4 were estimated with poor precision. Only the ratio k3/k4 was stable. Goodness of fit was not improved by using a 2CM as compared with a 1CM. The minimal study duration required to obtain stable k3/k4 estimates was 80 minutes. For routine use of [11C]-DASB, several simplified methods using the cerebellum as a reference region to estimate nonspecific binding were also evaluated. The transient equilibrium, the linear graphical analysis, the ratio of target to reference region, and the simplified reference tissue methods all gave binding potential values consistent with those obtained with the 2CM. The suitability of [11C]-DASB for research on the SERT using PET is thus supported by the observations that tissue data can be described using a kinetic analysis and that simplified quantitative methods, using the cerebellum as reference, provide reliable estimates of SERT binding parameters.

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