Literature DB >> 23111378

Three-dimensional positron emission tomography image texture analysis of esophageal squamous cell carcinoma: relationship between tumor 18F-fluorodeoxyglucose uptake heterogeneity, maximum standardized uptake value, and tumor stage.

Xinzhe Dong1, Ligang Xing, Peipei Wu, Zheng Fu, Honglin Wan, Dengwang Li, Yong Yin, Xiaorong Sun, Jinming Yu.   

Abstract

OBJECTIVE: To explore the relationship of a new PET image parameter, (18)F-fluorodeoxyglucose ((18)F-FDG) uptake heterogeneity assessed by texture analysis, with maximum standardized uptake value (SUV(max)) and tumor TNM staging.
MATERIALS AND METHODS: Forty consecutive patients with esophageal squamous cell carcinoma were enrolled. All patients underwent whole-body preoperative (18)F-FDG PET/CT. Heterogeneity of intratumoral (18)F-FDG uptake was assessed on the basis of the textural features (entropy and energy) of the three-dimensional images using MATLAB software. The correlations between the textural parameters and SUV(max), histological grade, tumor location, and TNM stage were analyzed.
RESULTS: Tumors with higher SUV(max) were seen to be more heterogenous on (18)F-FDG uptake. Significant correlations were observed between T stage and SUV(max) (r(s)=0.390, P=0.013), entropy (rs=0.693, P<0.001), and energy (r(s)=-0.469, P=0.002). Correlations were also found between SUV(max), entropy, energy, and N stage (r(s)=0.326, P=0.04; r(s)=0.501, P=0.001; r(s)=-0.413, P=0.008). The American Joint Committee on Cancer stage correlated significantly with all metabolic parameters. The receiver-operating characteristic curve demonstrated an entropy of 4.699 as the optimal cutoff point for detecting tumors above stage II(b) with an areas under the ROC curve of 0.789 (P<0.001).
CONCLUSION: This study provides initial evidence for the relationship between the new parameter of tumor uptake heterogeneity and the commonly used simplistic parameter of SUV and tumor stage. Our findings suggest a complementary role of these parameters in the staging and prognosis of esophageal squamous cell carcinoma.

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Year:  2013        PMID: 23111378     DOI: 10.1097/MNM.0b013e32835ae50c

Source DB:  PubMed          Journal:  Nucl Med Commun        ISSN: 0143-3636            Impact factor:   1.690


  33 in total

1.  The precision of textural analysis in (18)F-FDG-PET scans of oesophageal cancer.

Authors:  Georgia Doumou; Musib Siddique; Charalampos Tsoumpas; Vicky Goh; Gary J Cook
Journal:  Eur Radiol       Date:  2015-05-21       Impact factor: 5.315

Review 2.  Radiomics in Oncological PET/CT: Clinical Applications.

Authors:  Jeong Won Lee; Sang Mi Lee
Journal:  Nucl Med Mol Imaging       Date:  2017-10-20

Review 3.  Recent Trends in PET Image Interpretations Using Volumetric and Texture-based Quantification Methods in Nuclear Oncology.

Authors:  Muhammad Kashif Rahim; Sung Eun Kim; Hyeongryul So; Hyung Jun Kim; Gi Jeong Cheon; Eun Seong Lee; Keon Wook Kang; Dong Soo Lee
Journal:  Nucl Med Mol Imaging       Date:  2014-01-22

4.  Comparison of Contrast-Enhanced CT and [18F]FDG PET/CT Analysis Using Kurtosis and Skewness in Patients with Primary Colorectal Cancer.

Authors:  Franca Wagner; Yahya Ali Hakami; Geoffrey Warnock; Gabriel Fischer; Martin W Huellner; Patrick Veit-Haibach
Journal:  Mol Imaging Biol       Date:  2017-10       Impact factor: 3.488

5.  Intratumoral Metabolic Heterogeneity and Other Quantitative 18F-FDG PET/CT Parameters for Prognosis Prediction in Esophageal Cancer.

Authors:  Akilan Gopal; Yin Xi; Rathan M Subramaniam; Daniella F Pinho
Journal:  Radiol Imaging Cancer       Date:  2020-12-18

6.  Can Laws Be a Potential PET Image Texture Analysis Approach for Evaluation of Tumor Heterogeneity and Histopathological Characteristics in NSCLC?

Authors:  Seyhan Karacavus; Bülent Yılmaz; Arzu Tasdemir; Ömer Kayaaltı; Eser Kaya; Semra İçer; Oguzhan Ayyıldız
Journal:  J Digit Imaging       Date:  2018-04       Impact factor: 4.056

7.  Texture analysis of 18F-FDG PET/CT to predict tumour response and prognosis of patients with esophageal cancer treated by chemoradiotherapy.

Authors:  Masatoyo Nakajo; Megumi Jinguji; Yoshiaki Nakabeppu; Masayuki Nakajo; Ryutarou Higashi; Yoshihiko Fukukura; Ken Sasaki; Yasuto Uchikado; Shoji Natsugoe; Takashi Yoshiura
Journal:  Eur J Nucl Med Mol Imaging       Date:  2016-09-10       Impact factor: 9.236

Review 8.  Applications and limitations of radiomics.

Authors:  Stephen S F Yip; Hugo J W L Aerts
Journal:  Phys Med Biol       Date:  2016-06-08       Impact factor: 3.609

9.  The emerging field of radiomics in esophageal cancer: current evidence and future potential.

Authors:  Peter S N van Rossum; Cai Xu; David V Fried; Lucas Goense; Laurence E Court; Steven H Lin
Journal:  Transl Cancer Res       Date:  2016-08       Impact factor: 1.241

10.  Radiomics approach for preoperative identification of stages I-II and III-IV of esophageal cancer.

Authors:  Lei Wu; Cong Wang; Xianzheng Tan; Zixuan Cheng; Ke Zhao; Lifen Yan; Yanli Liang; Zaiyi Liu; Changhong Liang
Journal:  Chin J Cancer Res       Date:  2018-08       Impact factor: 5.087

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