Differentiating gastric cancer and gastric lymphoma using texture analysis (TA) of positron emission tomography (PET)

Abstract. Background:. Texture analysis (TA) can quantify intra-tumor heterogeneity using standard medical images. The present study aimed to assess the application of positron emission tomography (PET) TA in the differential diagnosis of gastric cancer and gastric lymphoma. Methods:. The pre-treatm...

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Main Authors: Yi-Wen Sun, Chang-Feng Ji, Han Wang, Jian He, Song Liu, Yun Ge, Zheng-Yang Zhou, Peng Lyu
Format: Article
Language:English
Published: Wolters Kluwer 2021-02-01
Series:Chinese Medical Journal
Online Access:http://journals.lww.com/10.1097/CM9.0000000000001206
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spelling doaj-36a7eca8aa644c708d966c81068508722021-02-26T03:48:16ZengWolters KluwerChinese Medical Journal0366-69992542-56412021-02-01134443944710.1097/CM9.0000000000001206202102200-00012Differentiating gastric cancer and gastric lymphoma using texture analysis (TA) of positron emission tomography (PET)Yi-Wen SunChang-Feng JiHan WangJian HeSong LiuYun GeZheng-Yang ZhouPeng LyuAbstract. Background:. Texture analysis (TA) can quantify intra-tumor heterogeneity using standard medical images. The present study aimed to assess the application of positron emission tomography (PET) TA in the differential diagnosis of gastric cancer and gastric lymphoma. Methods:. The pre-treatment PET images of 79 patients (45 gastric cancer, 34 gastric lymphoma) between January 2013 and February 2018 were retrospectively reviewed. Standard uptake values (SUVs), first-order texture features, and second-order texture features of the grey-level co-occurrence matrix (GLCM) were analyzed. The differences in features among different groups were analyzed by the two-way Mann-Whitney test, and receiver operating characteristic (ROC) analysis was used to estimate the diagnostic efficacy. Results:. InertiaGLCM was significantly lower in gastric cancer than that in gastric lymphoma (4975.61 vs. 11,425.30, z = −3.238, P = 0.001), and it was found to be the most discriminating texture feature in differentiating gastric lymphoma and gastric cancer. The area under the curve (AUC) of inertiaGLCM was higher than the AUCs of SUVmax and SUVmean (0.714 vs. 0.649 and 0.666, respectively). SUVmax and SUVmean were significantly lower in low-grade gastric lymphoma than those in high grade gastric lymphoma (3.30 vs. 11.80, 2.40 vs. 7.50, z = −2.792 and −3.007, P = 0.005 and 0.003, respectively). SUVs and first-order grey-level intensity features were not significantly different between low-grade gastric lymphoma and gastric cancer. EntropyGLCM12 was significantly lower in low-grade gastric lymphoma than that in gastric cancer (6.95 vs. 9.14, z = −2.542, P = 0.011) and had an AUC of 0.770 in the ROC analysis of differentiating low-grade gastric lymphoma and gastric cancer. Conclusions:. InertiaGLCM and entropyGLCM were the most discriminating features in differentiating gastric lymphoma from gastric cancer and low-grade gastric lymphoma from gastric cancer, respectively. PET TA can improve the differential diagnosis of gastric neoplasms, especially in tumors with similar degrees of fluorodeoxyglucose uptake.http://journals.lww.com/10.1097/CM9.0000000000001206
collection DOAJ
language English
format Article
sources DOAJ
author Yi-Wen Sun
Chang-Feng Ji
Han Wang
Jian He
Song Liu
Yun Ge
Zheng-Yang Zhou
Peng Lyu
spellingShingle Yi-Wen Sun
Chang-Feng Ji
Han Wang
Jian He
Song Liu
Yun Ge
Zheng-Yang Zhou
Peng Lyu
Differentiating gastric cancer and gastric lymphoma using texture analysis (TA) of positron emission tomography (PET)
Chinese Medical Journal
author_facet Yi-Wen Sun
Chang-Feng Ji
Han Wang
Jian He
Song Liu
Yun Ge
Zheng-Yang Zhou
Peng Lyu
author_sort Yi-Wen Sun
title Differentiating gastric cancer and gastric lymphoma using texture analysis (TA) of positron emission tomography (PET)
title_short Differentiating gastric cancer and gastric lymphoma using texture analysis (TA) of positron emission tomography (PET)
title_full Differentiating gastric cancer and gastric lymphoma using texture analysis (TA) of positron emission tomography (PET)
title_fullStr Differentiating gastric cancer and gastric lymphoma using texture analysis (TA) of positron emission tomography (PET)
title_full_unstemmed Differentiating gastric cancer and gastric lymphoma using texture analysis (TA) of positron emission tomography (PET)
title_sort differentiating gastric cancer and gastric lymphoma using texture analysis (ta) of positron emission tomography (pet)
publisher Wolters Kluwer
series Chinese Medical Journal
issn 0366-6999
2542-5641
publishDate 2021-02-01
description Abstract. Background:. Texture analysis (TA) can quantify intra-tumor heterogeneity using standard medical images. The present study aimed to assess the application of positron emission tomography (PET) TA in the differential diagnosis of gastric cancer and gastric lymphoma. Methods:. The pre-treatment PET images of 79 patients (45 gastric cancer, 34 gastric lymphoma) between January 2013 and February 2018 were retrospectively reviewed. Standard uptake values (SUVs), first-order texture features, and second-order texture features of the grey-level co-occurrence matrix (GLCM) were analyzed. The differences in features among different groups were analyzed by the two-way Mann-Whitney test, and receiver operating characteristic (ROC) analysis was used to estimate the diagnostic efficacy. Results:. InertiaGLCM was significantly lower in gastric cancer than that in gastric lymphoma (4975.61 vs. 11,425.30, z = −3.238, P = 0.001), and it was found to be the most discriminating texture feature in differentiating gastric lymphoma and gastric cancer. The area under the curve (AUC) of inertiaGLCM was higher than the AUCs of SUVmax and SUVmean (0.714 vs. 0.649 and 0.666, respectively). SUVmax and SUVmean were significantly lower in low-grade gastric lymphoma than those in high grade gastric lymphoma (3.30 vs. 11.80, 2.40 vs. 7.50, z = −2.792 and −3.007, P = 0.005 and 0.003, respectively). SUVs and first-order grey-level intensity features were not significantly different between low-grade gastric lymphoma and gastric cancer. EntropyGLCM12 was significantly lower in low-grade gastric lymphoma than that in gastric cancer (6.95 vs. 9.14, z = −2.542, P = 0.011) and had an AUC of 0.770 in the ROC analysis of differentiating low-grade gastric lymphoma and gastric cancer. Conclusions:. InertiaGLCM and entropyGLCM were the most discriminating features in differentiating gastric lymphoma from gastric cancer and low-grade gastric lymphoma from gastric cancer, respectively. PET TA can improve the differential diagnosis of gastric neoplasms, especially in tumors with similar degrees of fluorodeoxyglucose uptake.
url http://journals.lww.com/10.1097/CM9.0000000000001206
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