Cargando…

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

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 imag...

Descripción completa

Detalles Bibliográficos
Autores principales: Sun, Yi-Wen, Ji, Chang-Feng, Wang, Han, He, Jian, Liu, Song, Ge, Yun, Zhou, Zheng-Yang
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Lippincott Williams & Wilkins 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7909296/
https://www.ncbi.nlm.nih.gov/pubmed/33230019
http://dx.doi.org/10.1097/CM9.0000000000001206
_version_ 1783655902695391232
author Sun, Yi-Wen
Ji, Chang-Feng
Wang, Han
He, Jian
Liu, Song
Ge, Yun
Zhou, Zheng-Yang
author_facet Sun, Yi-Wen
Ji, Chang-Feng
Wang, Han
He, Jian
Liu, Song
Ge, Yun
Zhou, Zheng-Yang
author_sort Sun, Yi-Wen
collection PubMed
description 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: Inertia(GLCM) 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 inertia(GLCM) 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. Entropy(GLCM12) 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: Inertia(GLCM) and entropy(GLCM) 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.
format Online
Article
Text
id pubmed-7909296
institution National Center for Biotechnology Information
language English
publishDate 2021
publisher Lippincott Williams & Wilkins
record_format MEDLINE/PubMed
spelling pubmed-79092962021-03-01 Differentiating gastric cancer and gastric lymphoma using texture analysis (TA) of positron emission tomography (PET) Sun, Yi-Wen Ji, Chang-Feng Wang, Han He, Jian Liu, Song Ge, Yun Zhou, Zheng-Yang Chin Med J (Engl) Original Articles 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: Inertia(GLCM) 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 inertia(GLCM) 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. Entropy(GLCM12) 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: Inertia(GLCM) and entropy(GLCM) 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. Lippincott Williams & Wilkins 2021-02-20 2020-11-18 /pmc/articles/PMC7909296/ /pubmed/33230019 http://dx.doi.org/10.1097/CM9.0000000000001206 Text en Copyright © 2021 The Chinese Medical Association, produced by Wolters Kluwer, Inc. under the CC-BY-NC-ND license. http://creativecommons.org/licenses/by-nc-nd/4.0 This is an open access article distributed under the terms of the Creative Commons Attribution-Non Commercial-No Derivatives License 4.0 (CCBY-NC-ND), where it is permissible to download and share the work provided it is properly cited. The work cannot be changed in any way or used commercially without permission from the journal. http://creativecommons.org/licenses/by-nc-nd/4.0
spellingShingle Original Articles
Sun, Yi-Wen
Ji, Chang-Feng
Wang, Han
He, Jian
Liu, Song
Ge, Yun
Zhou, Zheng-Yang
Differentiating gastric cancer and gastric lymphoma using texture analysis (TA) of positron emission tomography (PET)
title 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_short 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)
topic Original Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7909296/
https://www.ncbi.nlm.nih.gov/pubmed/33230019
http://dx.doi.org/10.1097/CM9.0000000000001206
work_keys_str_mv AT sunyiwen differentiatinggastriccancerandgastriclymphomausingtextureanalysistaofpositronemissiontomographypet
AT jichangfeng differentiatinggastriccancerandgastriclymphomausingtextureanalysistaofpositronemissiontomographypet
AT wanghan differentiatinggastriccancerandgastriclymphomausingtextureanalysistaofpositronemissiontomographypet
AT hejian differentiatinggastriccancerandgastriclymphomausingtextureanalysistaofpositronemissiontomographypet
AT liusong differentiatinggastriccancerandgastriclymphomausingtextureanalysistaofpositronemissiontomographypet
AT geyun differentiatinggastriccancerandgastriclymphomausingtextureanalysistaofpositronemissiontomographypet
AT zhouzhengyang differentiatinggastriccancerandgastriclymphomausingtextureanalysistaofpositronemissiontomographypet