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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...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Lippincott Williams & Wilkins
2021
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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 |
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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 |
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