Differentiating gastric cancer and gastric lymphoma using texture analysis (TA) of positron emission tomography (PET).
10.1097/CM9.0000000000001206
- VernacularTitle:Differentiating gastric cancer and gastric lymphoma using texture analysis (TA) of positron emission tomography (PET)
- Author:
Yi-Wen SUN
1
;
Chang-Feng JI
2
;
Han WANG
2
;
Jian HE
2
;
Song LIU
2
;
Yun GE
3
;
Zheng-Yang ZHOU
1
Author Information
1. Department of Nuclear Medicine, Nanjing Drum Tower Hospital Clinical College of Nanjing Medical University, Nanjing, Jiangsu 210008, China.
2. Department of Radiology, Nanjing Drum Tower Hospital Clinical College of Nanjing Medical University, Nanjing, Jiangsu 210008, China.
3. School of Electronic Science and Engineering, Nanjing University, Nanjing, Jiangsu 210093, China.
- Publication Type:Journal Article
- MeSH:
Fluorodeoxyglucose F18;
Humans;
Lymphoma, Non-Hodgkin;
Positron Emission Tomography Computed Tomography;
Positron-Emission Tomography;
ROC Curve;
Radiopharmaceuticals;
Retrospective Studies;
Stomach Neoplasms/diagnostic imaging*
- From:
Chinese Medical Journal
2020;134(4):439-447
- CountryChina
- Language:English
-
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.
