دورية أكاديمية
أعرض في EDS

Texture analysis based on CT for predicting the differentiation of esophageal squamous cancer: An observational study.

التفاصيل البيبلوغرافية
العنوان: Texture analysis based on CT for predicting the differentiation of esophageal squamous cancer: An observational study.
المؤلفون: Wang D; Department of Thoracic Surgery, The First Affiliated Hospital of Hebei North University, Zhangjiakou, China., Shang Z; University College London, London, United Kingdom., Chen R; Department of Medicine, Hebei North University, Zhangjiakou, China., Yang Y; Department of Medicine, Hebei North University, Zhangjiakou, China., Su Y; Department of Nuclear medicine, The First Affiliated Hospital of Hebei North University, Zhangjiakou, China., Jia P; Department of Medical Imaging, Beijing Huairou Hospital, Beijing, China., Liu Y; Department of Operating rooms, The First Affiliated Hospital of Hebei North University, Zhangjiakou, China., Yang F; Department of Medical Imaging, The First Affiliated Hospital of Hebei North University, Zhangjiakou, China.
المصدر: Medicine [Medicine (Baltimore)] 2024 Sep 20; Vol. 103 (38), pp. e39683.
نوع المنشور: Journal Article; Observational Study
اللغة: English
بيانات الدورية: Publisher: Lippincott Williams & Wilkins Country of Publication: United States NLM ID: 2985248R Publication Model: Print Cited Medium: Internet ISSN: 1536-5964 (Electronic) Linking ISSN: 00257974 NLM ISO Abbreviation: Medicine (Baltimore) Subsets: MEDLINE
أسماء مطبوعة: Original Publication: Hagerstown, Md : Lippincott Williams & Wilkins
مواضيع طبية MeSH: Esophageal Neoplasms*/diagnostic imaging , Esophageal Neoplasms*/pathology , Tomography, X-Ray Computed*/methods , Esophageal Squamous Cell Carcinoma*/diagnostic imaging , Esophageal Squamous Cell Carcinoma*/pathology, Humans ; Male ; Female ; Middle Aged ; Aged ; ROC Curve ; Diagnosis, Differential ; Adult ; Feasibility Studies ; Carcinoma, Squamous Cell/diagnostic imaging ; Carcinoma, Squamous Cell/pathology ; Retrospective Studies
مستخلص: To explore the feasibility and application value of texture analysis based on computed tomography (CT) for predicting the differentiation of esophageal squamous cell carcinoma (ESCC). Patients diagnosed with ESCC who underwent chest contrast-enhanced CT before treatment were selected. Based on the pathological results, the patients were stratified into poorly differentiated and moderately well-differentiated groups. FireVoxel software was used to analyze the region of interest based on venous phase CT images. Texture parameters including the mean, median, standard deviation (SD), inhomogeneity, skewness, kurtosis, and entropy were obtained automatically. Differences in the texture parameters and their relationship with the degree of differentiation between the 2 groups were analyzed. The value of CT texture parameters in identifying poor differentiation and moderate-well differentiation of esophageal cancer was analyzed using the ROC curve. A total of 48 patients with ESCC were included, including 24 patients in the poorly differentiated group and 24 patients in the moderate-well-differentiated group. There were negative correlations between SD, inhomogeneity, entropy, and the degree of differentiation of esophageal cancer (P < .05). The correlation of inhomogeneity was the highest (r = -0.505, P < .001). SD, inhomogeneity, and entropy could effectively distinguish between the poorly and moderately well-differentiated groups, with statistically significant differences between the 2 groups (P < .05). The best critical values for SD, inhomogeneity, and entropy were 17.538, 0.017, and 3.917, respectively. The areas under the ROC curve were 0.793, 0.792, and 0.729, respectively, with the SD and inhomogeneity being the best. The application of texture analysis on venous phase CT images holds promise as a method for forecasting the degree of differentiation in esophageal cancers, which could significantly contribute to the preoperative noninvasive evaluation of tumor differentiation.
Competing Interests: The authors declare no conflict of interest.
(Copyright © 2024 the Author(s). Published by Wolters Kluwer Health, Inc.)
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معلومات مُعتمدة: 20220585 Hebei Medical Science Research Project
تواريخ الأحداث: Date Created: 20240923 Date Completed: 20240923 Latest Revision: 20240924
رمز التحديث: 20240924
DOI: 10.1097/MD.0000000000039683
PMID: 39312368
قاعدة البيانات: MEDLINE
الوصف
تدمد:1536-5964
DOI:10.1097/MD.0000000000039683