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Computed tomography radiomics identification of T1-2 and T3-4 stages of esophageal squamous cell carcinoma: two-dimensional or three-dimensional?

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机构: [1]Department of Radiology, The Fourth Hospital of HebeiMedical University, Shijiazhuang 050000, Hebei Province,People’s Republic of China [2]Department of Radiotherapy, The Fourth Hospital of HebeiMedical University, Shijiazhuang 050000, Hebei Province,People’s Republic of China [3]Department of Pathology, The Fourth Hospital of HebeiMedical University, Shijiazhuang 050000, Hebei Province,People’s Republic of China [4]Department of Thoracic Surgery, The Fourth Hospitalof Hebei Medical University, Shijiazhuang 050000,Hebei Province, People’s Republic of China [5]GE Healthcare China, Beijing 100176,People’s Republic of China
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关键词: Esophageal squamous cell carcinoma  Tumor stage  Computed tomography  Radiomics

摘要:
To evaluate two-dimensional (2D) and three-dimensional (3D) computed tomography (CT) radiomics analysis for the T stage of esophageal squamous cell carcinoma (ESCC).398 patients with pathologically confirmed ESCC were divided into training and testing sets. All patients underwent chest CT scans preoperatively. For each tumor, based on CT images, a 2D region of interest (ROI) was outlined on the largest cross-sectional area, and a 3D ROI was outlined layer by layer on each section of the tumor. The radiomics platform was used for feature extraction. For feature selection, stepwise logistic regression was used. The receiver operating characteristic (ROC) curve was used to assess the diagnostic performance of the 2D radiomics model versus the 3D radiomics model. The differences were compared using the DeLong test. The value of the clinical utility of the two radiomics models was evaluated.1595 radiomics features were extracted. After screening, two radiomics models were constructed. In the training set, the difference between the area under the curve (AUC) of the 2D radiomics model (AUC = 0.831) and the 3D radiomics model (AUC = 0.830) was not statistically significant (p = 0.973). In the testing set, the difference between the AUC of the 2D radiomics model (AUC = 0.807) and the 3D radiomics model (AUC = 0.797) was also not statistically significant (p = 0.748). A 2D model was equally useful as a 3D model in clinical situations.The performance of 2D radiomics model is comparable to that of 3D radiomics model in distinguishing between the T1-2 and T3-4 stages of ESCC. In addition, 2D radiomics model may be a more feasible option due to the shorter time required for segmenting the ROI.© 2023. The Author(s).

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出版当年[2025]版:
大类 | 3 区 医学
小类 | 4 区 核医学
最新[2025]版:
大类 | 3 区 医学
小类 | 4 区 核医学
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最新[2023]版:
Q2 RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING

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第一作者机构: [1]Department of Radiology, The Fourth Hospital of HebeiMedical University, Shijiazhuang 050000, Hebei Province,People’s Republic of China
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