https://scholars.lib.ntu.edu.tw/handle/123456789/627200
標題: | CT-Based Radiomic Analysis for Preoperative Prediction of Tumor Invasiveness in Lung Adenocarcinoma Presenting as Pure Ground-Glass Nodule | 作者: | Kao, Tzu-Ning MIN-SHU HSIEH WEI-LI CHEN Yang, Chi-Fu Jeffrey Chuang, Ching-Chia XU-HENG CHIANG Chen, Yi-Chang Lee, Yi-Hsuan HSAO-HSUN HSU CHUNG-MING CHEN MONG-WEI LIN JIN-SHING CHEN |
關鍵字: | ground-glass nodule; invasiveness; lung adenocarcinoma; lung cancer surgery; radiomic feature analysis | 公開日期: | 29-十一月-2022 | 出版社: | MDPI | 卷: | 14 | 期: | 23 | 來源出版物: | Cancers | 摘要: | It remains a challenge to preoperatively forecast whether lung pure ground-glass nodules (pGGNs) have invasive components. We aimed to construct a radiomic model using tumor characteristics to predict the histologic subtype associated with pGGNs. We retrospectively reviewed clinicopathologic features of pGGNs resected in 338 patients with lung adenocarcinoma between 2011-2016 at a single institution. A radiomic prediction model based on forward sequential selection and logistic regression was constructed to differentiate adenocarcinoma in situ (AIS)/minimally invasive adenocarcinoma (MIA) from invasive adenocarcinoma. The study cohort included 133 (39.4%), 128 (37.9%), and 77 (22.8%) patients with AIS, MIA, and invasive adenocarcinoma (acinar 55.8%, lepidic 33.8%, papillary 10.4%), respectively. The majority (83.7%) underwent sublobar resection. There were no nodal metastases or tumor recurrence during a mean follow-up period of 78 months. Three radiomic features-cluster shade, homogeneity, and run-length variance-were identified as predictors of histologic subtype and were selected to construct a prediction model to classify the AIS/MIA and invasive adenocarcinoma groups. The model achieved accuracy, sensitivity, specificity, and AUC of 70.6%, 75.0%, 70.0%, and 0.7676, respectively. Applying the developed radiomic feature model to predict the histologic subtypes of pGGNs observed on CT scans can help clinically in the treatment selection process. |
URI: | https://scholars.lib.ntu.edu.tw/handle/123456789/627200 | ISSN: | 2072-6694 | DOI: | 10.3390/cancers14235888 |
顯示於: | 病理學科所 |
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