Breast ImagingTexture Analysis of Computed Tomography Images in the Lung of Patients With Breast CancerHan, Meng MB∗; Qi, Yana MD†; Cui, Xiaoxiao MD‡; Li, Ranran MD†; Hou, Ruigang MM∗; Dun, Aishe MM∗ Author Information From the ∗School of Basic Medical Sciences, Shandong First Medical University & Shandong Academy of Medical Sciences, Taian †Cancer Therapy and Research Center, Shandong Provincial Hospital, Shandong First Medical University & Shandong Academy of Medical Sciences ‡School of Information Science and Engineering, Shandong University, Jinan, People's Republic of China. Received for publication January 23, 2021; accepted April 8, 2021. Correspondence to: Ruigang Hou, MM, School of Basic Medical Sciences, Shandong First Medical University & Shandong Academy of Medical Sciences, 2 Yingsheng East Road, 271000 Taian, China (e-mail: [email protected]); Aishe Dun, MM, School of Basic Medical Sciences, Shandong First Medical University & Shandong Academy of Medical Sciences, 2 Yingsheng East Road, 271000 Taian, China (e-mail: [email protected]). The authors declare no conflict of interest. This study was supported by the National College Students' Innovative Training Plan Programme (201910439061). R.H. and A.D. are co-first authors of the article. Journal of Computer Assisted Tomography: 11/12 2021 - Volume 45 - Issue 6 - p 837-842 doi: 10.1097/RCT.0000000000001198 Buy Metrics Abstract Objective The aim of this study was to investigate whether the texture features of lung computed tomography images were altered by primary breast cancer without pulmonary metastasis. Methods Texture analysis was performed on the regions of interest of lung computed tomography images from 36 patients with breast cancer and 36 healthy controls. Texture parameters between subjects with different clinical stages and hormone receptor (HR) statuses in patients with breast cancer were analyzed. Results Three texture parameters (mean, SD, and variance) were significantly different between patients with breast cancer and healthy controls and between preoperative and postoperative stages in patients with breast cancer. All 3 parameters showed an increasing trend under the tumor-bearing state. These parameters were significantly higher in the stage III + IV group than in the stage I + II group. The variance parameter was significantly higher in the HR-negative group than in the HR-positive group. Conclusions Texture analysis may serve as a novel additional tool for discovering conventionally invisible changes in the lung tissue of patients with breast cancer. Copyright © 2021 Wolters Kluwer Health, Inc. All rights reserved.