Literature DB >> 31216199

Attenuation and Morphologic Characteristics Distinguishing a Ground-Glass Nodule Measuring 5-10 mm in Diameter as Invasive Lung Adenocarcinoma on Thin-Slice CT.

Yi Zhan1, Xueqing Peng2, Fei Shan1, Mingxiang Feng3, Yuxin Shi1, Lei Liu2, Zhiyong Zhang1.   

Abstract

OBJECTIVE. The purpose of this study is to comprehensively investigate the role of multiple features seen on thin-section CT (TSCT) in the differential diagnosis of ground-glass nodules (GGNs) measuring 5-10 mm in diameter as invasive adenocarcinoma (IAC). MATERIALS AND METHODS. The TSCT features of 313 surgically diagnosed GGNs from 288 patients were retrospectively reviewed. A logistic regression model was applied, and the AUC values for the model and the size and attenuation of the lesions were compared using ROC curve analysis. RESULTS. A total of 247 lung adenocarcinomas in situ (AISs) and minimally invasive adenocarcinomas (MIAs) (hereafter referred to as the AIS-MIA group) and 66 invasive adenocarcinomas (IACs) were identified. Compared with the AIS-MIA group, the IAC groups were significantly larger in size and had higher attenuation values, a higher frequency of mixed GGNs (all p < 0.001), bubblelike appearance, spiculation, pleural indentation, different locations, and a lower frequency of clear tumor-lung interface (all p < 0.05). The logistic model included size and attenuation (both p < 0.001; odds ratio [OR], 1.872 and 1.009, respectively) as well as tumor-lung interface (p = 0.001; OR, 0.242), bubblelike appearance (p < 0.05; OR, 2.205), and type of nodule. The AUC value for the logistic model was 0.847 (sensitivity, 80.3%; specificity, 81.0%) and was significantly higher than that for size or attenuation (both p < 0.01). CONCLUSION. Radiologic features could help in the differential diagnosis of a GGN that was 5-10 mm in diameter as IAC versus AIS or MIA. GGNs larger than 8.12 mm and with attenuation greater than -449.52 HU were more likely to be IAC.

Entities:  

Keywords:  differential diagnosis; ground-glass nodule; invasive adenocarcinoma; lung cancer; thin-slice CT

Year:  2019        PMID: 31216199     DOI: 10.2214/AJR.18.21008

Source DB:  PubMed          Journal:  AJR Am J Roentgenol        ISSN: 0361-803X            Impact factor:   3.959


  11 in total

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Journal:  Gen Thorac Cardiovasc Surg       Date:  2022-03-18

2.  Natural history of pathologically confirmed pulmonary subsolid nodules with deep learning-assisted nodule segmentation.

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4.  Subsolid pulmonary nodules: Controversy and perspective.

Authors:  Mark M Hammer; Hiroto Hatabu
Journal:  Eur J Radiol Open       Date:  2020-09-04

5.  Radiomic signature based on CT imaging to distinguish invasive adenocarcinoma from minimally invasive adenocarcinoma in pure ground-glass nodules with pleural contact.

Authors:  Yining Jiang; Siyu Che; Shuangchun Ma; Xinyan Liu; Yan Guo; Ailian Liu; Guosheng Li; Zhiyong Li
Journal:  Cancer Imaging       Date:  2021-01-06       Impact factor: 3.909

6.  CT-Assisted Improvements in the Accuracy of the Intraoperative Frozen Section Examination of Ground-Glass Density Nodules.

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Journal:  Comput Math Methods Med       Date:  2022-01-07       Impact factor: 2.238

7.  Identification of pathological subtypes of early lung adenocarcinoma based on artificial intelligence parameters and CT signs.

Authors:  Weiyuan Fang; Guorui Zhang; Yali Yu; Hongjie Chen; Hong Liu
Journal:  Biosci Rep       Date:  2022-01-28       Impact factor: 3.840

8.  Differentiation of persistent pulmonary subsolid nodules with a solid component smaller than 6 mm: to be invasive adenocarcinoma or not to be?

Authors:  Jong Hyuk Lee; Chang Min Park
Journal:  J Thorac Dis       Date:  2020-05       Impact factor: 3.005

9.  Invasive Prediction of Ground Glass Nodule Based on Clinical Characteristics and Radiomics Feature.

Authors:  Hui Zheng; Hanfei Zhang; Shan Wang; Feng Xiao; Meiyan Liao
Journal:  Front Genet       Date:  2022-01-06       Impact factor: 4.599

10.  Comparison of Diagnostic Performance of Spread Through Airspaces of Lung Adenocarcinoma Based on Morphological Analysis and Perinodular and Intranodular Radiomic Features on Chest CT Images.

Authors:  Lin Qi; Xiaohu Li; Linyang He; Guohua Cheng; Yongjun Cai; Ke Xue; Ming Li
Journal:  Front Oncol       Date:  2021-06-25       Impact factor: 6.244

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