Lung Adenocarcinoma at CT with 0.25-mm Section Thickness and a 2048 Matrix: High-Spatial-Resolution Imaging for Predicting Invasiveness-Reference-Cited by-同舟云学术

Lung Adenocarcinoma at CT with 0.25-mm Section Thickness and a 2048 Matrix: High-Spatial-Resolution Imaging for Predicting Invasiveness

Published:2020-11 Issue:2 Volume:297 Page:462-471
ISSN:0033-8419
Container-title:Radiology
language:en
Short-container-title:Radiology

Author:

Yanagawa Masahiro¹^ORCID,Tsubamoto Mitsuko¹,Satoh Yukihisa¹^ORCID,Hata Akinori¹^ORCID,Miyata Tomo¹,Yoshida Yuriko¹^ORCID,Kikuchi Noriko¹^ORCID,Kurakami Hiroyuki¹^ORCID,Tomiyama Noriyuki¹^ORCID

Affiliation:

1. From the Department of Radiology, Osaka University Graduate School of Medicine, 2-2 Yamadaoka, Suita-city, Osaka 565-0871, Japan (M.Y., M.T., Y.S., A.H., T.M., Y.Y., N.K., N.T.); and Department of Medical Innovation, Osaka University, Suita-city, Osaka, Japan (H.K.).

Publisher

Radiological Society of North America (RSNA)

Subject

Radiology, Nuclear Medicine and imaging

Link

http://pubs.rsna.org/doi/pdf/10.1148/radiol.2020201911

Reference26 articles.

1. Cancer statistics, 2019

2. Non-Small Cell Lung Cancer: Epidemiology, Risk Factors, Treatment, and Survivorship

3. International Association for the Study of Lung Cancer/American Thoracic Society/European Respiratory Society International Multidisciplinary Classification of Lung Adenocarcinoma

4. Invasive Size is an Independent Predictor of Survival in Pulmonary Adenocarcinoma

5. The prognostic role of pathologic invasive component size, excluding lepidic growth, in stage I lung adenocarcinoma

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