Literature DB >> 28796590

Subsolid Lung Nodule Classification: A CT Criterion for Improving Interobserver Agreement.

Marie-Pierre Revel1, Inès Mannes1, Joseph Benzakoun1, Claude Guinet1, Thomas Léger1, Philippe Grenier1, Audrey Lupo1, Ludovic Fournel1, Guillaume Chassagnon1, Sébastien Bommart1.   

Abstract

Purpose To evaluate an objective computed tomographic (CT) criterion for distinguishing between part-solid (PS) and nonsolid (NS) lung nodules. Materials and Methods This study received institutional review board approval, and patients gave informed consent. Preoperative CT studies in all patients who underwent surgery for subsolid nodules between 2008 and 2015 were first reviewed by two senior radiologists, who subjectively classified the nodules as PS or NS. A second reading performed 1 month later used predefined classification criteria and involved a third senior radiologist as well as three junior radiologists. Subsolid nodules were classified as PS if a solid portion was detectable in the mediastinal window setting (nonmeasurable, < 50%, or > 50% of the entire nodule) and were otherwise classified as NS (subclassified as pure or heterogeneous). Interreader agreement was assessed with κ statistics and the intraclass correlation coefficient (ICC). Results A total of 99 nodules measuring a median of 20 mm (range, 5-47 mm) in lung window CT images were analyzed. Senior radiologist agreement on the PS/NS distinction increased from moderate (κ = 0.54; 95% confidence interval [CI]: 0.37, 0.71) to excellent (κ = 0.89; 95% CI: 0.80, 0.98) between the first and second readings. At the second readings, agreement among senior and junior radiologists was excellent for PS/NS distinction (ICC = 0.87; 95% CI: 0.83, 0.90) and for subcategorization (ICC = 0.82; 95% CI: 0.77, 0.87). When a solid portion was measurable in the mediastinal window, the specificity for adenocarcinoma invasiveness ranged from 86% to 96%. Conclusion Detection of a solid portion in the mediastinal window setting allows subsolid nodules to be classified as PS with excellent interreader agreement. If the solid portion is measurable, the specificity for adenocarcinoma invasiveness is high. © RSNA, 2017 Online supplemental material is available for this article.

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Year:  2017        PMID: 28796590     DOI: 10.1148/radiol.2017170044

Source DB:  PubMed          Journal:  Radiology        ISSN: 0033-8419            Impact factor:   11.105


  10 in total

1.  Implication of total tumor size on the prognosis of patients with clinical stage IA lung adenocarcinomas appearing as part-solid nodules: Does only the solid portion size matter?

Authors:  Hyungjin Kim; Jin Mo Goo; Young Joo Suh; Chang Min Park; Young Tae Kim
Journal:  Eur Radiol       Date:  2018-08-21       Impact factor: 5.315

2.  Predicting the histological invasiveness of pulmonary adenocarcinoma manifesting as persistent pure ground-glass nodules by ultra-high-resolution CT target scanning in the lateral or oblique body position.

Authors:  Hua Ren; Fufu Liu; Lei Xu; Fan Sun; Jing Cai; Lingwei Yu; Wenbin Guan; Haibo Xiao; Huimin Li; Hong Yu
Journal:  Quant Imaging Med Surg       Date:  2021-09

3.  Quantitative features can predict further growth of persistent pure ground-glass nodule.

Authors:  Zhe Shi; Jiajun Deng; Yunlang She; Lei Zhang; Yijiu Ren; Weiyan Sun; Hang Su; Chenyang Dai; Gening Jiang; Xiwen Sun; Dong Xie; Chang Chen
Journal:  Quant Imaging Med Surg       Date:  2019-02

4.  Multi-window CT based Radiomic signatures in differentiating indolent versus aggressive lung cancers in the National Lung Screening Trial: a retrospective study.

Authors:  Hong Lu; Wei Mu; Yoganand Balagurunathan; Jin Qi; Mahmoud A Abdalah; Alberto L Garcia; Zhaoxiang Ye; Robert J Gillies; Matthew B Schabath
Journal:  Cancer Imaging       Date:  2019-06-28       Impact factor: 3.909

5.  Multi-Window CT Based Radiological Traits for Improving Early Detection in Lung Cancer Screening.

Authors:  Hong Lu; Jongphil Kim; Jin Qi; Qian Li; Ying Liu; Matthew B Schabath; Zhaoxiang Ye; Robert J Gillies; Yoganand Balagurunathan
Journal:  Cancer Manag Res       Date:  2020-11-27       Impact factor: 3.989

6.  Predicting Malignancy and Invasiveness of Pulmonary Subsolid Nodules on CT Images Using Deep Learning.

Authors:  Tianle Shen; Runping Hou; Xiaodan Ye; Xiaoyang Li; Junfeng Xiong; Qin Zhang; Chenchen Zhang; Xuwei Cai; Wen Yu; Jun Zhao; Xiaolong Fu
Journal:  Front Oncol       Date:  2021-07-26       Impact factor: 6.244

7.  Differential Diagnosis of Nonabsorbable Inflammatory and Malignant Subsolid Nodules with a Solid Component ≤5 mm.

Authors:  Xiao-Qun He; Xian Li; Yan Wu; Shun Wu; Tian-You Luo; Fa-Jin Lv; Qi Li
Journal:  J Inflamm Res       Date:  2022-03-11

8.  Qualitative and quantitative imaging features of pulmonary subsolid nodules: differentiating invasive adenocarcinoma from minimally invasive adenocarcinoma and preinvasive lesions.

Authors:  Linlin Qi; Wenwen Lu; Lin Yang; Wei Tang; Shijun Zhao; Yao Huang; Ning Wu; Jianwei Wang
Journal:  J Thorac Dis       Date:  2019-11       Impact factor: 2.895

9.  Semiquantative Visual Assessment of Sub-solid Pulmonary Nodules ≦3 cm in Differentiation of Lung Adenocarcinoma Spectrum.

Authors:  Fu-Zong Wu; Po-An Chen; Carol C Wu; Pei-Lun Kuo; Shu-Ping Tsao; Chu-Chun Chien; En-Kuei Tang; Ming-Ting Wu
Journal:  Sci Rep       Date:  2017-11-17       Impact factor: 4.379

10.  Verification of the eighth edition of the UICC-TNM classification on surgically resected lung adenocarcinoma: Comparison with previous classification in a local center.

Authors:  Hiroshi Minato; Kazuyoshi Katayanagi; Hiroshi Kurumaya; Nobuhiro Tanaka; Hideki Fujimori; Yoshio Tsunezuka; Takeshi Kobayashi
Journal:  Cancer Rep (Hoboken)       Date:  2021-06-24
  10 in total

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