Reticulation Sign on Thin-Section CT: Utility for Predicting Invasiveness of Pure Ground-Glass Nodules

被引:9
作者
Liang, Zhang-Rui [1 ]
Lv, Fa-Jin [1 ]
Fu, Bin-Jie [1 ]
Lin, Rui-Yu [1 ]
Li, Wang-Jia [1 ]
Chu, Zhi-Gang [1 ]
机构
[1] Chongqing Med Univ, Dept Radiol, Affiliated Hosp 1, 1 Youyi Rd, Chongqing 400016, Peoples R China
关键词
CT; differential diagnosis; lung neoplasms; LUNG ADENOCARCINOMA; 10; MM; CLASSIFICATION; OPACITY; STATEMENT; INVASION; SOCIETY; CANCER;
D O I
10.2214/AJR.22.28892
中图分类号
R8 [特种医学]; R445 [影像诊断学];
学科分类号
1002 ; 100207 ; 1009 ;
摘要
BACKGROUND. Pure ground-glass nodules (pGGNs) may represent a diverse range of histologic entities of varying aggressiveness. OBJECTIVE. The purpose of this study was to evaluate the use of the reticulation sign on thin-section CT images for predicting the invasiveness of pGGNs. METHODS. This retrospective study included 795 patients (mean age, 53.4 +/- 11.1 [SD] years; 254 men, 541 women) with a total of 876 pGGNs on thin-section CT that underwent resection between January 2015 and April 2022. Two fellowship-trained thoracic radiologists independently reviewed unenhanced CT images to assess the pGGNs for a range of features, including diameter, attenuation, location, shape, air bronchogram, bubble lucency, vascular change, lobulation, spiculation, margins, pleural indentation, and the reticulation sign (defined as multiple small linear opacities resembling a mesh or a net); differences were resolved by consensus. The relationship between the reticulation sign and lesion invasiveness on pathologic assessment was evaluated. RESULTS. On pathologic assessment, the 876 pGGNs included 163 nonneoplastic and 713 neoplastic pGGNs (323 atypical adenomatous hyperplasias [AAHs] or adenocarcinomas in situ [AISs], 250 minimally invasive adenocarcinomas [MIAs], and 140 invasive adenocarcinomas [IACs]). Interobserver agreement for the reticulation sign, expressed as kappa, was 0.870. The reticulation sign was detected in 0.0% of nonneoplastic lesions, 0.0% of AAHs/AISs, 6.8% of MIAs, and 54.3% of IACs. The reticulation sign had sensitivity of 24.0% and specificity of 100.0% for a diagnosis of MIA or IAC and sensitivity of 54.3% and specificity of 97.7% for a diagnosis of IAC. In multivariable regression analyses including all of the assessed CT features, the reticulation sign was a significant independent predictor of IAC (OR, 3.64; p = .001) but was not a significant independent predictor of MIA or IAC. CONCLUSION. The reticulation sign, when observed in a pGGN on thin-section CT, has high specificity (albeit low sensitivity) for invasiveness and is an independent predictor of IAC. CLINICAL IMPACT. Those pGGNs that show the reticulation sign should be strongly suspected to represent IAC; this suspicion may guide risk assessments and follow-up recommendations.
引用
收藏
页码:69 / 78
页数:10
相关论文
共 41 条
  • [1] Reduced Lung-Cancer Mortality with Low-Dose Computed Tomographic Screening
    Aberle, Denise R.
    Adams, Amanda M.
    Berg, Christine D.
    Black, William C.
    Clapp, Jonathan D.
    Fagerstrom, Richard M.
    Gareen, Ilana F.
    Gatsonis, Constantine
    Marcus, Pamela M.
    Sicks, JoRean D.
    [J]. NEW ENGLAND JOURNAL OF MEDICINE, 2011, 365 (05) : 395 - 409
  • [2] Evaluation of Pulmonary Nodules Clinical Practice Consensus Guidelines for Asia
    Bai, Chunxue
    Choi, Chang-Min
    Chu, Chung Ming
    Anantham, Devanand
    Ho, James Chung-man
    Khan, Ali Zamir
    Lee, Jang-Ming
    Li, Shi Yue
    Saenghirunvattana, Sawang
    Yim, Anthony
    [J]. CHEST, 2016, 150 (04) : 877 - 893
  • [3] Enhancing capsule in hepatocellular carcinoma: intra-individual comparison between CT and MRI with extracellular contrast agent
    Cannella, Roberto
    Ronot, Maxime
    Sartoris, Riccardo
    Cauchy, Francois
    Hobeika, Christian
    Beaufrere, Aurelie
    Trapani, Loic
    Paradis, Valerie
    Bouattour, Mohamed
    Bonvalet, Fanny
    Vilgrain, Valerie
    Burgio, Marco Dioguardi
    [J]. DIAGNOSTIC AND INTERVENTIONAL IMAGING, 2021, 102 (12) : 735 - 742
  • [4] CT Characteristics for Predicting Invasiveness in Pulmonary Pure Ground-Glass Nodules
    Chu, Zhi-gang
    Li, Wang-jia
    Fu, Bin-jie
    Lv, Fa-jin
    [J]. AMERICAN JOURNAL OF ROENTGENOLOGY, 2020, 215 (02) : 351 - 358
  • [5] Pure ground-glass nodules: are they really indolent?
    Cohen, Julien G.
    Ferretti, Gilbert R.
    [J]. JOURNAL OF THORACIC DISEASE, 2017, 9 (09) : 2839 - 2842
  • [6] Tumor Size and Computed Tomography Attenuation of Pulmonary Pure Ground-Glass Nodules Are Useful for Predicting Pathological Invasiveness
    Eguchi, Takashi
    Yoshizawa, Akihiko
    Kawakami, Satoshi
    Kumeda, Hirotaka
    Umesaki, Tetsuya
    Agatsuma, Hiroyuki
    Sakaizawa, Takao
    Tominaga, Yoshiaki
    Toishi, Masayuki
    Hashizume, Masahiro
    Shiina, Takayuki
    Yoshida, Kazuo
    Asaka, Shiho
    Matsushita, Mina
    Koizumi, Tomonobu
    [J]. PLOS ONE, 2014, 9 (05):
  • [7] Significance of intra-nodular vessel sign in differentiating benign and malignant pulmonary ground-glass nodules
    Fu, Bin-jie
    Lv, Fa-jin
    Li, Wang-jia
    Lin, Rui-yu
    Zheng, Yi-neng
    Chu, Zhi-gang
    [J]. INSIGHTS INTO IMAGING, 2021, 12 (01)
  • [8] Arc concave sign on thin-section computed tomography:A novel predictor for invasive pulmonary adenocarcinoma in pure ground-glass nodules
    Fu, Gangze
    Yu, Huibo
    Liu, Jinjin
    Xia, Tianyi
    Xiang, Lanting
    Li, Peng
    Huang, Dingpin
    Lin, Liaoyi
    Zhuang, Yuandi
    Yang, Yunjun
    [J]. EUROPEAN JOURNAL OF RADIOLOGY, 2021, 139
  • [9] Evaluation of Individuals With Pulmonary Nodules: When Is It Lung Cancer? Diagnosis and Management of Lung Cancer, 3rd ed: American College of Chest Physicians Evidence-Based Clinical Practice Guidelines
    Gould, Michael K.
    Donington, Jessica
    Lynch, William R.
    Mazzone, Peter J.
    Midthun, David E.
    Naidich, David P.
    Wiener, Renda Soylemez
    [J]. CHEST, 2013, 143 (05) : E93 - E120
  • [10] CT quantitative parameters to predict the invasiveness of lung pure ground-glass nodules (pGGNs)
    Han, L.
    Zhang, P.
    Wang, Y.
    Gao, Z.
    Wang, H.
    Li, X.
    Ye, Z.
    [J]. CLINICAL RADIOLOGY, 2018, 73 (05) : 504.e1 - 504.e7