Comparison between solid component size on thin-section CT and pathologic lymph node metastasis and local invasion in T1 lung adenocarcinoma

被引:13
|
作者
Hayashi, Hideyuki [1 ]
Ashizawa, Kazuto [1 ]
Ogihara, Yukihiro [5 ]
Nishida, Akifumi [2 ]
Matsumoto, Keitaro [3 ]
Yamasaki, Naoya [3 ]
Nagayasu, Takeshi [3 ]
Fukuda, Minoru [1 ]
Honda, Sumihisa [4 ]
Uetani, Masataka [2 ]
机构
[1] Nagasaki Univ, Dept Clin Oncol, Unit Translat Med, Grad Sch Biomed Sci, 1-7-1 Sakamoto, Nagasaki 8528501, Japan
[2] Nagasaki Univ, Dept Radiol Sci, Grad Sch Biomed Sci, 1-7-1 Sakamoto, Nagasaki 8528501, Japan
[3] Nagasaki Univ, Dept Surg Oncol, Grad Sch Biomed Sci, 1-7-1 Sakamoto, Nagasaki 8528501, Japan
[4] Nagasaki Univ, Dept Publ Hlth, Grad Sch Biomed Sci, 1-7-1 Sakamoto, Nagasaki 8528501, Japan
[5] Nagasaki Prefectural Shimabara Hosp, Dept Radiol, Nagasaki, Japan
关键词
Lung neoplasms; Adenocarcinoma; CT; Ground-glass opacity; Lymph node metastasis; GROUND-GLASS OPACITY; PROGNOSTIC-SIGNIFICANCE; COMPUTED-TOMOGRAPHY; SUBLOBAR RESECTION; LIMITED RESECTION; CANCER; CONSOLIDATION; PREDICTOR; TUMORS;
D O I
10.1007/s11604-017-0610-6
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
To correlate the tumor size and solid component size on thin-section CT (TS-CT) with pathological findings including lymph node (LN) metastasis and local invasion in T1 lung adenocarcinoma. 188 patients with surgically resected T1 lung adenocarcinoma were retrospectively analyzed. Two chest radiologists measured the long-axis and short-axis dimensions of nodules and solid components with a lung and/or a mediastinal window setting (WS) on TS-CT. After analyzing interobserver agreement, average long-axis dimensions of the measured tumors and solid components were correlated with pathological findings. Seven of 188 patients (3.7%) had pathologic LN-positive metastasis. In patients in whom the long axis of the solid component was < 5 mm with a mediastinal WS or < 8 mm with a lung WS on TS-CT, no LN metastases were observed, resulting in a positive predictive value (PPV) for predicting a pathologic LN-negative status of 100% with each WS. Based on the same diagnostic criteria, the PPVs for a pathological local invasion (LI)-negative status were 91 (40/44) and 90% (55/61), respectively. Solid component size on TS-CT may have the potential to predict LN-negative or LI-negative status.
引用
收藏
页码:109 / 115
页数:7
相关论文
共 41 条
  • [1] Comparison between solid component size on thin-section CT and pathologic lymph node metastasis and local invasion in T1 lung adenocarcinoma
    Hideyuki Hayashi
    Kazuto Ashizawa
    Yukihiro Ogihara
    Akifumi Nishida
    Keitaro Matsumoto
    Naoya Yamasaki
    Takeshi Nagayasu
    Minoru Fukuda
    Sumihisa Honda
    Masataka Uetani
    Japanese Journal of Radiology, 2017, 35 : 109 - 115
  • [2] T1 invasive lung adenocarcinoma: Thin-section CT solid score and histological periostin expression predict tumor recurrence
    Iwamoto, Ryoji
    Tanoue, Shuichi
    Nagata, Shuji
    Tabata, Kazuhiro
    Fukuoka, Junya
    Koganemaru, Masamichi
    Sumi, Akiko
    Chikasue, Tomonori
    Abe, Toshi
    Murakami, Daigo
    Takamori, Shinzo
    Ishii, Hidenobu
    Ohshima, Koichi
    Ohta, Shoichiro
    Izuhara, Kenji
    Fujimoto, Kiminori
    MOLECULAR AND CLINICAL ONCOLOGY, 2021, 15 (05)
  • [3] Lymph node metastasis and its risk factors in T1 lung adenocarcinoma
    Zhang, Wenhao
    Mu, Guang
    Huang, Jingjing
    Bian, Chengyu
    Wang, Hongchang
    Gu, Yan
    Xia, Yang
    Chen, Liang
    Yuan, Mei
    Wang, Jun
    THORACIC CANCER, 2023, 14 (30) : 2993 - 3000
  • [4] Radiologic-Pathologic Correlation of Solid Portions on Thin-section CT Images in Lung Adenocarcinoma: A Multicenter Study
    Yanagawa, Masahiro
    Kusumoto, Masahiko
    Johkoh, Takeshi
    Noguchi, Masayuki
    Minami, Yuko
    Sakai, Fumikazu
    Asamura, Hisao
    Tomiyama, Noriyuki
    CLINICAL LUNG CANCER, 2018, 19 (03) : E303 - E312
  • [5] Significance of the depth of tumor invasion and lymph node metastasis in superficially invasive (T1) esophageal adenocarcinoma
    Liu, LX
    Hofstetter, WL
    Rashid, A
    Swisher, SG
    Correa, AM
    Ajani, JA
    Hamilton, SR
    Wu, TT
    AMERICAN JOURNAL OF SURGICAL PATHOLOGY, 2005, 29 (08) : 1079 - 1085
  • [6] Can peritumoral radiomics increase the efficiency of the prediction for lymph node metastasis in clinical stage T1 lung adenocarcinoma on CT?
    Wang, Xiang
    Zhao, Xingyu
    Li, Qiong
    Xia, Wei
    Peng, Zhaohui
    Zhang, Rui
    Li, Qingchu
    Jian, Junming
    Wang, Wei
    Tang, Yuguo
    Liu, Shiyuan
    Gao, Xin
    EUROPEAN RADIOLOGY, 2019, 29 (11) : 6049 - 6058
  • [7] Can peritumoral radiomics increase the efficiency of the prediction for lymph node metastasis in clinical stage T1 lung adenocarcinoma on CT?
    Xiang Wang
    Xingyu Zhao
    Qiong Li
    Wei Xia
    Zhaohui Peng
    Rui Zhang
    Qingchu Li
    Junming Jian
    Wei Wang
    Yuguo Tang
    Shiyuan Liu
    Xin Gao
    European Radiology, 2019, 29 : 6049 - 6058
  • [8] Genomic profiles and immune cell infiltration landscapes for lymph node metastasis in T1 lung adenocarcinoma
    Wu, Fang
    Pan, Yue
    Hu, Chunhong
    Chen, Chen
    Liu, Wenliang
    Fan, Songqing
    Shu, Long
    Zhao, Lishu
    Fu, Yucheng
    Zhang, Sujuan
    Liu, Junqi
    Zeng, Yue
    Peng, Yurong
    Zang, Hongjing
    Deng, Chao
    Qiu, Zhenhua
    Ma, Fang
    Yu, Fenglei
    Liu, Xianling
    Liu, Lijuan
    Yang, Lingling
    Shao, Yang
    CANCER RESEARCH, 2023, 83 (07)
  • [9] Correlation between the Size of the Solid Component on Thin-Section CT and the Invasive Component on Pathology in Small Lung Adenocarcinomas Manifesting as Ground-Glass Nodules
    Lee, Kyung Hee
    Goo, Jin Mo
    Park, Sang Joon
    Wi, Jae Yeon
    Chung, Doo Hyun
    Go, Heounjeong
    Park, Heae Surng
    Park, Chang Min
    Lee, Sang Min
    JOURNAL OF THORACIC ONCOLOGY, 2014, 9 (01) : 74 - 82
  • [10] Imbalanced Data Correction Based PET/CT Radiomics Model for Predicting Lymph Node Metastasis in Clinical Stage T1 Lung Adenocarcinoma
    Lv, Jieqin
    Chen, Xiaohui
    Liu, Xinran
    Du, Dongyang
    Lv, Wenbing
    Lu, Lijun
    Wu, Hubing
    FRONTIERS IN ONCOLOGY, 2022, 12