153 related articles for article (PubMed ID: 37755604)
1. Convolutional neural network-based program to predict lymph node metastasis of non-small cell lung cancer using
Kidera E; Koyasu S; Hirata K; Hamaji M; Nakamoto R; Nakamoto Y
Ann Nucl Med; 2024 Jan; 38(1):71-80. PubMed ID: 37755604
[TBL] [Abstract][Full Text] [Related]
2. Convolutional Neural Networks in Predicting Nodal and Distant Metastatic Potential of Newly Diagnosed Non-Small Cell Lung Cancer on FDG PET Images.
Tau N; Stundzia A; Yasufuku K; Hussey D; Metser U
AJR Am J Roentgenol; 2020 Jul; 215(1):192-197. PubMed ID: 32348182
[No Abstract] [Full Text] [Related]
3. Diagnostic accuracy of virtual 18F-FDG PET/CT bronchoscopy for the detection of lymph node metastases in non-small cell lung cancer patients.
Herbrik M; Treffert J; Geiger B; Riegger C; Hartung V; Rosenbaum-Krumme SJ; Forsting M; Antoch G; Heusner TA
J Nucl Med; 2011 Oct; 52(10):1520-5. PubMed ID: 21908390
[TBL] [Abstract][Full Text] [Related]
4. [Density and SUV ratios from PET/CT in the detection of mediastinal lymph node metastasis in non-small cell lung cancer].
Shao T; Yu L; Li Y; Chen M
Zhongguo Fei Ai Za Zhi; 2015 Mar; 18(3):155-60. PubMed ID: 25800571
[TBL] [Abstract][Full Text] [Related]
5. Prediction of Lymph Node Maximum Standardized Uptake Value in Patients With Cancer Using a 3D Convolutional Neural Network: A Proof-of-Concept Study.
Shaish H; Mutasa S; Makkar J; Chang P; Schwartz L; Ahmed F
AJR Am J Roentgenol; 2019 Feb; 212(2):238-244. PubMed ID: 30540209
[TBL] [Abstract][Full Text] [Related]
6. [Significance of dual-time-point 18F-FDG PET imaging in evaluation of hilar and mediastinal lymph node metastasis in non-small-cell lung cancer].
Hu M; Yu JM; Liu NB; Liu LP; Guo HB; Yang GR; Zhang PL; Xu XQ
Zhonghua Zhong Liu Za Zhi; 2008 Apr; 30(4):306-9. PubMed ID: 18788639
[TBL] [Abstract][Full Text] [Related]
7. Deep convolutional neural network for differentiating between sarcoidosis and lymphoma based on [
Aoki H; Miyazaki Y; Anzai T; Yokoyama K; Tsuchiya J; Shirai T; Shibata S; Sakakibara R; Mitsumura T; Honda T; Furusawa H; Okamoto T; Tateishi T; Tamaoka M; Yamamoto M; Takahashi K; Tateishi U; Yamaguchi T
Eur Radiol; 2024 Jan; 34(1):374-383. PubMed ID: 37535157
[TBL] [Abstract][Full Text] [Related]
8. Combination of Fluorine-18 Fluorodeoxyglucose Positron-Emission Tomography/Computed Tomography (¹⁸F-FDG PET/CT) and Tumor Markers to Diagnose Lymph Node Metastasis in Non-Small Cell Lung Cancer (NSCLC): A Retrospective and Prospective Study.
Zhai X; Guo Y; Qian X
Med Sci Monit; 2020 Jun; 26():e922675. PubMed ID: 32483109
[TBL] [Abstract][Full Text] [Related]
9. Diagnostic utility of metabolic parameters on FDG PET/CT for lymph node metastasis in patients with cN2 non-small cell lung cancer.
Nakanishi K; Nakamura S; Sugiyama T; Kadomatsu Y; Ueno H; Goto M; Ozeki N; Fukui T; Iwano S; Chen-Yoshikawa TF
BMC Cancer; 2021 Sep; 21(1):983. PubMed ID: 34474680
[TBL] [Abstract][Full Text] [Related]
10. Graph Neural Network Model for Prediction of Non-Small Cell Lung Cancer Lymph Node Metastasis Using Protein-Protein Interaction Network and
Ju H; Kim K; Kim BI; Woo SK
Int J Mol Sci; 2024 Jan; 25(2):. PubMed ID: 38255770
[TBL] [Abstract][Full Text] [Related]
11.
Sibille L; Seifert R; Avramovic N; Vehren T; Spottiswoode B; Zuehlsdorff S; Schäfers M
Radiology; 2020 Feb; 294(2):445-452. PubMed ID: 31821122
[TBL] [Abstract][Full Text] [Related]
12. Prediction of mediastinal lymph node metastasis based on
Yin G; Song Y; Li X; Zhu L; Su Q; Dai D; Xu W
Eur Radiol; 2021 Jun; 31(6):3983-3992. PubMed ID: 33201286
[TBL] [Abstract][Full Text] [Related]
13. Prediction of true-negative lymph node metastasis in clinical IA non-small cell lung cancer by measuring standardized uptake values on positron emission tomography.
Takenaka T; Yano T; Morodomi Y; Ito K; Miura N; Kawano D; Shoji F; Baba S; Abe K; Honda H; Maehara Y
Surg Today; 2012 Oct; 42(10):934-9. PubMed ID: 22864936
[TBL] [Abstract][Full Text] [Related]
14. Dual-Energy CT-Derived Electron Density for Diagnosing Metastatic Mediastinal Lymph Nodes in Non-Small Cell Lung Cancer: Comparison With Conventional CT and FDG PET/CT Findings.
Nagano H; Takumi K; Nakajo M; Fukukura Y; Kumagae Y; Jinguji M; Tani A; Yoshiura T
AJR Am J Roentgenol; 2022 Jan; 218(1):66-74. PubMed ID: 34319164
[No Abstract] [Full Text] [Related]
15. Use of maximum standardized uptake value on fluorodeoxyglucose positron-emission tomography in predicting lymph node involvement in patients with primary non-small cell lung cancer.
Muto J; Hida Y; Kaga K; Ohtaka K; Okamoto S; Tamaki N; Nakada-Kubota R; Hirano S; Matsui Y
Anticancer Res; 2014 Feb; 34(2):805-10. PubMed ID: 24511016
[TBL] [Abstract][Full Text] [Related]
16. Improving diagnostic performance of
Yang DD; Mirvis E; Goldring J; Patel ARC; Wagner T
Clin Radiol; 2019 Oct; 74(10):818.e17-818.e23. PubMed ID: 31420186
[TBL] [Abstract][Full Text] [Related]
17. Developing a primary tumor and lymph node 18F-FDG PET/CT-clinical (TLPC) model to predict lymph node metastasis of resectable T2-4 NSCLC.
Wang M; Liu L; Dai Q; Jin M; Huang G
J Cancer Res Clin Oncol; 2023 Jan; 149(1):247-261. PubMed ID: 36565319
[TBL] [Abstract][Full Text] [Related]
18. Mediastinal lymph nodes staging by 18F-FDG PET/CT for early stage non-small cell lung cancer: a multicenter study.
Li X; Zhang H; Xing L; Ma H; Xie P; Zhang L; Xu X; Yue J; Sun X; Hu X; Chen M; Xu W; Chen L; Yu J
Radiother Oncol; 2012 Feb; 102(2):246-50. PubMed ID: 22100657
[TBL] [Abstract][Full Text] [Related]
19. Tumor-to-liver standard uptake ratio using fluorine-18 fluorodeoxyglucose positron emission tomography computed tomography effectively predict occult lymph node metastasis of non-small cell lung cancer patients.
Shi YM; Niu R; Shao XL; Zhang FF; Shao XN; Wang JF; Wang XS; Liu B; Yu WJ; Wang YT
Nucl Med Commun; 2020 May; 41(5):459-468. PubMed ID: 32187163
[TBL] [Abstract][Full Text] [Related]
20. Risk Factors for Predicting Occult Lymph Node Metastasis in Patients with Clinical Stage I Non-small Cell Lung Cancer Staged by Integrated Fluorodeoxyglucose Positron Emission Tomography/Computed Tomography.
Kaseda K; Asakura K; Kazama A; Ozawa Y
World J Surg; 2016 Dec; 40(12):2976-2983. PubMed ID: 27456499
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]