166 related articles for article (PubMed ID: 37725128)
1. PET/CT-based deep learning grading signature to optimize surgical decisions for clinical stage I invasive lung adenocarcinoma and biologic basis under its prediction: a multicenter study.
Zhong Y; Cai C; Chen T; Gui H; Chen C; Deng J; Yang M; Yu B; Song Y; Wang T; Chen Y; Shi H; Xie D; Chen C; She Y
Eur J Nucl Med Mol Imaging; 2024 Jan; 51(2):521-534. PubMed ID: 37725128
[TBL] [Abstract][Full Text] [Related]
2. Multi-lesion radiomics of PET/CT for non-invasive survival stratification and histologic tumor risk profiling in patients with lung adenocarcinoma.
Zhao M; Kluge K; Papp L; Grahovac M; Yang S; Jiang C; Krajnc D; Spielvogel CP; Ecsedi B; Haug A; Wang S; Hacker M; Zhang W; Li X
Eur Radiol; 2022 Oct; 32(10):7056-7067. PubMed ID: 35896836
[TBL] [Abstract][Full Text] [Related]
3. Multivariate analysis based on the maximum standard unit value of
Wang Y; Lyu D; Zhou T; Tu W; Fan L; Liu S
Diagn Interv Radiol; 2023 Mar; 29(2):379-389. PubMed ID: 36988049
[TBL] [Abstract][Full Text] [Related]
4. Development and validation of a deep learning signature for predicting lymph node metastasis in lung adenocarcinoma: comparison with radiomics signature and clinical-semantic model.
Ma X; Xia L; Chen J; Wan W; Zhou W
Eur Radiol; 2023 Mar; 33(3):1949-1962. PubMed ID: 36169691
[TBL] [Abstract][Full Text] [Related]
5. [Value of PET/CT Combined with CT Three-dimensional Reconstruction
in Distinguishing Different Pathological Subtypes of Early Lung Adenocarcinoma].
You J; Zhang G; Gao X; Chen Y; Shu Y
Zhongguo Fei Ai Za Zhi; 2021 Jul; 24(7):468-474. PubMed ID: 34120430
[TBL] [Abstract][Full Text] [Related]
6. Solid Attenuation Components Attention Deep Learning Model to Predict Micropapillary and Solid Patterns in Lung Adenocarcinomas on Computed Tomography.
Chen LW; Yang SM; Chuang CC; Wang HJ; Chen YC; Lin MW; Hsieh MS; Antonoff MB; Chang YC; Wu CC; Pan T; Chen CM
Ann Surg Oncol; 2022 Nov; 29(12):7473-7482. PubMed ID: 35789301
[TBL] [Abstract][Full Text] [Related]
7. Preoperative CT-based radiomics combined with intraoperative frozen section is predictive of invasive adenocarcinoma in pulmonary nodules: a multicenter study.
Wu G; Woodruff HC; Sanduleanu S; Refaee T; Jochems A; Leijenaar R; Gietema H; Shen J; Wang R; Xiong J; Bian J; Wu J; Lambin P
Eur Radiol; 2020 May; 30(5):2680-2691. PubMed ID: 32006165
[TBL] [Abstract][Full Text] [Related]
8. A quantitative imaging biomarker for predicting disease-free-survival-associated histologic subgroups in lung adenocarcinoma.
Lu L; Wang D; Wang L; E L; Guo P; Li Z; Xiang J; Yang H; Li H; Yin S; Schwartz LH; Xie C; Zhao B
Eur Radiol; 2020 Jul; 30(7):3614-3623. PubMed ID: 32086583
[TBL] [Abstract][Full Text] [Related]
9. Clinical implication of the 2020 International Association for the Study of Lung Cancer histologic grading in surgically resected pathologic stage 1 lung adenocarcinomas: Prognostic value and association with computed tomography characteristics.
Cho IS; Shim HS; Lee HJ; Suh YJ
Lung Cancer; 2023 Oct; 184():107345. PubMed ID: 37611496
[TBL] [Abstract][Full Text] [Related]
10. [The correlation between metabolic parameters in (18)F-FDG PET-CT and solid and micropapillary histological subtypes in lung adenocarcinoma].
Guo Y; Yao ZM; Chen M; Chen CX
Zhonghua Zhong Liu Za Zhi; 2022 Jun; 44(6):555-561. PubMed ID: 35754230
[No Abstract] [Full Text] [Related]
11. PET/CT based cross-modal deep learning signature to predict occult nodal metastasis in lung cancer.
Zhong Y; Cai C; Chen T; Gui H; Deng J; Yang M; Yu B; Song Y; Wang T; Sun X; Shi J; Chen Y; Xie D; Chen C; She Y
Nat Commun; 2023 Nov; 14(1):7513. PubMed ID: 37980411
[TBL] [Abstract][Full Text] [Related]
12. A deep residual learning network for predicting lung adenocarcinoma manifesting as ground-glass nodule on CT images.
Gong J; Liu J; Hao W; Nie S; Zheng B; Wang S; Peng W
Eur Radiol; 2020 Apr; 30(4):1847-1855. PubMed ID: 31811427
[TBL] [Abstract][Full Text] [Related]
13. Validation Study of New IASLC Histology Grading System in Stage I Non-Mucinous Adenocarcinoma Comparing With Minimally Invasive Adenocarcinoma.
Woo W; Cha YJ; Kim BJ; Moon DH; Lee S
Clin Lung Cancer; 2022 Nov; 23(7):e435-e442. PubMed ID: 35945128
[TBL] [Abstract][Full Text] [Related]
14. Radiologic Predictors for Clinical Stage IA Lung Adenocarcinoma with Ground Glass Components: A Multi-Center Study of Long-Term Outcomes.
Li Z; Ye B; Bao M; Xu B; Chen Q; Liu S; Han Y; Peng M; Lin Z; Li J; Zhu W; Lin Q; Xiong L
PLoS One; 2015; 10(9):e0136616. PubMed ID: 26339917
[TBL] [Abstract][Full Text] [Related]
15. Use of a prognostic risk score that aggregates the FDG-PET/CT SUVmax, tumor size, and histologic group for predicting the prognosis of pStage I lung adenocarcinoma.
Kawakita N; Toba H; Kawakami Y; Takizawa H; Bando Y; Otuska H; Matsumoto D; Takashima M; Tsuboi M; Yoshida M; Kondo K; Tangoku A
Int J Clin Oncol; 2020 Jun; 25(6):1079-1089. PubMed ID: 32130543
[TBL] [Abstract][Full Text] [Related]
16. The value of preoperative positron emission tomography/computed tomography in differentiating the invasive degree of hypometabolic lung adenocarcinoma.
Su Y; Zhou H; Huang W; Li L; Wang J
BMC Med Imaging; 2023 Feb; 23(1):31. PubMed ID: 36765284
[TBL] [Abstract][Full Text] [Related]
17. Oncologic outcomes of segmentectomy compared with lobectomy for clinical stage IA lung adenocarcinoma: propensity score-matched analysis in a multicenter study.
Tsutani Y; Miyata Y; Nakayama H; Okumura S; Adachi S; Yoshimura M; Okada M
J Thorac Cardiovasc Surg; 2013 Aug; 146(2):358-64. PubMed ID: 23477694
[TBL] [Abstract][Full Text] [Related]
18. A Grading System for Invasive Pulmonary Adenocarcinoma: A Proposal From the International Association for the Study of Lung Cancer Pathology Committee.
Moreira AL; Ocampo PSS; Xia Y; Zhong H; Russell PA; Minami Y; Cooper WA; Yoshida A; Bubendorf L; Papotti M; Pelosi G; Lopez-Rios F; Kunitoki K; Ferrari-Light D; Sholl LM; Beasley MB; Borczuk A; Botling J; Brambilla E; Chen G; Chou TY; Chung JH; Dacic S; Jain D; Hirsch FR; Hwang D; Lantuejoul S; Lin D; Longshore JW; Motoi N; Noguchi M; Poleri C; Rekhtman N; Tsao MS; Thunnissen E; Travis WD; Yatabe Y; Roden AC; Daigneault JB; Wistuba II; Kerr KM; Pass H; Nicholson AG; Mino-Kenudson M
J Thorac Oncol; 2020 Oct; 15(10):1599-1610. PubMed ID: 32562873
[TBL] [Abstract][Full Text] [Related]
19. Preoperative CT-based Deep Learning Model for Predicting Disease-Free Survival in Patients with Lung Adenocarcinomas.
Kim H; Goo JM; Lee KH; Kim YT; Park CM
Radiology; 2020 Jul; 296(1):216-224. PubMed ID: 32396042
[TBL] [Abstract][Full Text] [Related]
20. Prognostic role of positron emission tomography and high-resolution computed tomography in clinical stage IA lung adenocarcinoma.
Uehara H; Tsutani Y; Okumura S; Nakayama H; Adachi S; Yoshimura M; Miyata Y; Okada M
Ann Thorac Surg; 2013 Dec; 96(6):1958-65. PubMed ID: 24021765
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
