114 related articles for article (PubMed ID: 38110306)
1. Radiomics Analysis to Predict Lymphovascular Invasion of Gastric Cancer Based on Iodine-Based Material Decomposition Images and Virtual Monoenergetic Images.
Shi C; Yan J; Yu Y; Hu C
J Comput Assist Tomogr; 2024 Mar-Apr 01; 48(2):175-183. PubMed ID: 38110306
[TBL] [Abstract][Full Text] [Related]
2. Preoperative prediction of lymphovascular and perineural invasion in gastric cancer using spectral computed tomography imaging and machine learning.
Ge HT; Chen JW; Wang LL; Zou TX; Zheng B; Liu YF; Xue YJ; Lin WW
World J Gastroenterol; 2024 Feb; 30(6):542-555. PubMed ID: 38463023
[TBL] [Abstract][Full Text] [Related]
3. Machine learning analysis for the noninvasive prediction of lymphovascular invasion in gastric cancer using PET/CT and enhanced CT-based radiomics and clinical variables.
Fan L; Li J; Zhang H; Yin H; Zhang R; Zhang J; Chen X
Abdom Radiol (NY); 2022 Apr; 47(4):1209-1222. PubMed ID: 35089370
[TBL] [Abstract][Full Text] [Related]
4. Study of radiomics based on dual-energy CT for nuclear grading and T-staging in renal clear cell carcinoma.
Wang N; Bing X; Li Y; Yao J; Dai Z; Yu D; Ouyang A
Medicine (Baltimore); 2024 Mar; 103(10):e37288. PubMed ID: 38457546
[TBL] [Abstract][Full Text] [Related]
5. Radiomics analysis of contrast-enhanced CT predicts lymphovascular invasion and disease outcome in gastric cancer: a preliminary study.
Chen X; Yang Z; Yang J; Liao Y; Pang P; Fan W; Chen X
Cancer Imaging; 2020 Apr; 20(1):24. PubMed ID: 32248822
[TBL] [Abstract][Full Text] [Related]
6. Dual-energy CT-based radiomics nomogram in predicting histological differentiation of head and neck squamous carcinoma: a multicenter study.
Li Z; Liu Z; Guo Y; Wang S; Qu X; Li Y; Pan Y; Zhang L; Su D; Yang Q; Tao X; Yue Q; Xian J
Neuroradiology; 2022 Feb; 64(2):361-369. PubMed ID: 34860278
[TBL] [Abstract][Full Text] [Related]
7. A clinical-radiomics nomogram based on dual-layer spectral detector CT to predict cancer stage in pancreatic ductal adenocarcinoma.
Wu L; Cen C; Yue X; Chen L; Wu H; Yang M; Lu Y; Ma L; Li X; Wu H; Zheng C; Han P
Cancer Imaging; 2024 May; 24(1):55. PubMed ID: 38725034
[TBL] [Abstract][Full Text] [Related]
8. Additional value of metabolic parameters to PET/CT-based radiomics nomogram in predicting lymphovascular invasion and outcome in lung adenocarcinoma.
Nie P; Yang G; Wang N; Yan L; Miao W; Duan Y; Wang Y; Gong A; Zhao Y; Wu J; Zhang C; Wang M; Cui J; Yu M; Li D; Sun Y; Wang Y; Wang Z
Eur J Nucl Med Mol Imaging; 2021 Jan; 48(1):217-230. PubMed ID: 32451603
[TBL] [Abstract][Full Text] [Related]
9. Preoperative prediction of perineural invasion and lymphovascular invasion with CT radiomics in gastric cancer.
He Y; Yang M; Hou R; Ai S; Nie T; Chen J; Hu H; Guo X; Liu Y; Yuan Z
Eur J Radiol Open; 2024 Jun; 12():100550. PubMed ID: 38314183
[TBL] [Abstract][Full Text] [Related]
10. The Value of Dual-Energy Computed Tomography-Based Radiomics in the Evaluation of Interstitial Fibers of Clear Cell Renal Carcinoma.
Bing X; Wang N; Li Y; Sun H; Yao J; Li R; Li Z; Ouyang A
Technol Cancer Res Treat; 2024; 23():15330338241235554. PubMed ID: 38404055
[TBL] [Abstract][Full Text] [Related]
11. The added value of radiomics from dual-energy spectral CT derived iodine-based material decomposition images in predicting histological grade of gastric cancer.
Shi C; Yu Y; Yan J; Hu C
BMC Med Imaging; 2022 Oct; 22(1):173. PubMed ID: 36192686
[TBL] [Abstract][Full Text] [Related]
12. [The value of spectral CT-based radiomics in preoperative prediction of lymph node metastasis of advanced gastric cancer].
Wang R; Li J; Fang MJ; Dong D; Liang P; Gao JB
Zhonghua Yi Xue Za Zhi; 2020 Jun; 100(21):1617-1622. PubMed ID: 32486595
[No Abstract] [Full Text] [Related]
13. Radiomics in Gastric Cancer: First Clinical Investigation to Predict Lymph Vascular Invasion and Survival Outcome Using
Yang L; Chu W; Li M; Xu P; Wang M; Peng M; Wang K; Zhang L
Front Oncol; 2022; 12():836098. PubMed ID: 35433451
[TBL] [Abstract][Full Text] [Related]
14. Prognostic aspects of lymphovascular invasion in localized gastric cancer: new insights into the radiomics and deep transfer learning from contrast-enhanced CT imaging.
Li Q; Feng QX; Qi L; Liu C; Zhang J; Yang G; Zhang YD; Liu XS
Abdom Radiol (NY); 2022 Feb; 47(2):496-507. PubMed ID: 34766197
[TBL] [Abstract][Full Text] [Related]
15. Prediction model based on radiomics and clinical features for preoperative lymphovascular invasion in gastric cancer patients.
Wang P; Chen K; Han Y; Zhao M; Abiyasi N; Peng H; Yan S; Shang J; Shang N; Meng W
Future Oncol; 2023 Jul; 19(23):1613-1626. PubMed ID: 37377070
[No Abstract] [Full Text] [Related]
16. 2D and 3D texture analysis to predict lymphovascular invasion in lung adenocarcinoma.
Yang G; Nie P; Zhao L; Guo J; Xue W; Yan L; Cui J; Wang Z
Eur J Radiol; 2020 Aug; 129():109111. PubMed ID: 32559593
[TBL] [Abstract][Full Text] [Related]
17. Preoperative prediction of lymphovascular invasion of colorectal cancer by radiomics based on 18F-FDG PET-CT and clinical factors.
Yang Y; Wei H; Fu F; Wei W; Wu Y; Bai Y; Li Q; Wang M
Front Radiol; 2023; 3():1212382. PubMed ID: 37614530
[TBL] [Abstract][Full Text] [Related]
18. Preoperative prediction of lymphovascular invasion in invasive breast cancer with dynamic contrast-enhanced-MRI-based radiomics.
Liu Z; Feng B; Li C; Chen Y; Chen Q; Li X; Guan J; Chen X; Cui E; Li R; Li Z; Long W
J Magn Reson Imaging; 2019 Sep; 50(3):847-857. PubMed ID: 30773770
[TBL] [Abstract][Full Text] [Related]
19.
Wang J; Zheng Z; Zhang Y; Tan W; Li J; Xing L; Sun X
Front Oncol; 2023; 13():1185808. PubMed ID: 37546415
[TBL] [Abstract][Full Text] [Related]
20. A clinical-radiomics model incorporating T2-weighted and diffusion-weighted magnetic resonance images predicts the existence of lymphovascular invasion / perineural invasion in patients with colorectal cancer.
Zhang K; Ren Y; Xu S; Lu W; Xie S; Qu J; Wang X; Shen B; Pang P; Cai X; Sun J
Med Phys; 2021 Sep; 48(9):4872-4882. PubMed ID: 34042185
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]