170 related articles for article (PubMed ID: 37230433)
1. Development and Validation of a Radiomics Model Based on Lymph-Node Regression Grading After Neoadjuvant Chemoradiotherapy in Locally Advanced Rectal Cancer.
Zhang S; Tang B; Yu M; He L; Zheng P; Yan C; Li J; Peng Q
Int J Radiat Oncol Biol Phys; 2023 Nov; 117(4):821-833. PubMed ID: 37230433
[TBL] [Abstract][Full Text] [Related]
2. Radiomics analysis of multiparametric MRI for prediction of pathological complete response to neoadjuvant chemoradiotherapy in locally advanced rectal cancer.
Cui Y; Yang X; Shi Z; Yang Z; Du X; Zhao Z; Cheng X
Eur Radiol; 2019 Mar; 29(3):1211-1220. PubMed ID: 30128616
[TBL] [Abstract][Full Text] [Related]
3. Radiomics signature as a new biomarker for preoperative prediction of neoadjuvant chemoradiotherapy response in locally advanced rectal cancer.
Zhang Z; Jiang X; Zhang R; Yu T; Liu S; Luo Y
Diagn Interv Radiol; 2021 May; 27(3):308-314. PubMed ID: 34003118
[TBL] [Abstract][Full Text] [Related]
4. MRI radiomics signature to predict lymph node metastasis after neoadjuvant chemoradiation therapy in locally advanced rectal cancer.
Fang Z; Pu H; Chen XL; Yuan Y; Zhang F; Li H
Abdom Radiol (NY); 2023 Jul; 48(7):2270-2283. PubMed ID: 37085730
[TBL] [Abstract][Full Text] [Related]
5. MRI-based delta-radiomics are predictive of pathological complete response after neoadjuvant chemoradiotherapy in locally advanced rectal cancer.
Wan L; Peng W; Zou S; Ye F; Geng Y; Ouyang H; Zhao X; Zhang H
Acad Radiol; 2021 Nov; 28 Suppl 1():S95-S104. PubMed ID: 33189550
[TBL] [Abstract][Full Text] [Related]
6. Radiomics Signature Based on Support Vector Machines for the Prediction of Pathological Complete Response to Neoadjuvant Chemoradiotherapy in Locally Advanced Rectal Cancer.
Li C; Chen H; Zhang B; Fang Y; Sun W; Wu D; Su Z; Shen L; Wei Q
Cancers (Basel); 2023 Oct; 15(21):. PubMed ID: 37958309
[TBL] [Abstract][Full Text] [Related]
7. Multiparametric MRI-based Radiomics approaches on predicting response to neoadjuvant chemoradiotherapy (nCRT) in patients with rectal cancer.
Cheng Y; Luo Y; Hu Y; Zhang Z; Wang X; Yu Q; Liu G; Cui E; Yu T; Jiang X
Abdom Radiol (NY); 2021 Nov; 46(11):5072-5085. PubMed ID: 34302510
[TBL] [Abstract][Full Text] [Related]
8. Feasibility of a CT-based lymph node radiomics nomogram in detecting lymph node metastasis in PDAC patients.
Li Q; Song Z; Zhang D; Li X; Liu Q; Yu J; Li Z; Zhang J; Ren X; Wen Y; Tang Z
Front Oncol; 2022; 12():992906. PubMed ID: 36276058
[TBL] [Abstract][Full Text] [Related]
9. Selecting Candidates for Organ-Preserving Strategies After Neoadjuvant Chemoradiotherapy for Rectal Cancer: Development and Validation of a Model Integrating MRI Radiomics and Pathomics.
Wan L; Sun Z; Peng W; Wang S; Li J; Zhao Q; Wang S; Ouyang H; Zhao X; Zou S; Zhang H
J Magn Reson Imaging; 2022 Oct; 56(4):1130-1142. PubMed ID: 35142001
[TBL] [Abstract][Full Text] [Related]
10. MRI-based radiomics to predict neoadjuvant chemoradiotherapy outcomes in locally advanced rectal cancer: A multicenter study.
Xiang Y; Li S; Wang H; Song M; Hu K; Wang F; Wang Z; Niu Z; Liu J; Cai Y; Li Y; Zhu X; Geng J; Zhang Y; Teng H; Wang W
Clin Transl Radiat Oncol; 2023 Jan; 38():175-182. PubMed ID: 36471751
[TBL] [Abstract][Full Text] [Related]
11. Radiomics Analysis for Evaluation of Pathological Complete Response to Neoadjuvant Chemoradiotherapy in Locally Advanced Rectal Cancer.
Liu Z; Zhang XY; Shi YJ; Wang L; Zhu HT; Tang Z; Wang S; Li XT; Tian J; Sun YS
Clin Cancer Res; 2017 Dec; 23(23):7253-7262. PubMed ID: 28939744
[No Abstract] [Full Text] [Related]
12. Predicting pathological complete response by comparing MRI-based radiomics pre- and postneoadjuvant radiotherapy for locally advanced rectal cancer.
Li Y; Liu W; Pei Q; Zhao L; Güngör C; Zhu H; Song X; Li C; Zhou Z; Xu Y; Wang D; Tan F; Yang P; Pei H
Cancer Med; 2019 Dec; 8(17):7244-7252. PubMed ID: 31642204
[TBL] [Abstract][Full Text] [Related]
13. Prediction of pathological nodal stage of locally advanced rectal cancer by collective features of multiple lymph nodes in magnetic resonance images before and after neoadjuvant chemoradiotherapy.
Zhu H; Zhang X; Li X; Shi Y; Zhu H; Sun Y
Chin J Cancer Res; 2019 Dec; 31(6):984-992. PubMed ID: 31949400
[TBL] [Abstract][Full Text] [Related]
14. Radiomics Based on T2-Weighted Imaging and Apparent Diffusion Coefficient Images for Preoperative Evaluation of Lymph Node Metastasis in Rectal Cancer Patients.
Li C; Yin J
Front Oncol; 2021; 11():671354. PubMed ID: 34041033
[TBL] [Abstract][Full Text] [Related]
15. T2WI-based texture analysis predicts preoperative lymph node metastasis of rectal cancer.
Zhuang Z; Zhang Y; Yang X; Deng X; Wang Z
Abdom Radiol (NY); 2024 Feb; ():. PubMed ID: 38411692
[TBL] [Abstract][Full Text] [Related]
16. Multi-modal radiomics model to predict treatment response to neoadjuvant chemotherapy for locally advanced rectal cancer.
Li ZY; Wang XD; Li M; Liu XJ; Ye Z; Song B; Yuan F; Yuan Y; Xia CC; Zhang X; Li Q
World J Gastroenterol; 2020 May; 26(19):2388-2402. PubMed ID: 32476800
[TBL] [Abstract][Full Text] [Related]
17. Predicting Treatment Response to Neoadjuvant Chemoradiotherapy in Rectal Mucinous Adenocarcinoma Using an MRI-Based Radiomics Nomogram.
Li Z; Li S; Zang S; Ma X; Chen F; Xia Y; Chen L; Shen F; Lu Y; Lu J
Front Oncol; 2021; 11():671636. PubMed ID: 34109121
[TBL] [Abstract][Full Text] [Related]
18. MRI-based Multiregional Radiomics for Pretreatment Prediction of Distant Metastasis After Neoadjuvant Chemoradiotherapy in Patients with Locally Advanced Rectal Cancer.
Zhao R; Wan L; Chen S; Peng W; Liu X; Wang S; Li L; Zhang H
Acad Radiol; 2024 Apr; 31(4):1367-1377. PubMed ID: 37802671
[TBL] [Abstract][Full Text] [Related]
19. T2WI-based MRI radiomics for the prediction of preoperative extranodal extension and prognosis in resectable rectal cancer.
Li H; Chai L; Pu H; Yin LL; Li M; Zhang X; Liu YS; Pang MH; Lu T
Insights Imaging; 2024 Feb; 15(1):57. PubMed ID: 38411722
[TBL] [Abstract][Full Text] [Related]
20. Radiomics analysis for prediction of lymph node metastasis after neoadjuvant chemotherapy based on pretreatment MRI in patients with locally advanced cervical cancer.
Liu J; Dong L; Zhang X; Wu Q; Yang Z; Zhang Y; Xu C; Wu Q; Wang M
Front Oncol; 2024; 14():1376640. PubMed ID: 38779088
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
