233 related articles for article (PubMed ID: 36050264)
1. Nomograms Combining Clinical and Imaging Parameters to Predict Recurrence and Disease-free Survival After Concurrent Chemoradiotherapy in Patients With Locally Advanced Cervical Cancer.
Zhang Y; Liu L; Zhang K; Su R; Jia H; Qian L; Dong J
Acad Radiol; 2023 Mar; 30(3):499-508. PubMed ID: 36050264
[TBL] [Abstract][Full Text] [Related]
2. IVIM-DWI and MRI-based radiomics in cervical cancer: Prediction of concurrent chemoradiotherapy sensitivity in combination with clinical prognostic factors.
Zhang Y; Zhang K; Jia H; Xia B; Zang C; Liu Y; Qian L; Dong J
Magn Reson Imaging; 2022 Sep; 91():37-44. PubMed ID: 35568271
[TBL] [Abstract][Full Text] [Related]
3. Development and validation of a
Liu H; Cui Y; Chang C; Zhou Z; Zhang Y; Ma C; Yin Y; Wang R
BMC Cancer; 2024 Jan; 24(1):150. PubMed ID: 38291351
[TBL] [Abstract][Full Text] [Related]
4. Multiparametric magnetic resonance imaging-derived radiomics for the prediction of disease-free survival in early-stage squamous cervical cancer.
Zhou Y; Gu HL; Zhang XL; Tian ZF; Xu XQ; Tang WW
Eur Radiol; 2022 Apr; 32(4):2540-2551. PubMed ID: 34642807
[TBL] [Abstract][Full Text] [Related]
5. MRI radiomics in overall survival prediction of local advanced cervical cancer patients tread by adjuvant chemotherapy following concurrent chemoradiotherapy or concurrent chemoradiotherapy alone.
Wei G; Jiang P; Tang Z; Qu A; Deng X; Guo F; Sun H; Zhang Y; Gu L; Zhang S; Mu W; Wang J; Tian J
Magn Reson Imaging; 2022 Sep; 91():81-90. PubMed ID: 35636572
[TBL] [Abstract][Full Text] [Related]
6. Prediction of outcome using pretreatment
Lucia F; Visvikis D; Desseroit MC; Miranda O; Malhaire JP; Robin P; Pradier O; Hatt M; Schick U
Eur J Nucl Med Mol Imaging; 2018 May; 45(5):768-786. PubMed ID: 29222685
[TBL] [Abstract][Full Text] [Related]
7. Nomograms combining computed tomography-based body composition changes with clinical prognostic factors to predict survival in locally advanced cervical cancer patients.
Fu B; Wei L; Wang C; Xiong B; Bo J; Jiang X; Zhang Y; Jia H; Dong J
J Xray Sci Technol; 2024; 32(2):427-441. PubMed ID: 38189735
[TBL] [Abstract][Full Text] [Related]
8. Machine Learning-Based Models for Assessing Postoperative Risk Factors in Patients with Cervical Cancer.
Yu Z; Zhihui Q; Linrui L; Long L; Qibing W
Acad Radiol; 2024 Apr; 31(4):1410-1418. PubMed ID: 37891091
[TBL] [Abstract][Full Text] [Related]
9. MRI-based radiomics value for predicting the survival of patients with locally advanced cervical squamous cell cancer treated with concurrent chemoradiotherapy.
Zhang X; Zhao J; Zhang Q; Wang S; Zhang J; An J; Xie L; Yu X; Zhao X
Cancer Imaging; 2022 Jul; 22(1):35. PubMed ID: 35842679
[TBL] [Abstract][Full Text] [Related]
10. Multiparametric PET/MR (PET and MR-IVIM) for the evaluation of early treatment response and prediction of tumor recurrence in patients with locally advanced cervical cancer.
Gao S; Du S; Lu Z; Xin J; Gao S; Sun H
Eur Radiol; 2020 Feb; 30(2):1191-1201. PubMed ID: 31493211
[TBL] [Abstract][Full Text] [Related]
11. Combining Intravoxel Incoherent Motion Diffusion Weighted Imaging and Texture Analysis for a Nomogram to Predict Early Treatment Response to Concurrent Chemoradiotherapy in Cervical Cancer Patients.
Zheng X; Li C; Zhang L; Cao F; Fang X; Qian L; Dong J
J Oncol; 2021; 2021():9345353. PubMed ID: 34976060
[TBL] [Abstract][Full Text] [Related]
12. An MRI-based radiomics signature and clinical characteristics for survival prediction in early-stage cervical cancer.
Zheng RR; Cai MT; Lan L; Huang XW; Yang YJ; Powell M; Lin F
Br J Radiol; 2022 Jan; 95(1129):20210838. PubMed ID: 34797703
[TBL] [Abstract][Full Text] [Related]
13. Prediction of disease progression following concurrent chemoradiotherapy for uterine cervical cancer: value of post-treatment diffusion-weighted imaging.
Park JJ; Kim CK; Park BK
Eur Radiol; 2016 Sep; 26(9):3272-9. PubMed ID: 26685853
[TBL] [Abstract][Full Text] [Related]
14. A nomogram based on pretreatment CT radiomics features for predicting complete response to chemoradiotherapy in patients with esophageal squamous cell cancer.
Luo HS; Huang SF; Xu HY; Li XY; Wu SX; Wu DH
Radiat Oncol; 2020 Oct; 15(1):249. PubMed ID: 33121507
[TBL] [Abstract][Full Text] [Related]
15. Prediction of early response to concurrent chemoradiotherapy in cervical cancer: Value of multi-parameter MRI combined with clinical prognostic factors.
Zheng X; Guo W; Dong J; Qian L
Magn Reson Imaging; 2020 Oct; 72():159-166. PubMed ID: 32621877
[TBL] [Abstract][Full Text] [Related]
16. Added-value of dynamic contrast-enhanced MRI on prediction of tumor recurrence in locally advanced cervical cancer treated with chemoradiotherapy.
Zhang Q; Guo J; Ouyang H; Chen S; Zhao X; Yu X
Eur Radiol; 2022 Apr; 32(4):2529-2539. PubMed ID: 34647177
[TBL] [Abstract][Full Text] [Related]
17. Whole lesion histogram analysis of apparent diffusion coefficients on MRI predicts disease-free survival in locally advanced squamous cell cervical cancer after radical chemo-radiotherapy.
Zhao B; Cao K; Li XT; Zhu HT; Sun YS
BMC Cancer; 2019 Nov; 19(1):1115. PubMed ID: 31729974
[TBL] [Abstract][Full Text] [Related]
18. Machine learning-based radiomics for predicting outcomes in cervical cancer patients undergoing concurrent chemoradiotherapy.
Xin W; Rixin S; Linrui L; Zhihui Q; Long L; Yu Z
Comput Biol Med; 2024 May; 177():108593. PubMed ID: 38801795
[TBL] [Abstract][Full Text] [Related]
19. External validation of a combined PET and MRI radiomics model for prediction of recurrence in cervical cancer patients treated with chemoradiotherapy.
Lucia F; Visvikis D; Vallières M; Desseroit MC; Miranda O; Robin P; Bonaffini PA; Alfieri J; Masson I; Mervoyer A; Reinhold C; Pradier O; Hatt M; Schick U
Eur J Nucl Med Mol Imaging; 2019 Apr; 46(4):864-877. PubMed ID: 30535746
[TBL] [Abstract][Full Text] [Related]
20. Prognostic Value of Hematological Parameters in Locally Advanced Cervical Cancer Patients Treated With Concurrent Chemoradiotherapy.
Lee HJ; Kim JM; Chin YJ; Chong GO; Park SH; Lee YH; Hong DG; Lee YS
Anticancer Res; 2020 Jan; 40(1):451-458. PubMed ID: 31892600
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
