386 related articles for article (PubMed ID: 32296896)
1. Clinical utility of radiomics at baseline rectal MRI to predict complete response of rectal cancer after chemoradiation therapy.
Petkovska I; Tixier F; Ortiz EJ; Golia Pernicka JS; Paroder V; Bates DD; Horvat N; Fuqua J; Schilsky J; Gollub MJ; Garcia-Aguilar J; Veeraraghavan H
Abdom Radiol (NY); 2020 Nov; 45(11):3608-3617. PubMed ID: 32296896
[TBL] [Abstract][Full Text] [Related]
2. MRI Radiomics Model Predicts Pathologic Complete Response of Rectal Cancer Following Chemoradiotherapy.
Shin J; Seo N; Baek SE; Son NH; Lim JS; Kim NK; Koom WS; Kim S
Radiology; 2022 May; 303(2):351-358. PubMed ID: 35133200
[TBL] [Abstract][Full Text] [Related]
3. 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]
4. [A prediction model of pathological complete response in patients with locally advanced rectal cancer after PD-1 antibody combined with total neoadjuvant chemoradiotherapy based on MRI radiomics].
Zhang XY; Zhu HT; Li XT; Li YJ; Li ZW; Wang WH; Wu AW; Sun YS; Zhang L
Zhonghua Wei Chang Wai Ke Za Zhi; 2022 Mar; 25(3):228-234. PubMed ID: 35340172
[No Abstract] [Full Text] [Related]
5. Radiomics performs comparable to morphologic assessment by expert radiologists for prediction of response to neoadjuvant chemoradiotherapy on baseline staging MRI in rectal cancer.
van Griethuysen JJM; Lambregts DMJ; Trebeschi S; Lahaye MJ; Bakers FCH; Vliegen RFA; Beets GL; Aerts HJWL; Beets-Tan RGH
Abdom Radiol (NY); 2020 Mar; 45(3):632-643. PubMed ID: 31734709
[TBL] [Abstract][Full Text] [Related]
6. MR Imaging of Rectal Cancer: Radiomics Analysis to Assess Treatment Response after Neoadjuvant Therapy.
Horvat N; Veeraraghavan H; Khan M; Blazic I; Zheng J; Capanu M; Sala E; Garcia-Aguilar J; Gollub MJ; Petkovska I
Radiology; 2018 Jun; 287(3):833-843. PubMed ID: 29514017
[TBL] [Abstract][Full Text] [Related]
7. Radiomics of MRI for pretreatment prediction of pathologic complete response, tumor regression grade, and neoadjuvant rectal score in patients with locally advanced rectal cancer undergoing neoadjuvant chemoradiation: an international multicenter study.
Shaish H; Aukerman A; Vanguri R; Spinelli A; Armenta P; Jambawalikar S; Makkar J; Bentley-Hibbert S; Del Portillo A; Kiran R; Monti L; Bonifacio C; Kirienko M; Gardner KL; Schwartz L; Keller D
Eur Radiol; 2020 Nov; 30(11):6263-6273. PubMed ID: 32500192
[TBL] [Abstract][Full Text] [Related]
8. MRI radiomics features of mesorectal fat can predict response to neoadjuvant chemoradiation therapy and tumor recurrence in patients with locally advanced rectal cancer.
Jayaprakasam VS; Paroder V; Gibbs P; Bajwa R; Gangai N; Sosa RE; Petkovska I; Golia Pernicka JS; Fuqua JL; Bates DDB; Weiser MR; Cercek A; Gollub MJ
Eur Radiol; 2022 Feb; 32(2):971-980. PubMed ID: 34327580
[TBL] [Abstract][Full Text] [Related]
9. Machine learning for prediction of chemoradiation therapy response in rectal cancer using pre-treatment and mid-radiation multi-parametric MRI.
Shi L; Zhang Y; Nie K; Sun X; Niu T; Yue N; Kwong T; Chang P; Chow D; Chen JH; Su MY
Magn Reson Imaging; 2019 Sep; 61():33-40. PubMed ID: 31059768
[TBL] [Abstract][Full Text] [Related]
10. 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]
11. 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]
12. Machine learning-based response assessment in patients with rectal cancer after neoadjuvant chemoradiotherapy: radiomics analysis for assessing tumor regression grade using T2-weighted magnetic resonance images.
Lee YD; Kim HG; Seo M; Moon SK; Park SJ; You MW
Int J Colorectal Dis; 2024 May; 39(1):78. PubMed ID: 38789861
[TBL] [Abstract][Full Text] [Related]
13. 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]
14. Evaluating treatment response to neoadjuvant chemoradiotherapy in rectal cancer using various MRI-based radiomics models.
Li Z; Ma X; Shen F; Lu H; Xia Y; Lu J
BMC Med Imaging; 2021 Feb; 21(1):30. PubMed ID: 33593304
[TBL] [Abstract][Full Text] [Related]
15. 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]
16. MRI-based radiomic score increased mrTRG accuracy in predicting rectal cancer response to neoadjuvant therapy.
Miranda J; Horvat N; Assuncao AN; de M Machado FA; Chakraborty J; Pandini RV; Saraiva S; Nahas CSR; Nahas SC; Nomura CH
Abdom Radiol (NY); 2023 Jun; 48(6):1911-1920. PubMed ID: 37004557
[TBL] [Abstract][Full Text] [Related]
17. 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]
18. Prognostic prediction value of the clinical-radiomics tumour-stroma ratio in locally advanced rectal cancer.
Cai C; Hu T; Rong Z; Gong J; Tong T
Eur J Radiol; 2024 Jan; 170():111254. PubMed ID: 38091662
[TBL] [Abstract][Full Text] [Related]
19. Radiomic Features of Primary Rectal Cancers on Baseline T
Antunes JT; Ofshteyn A; Bera K; Wang EY; Brady JT; Willis JE; Friedman KA; Marderstein EL; Kalady MF; Stein SL; Purysko AS; Paspulati R; Gollamudi J; Madabhushi A; Viswanath SE
J Magn Reson Imaging; 2020 Nov; 52(5):1531-1541. PubMed ID: 32216127
[TBL] [Abstract][Full Text] [Related]
20. Predicting the tumor response to chemoradiotherapy for rectal cancer: Model development and external validation using MRI radiomics.
Bulens P; Couwenberg A; Intven M; Debucquoy A; Vandecaveye V; Van Cutsem E; D'Hoore A; Wolthuis A; Mukherjee P; Gevaert O; Haustermans K
Radiother Oncol; 2020 Jan; 142():246-252. PubMed ID: 31431368
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
