BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

700 related articles for article (PubMed ID: 31327039)

  • 1. Developing a prediction model based on MRI for pathological complete response after neoadjuvant chemoradiotherapy in locally advanced rectal cancer.
    Wan L; Zhang C; Zhao Q; Meng Y; Zou S; Yang Y; Liu Y; Jiang J; Ye F; Ouyang H; Zhao X; Zhang H
    Abdom Radiol (NY); 2019 Sep; 44(9):2978-2987. PubMed ID: 31327039
    [TBL] [Abstract][Full Text] [Related]  

  • 2. [Predictive value of combination of MRI tumor regression grade and apparent diffusion coefficient for pathological complete remission after neoadjuvant treatment of locally advanced rectal cancer].
    Xu N; Huang FC; Li WL; Luan X; Jiang YM; He B
    Zhonghua Wei Chang Wai Ke Za Zhi; 2021 Apr; 24(4):359-365. PubMed ID: 33878826
    [No Abstract]   [Full Text] [Related]  

  • 3. 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]  

  • 4. [The value of MR T2WI signal intensity related parameters for predicting pathological complete response to neoadjuvant chemoradiotherapy in locally advanced rectal cancer].
    Wan LJ; Zhang CD; Zhang HM; Meng YK; Ye F; Liu Y; Zhao XM; Zhou CW
    Zhonghua Zhong Liu Za Zhi; 2019 Nov; 41(11):837-843. PubMed ID: 31770851
    [No 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. [Application value of texture analysis of magnetic resonance images in prediction of neoadjuvant chemoradiotherapy efficacy for rectal cancer].
    Shu Z; Fang S; Ding Z; Mao D; Pang P; Gong X
    Zhonghua Wei Chang Wai Ke Za Zhi; 2018 Sep; 21(9):1051-1058. PubMed ID: 30269327
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Does restaging MRI radiomics analysis improve pathological complete response prediction in rectal cancer patients? A prognostic model development.
    Chiloiro G; Cusumano D; de Franco P; Lenkowicz J; Boldrini L; Carano D; Barbaro B; Corvari B; Dinapoli N; Giraffa M; Meldolesi E; Manfredi R; Valentini V; Gambacorta MA
    Radiol Med; 2022 Jan; 127(1):11-20. PubMed ID: 34725772
    [TBL] [Abstract][Full Text] [Related]  

  • 8. MRI T2-weighted sequences-based texture analysis (TA) as a predictor of response to neoadjuvant chemo-radiotherapy (nCRT) in patients with locally advanced rectal cancer (LARC).
    Crimì F; Capelli G; Spolverato G; Bao QR; Florio A; Milite Rossi S; Cecchin D; Albertoni L; Campi C; Pucciarelli S; Stramare R
    Radiol Med; 2020 Dec; 125(12):1216-1224. PubMed ID: 32410063
    [TBL] [Abstract][Full Text] [Related]  

  • 9. 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]  

  • 10. Deep learning-based radiomic features for improving neoadjuvant chemoradiation response prediction in locally advanced rectal cancer.
    Fu J; Zhong X; Li N; Van Dams R; Lewis J; Sung K; Raldow AC; Jin J; Qi XS
    Phys Med Biol; 2020 Apr; 65(7):075001. PubMed ID: 32092710
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Utility of ctDNA in predicting response to neoadjuvant chemoradiotherapy and prognosis assessment in locally advanced rectal cancer: A prospective cohort study.
    Wang Y; Yang L; Bao H; Fan X; Xia F; Wan J; Shen L; Guan Y; Bao H; Wu X; Xu Y; Shao Y; Sun Y; Tong T; Li X; Xu Y; Cai S; Zhu J; Zhang Z
    PLoS Med; 2021 Aug; 18(8):e1003741. PubMed ID: 34464382
    [TBL] [Abstract][Full Text] [Related]  

  • 12. [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]  

  • 13. Diagnostic accuracy of MRI in assessing tumor regression and identifying complete response in patients with locally advanced rectal cancer after neoadjuvant treatment.
    Aker M; Boone D; Chandramohan A; Sizer B; Motson R; Arulampalam T
    Abdom Radiol (NY); 2018 Dec; 43(12):3213-3219. PubMed ID: 29767284
    [TBL] [Abstract][Full Text] [Related]  

  • 14. MRI features and texture analysis for the early prediction of therapeutic response to neoadjuvant chemoradiotherapy and tumor recurrence of locally advanced rectal cancer.
    Park H; Kim KA; Jung JH; Rhie J; Choi SY
    Eur Radiol; 2020 Aug; 30(8):4201-4211. PubMed ID: 32270317
    [TBL] [Abstract][Full Text] [Related]  

  • 15. 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]  

  • 16. Tumor compactness improves the preoperative volumetry-based prediction of the pathological complete response of rectal cancer after preoperative concurrent chemoradiotherapy.
    Hsu CY; Wang CW; Kuo CC; Chen YH; Lan KH; Cheng AL; Kuo SH
    Oncotarget; 2017 Jan; 8(5):7921-7934. PubMed ID: 27974702
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Extracellular volume fraction determined by equilibrium contrast-enhanced CT for the prediction of the pathological complete response to neoadjuvant chemoradiotherapy for locally advanced rectal cancer.
    Luo Y; Liu L; Liu D; Shen H; Wang X; Fan C; Zeng Z; Zhang J; Tan Y; Zhang X; Wu J; Zhang J
    Eur Radiol; 2023 Jun; 33(6):4042-4051. PubMed ID: 36462046
    [TBL] [Abstract][Full Text] [Related]  

  • 18. MR-based artificial intelligence model to assess response to therapy in locally advanced rectal cancer.
    Ferrari R; Mancini-Terracciano C; Voena C; Rengo M; Zerunian M; Ciardiello A; Grasso S; Mare' V; Paramatti R; Russomando A; Santacesaria R; Satta A; Solfaroli Camillocci E; Faccini R; Laghi A
    Eur J Radiol; 2019 Sep; 118():1-9. PubMed ID: 31439226
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Quantitative analysis of diffusion weighted imaging to predict pathological good response to neoadjuvant chemoradiation for locally advanced rectal cancer.
    Tang Z; Zhang XY; Liu Z; Li XT; Shi YJ; Wang S; Fang M; Shen C; Dong E; Sun YS; Tian J
    Radiother Oncol; 2019 Mar; 132():100-108. PubMed ID: 30825957
    [TBL] [Abstract][Full Text] [Related]  

  • 20. 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]  

    [Next]    [New Search]
    of 35.