These tools will no longer be maintained as of December 31, 2024. Archived website can be found here. PubMed4Hh GitHub repository can be found here. Contact NLM Customer Service if you have questions.


BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

347 related articles for article (PubMed ID: 31786652)

  • 1. Pre-treatment ADC image-based random forest classifier for identifying resistant rectal adenocarcinoma to neoadjuvant chemoradiotherapy.
    Yang C; Jiang ZK; Liu LH; Zeng MS
    Int J Colorectal Dis; 2020 Jan; 35(1):101-107. PubMed ID: 31786652
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Diffusion-weighted magnetic resonance imaging in locally advanced rectal cancer treated with neoadjuvant chemoradiotherapy.
    De Felice F; Magnante AL; Musio D; Ciolina M; De Cecco CN; Rengo M; Laghi A; Tombolini V
    Eur J Surg Oncol; 2017 Jul; 43(7):1324-1329. PubMed ID: 28363512
    [TBL] [Abstract][Full Text] [Related]  

  • 3. 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]  

  • 4. 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]  

  • 5. Diffusion-weighted imaging: Apparent diffusion coefficient histogram analysis for detecting pathologic complete response to chemoradiotherapy in locally advanced rectal cancer.
    Choi MH; Oh SN; Rha SE; Choi JI; Lee SH; Jang HS; Kim JG; Grimm R; Son Y
    J Magn Reson Imaging; 2016 Jul; 44(1):212-20. PubMed ID: 26666560
    [TBL] [Abstract][Full Text] [Related]  

  • 6. 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]  

  • 7. [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]  

  • 8. 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]  

  • 9. Locally advanced rectal cancer: predicting non-responders to neoadjuvant chemoradiotherapy using apparent diffusion coefficient textures.
    Liu M; Lv H; Liu LH; Yang ZH; Jin EH; Wang ZC
    Int J Colorectal Dis; 2017 Jul; 32(7):1009-1012. PubMed ID: 28497403
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Predicting Rectal Cancer Response to Neoadjuvant Chemoradiotherapy Using Deep Learning of Diffusion Kurtosis MRI.
    Zhang XY; Wang L; Zhu HT; Li ZW; Ye M; Li XT; Shi YJ; Zhu HC; Sun YS
    Radiology; 2020 Jul; 296(1):56-64. PubMed ID: 32315264
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Prediction of efficacy of neoadjuvant chemoradiotherapy for rectal cancer: the value of texture analysis of magnetic resonance images.
    Shu Z; Fang S; Ye Q; Mao D; Cao H; Pang P; Gong X
    Abdom Radiol (NY); 2019 Nov; 44(11):3775-3784. PubMed ID: 30852633
    [TBL] [Abstract][Full Text] [Related]  

  • 12. 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]  

  • 13. Predicting the pathological response to chemoradiotherapy of non-mucinous rectal cancer using pretreatment texture features based on intravoxel incoherent motion diffusion-weighted imaging.
    Liu S; Wen L; Hou J; Nie S; Zhou J; Cao F; Lu Q; Qin Y; Fu Y; Yu X
    Abdom Radiol (NY); 2019 Aug; 44(8):2689-2698. PubMed ID: 31030244
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Performance of diffusion-weighted magnetic resonance imaging at 3.0T for early assessment of tumor response in locally advanced rectal cancer treated with preoperative chemoradiation therapy.
    Delli Pizzi A; Cianci R; Genovesi D; Esposito G; Timpani M; Tavoletta A; Pulsone P; Basilico R; Gabrielli D; Rosa C; Caravatta L; Di Tommaso M; Caulo M; Filippone A
    Abdom Radiol (NY); 2018 Sep; 43(9):2221-2230. PubMed ID: 29332248
    [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. 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]  

  • 17. 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]  

  • 18. 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]  

  • 19. Apparent Diffusion Coefficient Predicts Pathology Complete Response of Rectal Cancer Treated with Neoadjuvant Chemoradiotherapy.
    Chen YG; Chen MQ; Guo YY; Li SC; Wu JX; Xu BH
    PLoS One; 2016; 11(4):e0153944. PubMed ID: 27100991
    [TBL] [Abstract][Full Text] [Related]  

  • 20. 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]  

    [Next]    [New Search]
    of 18.