BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

227 related articles for article (PubMed ID: 35501512)

  • 1. MRI-based radiomics to predict response in locally advanced rectal cancer: comparison of manual and automatic segmentation on external validation in a multicentre study.
    Defeudis A; Mazzetti S; Panic J; Micilotta M; Vassallo L; Giannetto G; Gatti M; Faletti R; Cirillo S; Regge D; Giannini V
    Eur Radiol Exp; 2022 May; 6(1):19. PubMed ID: 35501512
    [TBL] [Abstract][Full Text] [Related]  

  • 2. 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]  

  • 3. External validation and comparison of MR-based radiomics models for predicting pathological complete response in locally advanced rectal cancer: a two-centre, multi-vendor study.
    Wei Q; Chen Z; Tang Y; Chen W; Zhong L; Mao L; Hu S; Wu Y; Deng K; Yang W; Liu X
    Eur Radiol; 2023 Mar; 33(3):1906-1917. PubMed ID: 36355199
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Machine learning-based multiparametric MRI radiomics for predicting poor responders after neoadjuvant chemoradiotherapy in rectal Cancer patients.
    Wang J; Chen J; Zhou R; Gao Y; Li J
    BMC Cancer; 2022 Apr; 22(1):420. PubMed ID: 35439946
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Development and validation of a radiopathomics model to predict pathological complete response to neoadjuvant chemoradiotherapy in locally advanced rectal cancer: a multicentre observational study.
    Feng L; Liu Z; Li C; Li Z; Lou X; Shao L; Wang Y; Huang Y; Chen H; Pang X; Liu S; He F; Zheng J; Meng X; Xie P; Yang G; Ding Y; Wei M; Yun J; Hung MC; Zhou W; Wahl DR; Lan P; Tian J; Wan X
    Lancet Digit Health; 2022 Jan; 4(1):e8-e17. PubMed ID: 34952679
    [TBL] [Abstract][Full Text] [Related]  

  • 6. 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]  

  • 7. Prediction of locally advanced rectal cancer response to neoadjuvant chemoradiation therapy using volumetric multiparametric MRI-based radiomics.
    El Homsi M; Bane O; Fauveau V; Hectors S; Vietti Violi N; Sylla P; Ko HB; Cuevas J; Carbonell G; Nehlsen A; Vanguri R; Viswanath S; Jambawalikar S; Shaish H; Taouli B
    Abdom Radiol (NY); 2024 Mar; 49(3):791-800. PubMed ID: 38150143
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Development and validation of an MRI-based radiomic nomogram to distinguish between good and poor responders in patients with locally advanced rectal cancer undergoing neoadjuvant chemoradiotherapy.
    Wang J; Liu X; Hu B; Gao Y; Chen J; Li J
    Abdom Radiol (NY); 2021 May; 46(5):1805-1815. PubMed ID: 33151359
    [TBL] [Abstract][Full Text] [Related]  

  • 9. 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]  

  • 10. 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]  

  • 11. Radiomics of locally advanced rectal cancer: machine learning-based prediction of response to neoadjuvant chemoradiotherapy using pre-treatment sagittal T2-weighted MRI.
    Yardimci AH; Kocak B; Sel I; Bulut H; Bektas CT; Cin M; Dursun N; Bektas H; Mermut O; Yardimci VH; Kilickesmez O
    Jpn J Radiol; 2023 Jan; 41(1):71-82. PubMed ID: 35962933
    [TBL] [Abstract][Full Text] [Related]  

  • 12. 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]  

  • 13. Attention mechanism based multi-sequence MRI fusion improves prediction of response to neoadjuvant chemoradiotherapy in locally advanced rectal cancer.
    Zhou X; Yu Y; Feng Y; Ding G; Liu P; Liu L; Ren W; Zhu Y; Cao W
    Radiat Oncol; 2023 Oct; 18(1):175. PubMed ID: 37891611
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Applicability of a pathological complete response magnetic resonance-based radiomics model for locally advanced rectal cancer in intercontinental cohort.
    Boldrini L; Lenkowicz J; Orlandini LC; Yin G; Cusumano D; Chiloiro G; Dinapoli N; Peng Q; Casà C; Gambacorta MA; Valentini V; Lang J
    Radiat Oncol; 2022 Apr; 17(1):78. PubMed ID: 35428267
    [TBL] [Abstract][Full Text] [Related]  

  • 15. 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]  

  • 16. [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]  

  • 17. Analysis of MRI and CT-based radiomics features for personalized treatment in locally advanced rectal cancer and external validation of published radiomics models.
    Shahzadi I; Zwanenburg A; Lattermann A; Linge A; Baldus C; Peeken JC; Combs SE; Diefenhardt M; Rödel C; Kirste S; Grosu AL; Baumann M; Krause M; Troost EGC; Löck S
    Sci Rep; 2022 Jun; 12(1):10192. PubMed ID: 35715462
    [TBL] [Abstract][Full Text] [Related]  

  • 18. 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]  

  • 19. 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]  

  • 20. 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]  

    [Next]    [New Search]
    of 12.