BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

360 related articles for article (PubMed ID: 32822542)

  • 1. Radiomic signatures derived from multiparametric MRI for the pretreatment prediction of response to neoadjuvant chemotherapy in breast cancer.
    Bian T; Wu Z; Lin Q; Wang H; Ge Y; Duan S; Fu G; Cui C; Su X
    Br J Radiol; 2020 Nov; 93(1115):20200287. PubMed ID: 32822542
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Evaluation of Multiparametric MRI Radiomics-Based Nomogram in Prediction of Response to Neoadjuvant Chemotherapy in Breast Cancer: A Two-Center study.
    Wang X; Hua H; Han J; Zhong X; Liu J; Chen J
    Clin Breast Cancer; 2023 Aug; 23(6):e331-e344. PubMed ID: 37321954
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Multiparametric MRI-based radiomics analysis for prediction of breast cancers insensitive to neoadjuvant chemotherapy.
    Xiong Q; Zhou X; Liu Z; Lei C; Yang C; Yang M; Zhang L; Zhu T; Zhuang X; Liang C; Liu Z; Tian J; Wang K
    Clin Transl Oncol; 2020 Jan; 22(1):50-59. PubMed ID: 30977048
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Radiomics of Multiparametric MRI for Pretreatment Prediction of Pathologic Complete Response to Neoadjuvant Chemotherapy in Breast Cancer: A Multicenter Study.
    Liu Z; Li Z; Qu J; Zhang R; Zhou X; Li L; Sun K; Tang Z; Jiang H; Li H; Xiong Q; Ding Y; Zhao X; Wang K; Liu Z; Tian J
    Clin Cancer Res; 2019 Jun; 25(12):3538-3547. PubMed ID: 30842125
    [TBL] [Abstract][Full Text] [Related]  

  • 5. The accuracy of breast MRI radiomic methodologies in predicting pathological complete response to neoadjuvant chemotherapy: A systematic review and network meta-analysis.
    O'Donnell JPM; Gasior SA; Davey MG; O'Malley E; Lowery AJ; McGarry J; O'Connell AM; Kerin MJ; McCarthy P
    Eur J Radiol; 2022 Dec; 157():110561. PubMed ID: 36308849
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Radiomic Nomogram for Pretreatment Prediction of Pathologic Complete Response to Neoadjuvant Therapy in Breast Cancer: Predictive Value of Staging Contrast-enhanced CT.
    Huang X; Mai J; Huang Y; He L; Chen X; Wu X; Li Y; Yang X; Dong M; Huang J; Zhang F; Liang C; Liu Z
    Clin Breast Cancer; 2021 Aug; 21(4):e388-e401. PubMed ID: 33451965
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Nomogram for Early Prediction of Pathological Complete Response to Neoadjuvant Chemotherapy in Breast Cancer Using Dynamic Contrast-enhanced and Diffusion-weighted MRI.
    Zhao R; Lu H; Li YB; Shao ZZ; Ma WJ; Liu PF
    Acad Radiol; 2022 Jan; 29 Suppl 1():S155-S163. PubMed ID: 33593702
    [TBL] [Abstract][Full Text] [Related]  

  • 8. A delta-radiomic lymph node model using dynamic contrast enhanced MRI for the early prediction of axillary response after neoadjuvant chemotherapy in breast cancer patients.
    Liu S; Du S; Gao S; Teng Y; Jin F; Zhang L
    BMC Cancer; 2023 Jan; 23(1):15. PubMed ID: 36604679
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Development and Validation of a Preoperative Magnetic Resonance Imaging Radiomics-Based Signature to Predict Axillary Lymph Node Metastasis and Disease-Free Survival in Patients With Early-Stage Breast Cancer.
    Yu Y; Tan Y; Xie C; Hu Q; Ouyang J; Chen Y; Gu Y; Li A; Lu N; He Z; Yang Y; Chen K; Ma J; Li C; Ma M; Li X; Zhang R; Zhong H; Ou Q; Zhang Y; He Y; Li G; Wu Z; Su F; Song E; Yao H
    JAMA Netw Open; 2020 Dec; 3(12):e2028086. PubMed ID: 33289845
    [TBL] [Abstract][Full Text] [Related]  

  • 10. A Noninvasive Tool Based on Magnetic Resonance Imaging Radiomics for the Preoperative Prediction of Pathological Complete Response to Neoadjuvant Chemotherapy in Breast Cancer.
    Li C; Lu N; He Z; Tan Y; Liu Y; Chen Y; Wu Z; Liu J; Ren W; Mao L; Yu Y; Xie C; Yao H
    Ann Surg Oncol; 2022 Nov; 29(12):7685-7693. PubMed ID: 35773561
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Magnetic resonance imaging radiomics predicts preoperative axillary lymph node metastasis to support surgical decisions and is associated with tumor microenvironment in invasive breast cancer: A machine learning, multicenter study.
    Yu Y; He Z; Ouyang J; Tan Y; Chen Y; Gu Y; Mao L; Ren W; Wang J; Lin L; Wu Z; Liu J; Ou Q; Hu Q; Li A; Chen K; Li C; Lu N; Li X; Su F; Liu Q; Xie C; Yao H
    EBioMedicine; 2021 Jul; 69():103460. PubMed ID: 34233259
    [TBL] [Abstract][Full Text] [Related]  

  • 12. 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]  

  • 13. Impact of Machine Learning With Multiparametric Magnetic Resonance Imaging of the Breast for Early Prediction of Response to Neoadjuvant Chemotherapy and Survival Outcomes in Breast Cancer Patients.
    Tahmassebi A; Wengert GJ; Helbich TH; Bago-Horvath Z; Alaei S; Bartsch R; Dubsky P; Baltzer P; Clauser P; Kapetas P; Morris EA; Meyer-Baese A; Pinker K
    Invest Radiol; 2019 Feb; 54(2):110-117. PubMed ID: 30358693
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Multiparametric MRI-based radiomics nomogram for early prediction of pathological response to neoadjuvant chemotherapy in locally advanced gastric cancer.
    Li J; Yin H; Wang Y; Zhang H; Ma F; Li H; Qu J
    Eur Radiol; 2023 Apr; 33(4):2746-2756. PubMed ID: 36512039
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Radiomics-Based Pretherapeutic Prediction of Non-response to Neoadjuvant Therapy in Locally Advanced Rectal Cancer.
    Zhou X; Yi Y; Liu Z; Cao W; Lai B; Sun K; Li L; Zhou Z; Feng Y; Tian J
    Ann Surg Oncol; 2019 Jun; 26(6):1676-1684. PubMed ID: 30887373
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Ultrasound-based deep learning radiomics in the assessment of pathological complete response to neoadjuvant chemotherapy in locally advanced breast cancer.
    Jiang M; Li CL; Luo XM; Chuan ZR; Lv WZ; Li X; Cui XW; Dietrich CF
    Eur J Cancer; 2021 Apr; 147():95-105. PubMed ID: 33639324
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Value of radiomics based on CE-MRI for predicting the efficacy of neoadjuvant chemotherapy in invasive breast cancer.
    Li Q; Huang Y; Xiao Q; Duan S; Wang S; Li J; Niu Q; Gu Y
    Br J Radiol; 2022 Oct; 95(1139):20220186. PubMed ID: 36005646
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Prediction of neoadjuvant chemotherapy pathological complete response for breast cancer based on radiomics nomogram of intratumoral and derived tissue.
    Zheng G; Hou J; Shu Z; Peng J; Han L; Yuan Z; He X; Gong X
    BMC Med Imaging; 2024 Jan; 24(1):22. PubMed ID: 38245712
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Development and validation of a nomogram based on pretreatment dynamic contrast-enhanced MRI for the prediction of pathologic response after neoadjuvant chemotherapy for triple-negative breast cancer.
    Li Y; Chen Y; Zhao R; Ji Y; Li J; Zhang Y; Lu H
    Eur Radiol; 2022 Mar; 32(3):1676-1687. PubMed ID: 34767068
    [TBL] [Abstract][Full Text] [Related]  

  • 20. A radiomic model to classify response to neoadjuvant chemotherapy in breast cancer.
    McAnena P; Moloney BM; Browne R; O'Halloran N; Walsh L; Walsh S; Sheppard D; Sweeney KJ; Kerin MJ; Lowery AJ
    BMC Med Imaging; 2022 Dec; 22(1):225. PubMed ID: 36564734
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 18.