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 *

191 related articles for article (PubMed ID: 33504446)

  • 1. Difference of DCE-MRI Parameters at Different Time Points and Their Predictive Value for Axillary Lymph Node Metastasis of Breast Cancer.
    Ya G; Wen F; Xing-Ru L; Zhuan-Zhuan G; Jun-Qiang L
    Acad Radiol; 2022 Jan; 29 Suppl 1():S79-S86. PubMed ID: 33504446
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Preoperative prediction of lymphovascular invasion in invasive breast cancer with dynamic contrast-enhanced-MRI-based radiomics.
    Liu Z; Feng B; Li C; Chen Y; Chen Q; Li X; Guan J; Chen X; Cui E; Li R; Li Z; Long W
    J Magn Reson Imaging; 2019 Sep; 50(3):847-857. PubMed ID: 30773770
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Attention-based Deep Learning for the Preoperative Differentiation of Axillary Lymph Node Metastasis in Breast Cancer on DCE-MRI.
    Gao J; Zhong X; Li W; Li Q; Shao H; Wang Z; Dai Y; Ma H; Shi Y; Zhang H; Duan S; Zhang K; Yang P; Zhao F; Zhang H; Xie H; Mao N
    J Magn Reson Imaging; 2023 Jun; 57(6):1842-1853. PubMed ID: 36219519
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Prediction of axillary lymph node metastasis using a magnetic resonance imaging radiomics model of invasive breast cancer primary tumor.
    Shi W; Su Y; Zhang R; Xia W; Lian Z; Mao N; Wang Y; Zhang A; Gao X; Zhang Y
    Cancer Imaging; 2024 Sep; 24(1):122. PubMed ID: 39272199
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Tumor segmentation analysis at different post-contrast time points: A possible source of variability of quantitative DCE-MRI parameters in locally advanced breast cancer.
    Romeo V; Cavaliere C; Imbriaco M; Verde F; Petretta M; Franzese M; Stanzione A; Cuocolo R; Aiello M; Basso L; Amitrano M; Lauria R; Accurso A; Brunetti A; Salvatore M
    Eur J Radiol; 2020 May; 126():108907. PubMed ID: 32145597
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Magnetic resonance imaging features for predicting axillary lymph node metastasis in patients with breast cancer.
    Zhao M; Wu Q; Guo L; Zhou L; Fu K
    Eur J Radiol; 2020 Aug; 129():109093. PubMed ID: 32512504
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Non-invasive prediction model of axillary lymph node status in patients with early-stage breast cancer: a feasibility study based on dynamic contrast-enhanced-MRI radiomics.
    Chen W; Lin G; Kong C; Wu X; Hu Y; Chen M; Xia S; Lu C; Xu M; Ji J
    Br J Radiol; 2024 Feb; 97(1154):439-450. PubMed ID: 38308028
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Differentiating axillary lymph node metastasis in invasive breast cancer patients: A comparison of radiomic signatures from multiparametric breast MR sequences.
    Chai R; Ma H; Xu M; Arefan D; Cui X; Liu Y; Zhang L; Wu S; Xu K
    J Magn Reson Imaging; 2019 Oct; 50(4):1125-1132. PubMed ID: 30848041
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Preoperative MRI improves prediction of extensive occult axillary lymph node metastases in breast cancer patients with a positive sentinel lymph node biopsy.
    Loiselle C; Eby PR; Kim JN; Calhoun KE; Allison KH; Gadi VK; Peacock S; Storer BE; Mankoff DA; Partridge SC; Lehman CD
    Acad Radiol; 2014 Jan; 21(1):92-8. PubMed ID: 24331270
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Usefulness of preoperative breast magnetic resonance imaging with a dedicated axillary sequence for the detection of axillary lymph node metastasis in patients with early ductal breast cancer.
    Ahn HS; Jang M; Kim SM; La Yun B; Lee SH
    Radiol Med; 2019 Dec; 124(12):1220-1228. PubMed ID: 31422573
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Investigation of synthetic MRI with quantitative parameters for discriminating axillary lymph nodes status in invasive breast cancer.
    Qu M; Feng W; Liu X; Li Z; Li Y; Lu X; Lei J
    Eur J Radiol; 2024 Jun; 175():111452. PubMed ID: 38604092
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Comparison of Traditional Radiomics, Deep Learning Radiomics and Fusion Methods for Axillary Lymph Node Metastasis Prediction in Breast Cancer.
    Li X; Yang L; Jiao X
    Acad Radiol; 2023 Jul; 30(7):1281-1287. PubMed ID: 36376154
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Noninvasive nodal staging in patients with breast cancer using gadofosveset-enhanced magnetic resonance imaging: a feasibility study.
    Schipper RJ; Smidt ML; van Roozendaal LM; Castro CJ; de Vries B; Heuts EM; Keymeulen KB; Wildberger JE; Lobbes MB; Beets-Tan RG
    Invest Radiol; 2013 Mar; 48(3):134-9. PubMed ID: 23262788
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Prediction of Axillary Lymph Node Metastasis in Breast Cancer using Intra-peritumoral Textural Transition Analysis based on Dynamic Contrast-enhanced Magnetic Resonance Imaging.
    Zhan C; Hu Y; Wang X; Liu H; Xia L; Ai T
    Acad Radiol; 2022 Jan; 29 Suppl 1():S107-S115. PubMed ID: 33712393
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Prediction of the number of metastatic axillary lymph nodes in breast cancer by radiomic signature based on dynamic contrast-enhanced MRI.
    Li L; Yu T; Sun J; Jiang S; Liu D; Wang X; Zhang J
    Acta Radiol; 2022 Aug; 63(8):1014-1022. PubMed ID: 34162234
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Combination of IVIM with DCE-MRI for diagnostic and prognostic evaluation of breast cancer.
    Zhang J; Zheng Y; Li L; Wang R; Jiang W; Ai K; Gan T; Wang P
    Magn Reson Imaging; 2024 Nov; 113():110204. PubMed ID: 38971263
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Multiregional dynamic contrast-enhanced MRI-based integrated system for predicting pathological complete response of axillary lymph node to neoadjuvant chemotherapy in breast cancer: multicentre study.
    Li Z; Gao J; Zhou H; Li X; Zheng T; Lin F; Wang X; Chu T; Wang Q; Wang S; Cao K; Liang Y; Zhao F; Xie H; Xu C; Zhang H; Niu Q; Ma H; Mao N
    EBioMedicine; 2024 Sep; 107():105311. PubMed ID: 39191174
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Radiomic features of axillary lymph nodes based on pharmacokinetic modeling DCE-MRI allow preoperative diagnosis of their metastatic status in breast cancer.
    Luo HB; Liu YY; Wang CH; Qing HM; Wang M; Zhang X; Chen XY; Xu GH; Zhou P; Ren J
    PLoS One; 2021; 16(3):e0247074. PubMed ID: 33647031
    [TBL] [Abstract][Full Text] [Related]  

  • 19. 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]  

  • 20. Development and validation of a point-based scoring system for predicting axillary lymph node metastasis and disease outcome in breast cancer using clinicopathological and multiparametric MRI features.
    Chen X; Yang Z; Huang R; Li Y; Liao Y; Li G; Wang M; Chen X; Dai Z; Fan W
    Cancer Imaging; 2023 Jun; 23(1):54. PubMed ID: 37264446
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 10.