BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

231 related articles for article (PubMed ID: 32382845)

  • 1. MRI texture features differentiate clinicopathological characteristics of cervical carcinoma.
    Wang M; Perucho JAU; Tse KY; Chu MMY; Ip P; Lee EYP
    Eur Radiol; 2020 Oct; 30(10):5384-5391. PubMed ID: 32382845
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Radiomic Features of T2-weighted Imaging and Diffusion Kurtosis Imaging in Differentiating Clinicopathological Characteristics of Cervical Carcinoma.
    Wang M; Perucho JAU; Vardhanabhuti V; Ip P; Ngan HYS; Lee EYP
    Acad Radiol; 2022 Aug; 29(8):1133-1140. PubMed ID: 34583867
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Role of MR texture analysis in histological subtyping and grading of renal cell carcinoma: a preliminary study.
    Goyal A; Razik A; Kandasamy D; Seth A; Das P; Ganeshan B; Sharma R
    Abdom Radiol (NY); 2019 Oct; 44(10):3336-3349. PubMed ID: 31300850
    [TBL] [Abstract][Full Text] [Related]  

  • 4. MRI-based radiomics features for the non-invasive prediction of FIGO stage in cervical carcinoma: A multi-center study.
    Liu Y; Dong TF; Li PJ; Chen LB; Song T
    Magn Reson Imaging; 2024 Jul; 110():170-175. PubMed ID: 38035947
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Value of whole-lesion apparent diffusion coefficient (ADC) first-order statistics and texture features in clinical staging of cervical cancers.
    Guan Y; Li W; Jiang Z; Zhang B; Chen Y; Huang X; Zhang J; Liu S; He J; Zhou Z; Ge Y
    Clin Radiol; 2017 Nov; 72(11):951-958. PubMed ID: 28728757
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Preoperative tumor texture analysis on MRI predicts high-risk disease and reduced survival in endometrial cancer.
    Ytre-Hauge S; Dybvik JA; Lundervold A; Salvesen ØO; Krakstad C; Fasmer KE; Werner HM; Ganeshan B; Høivik E; Bjørge L; Trovik J; Haldorsen IS
    J Magn Reson Imaging; 2018 Dec; 48(6):1637-1647. PubMed ID: 30102441
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Radiomics strategy for glioma grading using texture features from multiparametric MRI.
    Tian Q; Yan LF; Zhang X; Zhang X; Hu YC; Han Y; Liu ZC; Nan HY; Sun Q; Sun YZ; Yang Y; Yu Y; Zhang J; Hu B; Xiao G; Chen P; Tian S; Xu J; Wang W; Cui GB
    J Magn Reson Imaging; 2018 Dec; 48(6):1518-1528. PubMed ID: 29573085
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Radiomics analysis of apparent diffusion coefficient in cervical cancer: A preliminary study on histological grade evaluation.
    Liu Y; Zhang Y; Cheng R; Liu S; Qu F; Yin X; Wang Q; Xiao B; Ye Z
    J Magn Reson Imaging; 2019 Jan; 49(1):280-290. PubMed ID: 29761595
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Classifying early stages of cervical cancer with MRI-based radiomics.
    Zhao X; Wang X; Zhang B; Liu X; Xuan D; Xia Y; Zhang X
    Magn Reson Imaging; 2022 Jun; 89():70-76. PubMed ID: 35337907
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Deep learning for fully automated tumor segmentation and extraction of magnetic resonance radiomics features in cervical cancer.
    Lin YC; Lin CH; Lu HY; Chiang HJ; Wang HK; Huang YT; Ng SH; Hong JH; Yen TC; Lai CH; Lin G
    Eur Radiol; 2020 Mar; 30(3):1297-1305. PubMed ID: 31712961
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Relationship between imaging biomarkers of stage I cervical cancer and poor-prognosis histologic features: quantitative histogram analysis of diffusion-weighted MR images.
    Downey K; Riches SF; Morgan VA; Giles SL; Attygalle AD; Ind TE; Barton DP; Shepherd JH; deSouza NM
    AJR Am J Roentgenol; 2013 Feb; 200(2):314-20. PubMed ID: 23345352
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Pre-treatment MRI minimum apparent diffusion coefficient value is a potential prognostic imaging biomarker in cervical cancer patients treated with definitive chemoradiation.
    Marconi DG; Fregnani JH; Rossini RR; Netto AK; Lucchesi FR; Tsunoda AT; Kamrava M
    BMC Cancer; 2016 Jul; 16():556. PubMed ID: 27469349
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Whole-tumor texture model based on diffusion kurtosis imaging for assessing cervical cancer: a preliminary study.
    Zhang Q; Yu X; Ouyang H; Zhang J; Chen S; Xie L; Zhao X
    Eur Radiol; 2021 Aug; 31(8):5576-5585. PubMed ID: 33464399
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Texture analysis versus conventional MRI prognostic factors in predicting tumor response to neoadjuvant chemotherapy in patients with locally advanced cancer of the uterine cervix.
    Ciolina M; Vinci V; Villani L; Gigli S; Saldari M; Panici PB; Perniola G; Laghi A; Catalano C; Manganaro L
    Radiol Med; 2019 Oct; 124(10):955-964. PubMed ID: 31254220
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Radiomic signature as a predictive factor for lymph node metastasis in early-stage cervical cancer.
    Kan Y; Dong D; Zhang Y; Jiang W; Zhao N; Han L; Fang M; Zang Y; Hu C; Tian J; Li C; Luo Y
    J Magn Reson Imaging; 2019 Jan; 49(1):304-310. PubMed ID: 30102438
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Integration of dynamic contrast-enhanced magnetic resonance imaging and T2-weighted imaging radiomic features by a canonical correlation analysis-based feature fusion method to predict histological grade in ductal breast carcinoma.
    Fan M; Liu Z; Xie S; Xu M; Wang S; Gao X; Li L
    Phys Med Biol; 2019 Oct; 64(21):215001. PubMed ID: 31470420
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Texture Analysis of Apparent Diffusion Coefficient Maps in Cervical Carcinoma: Correlation with Histopathologic Findings and Prognosis.
    Yamada I; Oshima N; Miyasaka N; Wakana K; Wakabayashi A; Sakamoto J; Saida Y; Tateishi U; Kobayashi D
    Radiol Imaging Cancer; 2020 May; 2(3):e190085. PubMed ID: 33778713
    [TBL] [Abstract][Full Text] [Related]  

  • 18. A histogram analysis of diffusion and perfusion features of cervical cancer based on intravoxel incoherent motion magnetic resonance imaging.
    Thapa D; Wang P; Wu G; Wang X; Sun Q
    Magn Reson Imaging; 2019 Jan; 55():103-111. PubMed ID: 29953932
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Radiomics Analysis of Multiparametric MRI Evaluates the Pathological Features of Cervical Squamous Cell Carcinoma.
    Wu Q; Shi D; Dou S; Shi L; Liu M; Dong L; Chang X; Wang M
    J Magn Reson Imaging; 2019 Apr; 49(4):1141-1148. PubMed ID: 30230114
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Feasibility of an ADC-based radiomics model for predicting pelvic lymph node metastases in patients with stage IB-IIA cervical squamous cell carcinoma.
    Yu YY; Zhang R; Dong RT; Hu QY; Yu T; Liu F; Luo YH; Dong Y
    Br J Radiol; 2019 May; 92(1097):20180986. PubMed ID: 30888846
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 12.