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  Prostate Cancer

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Articles published in Magn Reson Imaging

Retrieve available abstracts of 13 articles:
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Single Articles


    January 2024
  1. XINYANG S, Shuang Z, Tianci S, Xiangyu H, et al
    A machine learning radiomics model based on bpMRI to predict bone metastasis in newly diagnosed prostate cancer patients.
    Magn Reson Imaging. 2024;107:15-23.
    PubMed     Abstract available


    June 2023
  2. SONG E, Long J, Ma G, Liu H, et al
    Prostate lesion segmentation based on a 3D end-to-end convolution neural network with deep multi-scale attention.
    Magn Reson Imaging. 2023;99:98-109.
    PubMed     Abstract available


    April 2023
  3. YU VY, Otazo R, Wu C, Subashi E, et al
    Quantitative longitudinal mapping of radiation-treated prostate cancer using MR fingerprinting with radial acquisition and subspace reconstruction.
    Magn Reson Imaging. 2023 Apr 2:S0730-725X(23)00064.
    PubMed     Abstract available


    March 2023
  4. NAI YH, Cheong DLH, Roy S, Kok T, et al
    Comparison of quantitative parameters and radiomic features as inputs into machine learning models to predict the Gleason score of prostate cancer lesions.
    Magn Reson Imaging. 2023 Mar 16:S0730-725X(23)00050.
    PubMed     Abstract available


    January 2023
  5. GIBBONS M, Simko JP, Carroll PR, Noworolski SM, et al
    Prostate cancer lesion detection, volume quantification and high-grade cancer differentiation using cancer risk maps derived from multiparametric MRI with histopathology as the reference standard.
    Magn Reson Imaging. 2023 Jan 11:S0730-725X(23)00007.
    PubMed     Abstract available


    November 2022
  6. HU W, Chen L, Lin L, Wang J, et al
    Three-dimensional amide proton transfer-weighted and intravoxel incoherent motion imaging for predicting bone metastasis in patients with prostate cancer: A pilot study.
    Magn Reson Imaging. 2022;96:8-16.
    PubMed     Abstract available


    August 2022
  7. LAWRENCE EM, Zhang Y, Starekova J, Wang Z, et al
    Reduced field-of-view and multi-shot DWI acquisition techniques: Prospective evaluation of image quality and distortion reduction in prostate cancer imaging.
    Magn Reson Imaging. 2022 Aug 6. pii: S0730-725X(22)00142.
    PubMed     Abstract available


    June 2022
  8. TAJIMA T, Akai H, Sugawara H, Furuta T, et al
    Feasibility of accelerated whole-body diffusion-weighted imaging using a deep learning-based noise-reduction technique in patients with prostate cancer.
    Magn Reson Imaging. 2022 Jun 27. pii: S0730-725X(22)00108.
    PubMed     Abstract available


    January 2022
  9. REITER R, Majumdar S, Kearney S, Kajdacsy-Balla A, et al
    Investigating the heterogeneity of viscoelastic properties in prostate cancer using MR elastography at 9.4T in fresh prostatectomy specimens.
    Magn Reson Imaging. 2022 Jan 7. pii: S0730-725X(22)00006.
    PubMed     Abstract available


    October 2021
  10. GIBBONS M, Starobinets O, Simko JP, Kurhanewicz J, et al
    Identification of prostate cancer using multiparametric MR imaging characteristics of prostate tissues referenced to whole mount histopathology.
    Magn Reson Imaging. 2021 Oct 16. pii: S0730-725X(21)00175.
    PubMed     Abstract available


    August 2021
  11. FUKUNAGA T, Tamada T, Kanomata N, Takeuchi M, et al
    Quantitative diffusion-weighted imaging and dynamic contrast-enhanced MR imaging for assessment of tumor aggressiveness in prostate cancer at 3T.
    Magn Reson Imaging. 2021 Aug 25. pii: S0730-725X(21)00139.
    PubMed     Abstract available


    June 2021
  12. ZHANG KS, Schelb P, Kohl S, Radtke JP, et al
    Improvement of PI-RADS-dependent prostate cancer classification by quantitative image assessment using radiomics or mean ADC.
    Magn Reson Imaging. 2021;82:9-17.
    PubMed     Abstract available


    April 2021
  13. BOSCHHEIDGEN M, Schimmoller L, Kasprowski L, Abrar D, et al
    Arterial spin labelling as a gadolinium-free alternative in the detection of prostate cancer.
    Magn Reson Imaging. 2021 Apr 24. pii: S0730-725X(21)00068.
    PubMed     Abstract available


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