September 2025
1. ZHANG P, Feng Z, Chen S, Zhu J, et al
   Accelerating prostate rs-EPI DWI with deep learning: Halving scan time, enhancing image quality, and validating in vivo.
   Magn Reson Imaging. 2025;121:110418.
   

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   June 2025
2. WANG YF, Tadimalla S, Thiruthaneeswaran N, Holloway L, et al
   Longitudinal quantitative MRI in prostate cancer after radiation therapy with and without androgen deprivation therapy.
   Magn Reson Imaging. 2025;122:110431.
   

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   February 2025
3. BOSCHHEIDGEN M, Drewes L, Valentin B, Ullrich T, et al
   Use of deep learning-accelerated T2 TSE for prostate MRI: Comparison with and without hyoscine butylbromide admission.
   Magn Reson Imaging. 2025 Feb 10:110358. doi: 10.1016/j.mri.2025.110358.
   

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   December 2024
4. SHIRAISHI K, Nakaura T, Kobayashi N, Uetani H, et al
   Enhancing thin slice 3D T2-weighted prostate MRI with super-resolution deep learning reconstruction: Impact on image quality and PI-RADS assessment.
   Magn Reson Imaging. 2024;117:110308.
   

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   September 2024
5. STAROBINETS O, Simko JP, Gibbons M, Kurhanewicz J, et al
   The impact of benign tissue within cancerous regions in the prostate: Characterizing sparse and dense prostate cancers on whole-mount histopathology and on multiparametric MRI.
   Magn Reson Imaging. 2024 Sep 9:110233. doi: 10.1016/j.mri.2024.110233.
   

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   March 2024
6. WONG OL, Yuan J, Poon DMC, Chiu ST, et al
   Prostate diffusion-weighted imaging (DWI) in MR-guided radiotherapy: Reproducibility assessment on 1.5?T MR-Linac and 1.5?T MR-simulator.
   Magn Reson Imaging. 2024 Mar 18:S0730-725X(24)00076.
   

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   January 2024
7. 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.
   

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