Implementation of Multi-parametric Prostate MRI in Clinical Practice

被引:0
|
作者
Andrea S. Kierans
Samir S. Taneja
Andrew B. Rosenkrantz
机构
[1] NYU Langone Medical Center,Department of Radiology, Center for Biomedical Imaging
[2] NYU Langone Medical Center,Department of Urology, Division of Urologic Oncology
来源
Current Urology Reports | 2015年 / 16卷
关键词
Multi-parametric prostate MRI; PI-RADS; Clinical implementation; Detection;
D O I
暂无
中图分类号
学科分类号
摘要
While initial implementations of prostate MRI suffered from suboptimal performance in tumor detection, technological advances over the past decade have allowed modern multi-parametric prostate MRI (mpMRI) to achieve high diagnostic accuracy for detection, localization, and staging and thereby impact patient management. A particular emerging application of mpMRI is in the pre-biopsy setting to allow for MRI-targeted biopsy, for instance, through real-time MRI/ultrasound fusion, which may help reduce the over-detection of low-risk disease and selectively detect clinically significant cancers, in comparison with use of standard systematic biopsy alone. mpMRI and MRI-targeted biopsy are spreading beyond the large academic centers to increasingly be adopted within small and community practices. Aims of this review article are to summarize the hardware and sequences used for performing mpMRI, explore patient specific technical considerations, delineate approaches for study interpretation and reporting [including the recent American College of Radiology Prostate Imaging Reporting and Data System (PI-RADS) version 2], and describe challenges and implications relating to the widespread clinical implementation of mpMRI.
引用
下载
收藏
相关论文
共 50 条
  • [31] Focal therapy for localized prostate cancer in the era of routine multi-parametric MRI
    Connor, M. J.
    Gorin, M. A.
    Ahmed, H. U.
    Nigam, R.
    PROSTATE CANCER AND PROSTATIC DISEASES, 2020, 23 (02) : 232 - 243
  • [32] Particle swarm optimization based segmentation of Cancer in multi-parametric prostate MRI
    Gaurav Garg
    Mamta Juneja
    Multimedia Tools and Applications, 2021, 80 : 30557 - 30580
  • [33] MULTI-PARAMETRIC PROSTATE MRI AS A SCREENING TEST AMONG MALE BRCA CARRIERS
    Margel, David
    Sela, Sivan
    Tamir, Shlomit
    Kedar, Inbal
    Ber, Yaara
    Kedar, Daniel
    Nadu, Andrei
    Baniel, Jack
    JOURNAL OF UROLOGY, 2019, 201 (04): : E424 - E425
  • [34] The CADMUS trial - Multi-parametric ultrasound targeted biopsies compared to multi-parametric MRI targeted biopsies in the diagnosis of clinically significant prostate cancer
    Grey, Alistair
    Scott, Rebecca
    Charman, Susan
    van der Meulen, Jan
    Frinking, Peter
    Acher, Peter
    Liyanage, Sidath
    Madaan, Sanjeev
    Constantinescu, Gabriel
    Shah, Bina
    Graves, Chris Brew
    Freeman, Alex
    Jameson, Charles
    Ramachandran, Navin
    Emberton, Mark
    Arya, Manit
    Ahmed, Hashim U.
    CONTEMPORARY CLINICAL TRIALS, 2018, 66 : 86 - 92
  • [35] Multi-center validation of a model for prostate tumor delineation using multi-parametric MRI
    Dinh, C.
    Haustermans, K.
    Steenbergen, P.
    Ghobadi, G.
    Lerut, E.
    Oyen, R.
    Poel, H. V. D.
    Jong, J. D.
    Heijmink, S.
    Heide, U. V. D.
    RADIOTHERAPY AND ONCOLOGY, 2015, 115 : S384 - S384
  • [36] Logistic regression model for diagnosis of transition zone prostate cancer on multi-parametric MRI
    Dikaios, Nikolaos
    Alkalbani, Jokha
    Sidhu, Harbir Singh
    Fujiwara, Taiki
    Abd-Alazeez, Mohamed
    Kirkham, Alex
    Allen, Clare
    Ahmed, Hashim
    Emberton, Mark
    Freeman, Alex
    Halligan, Steve
    Taylor, Stuart
    Atkinson, David
    Punwani, Shonit
    EUROPEAN RADIOLOGY, 2015, 25 (02) : 523 - 532
  • [37] Correlation of multi-parametric MRI with template trans-perinteal prostate mapping in diagnosis of prostate cancer
    Yek, J.
    Chen, K.
    Tay, K. J.
    Ho, H.
    Yuen, J.
    Tan, E. C.
    Cheng, C.
    BJU INTERNATIONAL, 2014, 113 : 19 - 19
  • [38] Multi-parametric MRI-Pathologic correlation of prostate cancer using tracked biopsies
    Xu, Sheng
    Turkbey, Baris
    Kruecker, Jochen
    Yan, Pingkun
    Locklin, Julia
    Pinto, Peter
    Choyke, Peter
    Wood, Bradford
    MEDICAL IMAGING 2010: VISUALIZATION, IMAGE-GUIDED PROCEDURES, AND MODELING, 2010, 7625
  • [39] Development of a Computer Aided Diagnosis Model for Prostate Cancer Classification on Multi-Parametric MRI
    Alfano, R.
    Soetemans, D.
    Bauman, G. S.
    Gibson, E.
    Gaed, M.
    Moussa, M.
    Gomez, J. A.
    Chin, J. L.
    Pautler, S.
    Ward, A. D.
    MEDICAL IMAGING 2018: COMPUTER-AIDED DIAGNOSIS, 2018, 10575
  • [40] IMPACT OF MULTI-PARAMETRIC MRI IN PROSTATE CANCER STRATIFICATION AND PROPOSAL OF A NEW RISK CLASSIFICATION
    Di Trapani, Ettore
    Catellani, Michele
    Russo, Andrea
    Cozzi, Gabriele
    Bianchi, Roberto
    Delor, Maurizio
    Conti, Andrea
    Bianco, Raffaele
    Mistretta, Francesco Alessandro
    Bottero, Danilo
    Musi, Gennaro
    De Cobelli, Ottavio
    ANTICANCER RESEARCH, 2018, 38 (04) : 2539 - 2540