Literature DB >> 26367323

Role of MRI in the diagnosis and management of prostate cancer.

Andreas G Wibmer1, Hebert Alberto Vargas1, Hedvig Hricak1.   

Abstract

Multiparametric MRI of the prostate consists of T1- and T2-weighted sequences, which provide anatomical information, and one or more 'functional' sequences, that is, diffusion-weighted imaging, dynamic contrast-enhanced sequences and magnetic resonance spectroscopy. Prostate MRI is the most accurate imaging method for local staging of prostate cancer and can also be used for the noninvasive evaluation of tumor aggressiveness. By magnetic resonance-guided prostate biopsy it is possible to target the most cancer-suspicious areas of the gland, especially in patients with a negative transrectal biopsy. In patients with biochemical recurrence after radical treatment, MRI is a valuable tool for the detection of local tumor recurrence and whole-body MRI can be used for the diagnosis of distant metastases.

Entities:  

Keywords:  MRI; cancer detection; cancer recurrence; cancer staging; prostate cancer; risk assessment; whole-body MRI

Mesh:

Year:  2015        PMID: 26367323     DOI: 10.2217/fon.15.206

Source DB:  PubMed          Journal:  Future Oncol        ISSN: 1479-6694            Impact factor:   3.404


  2 in total

1.  Multiparametric MRI and Machine Learning Based Radiomic Models for Preoperative Prediction of Multiple Biological Characteristics in Prostate Cancer.

Authors:  Xuhui Fan; Ni Xie; Jingwen Chen; Tiewen Li; Rong Cao; Hongwei Yu; Meijuan He; Zilin Wang; Yihui Wang; Hao Liu; Han Wang; Xiaorui Yin
Journal:  Front Oncol       Date:  2022-02-07       Impact factor: 6.244

2.  External Validation of an MRI-Derived Radiomics Model to Predict Biochemical Recurrence after Surgery for High-Risk Prostate Cancer.

Authors:  Vincent Bourbonne; Georges Fournier; Martin Vallières; François Lucia; Laurent Doucet; Valentin Tissot; Gilles Cuvelier; Stephane Hue; Henri Le Penn Du; Luc Perdriel; Nicolas Bertrand; Frederic Staroz; Dimitris Visvikis; Olivier Pradier; Mathieu Hatt; Ulrike Schick
Journal:  Cancers (Basel)       Date:  2020-03-28       Impact factor: 6.639

  2 in total

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