[Selection of candidates for prostate biopsy using multiparametric magnetic resonance imaging in patients with persistently raising PSA]

Abstract

The current diagnosis of prostate cancer is based on randomized prostate biopsies to obtain histological material for study, without introducing any imaging technique in the diagnostic algorithm.

Objectives: To conduct a literature review of the role of multiparametric MRI ( mMRI ) in the diagnosis of prostate cancer, and present preliminary data from our series of 233 patients undergoing mRMN and transrectal ultrasound (TRUS) prostate biopsy.

Material and methods: We performed a PubMed search for those articles that refer to the usefulness of mMRI in the follow-up and monitoring of patients with persistently elevated PSA without previous biopsies, and those with a previous negative biopsy, and assess the power of mRMN for detecting PCa in both the peripheral and the central gland. We present the preliminary results of our series, consisting of 233 patients selected between 2008 and 2011 undergoing mMRI and TRUS-guided prostatic biopsy because of elevated PSA levels or suspicious digital rectal examination.

Results: We discuss several articles published from 2003 to 2014. We compare our results with those from the literature.

Discussion: The diagnostic algorithm of prostate cancer to date does not include any imaging technique in the decision-making process. The mMRI is a functional imaging technique that provides increasing evidence in deciding which patients should be biopsied and which patients may avoid it despite persisting high levels of PSA. The advantage of this technique lies not only in its high detection rate in intermediate and high risk lesions, but also in its high specificity. It allows us to avoid diagnosing clinically insignificant tumors and thus, avoids overtreatment.

Conclusion: The mRMN is a useful technique not yet incorporated in algorithms of prostate cancer diagnosis in urological societies. Its safety, effectiveness and efficiency are forcing to include its progressive use and with high probability will be soon incorporated into the decision-making charts.