Use of multiparametric magnetic resonance imaging (mpMRI) in localized prostate cancer

ABSTRACT

Introduction: Prostate magnetic resonance imaging (MRI) is commonly used for localized disease mainly to detect intraprostatic lesions and to guide biopsies. Despite its documented success in clinical practice, limitations still exist for prostate MRI. In this review, we discuss common clinical uses of prostate MRI, its limitations, and potential solutions for those limitations.

Areas covered: Current uses of prostate MRI and challenges discussed. Literature search in PubMed was completed using the keywords “prostate MRI, prostate cancer.”

Expert opinion: Prostate MRI is a useful method for localization, biopsy, and treatment guidance of prostate cancer. Certain limitations of prostate MRI such as false negatives due to spatial resolution and relatively low repeatability between different radiologists can potentially be solved by investing more on education training and artificial intelligence technology.

KEYWORDS:

• Prostate MRI
• prostate cancer
• biopsy

Article highlights

• The development of mpMRI has allowed more accurate visualization and sampling of localized prostate cancer than ever before.

• MRI-ultrasound fusion-guided biopsy at baseline reduces the risk of cancer upgrading on active surveillance, though this has only been validated up to 2 years.

• mpMRI has resulted in tremendous advancements in focal therapy for prostate cancer, though these treatments are generally still considered experimental.

• The utility of mpMRI for excluding prostate cancer is still unclear, with a wide range of reported negative predictive values (54–90%).

• Reporting of prostate mpMRI has been associated with a steep learning curve and suboptimal inter-reader agreement.

• Many groups have developed artificial intelligence tools that show great promise in aiding the detection of prostate cancer lesions.

Declaration of interest

B Turkbey has cooperative research and development agreements with Philips and Nvidia, has received royalties from Invivo and has a patent for related intellectual property in field of prostate computer-aided diagnosis (National Institutes of Health – owned). The authors have no other relevant affiliations or financial involvement with any organization or entity with a financial interest in or financial conflict with the subject matter or materials discussed in the manuscript apart from those disclosed.

Reviewer disclosures

Peer reviewers on this manuscript have no relevant financial or other relationships to disclose.

Additional information

Funding

This research is funded by intramural research program of NIH.