Login to Access Video or Poster Abstract: MP08-15
Sources of Funding: none

Introduction

The usage of multi-parametric Magnetic Resonance Imaging/Ultrasound fusion biopsy (Fbx) to aid in the diagnosis of clinically significant (CS) prostate cancer (CaP) has taken place in recent years. Our objective was to determine if the detection rate of our multi institutional experience with Fbx and standard 12 core sextant biopsy (SBx) in detecting clinically significant prostate cancer is improving over time.

Methods

A retrospective review of 803 patients who underwent FBx biopsy and SBx in the same setting between September 2014 and September 2016 was performed. Group 1 consisted of patients who underwent FBx and SBx in the first year of starting FBx and group 2 consisted of patients who underwent FBx and SBx in the second year of starting FBx. All patients underwent a 3-Tesla multi-parametric MRI (mpMRI) performed at 3 different institutions. mpMRI was performed using T1/T2 phases, dynamic contrast enhancement and diffusion weighted imaging. Using a 3-dimensional model fusion software [InVivo (Phillips), Gainesville (USA)], 2-5 fusion biopsies were performed on each prostate lesion. FBx was only performed on patients with at least 1 PIRADS ?3 lesion on mpMRI. Gleason score ? 7 was considered as clinically significant prostate cancer.

Results

341 patients underwent an FBx and SBx between September 2014-2015 and 462 patients underwent FBx and SBx between September 2015-2016. Age, PSA, race, BMI and location where mpMRI was not significantly different between both groups, p>0.05. 109/341 patients (32%) were diagnosed with CaP in 2015 and 162/462 patients (35%) were diagnosed with CaP in group 2. 56/341 patients (16%) were diagnosed with CS CaP in group 1 and 96/462 (21%) patients were diagnosed with CS CaP based off fusion biopsy in group 2 (Table 1). Compared to SBx, FBx is likely to detect clinically CS CaP as can be seen in both years on table 1.

Conclusions

Our experience show that FBx may have a learning curve with lower detection rate initially which improves over time. Although FBx is better at detecting CS CaP compared to SBx, more studies are required to determine the ideal number of FBx needed to overcome this initial learning curve and where detection rate would start to plateau.

Funding

none