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Characterizing the learning curve of MRI-US fusion prostate biopsies

Prostate Cancer and Prostatic Diseases volume 22, pages 546–551 (2019)Cite this article

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Abstract

Background

MRI-US fusion prostate biopsies are becoming a common procedure to diagnose prostate cancer. There is a paucity of information regarding the learning curve for fusion biopsies. We aim to study the amount of experience needed to be both accurate and time-efficient in this procedure.

Methods

We prospectively collected data on all MRI-US fusion biopsies performed from April 2014 to August 2017. We used two parameters to define the learning curve. Process Measurement (efficiency) was measured by time from the beginning of anesthesia to end of procedure. Outcome Measurement (accuracy) was measured by cancer detection rate for PI-RAD 3 lesions. The end of the learning curve was defined graphically and mathematically. We performed a separate analysis for transrectal and transperineal biopsies.

Results

We completed 779 fusion biopsies (523 transrectal, 256 transperineal). Patients median age was 66 years (IQR 61–70) and median PSA 6.95 ng/ml (IQR 4.2–10.6). Prostate cancer was diagnosed in 385 (49%). Process Measurement—Procedure time decreased from 45 min in the first transrectal fusion biopsy to 15 min after 109 biopsies and remained stable (p < 0.0001). Time decreased from 55 min in the first transperineal biopsy to 18 min after 124 biopsies (p < 0.0001). Outcome Measurement—In transrectal fusion-biopsies detection rate for PI-RADS 3 lesions increased from 35 to 50% after 104 biopsies. In transperineal fusion-biopsies, detection rate increased from 40 to 55% after 119 cases for PI-RADS 3 lesions.

Conclusions

We measured the learning curve of fusion biopsies graphically and mathematically. We demonstrated that proficiency occurs after 110 transrectal and 125 transperineal fusion-biopsies.

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Authors and Affiliations

  1. Department of Urology, Rabin Medical Center, Petah Tikva, Israel

    Daniel Halstuch, Jack Baniel, David Lifshitz, Sivan Sela, Yaara Ber & David Margel

  2. Division of Surgery, Sackler Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel

    Jack Baniel, David Lifshitz & David Margel

  3. Urology clinic, Ramat Aviv Medical Center, Tel-Aviv, Israel

    Jack Baniel & David Margel

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  1. Daniel Halstuch
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Correspondence to Daniel Halstuch.

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Halstuch, D., Baniel, J., Lifshitz, D. et al. Characterizing the learning curve of MRI-US fusion prostate biopsies. Prostate Cancer Prostatic Dis 22, 546–551 (2019). https://doi.org/10.1038/s41391-019-0137-2

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