Optimizing Spatial Biopsy Sampling for the Detection of Prostate Cancer

No AccessJournal of UrologyAdult Urology1 Sep 2021Optimizing Spatial Biopsy Sampling for the Detection of Prostate Cancer Alex G. Raman, Karthik V. Sarma, Steven S. Raman, Alan M. Priester, Sohrab Afshari Mirak, Hannah H. Riskin-Jones, Nikhil Dhinagar, William Speier, Ely Felker, Anthony E. Sisk, David Lu, Adam Kinnaird, Robert E. Reiter, Leonard S. Marks, and Corey W. Arnold Alex G. RamanAlex G. Raman Computational Diagnostics Lab, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, California Equal study contribution. More articles by this author , Karthik V. SarmaKarthik V. Sarma http://orcid.org/0000-0002-7442-9526 Computational Diagnostics Lab, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, California Department of Radiological Sciences, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, California Equal study contribution. More articles by this author , Steven S. RamanSteven S. Raman Department of Radiological Sciences, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, California More articles by this author , Alan M. PriesterAlan M. Priester Department of Radiological Sciences, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, California Department of Bioengineering, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, California More articles by this author , Sohrab Afshari MirakSohrab Afshari Mirak Department of Radiological Sciences, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, California More articles by this author , Hannah H. Riskin-JonesHannah H. Riskin-Jones Department of Radiological Sciences, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, California More articles by this author , Nikhil DhinagarNikhil Dhinagar Computational Diagnostics Lab, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, California Department of Radiological Sciences, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, California More articles by this author , William SpeierWilliam Speier Computational Diagnostics Lab, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, California Department of Radiological Sciences, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, California More articles by this author , Ely FelkerEly Felker Department of Radiological Sciences, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, California More articles by this author , Anthony E. SiskAnthony E. Sisk Department of Pathology and Laboratory Medicine, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, California More articles by this author , David LuDavid Lu Department of Radiological Sciences, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, California More articles by this author , Adam KinnairdAdam Kinnaird Department of Urology, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, California Division of Urology, Department of Surgery, University of Alberta, Edmonton, Alberta, Canada More articles by this author , Robert E. ReiterRobert E. Reiter Department of Urology, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, California More articles by this author , Leonard S. MarksLeonard S. Marks †Correspondence: Department of Urology, David Geffen School of Medicine at UCLA, Wasserman Bldg., 3rd Floor, Los Angeles, California 90095 telephone: 310-794-3070; E-mail Address: [email protected] Department of Urology, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, California More articles by this author , and Corey W. ArnoldCorey W. Arnold ‡Correspondence: Computational Diagnostics Lab, David Geffen School of Medicine at UCLA, 924 Westwood Blvd., Ste 600, Los Angeles, California 90024 telephone: 310-794-3538; E-mail Address: [email protected] http://orcid.org/0000-0002-4119-8143 Computational Diagnostics Lab, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, California Department of Radiological Sciences, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, California Department of Bioengineering, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, California Department of Pathology and Laboratory Medicine, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, California More articles by this author View All Author Informationhttps://doi.org/10.1097/JU.0000000000001832AboutFull TextPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookLinked InTwitterEmail Abstract Purpose: The appropriate number of systematic biopsy cores to retrieve during magnetic resonance imaging (MRI)-targeted prostate biopsy is not well defined. We aimed to demonstrate a biopsy sampling approach that reduces required core count while maintaining diagnostic performance. Materials and Methods: We collected data from a cohort of 971 men who underwent MRI-ultrasound fusion targeted biopsy for suspected prostate cancer. A regional targeted biopsy (RTB) was evaluated retrospectively; only cores within 2 cm of the margin of a radiologist-defined region of interest were considered part of the RTB. We compared detection rates for clinically significant prostate cancer (csPCa) and cancer upgrading rate on final whole mount pathology after prostatectomy between RTB, combined, MRI-targeted, and systematic biopsy. Results: A total of 16,459 total cores from 971 men were included in the study data sets, of which 1,535 (9%) contained csPCa. The csPCa detection rates for systematic, MRI-targeted, combined, and RTB were 27.0% (262/971), 38.3% (372/971), 44.8% (435/971), and 44.0% (427/971), respectively. Combined biopsy detected significantly more csPCa than systematic and MRI-targeted biopsy (p <0.001 and p=0.004, respectively) but was similar to RTB (p=0.71), which used on average 3.8 (22%) fewer cores per patient. In 102 patients who underwent prostatectomy, there was no significant difference in upgrading rates between RTB and combined biopsy (p=0.84). Conclusions: A RTB approach can maintain state-of-the-art detection rates while requiring fewer retrieved cores. This result informs decision making about biopsy site selection and total retrieved core count. References 1. : MRI-targeted or standard biopsy for prostate-cancer diagnosis. N Engl J Med 2018; 378: 1767. Google Scholar 2. : Comparison of targeted vs systematic prostate biopsy in men who are biopsy naive. JAMA Surg 2019; 154: 811. Google Scholar 3. : Multiparametric magnetic resonance imaging-ultrasound fusion biopsy improves but does not replace standard template biopsy for the detection of prostate cancer. 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Link, Google Scholar 27. : Comparison of the upgrading rates of International Society of Urological Pathology grades and tumor laterality in patients undergoing standard 12-core prostate biopsy versus fusion prostate biopsy for prostate cancer. Urol Int 2019; 103: 256. Google Scholar 28. : MRI–ultrasound fusion for guidance of targeted prostate biopsy. Curr Opin Urol 2013; 23: 43. Google Scholar Funded by NIH NCI R21 CA220352, NIH NCI P50 CA092131, and a NVIDIA Corporation Academic Hardware Grant (CWA); NCI F30CA210329, NIH NIGMS GM08042, and the UCLA-Caltech Medical Scientist Training Program (KVS); and NIH NCI R01 CA195505 and R01 CA158627 (LSM). All data were used for this work under the approval of the UCLA Institutional Review Board (IRB Nos. 11-001580 and 16-001087) and in compliance with HIPAA regulations. None of the sponsors of this study were involved in study design or performance, or in the writing or submission of this manuscript. Financial interest and/or other relationship with Avenda Health (LSM, AMP) and the American Medical Association (KVS). No other authors have competing interests to disclose. © 2021 by American Urological Association Education and Research, Inc.FiguresReferencesRelatedDetails Volume 206Issue 3September 2021Page: 595-603 Advertisement Copyright & Permissions© 2021 by American Urological Association Education and Research, Inc.Keywordsimage-guided biopsymagnetic resonance imagingprostatic neoplasmsultrasonography, interventionalbiopsy, adverse effectsMetricsAuthor Information Alex G. Raman Computational Diagnostics Lab, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, California Equal study contribution. More articles by this author Karthik V. Sarma Computational Diagnostics Lab, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, California Department of Radiological Sciences, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, California Equal study contribution. More articles by this author Steven S. Raman Department of Radiological Sciences, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, California More articles by this author Alan M. Priester Department of Radiological Sciences, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, California Department of Bioengineering, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, California More articles by this author Sohrab Afshari Mirak Department of Radiological Sciences, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, California More articles by this author Hannah H. Riskin-Jones Department of Radiological Sciences, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, California More articles by this author Nikhil Dhinagar Computational Diagnostics Lab, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, California Department of Radiological Sciences, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, California More articles by this author William Speier Computational Diagnostics Lab, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, California Department of Radiological Sciences, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, California More articles by this author Ely Felker Department of Radiological Sciences, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, California More articles by this author Anthony E. Sisk Department of Pathology and Laboratory Medicine, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, California More articles by this author David Lu Department of Radiological Sciences, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, California More articles by this author Adam Kinnaird Department of Urology, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, California Division of Urology, Department of Surgery, University of Alberta, Edmonton, Alberta, Canada More articles by this author Robert E. Reiter Department of Urology, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, California More articles by this author Leonard S. Marks Department of Urology, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, California †Correspondence: Department of Urology, David Geffen School of Medicine at UCLA, Wasserman Bldg., 3rd Floor, Los Angeles, California 90095 telephone: 310-794-3070; E-mail Address: [email protected] More articles by this author Corey W. Arnold Computational Diagnostics Lab, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, California Department of Radiological Sciences, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, California Department of Bioengineering, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, California Department of Pathology and Laboratory Medicine, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, California ‡Correspondence: Computational Diagnostics Lab, David Geffen School of Medicine at UCLA, 924 Westwood Blvd., Ste 600, Los Angeles, California 90024 telephone: 310-794-3538; E-mail Address: [email protected] More articles by this author Expand All Funded by NIH NCI R21 CA220352, NIH NCI P50 CA092131, and a NVIDIA Corporation Academic Hardware Grant (CWA); NCI F30CA210329, NIH NIGMS GM08042, and the UCLA-Caltech Medical Scientist Training Program (KVS); and NIH NCI R01 CA195505 and R01 CA158627 (LSM). All data were used for this work under the approval of the UCLA Institutional Review Board (IRB Nos. 11-001580 and 16-001087) and in compliance with HIPAA regulations. None of the sponsors of this study were involved in study design or performance, or in the writing or submission of this manuscript. Financial interest and/or other relationship with Avenda Health (LSM, AMP) and the American Medical Association (KVS). No other authors have competing interests to disclose. Advertisement PDF DownloadLoading ...