KMID : 0939920210530041148
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´ëÇѾÏÇÐȸÁö 2021 Volume.53 No. 4 p.1148 ~ p.1155
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A Predictive Model Based on Bi-parametric Magnetic Resonance Imaging and Clinical Parameters for Clinically Significant Prostate Cancer in the Korean Population
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Noh Tae-Il
Hyun Chang-Wan Kang Ha-Eun Jin Hyun-Jung Tae Jong-Hyun Shim Ji-Sung Kang Sung-Gu Sung Deuk-Jae Cheon Jun Lee Jeong-Gu Kang Seok-Ho
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Abstract
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Purpose: This study aimed to develop and validate a predictive model for the assessment of clinically significant prostate cancer (csPCa) in men, prior to prostate biopsies, based on bi-parametric magnetic resonance imaging (bpMRI) and clinical parameters.
Materials and Methods: We retrospectively analyzed 300 men with clinical suspicion of prostate cancer (prostate-specific antigen [PSA] ¡Ã 4.0 ng/mL and/or abnormal findings in a digital rectal examination), who underwent bpMRI-ultrasound fusion transperineal targeted and systematic biopsies in the same session, at a Korean university hospital. Predictive models, based on Prostate Imaging Reporting and Data Systems scores of bpMRI and clinical parameters, were developed to detect csPCa (intermediate/high grade [Gleason score ¡Ã 3+4]) and compared by analyzing the areas under the curves and decision curves.
Results: A predictive model defined by the combination of bpMRI and clinical parameters (age, PSA density) showed high discriminatory power (area under the curve, 0.861) and resulted in a significant net benefit on decision curve analysis. Applying a probability threshold of 7.5%, 21.6% of men could avoid unnecessary prostate biopsy, while only 1.0% of significant prostate cancers were missed.
Conclusion: This predictive model provided a reliable and measurable means of risk stratification of csPCa, with high discriminatory power and great net benefit. It could be a useful tool for clinical decision-making prior to prostate biopsies.
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KEYWORD
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Prostatic neoplasms, Bi-parametric magnetic resonance imaging, Transperineal prostate biopsy, Nomograms
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