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Original Research

Retrospective evaluation of our percutaneous biopsy results of renal masses


1  Van Yüzüncü Yıl University, Faculty of Medicine, Department of Radiology, Van, Turkey
2 University of Health Science, Van Training and Research Hospital, Department of Urology, Van, Turkey
3 University of Health Science, Bursa Yüksek İhtisas Training and Research Hospital, Department of Urology, Bursa, Turkey


DOI : 10.33719/yud.2021;16-2-818890
New J Urol. 2021; 16-(2): 131-139

Abstract

Prostate cancer (PCa) is a cancer with a broad spectrum of biological behavior and it is a
heterogeneous nature. In order to prevent overdiagnosis and overtreatment, and to detect clinically
significant PCa, standardized scoring and grading systems are used in imaging and pathological
examinations. However, reproducibility and agreement between readers in these diagnostic stages,
which require experience, are low. Promising results have been achieved by integrating artificial
intelligence (AI)-based applications into the diagnosis and management of PCa. In radiological
and pathological imaging, computer-aided diagnostic tools have increased clinical efficiency and
achieved diagnostic accuracy comparable to that of experienced healthcare professionals. This
review provides an overview of AI applications used in radiological imaging, prostate biopsy, and
histopathological examination in the diagnosis of PCa.


Abstract

Prostate cancer (PCa) is a cancer with a broad spectrum of biological behavior and it is a
heterogeneous nature. In order to prevent overdiagnosis and overtreatment, and to detect clinically
significant PCa, standardized scoring and grading systems are used in imaging and pathological
examinations. However, reproducibility and agreement between readers in these diagnostic stages,
which require experience, are low. Promising results have been achieved by integrating artificial
intelligence (AI)-based applications into the diagnosis and management of PCa. In radiological
and pathological imaging, computer-aided diagnostic tools have increased clinical efficiency and
achieved diagnostic accuracy comparable to that of experienced healthcare professionals. This
review provides an overview of AI applications used in radiological imaging, prostate biopsy, and
histopathological examination in the diagnosis of PCa.

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