Management Strategy for Prostate Imaging Reporting and Data System Category 3 Lesions

被引:4
|
作者
Kang, Zhen [1 ,6 ]
Margolis, Daniel J. [2 ]
Wang, Shaogang [3 ]
Li, Qiubai [4 ]
Song, Jian [5 ]
Wang, Liang [6 ]
机构
[1] Huazhong Univ Sci & Technol, Tongji Hosp, Tongji Med Coll, Dept Radiol, Wuhan, Peoples R China
[2] Weill Cornell Med, Dept Radiol, New York Presbyterian, New York, NY USA
[3] Huazhong Univ Sci & Technol, Tongji Hosp, Tongji Med Coll, Dept Urol, Wuhan, Peoples R China
[4] Univ Hosp Cleveland, Dept Radiol, Med Ctr, Cleveland, OH USA
[5] Capital Med Univ, Beijing Friendship Hosp, Dept Urol, Beijing, Peoples R China
[6] Capital Med Univ, Beijing Friendship Hosp, Dept Radiol, 36 Yongan Rd, Beijing 100016, Peoples R China
基金
中国国家自然科学基金;
关键词
Prostate Imaging Reporting and Data System category 3; Management strategy; PI-RADS V2; CANCER; RISK; MRI; EXPERIENCE; BIOPSY; ZONE; MEN;
D O I
10.1007/s11934-023-01187-0
中图分类号
R5 [内科学]; R69 [泌尿科学(泌尿生殖系疾病)];
学科分类号
1002 ; 100201 ;
摘要
Purpose of ReviewProstate Imaging Reporting and Data System (PI-RADS) category 3 lesions present a clinical dilemma due to their uncertain nature, which complicates the development of a definitive management strategy. These lesions have an incidence rate of approximately 22-32%, with clinically significant prostate cancer (csPCa) accounting for about 10-30%. Therefore, a thorough evaluation is warranted.Recent FindingsThis review highlights the need for radiology peer review, including the confirmation of dynamic contrast-enhanced (DCE) compliance, as the initial step. Additional MRI models such as VERDICT or Tofts need to be verified. Current evidence shows that imaging and clinical indicators can be used for risk stratification of PI-RADS 3 lesions. For low-risk lesions, a safety net monitoring approach involving annual repeat MRI can be employed. In contrast, lesions deemed potentially risky based on prostate-specific antigen density (PSAD), 68 Ga-PSMA PET/CT, MPS, Proclarix, or AI/machine learning models should undergo biopsy. It is recommended to establish a multidisciplinary team that takes into account factors such as age, PSAD, prostate, and lesion size, as well as previous biopsy pathological findings.SummaryCombining expert opinions, clinical-imaging indicators, and emerging methods will contribute to the development of management strategies for PI-RADS 3 lesions.
引用
收藏
页码:561 / 570
页数:10
相关论文
共 50 条
  • [21] Improving the Early Detection of Clinically Significant Prostate Cancer in Men in the Challenging Prostate Imaging-Reporting and Data System 3 Category
    Morote, Juan
    Campistol, Miriam
    Triquell, Marina
    Celma, Anna
    Regis, Lucas
    de Torres, Ines
    Semidey, Maria E.
    Mast, Richard
    Santamaria, Anna
    Planas, Jacques
    Trilla, Enrique
    EUROPEAN UROLOGY OPEN SCIENCE, 2022, 37 : 38 - 44
  • [22] Prostate health index can stratify patients with Prostate Imaging Reporting and Data System score 3 lesions on magnetic resonance imaging to reduce prostate biopsies
    Leung, John Shung-Lai
    Ma, Wai-Kit
    Ho, Brian Sze-Ho
    Chun, Stacia Tsun-Tsun
    Na, Rong
    Zhan, Yongle
    Ng, Chi-Yuen
    Ip, Chi-Ho
    Ng, Ada Tsui-Lin
    Lam, Yiu-Chung
    ASIAN JOURNAL OF ANDROLOGY, 2024, 26 (01): : 20 - 24
  • [23] Prostate Imaging Reporting and Data System 3 Category Cases at Multiparametric Magnetic Resonance for Prostate Cancer: A Systematic Review and Meta-analysis
    Maggi, Martina
    Panebianco, Valeria
    Mosca, Augusto
    Salciccia, Stefano
    Gentilucci, Alessandro
    Di Pierro, Giovanni
    Busetto, Gian Maria
    Barchetti, Giovanni
    Campa, Riccardo
    Sperduti, Isabella
    Del Giudice, Francesco
    Sciarra, Alessandro
    EUROPEAN UROLOGY FOCUS, 2020, 6 (03): : 463 - 478
  • [24] Prostate Imaging Reporting and Data System Version 2.1: 2019 Update of Prostate Imaging Reporting and Data System Version 2
    Turkbey, Baris
    Rosenkrantz, Andrew B.
    Haider, Masoom A.
    Padhani, Anwar R.
    Villeirs, Geert
    Macura, Katarzyna J.
    Tempany, Clare M.
    Choyke, Peter L.
    Cornud, Francois
    Margolis, Daniel J.
    Thoeny, Harriet C.
    Verma, Sadhna
    Barentsz, Jelle
    Weinreb, Jeffrey C.
    EUROPEAN UROLOGY, 2019, 76 (03) : 340 - 351
  • [25] Can magnetic resonance imaging texture analysis change the breast imaging reporting and data system category of breast lesions?
    Uysal, Emine
    Topaloglu, Omer Faruk
    Ari, Ayse
    Ozer, Halil
    Koplay, Mustafa
    CLINICAL IMAGING, 2023, 97 : 44 - 49
  • [26] Avoiding unnecessary biopsy: Development of a predictive calculator to identify non-prostate cancer in patients with Prostate Imaging Reporting and Data System category ≥ 4 lesions.
    Zeng, Hong
    Chen, Yuntian
    Xie, Yandong
    Dai, Jindong
    Wang, Minghao
    Wang, Qian
    Xu, Nanwei
    Chen, Junru
    Sun, Guangxi
    Zhao, Jinge
    Zeng, Hao
    Shen, Pengfei
    JOURNAL OF CLINICAL ONCOLOGY, 2024, 42 (16)
  • [27] Efficacy of plasma atherogenic index in predicting malignancy in the presence of Prostate Imaging–Reporting and Data System 3 (PI-RADS 3) prostate lesions
    Samet Senel
    Kazim Ceviz
    Yusuf Kasap
    Sedat Tastemur
    Erkan Olcucuoglu
    Emre Uzun
    Muhammed Emin Polat
    Antonios Koudonas
    Firathan Sarialtin
    International Urology and Nephrology, 2023, 55 : 255 - 261
  • [28] Modified Model for Diagnosing Breast Imaging Reporting and Data System Category 3 to 5 Breast Lesions Retrospective Analysis and Nomogram Development
    Zhou, Peng
    Jin, Chunchun
    Lu, Jianghao
    Xu, Lifeng
    Zhu, Xiaomin
    Lian, Qingshu
    Gong, Xuehao
    JOURNAL OF ULTRASOUND IN MEDICINE, 2021, 40 (01) : 151 - 161
  • [29] The value of noncontrast MRI in evaluating breast imaging reporting and data system category 0 lesions on digital mammograms
    Zhang, Ruixin
    Xu, Maosheng
    Zhou, Changyu
    Ding, Xuewei
    Lu, Huan
    Ge, Min
    Du, Liang
    Bu, Yangyang
    QUANTITATIVE IMAGING IN MEDICINE AND SURGERY, 2022, 12 (08) : 4069 - 4080
  • [30] Acoustic Radiation Force Impulse Elastography of Breast Imaging Reporting and Data System Category 4 Breast Lesions
    Jin, Zhan-Qiang
    Li, Xiu-Ru
    Zhou, Hong-Lian
    Chen, Jie-Xin
    Huang, Xing
    Dai, Hai-Xia
    Li, Jian-Wen
    Chen, Xiao-Dong
    Xu, Xiao-Hong
    CLINICAL BREAST CANCER, 2012, 12 (06) : 420 - 427