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临床试验/NCT05443412
NCT05443412招募中不适用

Artificial Intelligence (AI)-Assisted Risk-based Prostate Cancer Detection: A Synergy of Novel Biomarkers, Advanced Imaging, and Robotic-assisted Diagnosis

Chinese University of Hong Kong1 个研究点 分布在 1 个国家目标入组 510 人开始时间: 2023年8月1日最近更新:
适应症

试验速览

阶段
不适用
状态
招募中
入组人数
510
试验地点
1
主要终点
Diagnosis of clinically significant Prostate cancer (csPCa); • csPCa is diagnosis of ISUP Grade group ≥2 prostate cancer in at least 1 biopsy core

研究概览

简要总结

This is a prospective clinical study recruiting 510 men at risk of PCa to undergo urine, blood, AI-assisted ultrasound and AI-assisted MRI investigations to stratify risk of clinically significant PCa (csPCa). (sample size calculation in section 5)

详细描述

All recruited patients will undergo investigations including urine for spermine, blood for miRNA, TRUS, and MRI prostate. Patients with high suspicion of csPCa in any one step (urine, blood, ultrasound, OR MRI) will be offered an image-guided prostate biopsy. This will be followed by machine learning techniques to find the best combination in predicting csPCa.

研究设计

研究类型
Observational
观察模型
Cohort
时间视角
Prospective

入排标准

年龄范围
18 Years 至 —(Adult, Older Adult)
性别
Male
接受健康志愿者

入选标准

  • Men ≥18 years of age
  • Clinical suspicion of prostate cancer
  • Serum Prostate-specific antigen (PSA) 4-20 ng/mL
  • Digital rectal examination ≤ cT2 (organ confined cancer)
  • Able to provide written informed consent

排除标准

  • Prior prostate biopsy
  • Past or current history of prostate cancer
  • Contraindicated to undergo plain MRI scan (e.g. pacemaker in-situ, claustrophobia)
  • Contraindicated to transperineal prostate biopsy: active urinary tract infection, fail TRUS probe insertion or lithotomy position, uncorrectable coagulopathy, antiplatelet or anticoagulant which cannot be stopped

结局指标

主要结局

Diagnosis of clinically significant Prostate cancer (csPCa); • csPCa is diagnosis of ISUP Grade group ≥2 prostate cancer in at least 1 biopsy core

时间窗: Through study completion, an average of 1 year

Assessed by by machine learning algorithms utilizing clinical parameters, novel biomarkers and AI-assisted imaging

次要结局

  • Diagnosis of any grade of prostate cancer(Through study completion, an average of 1 year)
  • Proportion of men with diagnosis of clinically insignificant prostate cancer(Through study completion, an average of 1 year)
  • Prostate biopsies that can be avoided(Through study completion, an average of 1 year)
  • The concordance of AI-assisted TRUS & MRI diagnosis and biopsy outcomes(Through study completion, an average of 1 year)

研究者

申办方类型
Other
责任方
Principal Investigator
主要研究者

CHIU Ka Fung Peter

Associate Professor

Chinese University of Hong Kong

研究点 (1)

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