跳至主要内容
临床试验/NCT06575361
NCT06575361已完成不适用

Comprehensive Evaluation of MRI-AI in Prostate Cancer Diagnosis: a Real-World Prospective Diagnostic Study

Peking University First Hospital1 个研究点 分布在 1 个国家目标入组 365 人开始时间: 2024年1月1日最近更新:
适应症
干预措施

试验速览

阶段
不适用
状态
已完成
入组人数
365
试验地点
1
主要终点
The clinically significant prostate cancer (csPCa) detection rate for suspicious lesions found by MRI-AI and urogenital radiologists

研究概览

简要总结

The goal of this real-world prospective diagnostic study is to comprehensively evaluate the value of MRI artificial intelligence (MRI-AI) in assisting the diagnosis of prostate cancer (PCa). The main questions it aims to answer are:

Does MRI-AI promote the accurate diagnosis and treatment of prostate cancer? What's the capability of prostate MRI-AI in calculating the prostate volumn? What's the value of prostate MRI-AI assistant diagnosis system in detecting the suspicious lesions on MRI and guiding prostate targeted biopsy? What's the value of prostate MRI-AI assistant diagnosis system in predicting the pathological results of prostate targeted biopsy? Researchers will compare the cancer detection rates of suspicious lesions detected by MRI-AI and senior radiologists.

Participants will:

Receive combination of systematic biopsy and targeted biopsy.

详细描述

In recent years, there have been remarkable advancements in the field of artificial intelligence (AI) techniques, particularly in the medical domain. These AI techniques have demonstrated the ability to significantly enhance various medical tasks, such as tumor detection, classification, and prognosis prediction. Increasing evidence supports the ability of AI to facilitate precise diagnosis of PCa and assist in therapeutic decisions. Compared with doctors, AI has the potential to identify not only holistic tumor morphology but also task-specific and granular radiological patterns that cannot be detected by the naked eye. Therefore, AI has great potential to reduce inconsistencies between observers and improve diagnostic accuracy. Previous AI studies at our institution have developed deep learning-based AI models trained on MR images that achieve good performance in the detection and localization of clinically significant prostate cancer (csPCa). Furthermore, the trained AI algorithms were embedded into proprietary structured reporting software, and radiologists simulated their real-life work scenarios to interpret and report the PI-RADS category of each patient using this AI-based software. However, the data is mostly retrospective. The capability of detecting the suspicious lesions on MRI, guiding the prostate targeted biopsy, and optimizing the biopsy scheme warrants further investigation.

The goal of this real-world prospective diagnostic study is to comprehensively evaluate the value of MRI artificial intelligence (MRI-AI) in assisting the diagnosis of prostate cancer (PCa). The main questions it aims to answer are:

Does MRI-AI promote the accurate diagnosis and treatment of prostate cancer? What's the capability of prostate MRI-AI in calculating the prostate volumn? What's the value of prostate MRI-AI assistant diagnosis system in detecting the suspicious lesions on MRI and guiding prostate targeted biopsy? What's the value of prostate MRI-AI assistant diagnosis system in predicting the pathological results of prostate targeted biopsy? Researchers will compare the cancer detection rates of suspicious lesions detected by MRI-AI and senior radiologists.

Participants will:

Receive combination of systematic biopsy and targeted biopsy.

研究设计

研究类型
Interventional
分配方式
Na
干预模型
Single Group
主要目的
Diagnostic
盲法
None

入排标准

年龄范围
45 Years 至 85 Years(Adult, Older Adult)
性别
Male
接受健康志愿者

入选标准

  • The age of the patient is between 45 and
  • Patients with complete magnetic resonance imaging (MRI) data, qualified image quality control.
  • Patients were in accordance with the indication of prostate biopsy, including patients with suspicious prostate nodes found by digital rectal examination (DRE), the suspicious lesions found by transrectal ultrasound (TRUS) or MRI, total prostate-specific antigen (tPSA) >10ng/mL, tPSA 4-10ng/mL with free-to-total PSA ratio (f/tPSA) <0.16 or PSA density (PSAD) >0.
  • Patients had no history of prior prostate surgery or biopsy.
  • The PSA of patients should be ≤20 ng/mL.
  • The prostate biopsy pathological results of above lesions were complete. The time interval between targeted prostate biopsy and prostate MRI examination should not exceed one month.
  • Patients with complete clinical information.

排除标准

  • The clinicopathological information and MRI data was unqualified or incomplete.
  • Patients had received radiotherapy, chemotherapy, androgen deprivation therapy, or surgery treatment before prostate MRI examination or prostate biopsy.
  • Patients received prior prostate biopsy.
  • Patients had contraindications to MRI or prostate biopsy.
  • Patients were not in accordance with the indication of prostate biopsy.

研究组 & 干预措施

Patients with the indication of prostate biopsy

Experimental

The trained AI algorithms were embedded into proprietary structured reporting software. Before prostate biopsy, the MR images of patients were uploaded to the AI software. The prostate gland and suspicious lesions were annotated and highlighted by AI software. Urogenital radiologists who were blinded to MRI-AI reports independently reviewed the MR images, annotated the suspicious lesions. Then the urologists read both the MRI-AI reports and urogenital radiologist's reports, and conducted 3-5 core targeted biopsy (TB) at each suspicious lesion found by MRI-AI and urogenital radiologists, followed by 12 core systematic biopsy (SB).

干预措施: Combination of targeted biopsy and systematic biopsy (Diagnostic Test)

结局指标

主要结局

The clinically significant prostate cancer (csPCa) detection rate for suspicious lesions found by MRI-AI and urogenital radiologists

时间窗: One month after the biopsy procedure.

csPCa was defined as PCa with a grade group ≥ 2 or GS ≥ 3+4. The reference standard was the pathological results of targeted biopsies for the suspicious lesions.

High-grade PCa detection rate

时间窗: One month after the biopsy procedure.

High-grade PCa was defined as PCa with a grade group ≥3 or GS ≥ 4+3. The reference standard was the pathological results of targeted biopsies for the suspicious lesions.

次要结局

  • The PCa detection rate(One month after the biopsy procedure.)
  • Diagnostic performance(One month after the biopsy procedure)
  • clinically insignificant PCa (ciPCa) detection rate(One month after the biopsy procedure.)

研究者

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

LIU Yi

Associate chief physician

Peking University First Hospital

研究点 (1)

Loading locations...

相似试验