AI-based Prediction of Prostate Cancer Metastasis Using Biopsy Pathology
Development and Validation of an AI-Based Metastasis Prediction Model Using Prostate Cancer Biopsy Pathology
This observational study aims to develop and validate an artificial intelligence-based model using prostate cancer biopsy pathology to predict lymph node metastasis and distant metastasis in patients with prostate cancer. The main questions it aims to answer are:
Can artificial intelligence-assisted analysis of prostate cancer biopsy pathology accurately predict lymph node metastasis? Can the model accurately predict distant metastasis and assess metastatic risk in patients with prostate cancer?
Researchers aim to evaluate whether the model can provide additional information for clinical decision-making and surgical planning.
Participants will:
Provide prostate biopsy pathology specimens and related clinical information; Undergo assessment of lymph node and distant metastatic status based on clinical and imaging data; Be included in the development and validation of the artificial intelligence prediction model.
研究概览
研究类型
注册 (估计的)
联系人和位置
学习地点
-
-
Hunan
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Changsha、Hunan、中国、410008
- Xiangya Hospital, Central South University
-
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参与标准
资格标准
适合学习的年龄
- 成人
- 年长者
接受健康志愿者
取样方法
研究人群
描述
Inclusion Criteria:
- Male patients aged between 18 and 90 years; Patients who underwent prostate biopsy due to elevated prostate-specific antigen (PSA), abnormal digital rectal examination (DRE), or abnormal imaging findings, were pathologically diagnosed with prostate cancer, and had available prostate biopsy pathology specimens; Patients who underwent radical prostatectomy with extended pelvic lymph node dissection (ePLND) or pelvic lymph node dissection (PLND), with definitive pathological information regarding lymph node metastasis; Patients who underwent PSMA PET/CT, MRI, bone scintigraphy, or prostate MRI capable of identifying regional lymph node metastasis or distant metastasis; Adequate cardiac, pulmonary, hepatic, and renal function; Eastern Cooperative Oncology Group (ECOG) performance status of 0-1; Expected survival time greater than 1 year; Written informed consent signed by the patient or legally authorized representative.
Exclusion Criteria:
- History of other malignancies; Severe dysfunction of major organs, including cardiac, pulmonary, hepatic, or renal insufficiency, or an expected survival time of less than 1 year; Prostate biopsy pathology specimens with inadequate whole-slide image scanning quality or failure of quality control assessment; Patients with prostate cancer diagnosed from transurethral resection specimens.
学习计划
研究是如何设计的?
设计细节
队列和干预
团体/队列 |
干预/治疗 |
|---|---|
|
Prostate Cancer Cohort
Patients with prostate cancer undergoing biopsy pathology assessment for development and validation of an AI-based metastasis prediction model.
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Artificial intelligence-assisted analysis of prostate cancer biopsy pathology specimens for prediction of lymph node and distant metastasis risk.
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研究衡量的是什么?
主要结果指标
结果测量 |
措施说明 |
大体时间 |
|---|---|---|
|
Prediction of Regional Lymph Node Metastasis
大体时间:Baseline
|
Assessment of the ability of the artificial intelligence-based model using prostate cancer biopsy pathology to predict regional lymph node metastasis.
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Baseline
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合作者和调查者
调查人员
- 首席研究员:Yi Cai、Xiangya Hospital Central South University Department of Urology
研究记录日期
研究主要日期
学习开始 (实际的)
初级完成 (估计的)
研究完成 (估计的)
研究注册日期
首次提交
首先提交符合 QC 标准的
首次发布 (实际的)
研究记录更新
最后更新发布 (实际的)
上次提交的符合 QC 标准的更新
最后验证
更多信息
与本研究相关的术语
其他研究编号
- 2026010083_4
计划个人参与者数据 (IPD)
计划共享个人参与者数据 (IPD)?
IPD 计划说明
药物和器械信息、研究文件
研究美国 FDA 监管的药品
研究美国 FDA 监管的设备产品
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