Pilot Study on Artificial Intelligence-assisted Uro-Cam Catheter Assessment System for Diagnosing Bladder Cancer
试验速览
- 阶段
- 不适用
- 状态
- 尚未招募
- 入组人数
- 60
- 试验地点
- 2
- 主要终点
- 30-day complications
研究概览
简要总结
This is a single-arm study investigating the safety, feasibility and diagnostic performance of AI-assisted Uro-Cam catheter assessment that will be performed at the Prince of Wales Hospital. All patients who are referred to the urology outpatient clinic for hematuria workup, and bladder cancer patients who require follow-up cystoscopy, will be screened for study eligibility. If eligible, patients will be recruited into the study with a proper informed consent. All recruited patients will undergo the AI-assisted Uro-Cam catheter assessment followed by a conventional flexible cystoscopy. The study will be conducted in accordance with the Declaration of Helsinki, and it will be registered in ClinicalTrials.gov.
An AI-assisted Uro-Cam catheter assessment will be arranged for all recruited study subjects. After the AI-assisted Uro- Cam catheter assessment, a conventional flexible cystoscopy will be conducted in the same session. Biopsy will be taken from any suspicious lesion detected upon AI-assisted Uro-Cam catheter assessment or conventional flexible cystoscopy.
After all the procedures, an End-of-study visit will be arranged 4-6 weeks later. The primary outcomes include 30-day complications, and the technical success rate of the AI-assisted Uro-Cam catheter assessment. 30-day complications will be assessed and grading according to the Clavien-Dindo classification. Technical success is defined by the completion of the whole Uro-Cam catheter assessment. The secondary outcomes include the AUC, sensitivity, specificity, positive predictive value, and negative predictive value in detecting histologically confirmed bladder cancer.
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
- 18 Years 至 —（Adult, Older Adult）
- 性别
- All
- 接受健康志愿者
- 否
入选标准
- •Age 18 years or above
- •Fulfil any one of the following three criteria: (1) Macroscopic haematuria or persistent microscopic haematuria (microscopic haematuria in at least two urine tests), (2) Abnormal urine cytology results (Atypical cells in at least two urine cytology tests, OR Suspicious cells or malignant cells in at least one urine cytology test), (3)History of non-muscle-invasive bladder cancer with complete transurethral resection of bladder tumour performed
排除标准
- •Presence of clinically significant cardiovascular disease (History of acute myocardial infarction, presence of uncontrolled angina within 3 months before screening, New York Heart Association Class III or IV congestive heart failure, presence of ventricular arrhythmias, or presence of second-degree or third-degree heart block)
- •Any evidence of active urinary tract infection
- •Presence of GOLD Stage III or IV chronic obstructive pulmonary disease
- •ECOG performance status ≥ 2 (Ambulatory and capable of all self-care but unable to carry our any work activities)
- •History of bleeding disorder or use of anti-coagulants
- •Presence of other active malignancy
- •Pregnancy
研究组 & 干预措施
AI Uro-Cam
All recruited patients will undergo the AI-assisted Uro-Cam catheter assessment followed by a conventional flexible cystoscopy in the same session. Biopsy will be taken from any suspicious lesion detected upon AI-assisted Uro-Cam catheter assessment or conventional flexible cystoscopy.
干预措施: AI Uro-Cam (Device)
结局指标
主要结局
30-day complications
时间窗: Thirty days after the allocated treatment
30-day complications will be assessed and grading according to the Clavien-Dindo classification.
Technical success rate
时间窗: Immediately post-operative
Technical success is defined by the completion of the whole Uro-Cam catheter assessment.
Technical success rate
时间窗: Immediately post-operative
Technical success is defined by the completion of the whole Uro-Cam catheter assessment.
次要结局
- Performance Evaluation(Thirty days after the allocated treatment)
- Performance Evaluation(Thirty days after the allocated treatment)
研究者
Jeremy Yuen Chun TEOH
Assistant Professor
Chinese University of Hong Kong