A Prospective Cohort Study Comparing Artificial Intelligence Multimodal Fusion Prediction Models With Conventional Imaging Assessment for the Diagnosis of Pelvic Lymph Node Metastasis in Cervical Cancer
试验速览
- 阶段
- 不适用
- 状态
- 尚未招募
- 发起方
- 入组人数
- 230
- 试验地点
- 1
- 主要终点
- Accuracy in determining pelvic lymph node metastasis
研究概览
简要总结
The goal of this prospective cohort study is to learn whether artificial intelligence multimodal fusion prediction models are effective in diagnosing pelvic lymph node metastasis in cervical cancer. The main question it aims to answer is: can artificial intelligence multimodal fusion prediction models improve the accuracy of preoperative diagnosis of pelvic lymph node metastasis in cervical cancer? The researchers compared the AI multimodal fusion prediction model with traditional imaging physician assessments to see if the prediction model could yield more accurate lymph node metastasis determinations. Participants will undergo pelvic MRI after pathologically confirming a diagnosis of cervical cancer, and the results will be used to determine pelvic lymph node metastasis status by the predictive model and the imaging physician, respectively. Subsequent pathology results after surgical lymph node clearance will be used as the gold standard to determine the accuracy of the two preoperative lymph node diagnostic modalities.
研究设计
- 研究类型
- Interventional
- 分配方式
- Non Randomized
- 干预模型
- Factorial
- 主要目的
- Diagnostic
- 盲法
- None
入排标准
- 年龄范围
- 18 Years 至 80 Years（Adult, Older Adult）
- 性别
- Female
- 接受健康志愿者
- 否
入选标准
- •patients with preoperative diagnosis of invasive cervical cancer stage I-III, with any type of pathology, and patients who underwent radical/modified radical cervical cancer surgery + pelvic lymph node dissection in our hospital or sub-center;
- •Age ≥18 years and ≤80 years;
- •patients who underwent preoperative pelvic MRI (plain/enhanced) imaging in our hospital or sub-centers.
排除标准
- •patients during pregnancy or lactation, patients with abortion within 42 days;
- •patients who are undergoing or have undergone preoperative neoadjuvant chemotherapy or radiotherapy for this cervical cancer;
- •Patients with other malignant tumors within 5 years;
- •Combination of other underlying diseases that may lead to enlarged pelvic lymph nodes;
- •patients whose preoperative pelvic MRI date is more than 1 month from the day of surgery;
- •poor quality imaging images that are unrecognizable.
结局指标
主要结局
Accuracy in determining pelvic lymph node metastasis
时间窗: The time frame was from subject enrollment until surgical pathology results were obtained. The time between subject enrollment and the availability of surgical pathology results was approximately 1 to 1.5 months.
After the subjects underwent surgical treatment, surgical pathology served as the gold standard for evaluating the accuracy of the AI predictive model in comparison to traditional imaging diagnosis. In the statistical analysis phase, sensitivity and specificity were utilized as the primary indicators to assess the accuracy of both diagnostic modalities.
次要结局
未报告次要终点
研究者
Xin Wu
Deputy Chief of Gynecologic Oncology
Obstetrics & Gynecology Hospital of Fudan University