The Value of Artificial Intelligence-based 18F-FDG PET/CT in Diferential Diagnosis, Efficacy Prediction and Prognosis Prediction of T-NK Cell Lymphoma: a Clinical Study
试验速览
- 阶段
- 不适用
- 状态
- 尚未招募
- 入组人数
- 200
- 试验地点
- 1
- 主要终点
- Evaluation the value of Artificial Intelligence-based 18F-FDG PET/CT of T-NK Cell Lymphoma
研究概览
简要总结
Based on the PET/CT imaging data of patients with T-NK cell lymphoma, machine learning and deep learning methods are used to extract imaging features, establish a T-NK cell lymphoma prediction model, and provide more scientific and accurate prognosis prediction for the clinic.
详细描述
This study adopts a multicenter retrospective cohort study design，we provided PET/CT of 200 patients with T-NK cell lymphoma as an external validation set for model validation.
研究设计
- 研究类型
- Observational
- 观察模型
- Other
- 时间视角
- Retrospective
入排标准
- 年龄范围
- 18 Years 至 75 Years（Adult, Older Adult）
- 性别
- All
- 接受健康志愿者
- 否
入选标准
- •Pathological histology confirmed as T-NK Cell Lymphoma; 2.18F-FDG PET/CT examination before treatment;
- •Using modern best practice treatment options;
- •Complete clinicopathological and follow-up data were obtained.
排除标准
- •The patient had previously received antitumor therapy;
- •The patient had a history of other tumors;
- •Incomplete clinical information or imaging data;
- •Concomitant other malignant tumors.
结局指标
主要结局
Evaluation the value of Artificial Intelligence-based 18F-FDG PET/CT of T-NK Cell Lymphoma
时间窗: Within 1 week of enrollment and after 3 months treatment
The Value of Artificial Intelligence-based 18F-FDG PET/CT in Diferential Diagnosis, Efficacy Prediction and Prognosis Prediction of T-NK Cell Lymphoma
次要结局
- Progress free survival(3 years)
- Overall survival(3 years)