Novel Imaging Techniques for the Characterization of Musculoskeletal Tumors II: Texture Analysis and Artificial Intelligence
试验速览
- 阶段
- 不适用
- 状态
- 招募中
- 发起方
- 入组人数
- 740
- 试验地点
- 1
- 主要终点
- Lesion benignancy or malignancy
研究概览
简要总结
This study aims at evaluating the value of various artificial intelligence based techniques to improve the characterization and image post-processing for patients with musculoskeletal tumors.
详细描述
Comparison of values relating to the texture parameters of tumors evaluated by MRI and ultra-high resolution CT between benign and malignant lesions using histological analysis as the standard of reference.
Comparison of the diagnostic performance of texture parameters derived from different MRI sequences and ultra-high resolution CT for musculoskeletal tumor characterization.
Evaluate the impact of ultra-high resolution with respect to standard resolution on CT images Comparison of the diagnostic performance of the texture parameters for the tumor on the diagnostic performance of texture analysis derived parameters for the characterization of musculoskeletal tumors.
Evaluate the effectiveness and accuracy of automatic artificial intelligence (AI) based tumor segmentation tools.
Evaluate the use of trabecular analysis on ultra-high resolution CT images for the evaluation of tumor-bone interfaces.
研究设计
- 研究类型
- Observational
- 观察模型
- Cohort
- 时间视角
- Prospective
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
- •Patients suspected to have a bone or soft-tissue tumor referred for imaging for initial tumors characterization and staging.
排除标准
- •Pregnancy
- •Breast feeding patients
- •Renal insufficiency
- •Contra indications to MRI or CT
- •Prior surgery or treatment to the evaluated lesion.
结局指标
主要结局
Lesion benignancy or malignancy
时间窗: Performed up to 6 months after CT and Magnetic Resonance (MR) imaging
Histologic determination of lesion aggressiveness (benign versus malignant) on core biopsy material
次要结局
- Sarcoma FNCLCC (fédération Nationale des Centres de Lutte Contre le Cancer) grade(Performed up to 1 year after CT and MR imaging)