Prospective Clinical Validation Study of a Deep Learning Model for Opportunistic Osteoporosis Screening Based on Non-Contrast CT Scans
试验速览
- 阶段
- 不适用
- 状态
- 进行中（未招募）
- 发起方
- 入组人数
- 100
- 试验地点
- 1
- 主要终点
- Diagnostic performance of DeepBMD model for osteoporosis screening
研究概览
简要总结
The goal of this clinical trial is to test if an artificial intelligence (AI) tool called DeepBMD can accurately identify people at high risk for osteoporosis using routine chest or abdomen CT scans. The main questions it aims to answer are:
- Can the DeepBMD tool correctly identify people who have osteoporosis compared to the standard bone density test, dual-energy X-ray absorptiometry (DXA)?
- Is it practical to use this AI tool in real-world hospital settings to find and contact high-risk patients? Researchers will use the DeepBMD tool to analyze existing CT scans. If the tool flags a patient as high risk, researchers will call them to invite them for a standard bone density test (DXA).
Participants will:
- Have their existing chest or abdomen CT scan analyzed by the DeepBMD AI tool;
- Receive a phone call from the research team if identified as high risk;
- Visit the clinic for a free standard bone density test (DXA) if they agree to participate.
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
- •Underwent non-contrast CT at our institution, with qualified image quality and no severe artifacts;
- •Identified as high-risk for osteoporosis by the DeepBMD model;
- •Had valid contact information available in the PACS, possessed normal cognitive and communication abilities, and was able to cooperate with telephone follow-ups and on-site examinations;
- •Voluntarily participated in the study, was able to sign a written informed consent form on-site, and agreed to undergo DXA examination.
排除标准
- •Severe spinal deformity, postoperative spinal internal fixation, malignant bone metastasis, or severe osteolytic lesions that may interfere with measurements;
- •A confirmed diagnosis of osteoporosis with ongoing standardized treatment;
- •Inability to be contacted, explicit refusal of follow-up, or inability to visit the hospital for informed consent signing and DXA examination.
研究组 & 干预措施
High-risk patients for osteoporosis identified by DeepBMD model
Patients who underwent routine chest or abdominal CT scans and were identified as high risk for osteoporosis by the DeepBMD AI model. These participants will be contacted via telephone, invited to the clinic, and undergo a free DXA scan to verify bone mineral density.
干预措施: DeepBMD model for osteoporosis risk screening (Diagnostic Test)
结局指标
主要结局
Diagnostic performance of DeepBMD model for osteoporosis screening
时间窗: Concurrent with the DXA validation visit following the CT analysis (within 7 days).
The diagnostic performance of the DeepBMD model will be evaluated by comparing its predictions against the gold standard Dual-energy X-ray Absorptiometry (DXA). Specifically, we will calculate the sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and the Area Under the Receiver Operating Characteristic Curve (AUC) for identifying patients with osteoporosis.
次要结局
- Feasibility of the DeepBMD screening and recall workflow(At the end of recruitment)
研究者
Yang Fan
Professor and Chief Physician
Union Hospital, Tongji Medical College, Huazhong University of Science and Technology