New Strategy of Knowledge-Enhanced Large Model for Ultrasound Scanning and Diagnosis of Ovarian Masses
试验速览
- 阶段
- 不适用
- 状态
- 尚未招募
- 入组人数
- 250
- 试验地点
- 2
- 主要终点
- Completeness of ultrasound feature acquisition
研究概览
简要总结
Investigators developed an interactive agentic system designed to guide newly qualified sonographers in ovarian lesion scanning and improve their scanning quality and diagnostic performance toward expert-level standards. Our agentic system is capable of capturing key features including the max-diameter plane of ovarian lesions from dynamic ultrasound videos, translating these findings into standardized International Ovarian Tumor Analysis (IOTA) descriptors, and providing multi-turn guidance for subsequent scanning, and ultimately generating an AI-assisted diagnostic assessment based on embedded expert knowledge.
In this multicenter study, participants are asked to undergo gynecological ultrasonography performed by sonographers with less than 3 years of experience with or without AI assistance. Our researchers will compare the performance of operators working with AI against that of operators working without AI, as well as against the performance of expert sonographers, to see whether AI assistance enhances the proficiency of less experienced operators and help them approach the scanning quality and diagnostic accuracy of expert sonographers in real-world clinical scenarios.
详细描述
This multicenter, prospective study will be conducted at tertiary cancer centers and primary healthcare institutions across China. Participants will be recruited from gynecological ultrasound clinics of each site.
Each participant will undergo gynecological ultrasonography under both AI-assisted and unassisted conditions according to their group allocation. Following completion of the study examinations, expert sonographers with more than 10 years of experience, blinded to the scanning and diagnostic results of the junior sonographers, will independently perform a repeat gynecological ultrasound examination of each participant. Based solely on their independent examination, they will issue the final clinical report for each participant. The expert assessments will serve as one reference standard for evaluating scanning completeness, feature interpretation accuracy and diagnostic agreement. Histopathological findings, when available, or clinical follow-up for conservatively managed lesions will serve as the reference standard for evaluating diagnostic accuracy.
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 75 Years（Adult, Older Adult）
- 性别
- Female
- 接受健康志愿者
- 否
入选标准
- •Female aged 18-75 years
- •With suspected ovarian masses identified clinically or by previous imaging examination
- •Eligible for and able to undergo transvaginal or transabdominal ultrasonography
- •Agree to provide written informed consent before enrollment
排除标准
- •No ovarian mass identified on ultrasound examination
- •Previous bilateral oophorectomy
- •Previous surgery or chemotherapy for ovarian cancer
- •Previous treatment for other malignant tumors
- •Presence of any psychiatric or psychological disorders that may prevent completion of the study procedures or follow-up
- •Concurrent participation in other clinical trials that may interfere with the outcomes of this study
研究组 & 干预措施
Arm A: experimental sequence of non-AI exertion followed by AI-assisted exertion
The goal is to test the within-operator effect associated with AI assistance by comparing the performance of the same junior sonographer before and after AI guidance, and to compare the performance of both AI-assisted and unaided junior sonographers with that of the standalone AI model.
干预措施: non-AI assisted and then AI assisted (Other)
Arm B: experimental sequence of AI-assisted exertion followed by non-AI exertion
The goal is to test the clinical utility of AI with minimized potential carry-over effects and recall bias caused by repeated examinations on the same patient, by comparing the performance of one junior sonographer with AI-assisted, with that of independent unaided junior sonographers, and by comparing the performance of both AI-assisted junior sonographers and another unaided ones with that of the standalone AI model.
干预措施: AI assisted and then non-AI assisted (Other)
结局指标
主要结局
Completeness of ultrasound feature acquisition
时间窗: Up to 7 days from completion of the study
The completeness of ultrasound feature acquisition will be assessed with reference to national authoritative quality-control standards. After each examination, all stored ultrasound images and videos will be labeled according to their intended purpose. A feature will be considered adequately acquired when at least one stored image or video provides sufficient visual evidence for assessment of that feature. The proportion of required features successfully acquired will be calculated. The proportion of redundant stored images will also be recorded as an additional indicator of acquisition quality.
Accuracy of interpretation of individual ultrasound features
时间窗: Up to 7 days from completion of the study
The accuracy of interpretation of ultrasound features will be assessed by comparing the assessments made by junior sonographers under AI-assisted and unassisted conditions with the findings independently acquired and interpreted by expert sonographers during a separate repeat ultrasound examination. The accuracy rate for each feature will be calculated.
Agreement between junior and expert sonographers in ultrasound diagnosis
时间窗: Up to 7 days from completion of the study
Agreement between junior and expert sonographers will be assessed for the final diagnosis of ovarian lesions. The assessments made by junior sonographers under AI-assisted and unassisted conditions will be compared with the corresponding diagnoses independently obtained by expert sonographers during a separate repeat ultrasound examination, which will then be quantified using appropriate agreement statistics.
Diagnostic accuracy of ovarian tumors
时间窗: Within 3 months after the ultrasonography examination
Diagnostic accuracy will be assessed against histopathological diagnosis as the golden reference standard. This outcome will be evaluated only in participants who undergo surgical treatment and have definitive histopathological findings based on paraffin-embedded surgical specimens.
Diagnostic performance of ovarian tumors
时间窗: Within 3 months after the ultrasonography examination
Area under curve will be assessed against histopathological diagnosis as the golden reference standard. This outcome will be evaluated only in participants who undergo surgical treatment and have definitive histopathological findings based on paraffin-embedded surgical specimens.
次要结局
- Confidence in ultrasound feature acquisition and diagnosis(Up to 7 days from completion of the study)
研究者
Jiale Qin
Professor/Chief Physician in Ultrasound, M.D.
Women's Hospital School Of Medicine Zhejiang University