A Prospective Multicenter Clinical-Performance Study of Federated Machine Learning for Automated Interpretation of Point-of-Care Cardiac Ultrasound
试验速览
- 阶段
- 不适用
- 状态
- Enrolling By Invitation
- 发起方
- 入组人数
- 3,000
- 试验地点
- 1
- 主要终点
- Diagnostic Performance for Detecting Reduced Left Ventricular Systolic Function
研究概览
简要总结
This prospective, multicenter study will evaluate a federated machine-learning system designed to analyze focused cardiac point-of-care ultrasound examinations. Federated learning allows participating clinical sites to contribute to model development while keeping raw ultrasound images and directly identifiable patient information within each site's controlled computing environment. Encrypted model updates, rather than patient images, will be transmitted for secure aggregation.
The prospective validation cohort will include approximately 3,000 adults undergoing clinically indicated focused cardiac ultrasound. Model performance will be compared with an expert interpretation of a comprehensive transthoracic echocardiogram performed within 24 hours. The primary objective is to determine how accurately the model identifies reduced left ventricular systolic function, defined as a left ventricular ejection fraction below 40%.
During the initial validation period, the investigational software will operate in silent mode. Its results will not be displayed to treating clinicians and will not be used to diagnose participants, select treatment, or replace standard clinical interpretation.
The study will also evaluate image-quality classification, cardiac-view recognition, performance across clinical sites and ultrasound systems, model calibration, processing time, cybersecurity, privacy resilience, and performance across demographic and clinical subgroups. Long-term monitoring will assess whether model performance changes as clinical populations, ultrasound equipment, acquisition practices, and software environments evolve during the 2026-2037 study period.
详细描述
Federated Learning for Point-of-Care Cardiac Ultrasound (FL-POCUS) is a prospective, multicenter clinical-performance study of a federated machine-learning system for focused cardiac point-of-care ultrasound. The study is intended to determine whether a diagnostic model can be developed and validated across multiple clinical environments without routinely transferring raw ultrasound images or directly identifiable participant information to a central training repository.
Participating institutions may use previously collected, locally governed ultrasound examinations during the federated model-development stage. Each institution will operate a local computing node using a common model architecture, data specification, and quality-control framework. Local model updates will be encrypted and transmitted to a secure aggregation service. The aggregated parameters will then be redistributed to participating sites for subsequent training rounds. Training events, software versions, data-quality findings, and model changes will be documented in an auditable version-control system.
Privacy protections will include access controls, secure aggregation, data-minimization procedures, cybersecurity testing, and evaluation for membership-inference and model-inversion risk. Raw ultrasound images, protected health information, consent records, participant identifiers, and authentication credentials will not be placed on a public blockchain. Any distributed ledger used by the study will be limited to document hashes, version identifiers, authorized attestations, and non-sensitive audit records.
After federated development is complete, the model will be version-locked before prospective clinical validation. Approximately 3,000 adult participants will be enrolled across at least six geographically and technically diverse clinical sites. Eligible participants will be undergoing a clinically indicated focused cardiac point-of-care ultrasound examination and will have an eligible comprehensive transthoracic echocardiogram available within 24 hours of the index examination.
The locked model will operate in silent mode. Investigational outputs will not be displayed to treating clinicians and will not influence diagnosis, treatment, patient disposition, or the decision to obtain additional testing. All clinical decisions will continue to be made through the participating institution's standard care processes.
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
- •Age 18 years or older.
- •Undergoing a clinically indicated point-of-care cardiac ultrasound (POCUS) examination at a participating site.
- •Reference transthoracic echocardiogram completed within 24 hours of the index POCUS examination.
- •At least one cardiac ultrasound view attempted during the index examination.
- •POCUS and reference echocardiography records can be linked using an authorized coded study identifier.
- •Participant consent obtained or inclusion authorized under an Institutional Review Board-approved consent waiver, as applicable.
排除标准
- •Reference transthoracic echocardiogram not completed within 24 hours of the index POCUS examination.
- •Major cardiac procedure or substantial hemodynamic intervention occurring between the POCUS examination and reference echocardiogram, including cardiac surgery, cardioversion, cardiac arrest, or initiation of mechanical circulatory support.
- •Ultrasound or reference data are missing, corrupted, irretrievable, or cannot be securely linked.
- •Previous inclusion of the same participant in the primary validation cohort, unless repeat examinations are authorized under a prespecified longitudinal analysis.
- •Declines participation when individual informed consent is required.
- •Member of a population not authorized for enrollment under the applicable Institutional Review Board approval.
研究组 & 干预措施
Prospective Silent-Mode Federated Cardiac Ultrasound Validation Cohort
Approximately 3,000 adults undergoing clinically indicated focused cardiac point-of-care ultrasonography will be included in this prospective cohort. Each participant's cardiac ultrasound examination will be evaluated by the locked Federated Learning for Point-of-Care Cardiac Ultrasound (FL-POCUS) machine-learning model and compared with a reference transthoracic echocardiogram completed within 24 hours. Investigational model outputs will remain in silent mode and will not be displayed to treating clinicians or used to direct diagnosis, treatment, patient disposition, or additional testing. All attempted examinations, including technically limited studies and examinations with incomplete views, will remain in the primary intention-to-diagnose analysis.
干预措施: Focused Cardiac Point-of-Care Ultrasonography (Diagnostic Test)
Prospective Silent-Mode Federated Cardiac Ultrasound Validation Cohort
Approximately 3,000 adults undergoing clinically indicated focused cardiac point-of-care ultrasonography will be included in this prospective cohort. Each participant's cardiac ultrasound examination will be evaluated by the locked Federated Learning for Point-of-Care Cardiac Ultrasound (FL-POCUS) machine-learning model and compared with a reference transthoracic echocardiogram completed within 24 hours. Investigational model outputs will remain in silent mode and will not be displayed to treating clinicians or used to direct diagnosis, treatment, patient disposition, or additional testing. All attempted examinations, including technically limited studies and examinations with incomplete views, will remain in the primary intention-to-diagnose analysis.
干预措施: FL-POCUS Federated Machine-Learning Analysis System (Device)
结局指标
主要结局
Diagnostic Performance for Detecting Reduced Left Ventricular Systolic Function
时间窗: Day 1 (within 24 hours after the index point-of-care ultrasound examination)
Area under the receiver operating characteristic curve (AUROC) of the locked federated-learning point-of-care ultrasound (POCUS) model for identifying left ventricular ejection fraction below 40%, using masked expert core-laboratory interpretation of the reference transthoracic echocardiogram as the reference standard. Analysis will be performed at the participant level with a two-sided 95% confidence interval.
次要结局
- Sensitivity and Specificity for Detecting Left Ventricular Ejection Fraction Below 40%(Day 1 (within 24 hours after the index point-of-care ultrasound examination))
- Diagnostic Performance for Detecting Severe Left Ventricular Systolic Dysfunction(Day 1 (within 24 hours after the index point-of-care ultrasound examination))
- Cardiac Ultrasound View Classification Accuracy(Day 1 (index point-of-care ultrasound examination))
- Agreement of Automated and Expert Image-Quality Classification(Day 1 (index point-of-care ultrasound examination))
- Nondiagnostic Model Output Rate(Day 1 (index point-of-care ultrasound examination))
- Calibration of Predicted Reduced Left Ventricular Function Risk(Day 1 (within 24 hours after the index point-of-care ultrasound examination))
- Model Processing Time(Day 1 (index point-of-care ultrasound examination))
- Cross-Site and Ultrasound-Device Generalizability(From model lock through primary completion, up to 10 years.)
- Longitudinal Model Performance Drift(Annually from model lock through primary completion, up to 10 years.)