An observational study in Ventricular Dysfunction, Left, Ventricular Function, Left and Echocardiography, sponsored by Truway Health, Inc.. Enrolling by invitation at 1 site in United States. Open to participants aged 18 Years and older. Per ClinicalTrials.gov, last updated 2026-09-02.
Sponsored by Truway Health, Inc. · Observational
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.
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.
The model will evaluate standard focused cardiac views, including parasternal long-axis, parasternal short-axis, apical four-chamber, and subcostal views when available. Investigational functions may include cardiac-view classification, image-quality assessment, identification of technically limited examinations, and detection of reduced left ventricular systolic function.
The primary outcome is the area under the receiver-operating-characteristic curve for detecting a reference-standard left ventricular ejection fraction below 40%. The proposed performance criterion is an area under the curve of at least 0.85, with the lower bound of the two-sided 95% confidence interval exceeding 0.80.
The reference standard will be established using comprehensive transthoracic echocardiography. Two qualified echocardiography readers, masked to the investigational model result, will independently review eligible reference examinations. Disagreements affecting the prespecified ejection-fraction category will be resolved by a third senior reader.
Secondary evaluations will include sensitivity, specificity, positive and negative predictive values, detection of severe systolic dysfunction, cardiac-view classification accuracy, agreement with expert image-quality assessments, nondiagnostic examination rate, calibration, processing time, site-level heterogeneity, and performance by ultrasound manufacturer and transducer type.
Prespecified subgroup analyses will examine performance by age, sex, race, ethnicity, body mass index category, clinical environment, cardiac rhythm, acquisition experience, study site, and ultrasound system. Subgroup results will be reported even when the model satisfies the overall primary performance criterion.
All attempted examinations will remain in the primary intention-to-diagnose analysis, including technically limited studies and examinations with incomplete cardiac views. A model output that cannot produce a valid diagnostic classification will be counted as a test failure in the primary analysis. An evaluable-case analysis may be performed as a secondary analysis.
The study includes a long-term performance-surveillance period extending through September 30, 2037. This period will evaluate model drift, calibration changes, equipment transitions, software updates, cybersecurity events, evolving acquisition practices, and changes in the enrolled population. Prospective data used for final validation will remain separated from model-development data unless a separately governed amendment authorizes a new model version. Any updated model will receive a new version designation and must undergo independent validation before clinical use.
Reportable study events will include unauthorized data disclosure, attempted reconstruction of participant information, incorrect linkage between examinations and participants, inadvertent display of investigational results, validation-data leakage into training, material subgroup-performance disparities, cybersecurity incidents, and significant protocol deviations.
The study will not authorize automated diagnosis or autonomous clinical management. Any later investigation in which model results are displayed to clinicians or used to influence care will require a separately approved protocol, updated risk assessment, applicable regulatory review, and independent Institutional Review Board authorization.
The study population will consist of adults receiving care in emergency departments, inpatient units, outpatient clinics, or other participating clinical settings who undergo a clinically indicated point-of-care cardiac ultrasound examination and a reference transthoracic echocardiogram within 24 hours. Consecutive eligible participants will be enrolled without selection based on expected left ventricular function or image quality. The cohort is intended to represent diverse clinical sites, ultrasound devices, operators, demographic groups, body compositions, cardiac rhythms, and levels of left ventricular systolic function encountered in routine care.
Exclusion Criteria:
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.
Diagnostic Test: Focused Cardiac Point-of-Care Ultrasonography · Device: FL-POCUS Federated Machine-Learning Analysis System
A clinically indicated, noninvasive focused cardiac ultrasound examination performed through a point-of-care ultrasound system. Standard views may include parasternal long-axis, parasternal short-axis, apical four-chamber, and subcostal views. The examination will be evaluated for image quality, cardiac-view classification, left ventricular function, and evidence of reduced left ventricular ejection fraction.
Also known as: Point-of-Care Ultrasound; POCUS; Focused Cardiac Ultrasound; FoCUS; Cardiac Ultrasonography
Investigational software that analyzes focused cardiac point-of-care ultrasound examinations using a version-locked federated machine-learning model. The system evaluates cardiac-view classification, image quality, left ventricular function, and the probability of a left ventricular ejection fraction below 40%. During this observational validation study, all model outputs will remain in silent mode and will not influence clinical care. Raw ultrasound images and directly identifiable participant information will remain within each participating site's controlled environment.
Also known as: FL-POCUS; Federated Learning POCUS System; Federated Cardiac Ultrasound Model; Silent-Mode Echocardiography AI
Diagnostic Performance for Detecting Reduced Left Ventricular Systolic Function
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.
Time frame: Day 1 (within 24 hours after the index point-of-care ultrasound examination)
Sensitivity and Specificity for Detecting Left Ventricular Ejection Fraction Below 40%
Participant-level sensitivity and specificity of the locked model at the prespecified decision threshold for detecting left ventricular ejection fraction below 40%, compared with masked expert core-laboratory interpretation of the reference transthoracic echocardiogram. Results will include two-sided 95% confidence intervals.
Time frame: Day 1 (within 24 hours after the index point-of-care ultrasound examination)
Diagnostic Performance for Detecting Severe Left Ventricular Systolic Dysfunction
AUROC of the locked model for identifying severe left ventricular systolic dysfunction, defined as a reference left ventricular ejection fraction below 30%. Sensitivity and specificity at the prespecified decision threshold will also be reported.
Time frame: Day 1 (within 24 hours after the index point-of-care ultrasound examination)
Cardiac Ultrasound View Classification Accuracy
Percentage of acquired ultrasound clips correctly classified by the model as parasternal long-axis, parasternal short-axis, apical four-chamber, subcostal, or other view, compared with blinded expert-reader classification.
Time frame: Day 1 (index point-of-care ultrasound examination)
Agreement of Automated and Expert Image-Quality Classification
Agreement between model-generated and blinded expert-reader image-quality ratings. Images will be categorized as diagnostic, technically limited, or nondiagnostic. Percentage agreement and weighted kappa with a two-sided 95% confidence interval will be reported.
Time frame: Day 1 (index point-of-care ultrasound examination)
Nondiagnostic Model Output Rate
Percentage of attempted participant examinations for which the locked model cannot generate a valid left ventricular systolic-function classification because of inadequate image quality, incomplete acquisition, unsupported cardiac view, or technical processing failure.
Time frame: Day 1 (index point-of-care ultrasound examination)
Calibration of Predicted Reduced Left Ventricular Function Risk
Agreement between the model-predicted probability and observed occurrence of left ventricular ejection fraction below 40%. Calibration will be evaluated using the calibration intercept, calibration slope, and Brier score.
Time frame: Day 1 (within 24 hours after the index point-of-care ultrasound examination)
Model Processing Time
Median elapsed time, measured in seconds, from availability of the completed ultrasound examination to generation of the locked model output. The interquartile range and 95th percentile will also be reported.
Time frame: Day 1 (index point-of-care ultrasound examination)
Cross-Site and Ultrasound-Device Generalizability
AUROC for detecting left ventricular ejection fraction below 40% will be calculated separately by participating site and ultrasound-device manufacturer. Performance heterogeneity will be summarized using the range of site-specific and device-specific AUROCs and a hierarchical random-effects analysis.
Time frame: From model lock through primary completion, up to 10 years.
Longitudinal Model Performance Drift
Annual change in AUROC, sensitivity, specificity, calibration slope, and nondiagnostic output rate relative to the first completed validation year. The model and decision threshold will remain locked during prospective validation unless a protocol-defined model update is separately evaluated.
Time frame: Annually from model lock through primary completion, up to 10 years.
Federated-Learning Privacy Attack Resistance
Resistance of the federated-learning system to prespecified membership-inference and model-inversion tests. Membership-inference attack AUROC and the percentage of testing attempts producing recognizable reconstruction of source ultrasound data will be reported.
Time frame: Before prospective deployment and annually through study completion, up to 11 years.
Plan to share: Yes — De-identified individual participant data underlying the reported study results will be made available. Shared data may include coded demographic characteristics, clinical setting, ultrasound-device category, POCUS acquisition characteristics, expert reference left ventricular ejection fraction, locked-model predictions, image-quality classifications, and analyzed outcome variables. Direct identifiers will not be shared. Raw ultrasound files will be available only through controlled access when permitted by the originating site, informed-consent terms, and applicable privacy requirements.
Supporting information: Study protocol, Sap, Icf, Csr, Analytic code
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Ventricular Dysfunction, Left→
Truway Health, Inc.