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Us2.v1
Us2.v1
Us2.ai
Us2.ai supports cardiovascular disease diagnostics by providing machine learning based solutions that analyze and interpret echocardiograms, which are ultrasound images of the heart, creating patient reports, at scale, on mobile, on premises and cloud-based platforms.
Information source:
Vendor
Last updated:
December 4, 2024
General Information
Technical Specifications
Regulatory
Market
Evidence
General Information
General
Product name
Us2.v1
Company
Us2.ai
Subspeciality
Cardiac
Modality
Ultrasound
Disease targeted
Heart disease, Pulmonary Hypertension
Key-features
Automated measurements include 2-dimensional (cardiac volumes, all 4 chambers of the heart), M-mode (e.g. tricuspid annular plane systolic excursion), spectral Doppler (blood flow across all valves, both PW and CW measurements) and tissue Doppler
Suggested use
During: perception aid (prompting all abnormalities/results/heatmaps), report suggestion
Technical Specifications
Data characteristics
Population
Vast majority of adult transthoracic echocardiograms. Not intended for reporting measurements associated with valve disease, pericardial disease, or right-sided hemodynamics (e.g. estimated pulmonary artery systolic pressure); intra-cardiac lesions (e.g. tumours, thrombi); and will not report measurements for complex adult congenital heart disease.
Input
Transthoracic echocardiography
Input format
DICOM
Output
Patient report, editable image annotations, comparison to international reference guidelines
Output format
DICOM SR, PDF, CSV
Technology
Integration
Integration in standard reading environment (PACS), Integration CIS (Clinical Information System), Integration via AI marketplace or distribution platform, Stand-alone third party application, Stand-alone webbased
Deployment
Locally on dedicated hardware, Locally virtualized (virtual machine, docker), Cloud-based, Hybrid solution
Trigger for analysis
Automatically, right after the image acquisition, On demand, triggered by a user through e.g. a button click, image upload, etc.
Processing time
1 - 10 minutes
Regulatory
Certification
CE
Certified, Class IIb
, MDR
FDA
510(k) cleared , Class II
Intended Use Statements
Intended use (according to CE)
Us2.v1 is a software platform that automatically processes, analyses and makes measurements on acquired transthoracic cardiac ultrasound images, producing a full report with measurements of several key cardiac structural and functional parameters. The data produced by this software is intended to be used to support qualified cardiologists, sonographers, or other licensed professional healthcare practitioners for clinical decision- making. Us2.v1 is indicated for use in adult patients. Us2.v1 has not been validated for the assessment of congenital heart disease, valve disease, pericardial disease, and/or intra- cardiac lesions (e.g. tumours, thrombi).
Market
Market presence
On market since
06-2022
Distribution channels
Blackford, Aidoc aiOS, Viz Platform, Eureka Clinical AI, Nuance PIN
Countries present (clinical, non-research use)
USA, Canada, EU, Australia, New Zealand, Singapore
Paying clinical customers (institutes)
Research/test users (institutes)
Pricing
Pricing model
Subscription
Based on
Number of analyses
Evidence
Evidence
Peer reviewed papers on performance
Concordance of left ventricular volumes and function measurements between two human readers, a fully automated AI algorithm, and the 3D heart model
(read)
Point‑of‑care AI‑enhanced novice echocardiography for screening heart failure (PANES‑HF)
(read)
Artificial intelligence-assisted automated heart failure detection and classification from electronic health records
(read)
Nurse-led home-based detection of cardiac dysfunction by ultrasound: results of the CUMIN pilot study
(read)
External validation of a deep learning algorithm for automated echocardiographic strain measurements
(read)
A formal validation of a deep learning-based automated workflow for the interpretation of the echocardiogram
(read)
Automated interpretation of systolic and diastolic function on the echocardiogram: a multicohort study
(read)
Non-peer reviewed papers on performance
Other relevant papers
AHA24 presentation: Artificial Intelligence-Based Automated Echocardiographic Measurements and the Workflow of Sonographers: Randomized Crossover Trial (AI-ECHO RCT)
(read)
OPERA-AI: Artificial Intelligence Reporting of Handheld Echocardiography in Suspected Heart Failure
(read)
Democratizing Echocardiography with Augmented Intelligence
(read)