Read about updates on iCardio.ai.

Reach out to us and integrate AI into your pipeline today.

EchoMeasure™

CardioVision™

Team

Releases

Careers

bringing ai to ultrasound

iCardio.ai solutions.

Redefining the future of heart imaging.

iCardio.ai solutions.

Using machine learning, we build tools for everything echo.
Take a tour of our solutions below.

510(k) cleared solution

iCardio.ai EchoMeasure™

Bringing AI precision to Echocardiography

Despite its ubiquity, echocardiography is prone to significant intra-reader variability. As a solution to this issue, AI has been extensively investigated as a means to minimize variability in quantitative interpretation of echocardiography. Artificial intelligence AI has shown superiority over human readers in the interpretation of echocardiography, including ejection fraction estimation.^[4] EchoMeasure™ can automate over a dozen cardiac measurements and can be seamlessly integrated into the standard reporting workflow.

[4] He, Bryan, et al. "Blinded, randomized trial of sonographer versus AI cardiacfunction assessment." Nature (2023): 1-5.

Bring EchoMeasure™ to Your Lab

Considering the ever-growing demand for echocardiograms, cardiologists and sonographers often spend valuable time adjusting and creating measurements. These repetitive tasks require the consideration of numerous parameters, and multiple button clicks. A study indicated 90% of clinical sonographers experienced symptoms of WRMSDs Work-Related Musculoskeletal Disorders).^[5] To combat this, EchoMeasure™ can automate many of the standard linear and volumetric measurements of the heart ordinarily performed manually.

[5] Forecasting the Future of Cardiovascular Disease in the United States, AHAPolicy Statement, 2011, source: CIR.0b013e31820a55f5

EchoMeasure™ FDA-cleared measurements

The following measurements are currently available through EchoMeasure™ via the iCardio.ai API.

Parasternal Long Axis (PLAX)

Left Ventricular Diastolic Diameter (LVDd)

Left Ventricular Systolic Diameter (LVSd)

Right Ventricular Diastolic Diameter (RVDd)

Right Ventricular Systolic Diameter (RVSd)

Right Ventricular Outflow Tract Diameter (RVOTd)

Left Atrial Dimension (LAd)Posterior Wall Thickness (PWd)

Interventricular Septal Thickness (IVSd)

Left Ventricular Outflow Tract Diameter (LVOTd)

Diameter of the Aortic Annulus (AAd)

Left Atrial Dimension (LAd)

Posterior Wall Diameter of the Sinus of Valsalva (SoVd)

Diameter of the Sinotubular Junction (StJd)

Apical 4 Chamber (A4C)

Ejection Fraction (LVEF Simpson’s Biplane)

Left Ventricular Diastolic Area (LVDa)

Left Ventricular Systolic Area (LVSa)

Apical 2 Chamber (A4C)

Ejection Fraction (LVEF Simpson’s Biplane)

Left Ventricular Diastolic Area (LVDa)

Left Ventricular Systolic Area (LVSa)

Biplane (A4C + A2C)

Left Ventricular Ejection Fraction (Simpson’s method of discs)

510(k) cleared solution

breakthrough designation

iCardio.ai CardioVision™

iCardio.ai CardioVision™ is an FDA-cleared AI software indicated as a diagnostic aid to support the detection of Aortic Stenosis. Taking in a parasternal long axis (PLAX) clip, iCardio.ai CardioVision™ is used during a diagnostic workup to determine the likelihood of clinically significant aortic stenosis.

Internally studied performance of iCardio.ai CardioVision™

iCardio.ai CardioVision™ uses deep learning to predict aortic stenosis without explicitly measuring any variable, relying on deep learning. (Wessler, Benjamin S., et al. "Automated detection of aortic stenosis using machine learning." Journal of the American Society of Echocardiography 36.4 (2023): 411-420.)

Aortic stenosis (AS) is a progressive disease associated with important morbidity and mortality.^[1] Prior observational studies have demonstrated a significant decrease in survival with AS, especially when the aortic valve obstruction is deemed severe.^[2]Recently, observational data have suggested that untreated moderate AS is also associated with poor prognosis.^[3,4,5] Unfortunately, the only therapy available for treatment of aortic stenosis is a valve replacement.^[6]

[1] Généreux, Philippe, et al. “The mortality burden of untreated aortic stenosis.” Journal of the American College of Cardiology 82.22 (2023): 2101-2109.
[2] Otto C.M., Burwash I.G., Legget M.E., et al. “Prospective study of asymptomatic valvular aortic stenosis. Clinical, echocardiographic, and exercise predictors of outcome”. Circulation . 1997;95:2262-2270.
[3] Strange G., Stewart S., Celermajer D., et al. “Poor long-term survival in patients with moderate aortic stenosis”. JAm Coll Cardiol . 2019;74:1851-1863.
[4] Coisne A., Scotti A., Latib A., et al. “Impact of moderate aortic stenosis on long-term clinical outcomes: a systematic review and meta-analysis”. J Am Coll Cardiol Intv . 2022;15:1664-1674.
[5] Khan K.R., Khan O.A., Chen C., et al. “Impact of moderate aortic stenosis in patients with heart failure with reduced ejection fraction”. J Am Coll Cardiol . 2023;81:1235-1244.
[6]. Lindman, Brian R., et al. "Evaluating medical therapy for calcific aortic stenosis: JACC state-of-the-art review." Journal of the American College of Cardiology 78.23 (2021): 2354-2376.

Maximize revenue stream

With the national average reimbursement (MS-DRG 267/277) for aortic valve replacement exceeding $45,000, the unmet financial opportunity to address the eligible untreated aortic stenotic patient population is significant. An analysis of the literature suggests more than 50% of patients eligible for intervention are not treated, or about 105,000 persons, and the consequential hospital revenue generation potential exceeds $4 billion.^[7]

[7] Li, Shawn X., et al. “Trends in utilization of aortic valve replacement for severe aortic stenosis.” JACC 79.9 (2022)

Explore Partnerships with iCardio.ai

iCardio.ai Chamber Measurements

Automated Measurement of Right Ventricular Diameter, Interventricular Septum. Left Ventricular Diameter, and Posterior Wall.

Calculate left ventricular dimension, right ventricular dimension, wall dimenstions, at systolic, diastolic and mid points in the cardiac cycle in the PLAX perspectives.

rv: 2.2cm

ivs: 1.2cm

lvdd: 5.1cm

lvsd: 3.7cm

iCardio.ai Aortic Apparatus Measurements

This model extracts features of the aortic apparatus, including the Left Ventricular Outflow Tract, the Aortic Annulus, the Sinus of Valsalva and the Sinotubular Junction.

high fidelity in sub-par and moving conditions

View Classification and Grading

This model extracts features in real-time using a mobilenet model architecture. By providing labeled features of the heart, ultrasound novices can orient themselves around the heart.

classify over 30 b-mode perspectives

Performance and Data Science

All models undergo rigorous performance testing. In this example, we can visualize performance of the model's prediction over each frame of the cardiac cycle.

Discover tailored iCardio.ai services.

Anonymization Services

Securely de-identify your DICOM data to meet regulatory compliance and facilitate research. We help you unlock the value of your data while maintaining patient privacy.

Explore Anonymization

Custom Model Development

Collaborate with our AI experts to build bespoke echocardiography models tailored to your specific clinical and research objectives.

Explore Custom Model Development

Data Annotation and Curation

Transform raw data into AI-ready assets. Our specialized team of clinical experts can accurately label, segment, and validate large datasets of medical images and clips, essential for training and refining high-performance AI models.

Explore Data Annotation & Curation