Ventripoint Diagnostics is supporting the newly forming Global Congenital Heart Disease Alliance, an industry initiative focused on accelerating the development, commercialisation and global adoption of technologies for congenital cardiovascular care.
As part of the alliance’s initial work, it will help fund and place four of Ventripoint’s VMS+ cardiac imaging units to support congenital heart disease assessment. The initiative is positioned around improving access to advanced imaging tools for patients who may not have consistent access to specialist cardiac imaging infrastructure.
This is relevant because congenital heart disease remains one of the most common and underserved lifelong cardiovascular conditions. According to the World Heart Federation’s World Heart Report 2026, congenital heart disease affects around 2 per cent of live births globally, with an estimated 16 million people living with the condition worldwide.
The care gap is especially significant in lower- and middle-income countries. The same report found that more than 90 per cent of children in these settings lack timely access to congenital heart disease care. Without early diagnosis, monitoring and intervention, children and adults with congenital heart disease may face avoidable complications, delayed treatment and poorer long-term outcomes.
Ventripoint’s VMS+ platform uses artificial intelligence to convert standard two-dimensional echocardiograms into three-dimensional models of all four heart chambers. The company positions the platform as capable of delivering cardiac MRI-level measurement accuracy at the point of care, using existing ultrasound infrastructure rather than requiring new scanning systems.
This differentiation is important in congenital heart disease because patients often have complex cardiac anatomy. Many have irregular chamber shapes, surgically altered structures or disease patterns that are difficult to assess using conventional linear measurements. A platform that can generate more complete three-dimensional chamber analysis from standard ultrasound images could help clinicians make more consistent assessments.
The technology may also help address access barriers linked to cardiac MRI. While MRI is an important tool for detailed cardiac assessment, it can be expensive, time-consuming and difficult to access in many health systems. In some cases, patients may also require travel to tertiary centres, sedation or longer waiting times. By extending advanced analysis through echocardiography, AI-supported imaging could help bring more detailed cardiac assessment closer to routine clinical workflows.
The VMS+ platform has regulatory clearances in the United States, Europe and Canada. In addition to congenital heart disease, Ventripoint has positioned the system for use in pulmonary hypertension and cardiotoxicity monitoring in oncology patients. These applications show how the same imaging platform may be used across conditions where accurate heart chamber assessment is clinically important.
The alliance model is also commercially relevant. For medtech companies addressing underserved disease areas, adoption often depends on more than device availability. It requires clinical champions, training, funding pathways, institutional partnerships and evidence that the technology can fit into real-world care delivery. The Global Congenital Heart Disease Alliance could provide a platform to coordinate these elements across markets.
However, adoption will still face practical barriers. AI imaging tools require trained operators, reliable ultrasound acquisition, local clinical capacity and pathways for follow-up care. In lower-resource settings, placing devices alone will not close the care gap unless health systems can also support diagnosis, referral, intervention and long-term monitoring.
Reimbursement and procurement may also shape uptake in higher-income markets. Hospitals will need to assess whether VMS+ improves workflow, measurement consistency, diagnostic confidence or patient outcomes compared with existing echocardiography and MRI pathways. Evidence generation will be important as AI-enabled imaging tools move from specialist use into broader cardiac care settings.
The development reflects a broader shift in medical imaging, where AI is increasingly being used to extend specialist-level analysis beyond major centres. For congenital heart disease, the long-term opportunity is not only faster or more detailed imaging, but more equitable lifelong monitoring for a patient population that often requires care from infancy into adulthood.
If the alliance can translate funding and technology placement into sustainable clinical use, it could offer a model for how AI imaging companies support underserved disease areas. The key measure will be whether these tools improve access, decision-making and continuity of care for congenital heart disease patients beyond the initial deployment stage.
