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Problem Tech Solves
Tech Brief
Ultrasound technology is safe and highly effective, but it requires a high degree of human expertise. Most marketed software packages fail to ease the technical burden, lacking instructions on how to move the ultrasound transducer or any real-time feedback on the quality of images. Poor quality images can lead to misdiagnosis, repeat studies, and inconsistent interpretation. Because the exam itself requires unnatural hand-eye coordination and unintuitive visuals, sonographers must go through years of training to perform competent exams. Even healthcare professionals with prior experience have difficulty obtaining the best image quality. As heart disease rates continue to climb, the rising demand for skilled sonographers has contributed to a nationwide shortage, effectively siloing expertise in hospitals. Caption Health is addressing this need with an AI trained on the techniques of skilled sonographers, enabling a broader set of clinicians to capture diagnostic images. Because the software is available on handheld units like the Butterfly iQ+, care providers can perform heart ultrasounds anywhere. This go-anywhere ultrasound is changing the approach to heart disease. When at-risk patients can get a screening that includes cardiac ultrasound at a community center, a doctor’s office or even their home, disease can be detected early enough to design a course of treatment that changes outcomes.
Tech Differentiators
Caption AI is the only AI-guided heart ultrasound software on the market, and has received both 510(k) clearances from the FDA and a European CE Mark. It can take ultrasound where no one else can bring it, empowering heart failure detection anywhere. Caption has also partnered with Heartbeat Health to offer virtual cardiologist reads for images gathered by Caption’s AI, expanding access to quality cardiovascular care wherever a patient may be. The need is great. Heart failure kills hundreds of thousands of Americans every year and rising, due in part to our aging population. COVID-19 may cause the disease burden to spike further. With early detection and intervention, many of these deaths are preventable. Caption Health is dedicated to improving access to quality early heart care, everywhere. Our mission is to leverage this cutting-edge technology to improve heart health everywhere, through affordable early disease detection – when there is the highest potential for impact. We will continue to grow our Caption Care service, and partner with key players, to enable us to address issues around access to heart health care in the U.S. and globally. As Caption Health looks to the future, we are reaching beyond cardiac health to look at broader applications for our AI technology. Work has already begun on developing the capabilities for AI-guided lung ultrasounds through work with the Bill & Melinda Gates Foundation, and we are exploring other disease conditions where early diagnosis is an obstacle to improved care.
Validation
In a study published last year in JAMA Cardiology, 8 nurses without prior ultrasonography experience used Caption AI to scan 240 patients with a 10-view echocardiographic protocol. This study served as the basis for Caption Health’s landmark FDA De Novo authorization and subsequent 510(k) clearance for Caption Guidance. [Narang A et al., “Utility of a Deep-Learning Algorithm to Guide Novices to Acquire Echocardiograms for Limited Diagnostic Use” JAMA Cardiol. (2021)] Caption’s interpretation software was used to automatically evaluate left ventricular (LV) ejection fraction and detect LV dysfunction in 233 patients across 2 protocols, with accuracy similar to that of visual interpretation by experienced imaging cardiologists. [Asch, F. et al. “Quantification of Left Ventricular Ejection Fraction: A Point-of-Care Solution.” Circulation: Cardiovascular Imaging. (2021)] Physicians from Northwestern Medicine present 5 real-world case studies detailing Caption AI use to address the acute cardiac impact of COVID-19 in the ICU, providing a valuable insight into the potentials of AI-enabled tools in clinical medicine. [Raina, S. et al. “AI-Powered Navigation System for Steering POCUS in the COVID-ICU.” JACC Case Rep. (2021)]
