CEO Joseph DeVivo says 20% of serious-condition patients are first misdiagnosed, and point-of-care ultrasound can change that. The readthrough for traditional imaging players is direct.
Butterfly Network (BFLY) CEO Joseph DeVivo laid out a case for point-of-care ultrasound as a diagnostic default rather than a specialist referral, speaking at the Bank of America Global Healthcare Conference on May 12. The presentation framed the company’s semiconductor-based device as a direct challenge to the cost structure and physical footprint of traditional cart-based ultrasound systems. The readthrough for the broader medical imaging sector hinges on how quickly point-of-care adoption erodes the volume funnel that feeds hospital radiology departments.
DeVivo described Butterfly’s core technology as a single silicon chip that replaces the piezoelectric crystals found in conventional ultrasound probes. “We are a semiconductor-based ultrasound device. So that semiconductor acts very much like a TV screen where we are able to program it to deliver all different types of sound dynamically,” he said. That programmability means one probe can perform multiple imaging modes–cardiac, abdominal, vascular–without swapping hardware. For competitors still selling dedicated probes for each application, the cost and convenience gap widens with every software update.
Semiconductor fabrication benefits from the same Moore’s Law dynamics that drive down cost in consumer electronics. Butterfly’s bill of materials shrinks over time, while traditional ultrasound makers face a floor set by precision-machined piezoelectric elements. The unit economics allow Butterfly to target price points below $3,000, compared with $20,000 to $100,000 for cart-based systems. That price delta is the mechanism that opens the addressable market beyond hospitals into primary care clinics, ambulances, and eventually home care.
The programmable chip also turns the device into a platform for AI-assisted image interpretation. DeVivo did not detail AI features in this presentation, however the architecture inherently supports it. Competitors with fixed-hardware probes must add AI at the system level, often requiring a separate cart or cloud connection. Butterfly’s integrated approach could compress the time from image capture to clinical decision, a metric that matters in emergency and rural settings.
DeVivo cited a statistic that frames the clinical argument: “About 20% of patients with serious conditions are first misdiagnosed. About 80% of diagnostic dilemmas can be solved with simple imaging.” When that imaging happens at the first point of contact–the primary care chair, the urgent care bay, the paramedic’s hands–the downstream demand for formal radiology studies may decline for a subset of cases. Hospitals that rely on imaging revenue to subsidize other service lines face a volume headwind if point-of-care ultrasound becomes standard for initial triage.
In the current model, a primary care physician who suspects a gallstone or pleural effusion refers the patient to a hospital imaging center. That referral generates a radiology consult, a facility fee, and often a follow-up visit. Point-of-care ultrasound short-circuits that sequence: the physician images the patient during the same visit, makes a diagnosis, and initiates treatment. For health systems paid on fee-for-service, that is a revenue loss. For capitated systems and value-based care models, it is a cost saving. The tension between these reimbursement models will determine adoption speed.
Large imaging companies have not ignored handheld ultrasound. They have launched portable devices, however most still rely on piezoelectric technology and carry price tags well above Butterfly’s. The real competitive threat is not the existence of a handheld device but the combination of semiconductor economics, software-defined imaging, and a direct sales model that bypasses the capital equipment purchasing cycle. Incumbents that depend on razor-and-blade models–selling the system at a discount and making margin on proprietary probes–face a structural challenge from a single-probe, software-updatable alternative.
DeVivo pointed to a stark statistic: “About 2/3 of the world doesn’t have access to medical imaging.” That is not a niche; it is roughly 5 billion people. The traditional response–building more hospitals and installing more $100,000 ultrasound machines–is capital-intensive and slow. A sub-$3,000 device that connects to a smartphone changes the deployment math. Midwives in sub-Saharan Africa, rural clinicians in India, and community health workers in Southeast Asia become potential users. The addressable market expands from the installed base of hospital radiology departments to the global healthcare workforce.
The global opportunity is not frictionless. Each country has its own medical device registration requirements, and many restrict who can perform and interpret ultrasound. Butterfly will need to navigate those regulatory pathways country by country. Training is another bottleneck: putting a device in a clinician’s hand does not guarantee diagnostic accuracy. Butterfly has invested in education and software guidance, however the pace of adoption in low-resource settings will depend on partnerships with governments and NGOs that can fund training programs.
Point-of-care ultrasound fits into the broader telemedicine stack. A remote clinician can guide a patient or a community health worker through an image acquisition, then interpret the images from a distance. That model gained traction during the COVID-19 pandemic and is now being codified into reimbursement policies in several markets. Butterfly’s device, which streams images to a paired phone or tablet, is purpose-built for that workflow. Companies in the telehealth platform space–those providing the software layer for remote consultations–stand to benefit from a growing library of point-of-care imaging data.
The shift from cart-based to handheld ultrasound rewires the supply chain. Traditional ultrasound systems require a network of distributors, service contracts, and probe replacement cycles. Butterfly’s direct-to-consumer and direct-to-clinic model compresses that chain. The readthrough for distributors of capital imaging equipment is negative if the handheld segment grows faster than the cart segment declines. For component suppliers, the shift from piezoelectric materials to semiconductor wafers redirects demand toward chip foundries and away from specialized crystal manufacturers.
Key insight: The semiconductor architecture turns ultrasound from a capital equipment purchase into a consumable-like device, with upgrade cycles tied to software releases rather than hardware depreciation schedules.
Hospitals typically replace ultrasound systems on a 7- to 10-year cycle, budgeting for six-figure outlays. A handheld device that costs less than the annual service contract on a cart system changes the procurement conversation. Department heads can buy multiple units out of operating budgets without triggering the capital approval process. That shifts purchasing power from centralized procurement to individual clinicians and department chairs, a dynamic that favors vendors with strong brand recognition among end users rather than those with deep relationships in the C-suite.
Every Butterfly scan generates data that can train AI models. Butterfly has stated ambitions to build automated interpretation tools. The immediate readthrough is that the device’s installed base becomes a data-generation engine. Competitors with smaller fleets of internet-connected devices will struggle to match the training data volume. This dynamic mirrors the data network effects seen in other tech-enabled hardware markets, however it is underappreciated in medtech valuation frameworks.
For point-of-care ultrasound to move from early adoption to standard of care, professional societies must include it in clinical guidelines, and payers must reimburse for its use outside radiology. DeVivo did not provide a timeline, however the presentation implied that the clinical evidence base is building. The next concrete catalyst for the sector will be a major guideline update–for example, from the American College of Cardiology or the American College of Emergency Physicians–that explicitly recommends point-of-care ultrasound as a first-line imaging tool for specific indications. When that happens, the volume shift from radiology suites to exam rooms accelerates.
The Bank of America conference appearance served as a reminder that point-of-care ultrasound is no longer a curiosity. It is a category with a growing evidence base, a semiconductor cost curve, and a global unmet need that traditional imaging infrastructure cannot address. The sector readthrough extends to every company that derives revenue from hospital-based imaging volumes, sells capital equipment into radiology departments, or supplies components to legacy ultrasound manufacturers. The speed of the shift remains uncertain. The direction is not. The presentation followed a similarly upbeat structural heart growth update from Edwards Lifesciences at the same conference, underscoring a broader medtech theme: procedure volumes and diagnostic tools are migrating out of the hospital and into lower-cost, higher-access settings.
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