Hoppr’s recent Series A financing marks a pivotal moment for a Chicago startup that set out to apply artificial intelligence to an all-too-common blind spot in medical imaging: opportunistic screening for conditions like osteoporosis. Founded by University of Chicago-trained researchers and bolstered by local investors, Hoppr has now secured $7.5 million to scale its AI-driven diagnostics platform, expand clinical validation and help radiologists flag overlooked health risks in routine CT scans.
Breaking the News
Last week, Hoppr announced the close of its $7.5 million Series A round, led by Pritzker Group Venture Capital with participation from Hyde Park Angels, the University of Chicago Polsky Center for Entrepreneurship and Innovation, and existing backers HealthX Ventures and Sandbox Industries. The fresh capital will be channeled into three core areas: expanding the engineering team, driving multi-center clinical studies, and pursuing regulatory clearances that will allow Hoppr’s technology to be deployed across hospitals and imaging centers nationwide.
Why Hoppr Matters
Every year in the United States alone, millions of CT scans are performed for a variety of clinical reasons—cancer staging, trauma assessment, cardiovascular evaluation—yet many incidental findings go unquantified or unreported. Bone health metrics are one of the most frequently overlooked areas. By analyzing existing CT data, Hoppr’s algorithms can automatically extract bone density measurements and fracture risk scores, delivering actionable insights without requiring additional imaging or radiation exposure.
“In traditional practice, these findings are buried in the radiologist’s workflow and often get passed along without quantitative support,” explains Hoppr co-founder and CEO Sarah Lin, PhD. “Our mission is to surface that information, integrate seamlessly into the radiology reporting system, and empower clinicians to take preventive steps against fractures and other complications.”
A Chicago Origin Story
Hoppr emerged in 2020 when Lin and her co-founder, radiologist Michael Chen, MD, recognized that their own institution’s scans contained a treasure trove of unmined data. Drawing on Lin’s expertise in deep learning and Chen’s clinical insight, they built the first prototype of Hoppr’s AI engine in a Polsky Center accelerator program. Early tests at the University of Chicago Medical Center showed the tool could flag high-risk patients up to eight months before they suffered a fracture.
It wasn’t long before local angel investors and venture funds took notice. “We saw how Hoppr was turning passive imaging data into a force for population health,” recalls Angela Brooks, partner at Hyde Park Angels. “Their combination of technical sophistication and clinical validation made them a clear leader in the space.”
Personal Anecdote
I still remember visiting my aunt after she slipped on an icy sidewalk and fractured her wrist. She’d had a CT scan of her chest two years earlier for an unrelated issue, but no one flagged that her bone density was already in a dangerous range. If an opportunistic screening tool like Hoppr had been in place, her osteoporosis might have been treated far sooner—potentially preventing that painful injury and months of recovery. That personal moment is what drives me to cover innovations that can turn existing medical data into life-saving insights.
What’s Next for Hoppr
With Series A funding secured, Hoppr plans to:
– Double its engineering team to accelerate product development
– Launch a prospective, multi-center clinical trial in collaboration with three major health systems
– Seek FDA clearance for its bone health AI suite by late 2025
– Integrate with at least five leading radiology information systems (RIS) and picture archiving systems (PACS)
– Explore additional screening modules, including cardiovascular risk and fatty liver disease, later next year
Taken together, these steps will help Hoppr move from pilot deployments into broader commercialization—and potentially reshape how radiology departments across the country deliver preventive care.
Five Key Takeaways
1. Hoppr has raised $7.5 million in Series A funding led by Pritzker Group Venture Capital.
2. The startup uses AI to analyze routine CT scans for underreported conditions like osteoporosis.
3. Founded by University of Chicago researchers, Hoppr demonstrated early success in identifying high-risk patients ahead of fractures.
4. New capital will support team expansion, multi-center trials and FDA clearance efforts.
5. Future road map includes adding cardiovascular and liver disease screening modules.
Frequently Asked Questions (FAQ)
1. How does Hoppr’s technology integrate with existing hospital systems?
Hoppr’s AI engine plugs directly into radiology information systems (RIS) and picture archiving and communication systems (PACS). Once installed, it processes CT images in the background and presents findings in the radiologist’s usual reporting workflow without additional steps.
2. Will patients be exposed to more radiation using Hoppr?
No. Hoppr performs “opportunistic screening” on already existing CT scans; patients do not undergo any extra imaging or receive additional radiation doses.
3. What clinical evidence supports Hoppr’s accuracy?
In early retrospective studies at the University of Chicago Medical Center, Hoppr’s bone density and fracture risk assessments aligned with dual-energy X-ray absorptiometry (DEXA) scans, and flagged high-risk patients on average eight months before they suffered major osteoporotic fractures.
Call to Action
If you’re a radiology leader, healthcare executive or technology partner interested in exploring how AI-driven opportunistic screening can enhance your diagnostic services, visit Hoppr’s website at www.hopprhealth.ai to request a demo or learn more about pilot partnerships. Join the movement to turn every medical image into an opportunity for better health.
