Impressions | 14th Edition

Campbell Arnold
May 13
4 min read

Updated: May 19

Welcome to RadAccess: Impressions—your quick-read companion to the main RadAccess newsletter. Like a radiology report's impressions section, we only deliver the essential information to respect your time. For more details, you can always turn to the full RadAccess newsletter.

In this issue, we cover:

Chipiron Raises $17M to Reinvent MRI for the Frontlines
LowGAN: Generating High-Quality Images from Low-Field MRI
Function Health Acquires Ezra, Offers $499 Full-Body MRI Scans
Health Tech Investment Act Introduced in Congress

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Chipiron Raises $17M to Reinvent MRI for the Frontlines

And how their technology differs from other low-field scanners.

Chipiron, a Paris-based startup, has raised $17 million in Series A funding to develop an ultra-low-field MRI system designed for point-of-care use in settings like ICUs, operating rooms, ambulances, and remote clinics. Unlike most recent low-field MRI systems that operate at 50–100 mT using heavy permanent magnets, Chipiron is targeting sub-10 mT fields with lightweight resistive magnets, enabling flexible designs that fit into constrained environments. The company believes previous low-field systems failed due to rigid product design and sees ultra-low-field imaging as key to expanding MRI access for routine and frontline care. With funding in hand, Chipiron plans to begin clinical deployment in the EU in 2025, pursue in-human studies, grow their team, and initiate FDA filings in 2026.

LowGAN: Generating High-Quality Images from Low-Field MRI

Using AI to bridge the field strength gap & expand access to diagnostic imaging.

I'm excited to share a recent Radiology publication I co-authored with my University of Pennsylvania colleagues where we present LowGAN, an AI-based image enhancement method to improve low-field MRI scans from the Hyperfine portable system. In the study, we used paired 64mT and 3T brain scans of MS patients to train a GAN that generates 3T-like images from low-field data. The enhanced images were more similar to high-field scans, improved brain volume measurement accuracy, and made white matter lesions more visible—though lesions not captured in the original scans remained undetected. This work highlights both the potential and the limitations of AI in increasing the clinical utility of portable, low-cost MRI and expanding access to high-quality neuroimaging.

Function Health Acquires Ezra, Offers $499 Full-Body MRI Scans

And what consolidation means for the preventive healthcare care space.

Function Health, known for its blood diagnostics platform, has acquired full-body MRI startup Ezra in a bold move to create an integrated preventive screening service that combines imaging and lab diagnostics. Alongside the acquisition, Function dramatically reduced the price of Ezra’s MRI scans to $499—far below other competitors. The company hopes this low-cost offering will attract new users, who will convert into long-term subscribers for ongoing health monitoring. While the aggressive pricing strategy raises questions about long-term sustainability, it reflects a broader trend of AI-driven efficiency transforming full-body MRI from a luxury service into a potential cornerstone of mainstream preventive care.

Health Tech Investment Act Introduced in Congress

And what that means for Radiology AI.

The Health Tech Investment Act, a bipartisan bill recently introduced in Congress, aims to create a clearer, more sustainable reimbursement pathway for FDA-approved AI-enabled medical devices. Currently, companies rely on a patchwork of temporary codes with no long-term coverage guarantees. The bill proposes assigning all new devices a Category III code and New Technology payment status, allowing structured reimbursement and cost data collection over five years. Meanwhile, companies like MRIguidance and Icometrix aren't waiting around and have already secured Medicare and CPT codes, signaling growing momentum for radiology AI reimbursement. This legislation could be pivotal for AI tools that improve care but lack a clear financial ROI.

Resource Highlight: Pranav Rajpurkar

Follow Pranav Rajpurkar (LinkedIn, X), Assistant Professor of Radiology at Harvard and co-founder of a2z Radiology AI. In just the past few weeks, his team released three major datasets: ReXGradient-160K, ReXErr-v1, and Collab-CXR.

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References

Disclaimer: There are no paid sponsors of this content. The opinions expressed are solely those of the newsletter authors, and do not necessarily reflect those of referenced works or companies.