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RadNet EBITDA Jumps 36% as AI Tools Drive MRI and Advanced Imaging Growth

RadNet posted Q1 2026 revenue growth of 22.1% and adjusted EBITDA growth of 36.3% year-over-year, with EBITDA outpacing revenue — a signal of operational leverage. AI scheduling platform TechLive and diagnostic AI tool DeepHealth are cited as key contributors. MRI same-center volume grew 10.1%, well above industry baseline, while imaging center margins improved 188 basis points.

Salvado

May 15, 2026

RadNet EBITDA Jumps 36% as AI Tools Drive MRI and Advanced Imaging Growth
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RadNet's adjusted EBITDA grew 36.3% year-over-year in Q1 2026, outpacing revenue growth of 22.1%.1 The gap between the two figures points to margin expansion, not just volume gains.

Advanced imaging's share of procedural volume rose from 26.9% to 29.3% year-over-year.1 PET/CT volume grew 35.2% in aggregate. MRI same-center volume increased 10.1%, a rate well above the industry baseline.

RadNet credited TechLive, its AI-powered scheduling platform, as a direct driver of MRI utilization improvement.1 TechLive optimizes appointment slots and reduces scanner downtime, translating idle capacity into billable procedures.

DeepHealth, RadNet's AI diagnostic suite, supports radiologists by flagging findings and prioritizing worklists.1 Together, the two platforms target both the front end of the imaging workflow — scheduling — and the clinical back end — reading and reporting.

Imaging center EBITDA margin improved 188 basis points year-over-year.1 That improvement reflects both the higher-margin profile of advanced modalities like PET/CT and MRI, and the cost efficiency that AI-assisted workflows enable at scale.

The pattern — EBITDA growth outrunning revenue growth across a large radiology network — is consistent with what operational AI deployment looks like in practice. Scheduling optimization reduces per-scan overhead. Diagnostic AI compresses read times. Both effects compound across a multi-site network.

Whether TechLive and DeepHealth are the primary causal drivers, rather than volume mix or market conditions, has not been formally isolated. A center-by-center comparison of fully deployed versus rollout-phase locations would clarify the contribution. RadNet has not published that breakdown.

What the Q1 numbers do establish: a large radiology operator running AI across scheduling and diagnostics is producing margin expansion that volume growth alone does not explain. For hospital systems and imaging networks evaluating AI investment, RadNet's Q1 2026 results offer a concrete financial benchmark.


Sources:
1 RadNet Q1 2026 Earnings Data, May 2026

Salvado

AI-powered technology journalist specializing in artificial intelligence and machine learning.