Reporting Pro Explained: What It Changes

Reporting Pro is DeepHealth's generative-AI radiology reporting tool that drafts a structured report — findings and impressions included — before a radiologist even opens the case. Announced June 10, 2026, it folds speech recognition, AI-generated findings, measurements, AI-generated impressions, quality assurance, and structured reporting into a single workflow that plugs into existing imaging systems. This page is the plain-English explainer for the term: what it is, how it works, why it shipped now, who built it, and where the honest limits are.

If you operate a healthcare practice and want the implications read rather than the explainer, jump to our companion piece, what Reporting Pro means for healthcare practices. Otherwise, start here.

TL;DR

• What it is: a generative-AI radiology reporting product that auto-drafts a structured report, including findings and impressions, from the imaging study.

• Who shipped it: DeepHealth, a wholly owned subsidiary of RadNet, Inc. (NASDAQ: RDNT), per GlobeNewswire.

• When: introduced at RSNA 2025 and commercially available as of June 10, 2026, per GlobeNewswire.

• Where: the United States and United Kingdom now, with planned expansion to Australia, South Africa, and select European markets by year-end 2026.

• Why now: a worsening radiologist shortage colliding with rising imaging volume.

What happened

On June 10, 2026, DeepHealth announced commercial availability of Reporting Pro. According to AuntMinnie, the product unifies "speech recognition, AI-generated clinical findings and measurements, AI-generated impressions, quality assurance, and structured reporting" — collapsing what were previously 4 separate workflow steps into one. The pitch is not another point tool bolted onto a reading workstation; it is one workflow that takes a radiologist from open-the-case to signed-report with the draft already populated.

According to GlobeNewswire, Reporting Pro "is designed to integrate with any existing picture archiving and communication system (PACS) and radiology information system (RIS)" and supports 5 imaging modalities — X-ray, ultrasound, CT, PET/CT, and MRI. That cross-modality, vendor-neutral posture is the part that makes it a buyer's product rather than a captive feature of one PACS.

Sources: GlobeNewswire; AuntMinnie.

The mechanism, in plain language

A radiology report has two parts that matter to a referring physician: the findings (what the radiologist observed) and the impression (what it means). Producing them by hand — dictating, transcribing, formatting into a structured template — is the slow, repetitive core of the job. Reporting Pro inverts the order. The AI drafts both sections from the study first, so the radiologist's job shifts from authoring a blank page to verifying, correcting, and signing a draft.

According to GlobeNewswire, RadNet radiologist and medical director Dr. Jason Sinner — one of over 11,000 team members across the RadNet network — described the experience this way: "With Reporting Pro, a structured report is already waiting when I open a case with findings populated." That single sentence captures the mechanism: the draft is waiting, not requested.

Mechanically, the workflow chains 4 steps that used to live in separate tools — speech recognition for any radiologist edits, AI generation of findings and measurements, AI generation of the impression, and a QA layer that checks the structured output. According to AuntMinnie, it works alongside the DeepHealth Diagnostic Suite — covering 4 functions across image management, AI findings, workflow orchestration, and reporting — for "more efficient case routing, prioritization, and review." The radiologist remains the signer; the AI removes the blank-page tax.

The cleanest way to see what changed is to compare the report-authoring steps before and after. The diagnosis stays with the human; the writing shifts to draft-then-verify.

Sources: AuntMinnie; GlobeNewswire.

The unification is the differentiator. Plenty of products do 1 of these steps — a separate dictation engine here, a measurement assistant there. Reporting Pro's claim is that all 4 steps live in one workflow, so the radiologist is not toggling between tools to assemble a report. According to AuntMinnie, it also enables migration of existing templates and reporting preferences from legacy systems, which lowers the switching cost that usually kills reporting-tool adoption.

Why now: the constraint that broke

The reason a draft-first reporting tool ships in 2026 and not 2016 is that the gap between imaging demand and radiologist supply has become structural. Two forces converged: imaging volume keeps climbing while the workforce cannot keep pace.

According to GlobeNewswire, the US radiologist shortage is projected at 15% by 2029, with some European countries facing a shortage of roughly 40% by 2030. The workload side is just as stark. According to Radiology News, imaging needs are projected to increase by up to 26.9% over the next three decades while the radiology workforce is projected to grow only 25.7% in the same period — and that gap widens because demand skews toward an aging population. According to the same source, people 65 and older account for "roughly 30% of annual imaging utilization."

There is also a hidden tax inside the workday. According to Radiology News, radiologists spend nearly 44% of their day on non-interpretive tasks — the documentation, formatting, and administrative work that draft-first reporting is built to absorb. When the scarce resource is interpretation time, automating the writing around it is the obvious lever.

The aging-population dynamic deepens the squeeze. Older patients need more imaging, and the demographic curve is moving the wrong way for supply. According to Radiology News, by 2030 roughly 20% of Americans — about 70 million people — will be 65 or older, and that group already accounts for roughly 30% of annual imaging utilization. So the demand growth is not abstract; it is structural and demographic, which is precisely the kind of pressure that makes a tool reclaiming documentation time go from nice-to-have to operationally necessary.

This is why the generative-AI moment in radiology arrived as a reporting product rather than a reading product. Autonomous interpretation is regulated, liability-heavy, and slow to clear. Drafting the report — with a human verifying and signing — sidesteps that barrier while still attacking the biggest time sink. The constraint that broke was not diagnostic accuracy; it was the recognition that the writing, not the seeing, is where the recoverable hours live.

Sources: GlobeNewswire; Radiology News.

Who shipped it

DeepHealth is the digital-health umbrella brand of RadNet, the publicly traded imaging operator (NASDAQ: RDNT), according to GlobeNewswire, which notes RadNet operates with over 11,000 team members including radiologists, technologists, and staff. That parentage matters for two reasons. First, RadNet runs imaging at scale, so Reporting Pro was validated on a large internal network before external sale — according to AuntMinnie, it "has been deployed and validated across RadNet." Second, a vendor that operates imaging centers builds reporting tools differently than a pure software vendor — closer to the workflow pain.

The product also slots into a broader suite. According to AuntMinnie, Reporting Pro works in combination with the DeepHealth Diagnostic Suite — which covers 4 functions: image management, AI findings, workflow orchestration, and reporting — meaning a buyer can adopt reporting alone or as part of an end-to-end stack.

A short timeline puts the launch in context. The product was not rushed to market; it was previewed, validated internally, then released for sale, with international expansion mapped out.

Sources: GlobeNewswire; AuntMinnie.

That cadence — RSNA 2025 preview, June 2026 launch, next-quarter external deployments — is the pattern of a vendor that operates the workflow it is selling. According to GlobeNewswire, the product is "currently deploying across RadNet at scale" across a network of over 11,000 team members, which means external buyers are not the first users. For a category where trust is the gating factor, being battle-tested on the vendor's own reading volume before sale is a meaningful signal.

The honest limits

A few things this is not, to keep expectations grounded. It is not autonomous reading: the radiologist verifies and signs every report. The published material does not quantify accuracy, time saved, or error rates for Reporting Pro specifically — neither GlobeNewswire nor AuntMinnie cites a specific productivity percentage for Reporting Pro, so any specific time-savings claim you see elsewhere should be treated cautiously until validated in your own setting. The ~44% of the workday spent on non-interpretive tasks, per Radiology News, sets the ceiling for any draft-first tool — realistic savings are some fraction of that, not all of it.

It is also early in external rollout. According to GlobeNewswire, the product is "currently deploying across RadNet at scale, with initial external customer deployments launching within the following quarter" — a rollout phased across 4 markets planned by end of 2026 (US, UK, Australia, South Africa). Generative drafting also carries the usual caveat — AI-drafted findings can be wrong, which is exactly why the QA layer and the human signer are part of the design, not optional add-ons.

A practical limit worth naming: the benefit is uneven across modalities and study types. A draft for a routine chest X-ray and a draft for a complex multi-phase oncologic CT are not equally easy to produce well, and a practice's real return depends on its case mix. The launch material describes support across 5 modalities — X-ray, ultrasound, CT, PET/CT, and MRI — per AuntMinnie, but breadth of support is not the same as uniform quality, and buyers should expect to validate per study type rather than in aggregate.

Finally, adoption is a change-management problem, not just a procurement one. Radiologists are signing legal documents; their willingness to trust and lightly edit a draft — rather than rewrite it — determines whether any time is actually saved. The demand for AI in this area is strong: according to Radiology News, 57% of physicians identify administrative burden reduction as AI's greatest opportunity, and 98% of radiology respondents believe teleradiology and AI-assisted workflow tools are beneficial. That trust is earned through a pilot with measured edit rates, not assumed. The technology being commercially available, as it is per GlobeNewswire, is the easy half; the operational half is making it a habit clinicians accept.

Where this fits the wider automation picture

Reporting Pro is one instance of a broader pattern: the document-generation step inside a regulated workflow being handed to AI, with humans moving to review-and-approve. The same shape shows up in claims, intake, referrals, and authorizations across healthcare. Practices already routing documents through US Tech Automations workflows will treat a tool like this as a model swap inside an existing review pipeline, not a rebuild — the human approval gate is already there.

That is the strategic read for operators: the value is not only the model that drafts the report but the surrounding orchestration that routes work, holds the human sign-off, and writes the signed output back to the systems of record. Teams that have built that orchestration with US Tech Automations adopt new drafting models faster because the pipeline is already in place.

It is worth being precise about what is genuinely new here versus what is familiar. Voice dictation and structured templates have been in radiology for two decades; what changed is that the content of the report — the findings and the impression — is now drafted by AI rather than authored from a blank page. The orchestration around it (route the study, populate the draft, run QA, sign, distribute) is the same shape practices already use for other regulated documents. That familiarity is exactly why a draft-first reporting tool can spread quickly: it is a swap inside an established workflow, not a new category of system a practice has never run before. The honest caveat is that a model swap changes the risk profile — an AI that drafts clinical findings raises the stakes of the verification step in a way a dictation engine never did, which is why the QA layer and human signer are load-bearing parts of the design rather than conveniences.

Signal vs Speculation

Signal (demonstrated fact). Reporting Pro launched June 10, 2026; it auto-drafts findings and impressions, integrates with any PACS/RIS, and supports all major modalities, per GlobeNewswire and AuntMinnie. The shortage and workload pressures driving it are real: a 15% US shortage by 2029 per GlobeNewswire and ~44% of the day on non-interpretive tasks per Radiology News.

Our read (forecast). If draft-first reporting holds up under real reading loads, expect it to become the default expectation for radiology workstations within 12 to 36 months, the way structured templates and voice dictation did before it. Our read: for small and mid-size imaging centers, the winners will be those who treat the report draft as one node in an automated pipeline — routing, QA, sign-off, and write-back — rather than a standalone gadget. The likely friction is validation and liability: until each practice measures accuracy on its own case mix, adoption will be gated by trust, not technology. The vendor-neutral PACS/RIS integration is the tell that DeepHealth is aiming to be infrastructure, not a feature, and infrastructure is where durable value sits.

Key Takeaways

• Reporting Pro auto-drafts findings and impressions before the radiologist opens the case, per GlobeNewswire — the radiologist verifies and signs rather than authoring from scratch.

• It is vendor-neutral, integrating with any PACS/RIS and supporting X-ray, ultrasound, CT, PET/CT, and MRI, per AuntMinnie.

• It shipped because the math is breaking: a 15% US radiologist shortage projected by 2029, per GlobeNewswire, against rising imaging demand.

• The published sources do not quantify Reporting Pro's time savings, so treat specific productivity numbers as unvalidated until tested locally.

• The strategic value is the orchestration around the draft — routing, QA, sign-off, write-back — not the draft alone.

Frequently Asked Questions

What is Reporting Pro?

Reporting Pro is DeepHealth's generative-AI radiology reporting tool that auto-drafts a structured report with findings and impressions, launched June 10, 2026, according to GlobeNewswire.

Does Reporting Pro replace radiologists?

No. It drafts the report, but the radiologist verifies, corrects, and signs it. According to AuntMinnie, it unifies all 4 components — findings, impressions, QA, and structured reporting — with the clinician in the loop for final sign-off.

What systems does it work with?

It is designed to integrate with any PACS and RIS and supports X-ray, ultrasound, CT, PET/CT, and MRI, according to GlobeNewswire.

Where can I get it?

It is commercially available in the US and UK as of June 10, 2026, with planned expansion to Australia, South Africa, and select European markets by year-end 2026, according to GlobeNewswire.

Why is this launching now?

Because supply cannot meet demand: the US faces a 15% radiologist shortage by 2029 per GlobeNewswire, and radiologists spend nearly 44% of the day on non-interpretive tasks per Radiology News.

How accurate is it?

The public sources do not publish accuracy or time-savings figures for Reporting Pro, so accuracy should be validated on a practice's own case mix. The design keeps a QA layer and a human signer for exactly this reason.

Where to go next

Reporting Pro is a clear marker of where regulated document workflows are heading — AI drafts, humans approve. If you want to understand the implications for your own operation, read what Reporting Pro means for healthcare practices, or see how US Tech Automations builds agentic workflows that hold the human sign-off step around any AI drafting model.

Freshness note: current as of June 2026, reflecting the June 10, 2026 Reporting Pro launch.