Vesta Teleradiology | Jennifer Nguyen

Radiology AI in 2026: From “Cool Tools” to Governance, Workflow & Quality

In 2026, the radiology AI conversation is shifting from “Which algorithm is best?” to “How do we run AI in production without creating new risks or new bottlenecks?” Hospitals and imaging leaders are under pressure to improve turnaround times, reduce backlogs, and keep quality consistent—yet everyone knows that technology layered onto an already complex workflow can backfire if it isn’t governed properly.

The most successful AI programs aren’t defined by a single tool. They’re defined by governance, interoperability, and measurable performance—and by a workflow design that supports radiologists rather than fragmenting their attention.

Why AI success looks different in 2026

Early AI adoption often focused on point solutions: a triage tool here, a detection aid there. Today, organizations want outcomes: faster reads, fewer misses, more consistent reporting, and fewer operational disruptions. That’s why governance is taking center stage. The American College of Radiology (ACR) has emphasized the need for formal AI governance and oversight structures to keep patient safety and reliability at the forefront.

At the same time, the industry is pushing hard on interoperability—making sure AI tools integrate into PACS/RIS and clinical communication rather than living in “yet another dashboard.” RSNA has showcased how workflow integration and standards can reduce friction points and help AI support real clinical scenarios.

The 2026 AI governance checklist (simple, practical, usable)

Whether you’re adopting your first tool or scaling across modalities, governance doesn’t need to be complicated—but it does need to be real. A strong governance model typically includes:

1) Clear clinical ownership

AI cannot be “owned by IT.” Radiology leaders should define:

Where AI is allowed to influence priority or interpretation
When radiologists can override AI outputs (and how overrides are documented)
What happens when AI and clinical suspicion conflict

2) Validation before scale

Before broad rollout, validate performance in your setting:

Scanner/protocol differences
Patient population differences
Volume and study mix differences

Even a great algorithm can underperform when protocols change or volumes surge.

3) Ongoing monitoring for drift

AI isn’t “install and forget.” Real-world performance changes over time—new scanners, new protocols, and shifting patient demographics can all cause drift. That’s why long-term monitoring is a growing focus in radiology AI standards efforts. For example, ACR has discussed practice parameters and programs aimed at integrating AI safely into clinical practice.

4) Operational metrics that matter

Track the metrics your hospital actually feels:

ED and inpatient turnaround time (TAT)
Backlog hours by modality
Discrepancy rates and peer-review signals
Percentage of cases escalated via triage
Radiologist interruption load (alerts, worklist reshuffles)

If AI improves one metric by harming another, it’s not a net win.

Where Vesta fits: AI + subspecialty reads + QA

For many hospitals, the most practical 2026 strategy isn’t “AI replaces humans.” It’s AI improves routing and prioritization, while subspecialty radiologists deliver the interpretation quality that clinical teams depend on.

A common best-practice workflow looks like this:

AI supports triage and worklist prioritization (especially for time-sensitive pathways)
Subspecialty radiologists provide consistent, high-confidence reads
QA processes (peer review, discrepancy tracking, feedback loops) ensure reliability over time

That combination is how you get the real goal: speed and confidence together—not speed at the expense of quality.

What to do next

If you’re building or refining an AI program in 2026, start with your workflow map—then add tools where they reduce friction. And make sure governance is designed before adoption accelerates.

If your team needs scalable subspecialty coverage to support operational goals (nights/weekends, overflow, or targeted service lines), Vesta Teleradiology can help you build a coverage model that keeps reads moving without sacrificing consistency. Learn more at https://vestarad.com.

CY 2026 Physician Fee Schedule: What Imaging Leaders Should Watch (and Why “Average” Doesn’t Apply)

Every year, the Medicare Physician Fee Schedule (PFS) creates ripple effects across imaging—often in ways that don’t show up in headlines. In late 2025, CMS released the CY 2026 PFS final rule, effective January 1, 2026.

Here’s the most important operational truth for radiology leaders in 2026:

The revenue impact isn’t uniform—so “average change” isn’t actionable

Even if the overall conversion factor movement looks modest, imaging departments don’t bill an “average” service. You bill your mix of modalities, your setting, your patient population, and your staffing model.

That’s why the right response to the 2026 PFS is not a quick budget adjustment—it’s a targeted modeling exercise.

What to model first (a simple sequence that works)

Instead of trying to interpret every line of the rule at once, start by modeling what can materially impact decisions:

1) Modality mix

Break your radiology work into buckets that align with how your service lines actually function:

CT
MR
X-ray
Ultrasound
Nuclear Medicine / PET
Interventional (if applicable)

Then estimate the revenue shift by bucket based on your billed codes and volumes.

2) Code mix inside each modality

Within CT or MR, the mix matters:

ED-heavy vs outpatient-heavy patterns
Trauma and stroke volumes vs routine follow-ups
High-complexity oncology imaging vs general imaging

Small per-code shifts can become meaningful if a code represents a high-volume pathway.

3) Setting and coverage realities

Your operational plan should reflect how studies arrive and when they must be read:

ED surges
Nights/weekends
Seasonal peaks
Staff vacation coverage

If you model reimbursement without modeling coverage demands, you risk cutting resources that protect throughput and clinician satisfaction.

Why the conversion factor is only the starting point

The PFS conversion factor tends to get the most attention, but radiology leaders often feel the downstream effects through:

Service line prioritization (what gets resourced vs delayed)
Pressure to improve productivity and reduce “avoidable” repeats
Coverage decisions (especially after-hours)
Subspecialty availability (which can impact quality and clinician confidence)

Professional societies also track conversion-factor details and implementation considerations for specialties impacted by the rule.

A practical 2026 strategy: protect throughput, not just budget

A department that protects patient flow and ED throughput often becomes more valuable—even in tight reimbursement environments. Three operational levers tend to produce outsized returns:

1) Standardize protocols where possible

Reducing variation can lower repeat imaging and improve consistency.

2) Reduce time-to-read friction

Worklist management, routing, and coverage planning can take pressure off your core team.

3) Ensure subspecialty access when it matters

Oncology, neuro, MSK, and complex body imaging are often the studies that drive high clinical impact—and the highest risk when resources are stretched.

Where Vesta helps

If your 2026 modeling shows that coverage needs to be more flexible—without compromising quality—Vesta Teleradiology can help you stabilize operations with scalable subspecialty interpretation for overflow, after-hours, or targeted service lines.

If you want to pressure-test your coverage model against your real modality and code mix, visit https://vestarad.com.

The Radiologist Shortage in 2026: Coverage Models That Actually Work

By 2026, many imaging leaders have reached the same conclusion: the answer to workforce pressure isn’t simply “hire harder.” Demand remains high, burnout is real, and subspecialty gaps can be difficult (or impossible) to fill quickly.

That’s why the most resilient organizations are redesigning coverage: building models that protect turnaround time, clinical confidence, and staff sustainability.

The shortage isn’t just a feeling—it’s showing up in projections

Recent research and analysis have focused on projecting radiologist supply and imaging demand over the coming decades, highlighting the risk of persistent shortages if current conditions continue. The Neiman Health Policy Institute summarized companion studies published in JACR projecting supply and demand trends through 2055.

The operational translation is simple: if your department plans like staffing will “normalize soon,” you may be planning for a world that doesn’t arrive on schedule.

What breaks first when coverage is thin

When departments run lean, the pain doesn’t spread evenly. It concentrates in predictable places:

Nights and weekends (coverage strain + fatigue)
ED/inpatient surges (worklist spikes)
Subspecialty-demand studies (oncology, neuro, MSK, complex body)
Communication friction (more callbacks, more clinician dissatisfaction)

The hospitals that stay stable build models that defend those pressure points first.

Coverage models that work in 2026

Here are four models that are proving practical in the real world:

1) “Core + overflow” (daytime stability, surge protection)

Your in-house team remains the core, but overflow coverage prevents backlog spirals when volume spikes. This is especially useful during:

seasonal peaks
staffing gaps (vacations, sick leave)
new service line growth

2) Dedicated after-hours coverage (protect your daytime team)

Instead of stretching your day staff into nights, create a defined after-hours plan. The goal is not just coverage—it’s preventing cumulative fatigue that degrades performance over time.

3) Subspecialty on-demand (quality where it matters most)

Rather than trying to hire every subspecialty locally, many hospitals use targeted subspecialty coverage for:

oncology staging/follow-up
neuro pathways
high-impact MSK cases
complex body imaging

This reduces risk and increases clinician confidence—without requiring full-time local recruitment for every niche.

4) Hybrid scheduling (reduce burnout and stabilize throughput)

Hybrid models combine:

predictable in-house shifts for continuity and relationships
external support to protect turnaround time and reduce overtime

These models can also support recruitment—because fewer radiologists want “always-on” schedules in 2026.

How to evaluate whether your model is working

Pick metrics that reflect real operational health:

Median and 90th percentile TAT by modality
Backlog hours at key times (end of day, weekends)
Discrepancy trends / peer review signals
Clinician satisfaction or complaint patterns
Radiologist overtime hours and call burden

If those metrics are improving, your model is working—even if you still feel “busy.”

Where Vesta fits

Vesta Teleradiology supports hospitals with flexible coverage models—overflow, nights/weekends, and subspecialty interpretation—built to protect turnaround times and clinical confidence without overloading your core team.

If you’re redesigning coverage for 2026, start with your pressure points and build outward. Learn more at https://vestarad.com.

2025 Year-End Review: The Radiology & Diagnostic Imaging Headlines That Mattered

Key Takeaways

AI shifted from pilot projects to real workflow infrastructure—with more focus on governance, validation, and safety in daily operations.

Photon-counting CT moved closer to mainstream adoption, strengthening the business case for next-gen CT planning and protocol upgrades.

Reimbursement and policy pressure stayed intense, keeping budgeting, contracting, and service-line ROI under a microscope.

Prior authorization and imaging appropriateness remained major throughput challenges, impacting scheduling, patient access, and operational efficiency.

Cybersecurity and downtime readiness became core imaging priorities, as ransomware and system disruptions increasingly threaten continuity of interpretation.

Radiology didn’t have a single “one story” year—it had a “many small shifts became operational reality” year. In 2025, diagnostic imaging leaders saw AI move from pilots into production workflows, next-gen CT mature from promise to procurement conversations, reimbursement pressures intensify, and cybersecurity become inseparable from patient care. Meanwhile, staffing strain and consolidation continued to reshape how coverage is delivered.

Below is a practical wrap-up of the biggest breakout themes from 2025—and what they signal for 2026 planning.

1) AI moved from point solutions to regulated, workflow-embedded infrastructure

If 2023–2024 was the era of “AI can detect X,” 2025 was the era of “AI has to behave safely inside real clinical systems.” Regulatory claritya and operational expectations became the story as much as the algorithms themselves. RSNA’s coverage highlighted how the FDA has been articulating pathways and challenges for AI-enabled radiology devices—making governance, validation, monitoring, and safety considerations a board-level topic, not just an R&D conversation. Daily Bulletin

At the same time, 2025’s conversation broadened from task-specific tools to foundation models and multimodal systems (images + text) that could impact triage, reporting support, and quality workflows—while also raising new risks around bias, generalizability, and clinical readiness. DirJournal

Operational takeaway for imaging leaders: AI value in 2025 increasingly depended on integration (PACS/RIS/reporting), change management, and clear accountability—especially as adoption expands and expectations shift from novelty to measurable outcomes. The Washington Post

2) Photon-counting CT stepped into the “real adoption” phase

Photon-counting CT (PCCT) wasn’t framed as a future curiosity this year—it showed up as a maturing platform with expanding clinical evidence and increasing operational readiness. RSNA 2025 coverage specifically called out how PCCT is taking center stage as the next CT evolution. Applied Radiology

Across 2025 literature and trade coverage, the narrative tightened around what administrators care about: clearer visualization and characterization, potential dose efficiencies, and broader specialty applications as the evidence base grows. ScienceDirect

Operational takeaway: If you’re building 3–5 year replacement plans, 2025 made PCCT a serious line item conversation—especially for high-volume sites where incremental image quality and protocol optimization can compound into throughput, repeat-scan reduction, and clinician confidence.

3) Payment pressure stayed relentless—and policy debates sharpened

For many departments, 2025 felt like a year of doing more with less. The 2025 Medicare Physician Fee Schedule (MPFS) final rule remained a major planning input for imaging groups and hospital finance teams, with ACR publishing a detailed imaging-focused summary of provisions and QPP updates. American College of Radiology

At the end of the year, broader Medicare payment policy debates also made headlines—reinforcing that specialty payment and “efficiency” assumptions are likely to stay politically active topics heading into 2026. Axios

Operational takeaway: Contracting, service line budgeting, and modality ROI assumptions increasingly need “policy sensitivity” built in—especially for outpatient imaging strategy and subspecialty coverage models.

4) Utilization management: prior auth and “right test, right patient” stayed in focus

Utilization controls continued to evolve. CMS prior authorization programs for certain outpatient services remain part of the broader backdrop of controlling unnecessary volume. CMS And late-2025 headlines underscored expanding demonstrations tied to prior authorization in additional settings, which imaging leaders often experience downstream as scheduling friction, referral leakage, or delayed care. Kiplinger

On the imaging appropriateness front, the Medicare AUC program remains a major framework (even as implementation timelines and mechanisms continue to be debated). CMS In 2025, ACR also publicly backed federal legislation (the ROOT Act) positioned as a way to revitalize Medicare imaging appropriateness workflows. American College of Radiology

Operational takeaway: Expect “appropriateness” and “utilization proof” to keep rising as operational requirements—meaning your radiology operation will benefit from tighter ordering communication loops, smarter triage, and documentation hygiene.

5) Breast imaging compliance stayed operationally important—density language included

Breast density notification requirements became routine compliance work after enforcement of MQSA’s amended regulations began in 2024, and 2025 was about living with the operational realities: consistent report language, patient communication workflows, and inspection readiness. U.S. Food and Drug Administration

Notably, 2025 also saw attention on density reporting language options under MQSA—an example of how “small wording changes” can have major downstream effects in templates, patient letters, and audit processes. DenseBreast-info, Inc.

Operational takeaway: Standardization wins here—clear templates, audit trails, and staff training reduce risk while improving patient communication consistency.

6) Workforce strain and burnout remained the constant—and coverage models kept shifting

Radiology’s capacity crunch persisted in 2025. ACR continued to flag ongoing workforce shortages amid rising imaging demand, while national physician burnout tracking suggested improvement from prior peaks but still elevated rates that affect retention and coverage reliability.

Operational takeaway: The “coverage plan” is now a strategic asset. Departments that treat coverage as a system (subspecialty access, peak-demand flex, nights/weekends/holidays, overflow protection, and consistent turnaround governance) are better positioned for 2026.

7) Cybersecurity became inseparable from imaging operations

Cyber risk is no longer “IT’s problem”—it’s a continuity-of-care risk, especially for imaging organizations that depend on always-on networks and data flow. In 2025, radiology-specific alerts and incidents reinforced how real the threat landscape is, from FBI-linked warnings about ransomware targeting healthcare entities to major breach reporting involving large imaging providers. Radiology Business

Operational takeaway: Imaging leaders should be asking: Do we have downtime playbooks? How resilient is PACS access? How are third-party integrations governed? How do we preserve interpretation continuity if local systems are disrupted?

A 2026-ready checklist for imaging leaders

Here’s what 2025’s headlines suggest you prioritize next:

AI governance that’s operational, not theoretical: validation, monitoring, and workflow accountability.
Modern CT strategy: map where photon-counting CT could change protocols, dose strategy, and long-term equipment planning. Applied Radiology
Payment + policy resilience: bake MPFS sensitivity into budgets and service line forecasts.
Utilization friction planning: anticipate prior-auth expansion impacts on scheduling and throughput.
Compliance consistency in breast imaging: templates, audits, and MQSA-ready workflows.
Coverage strategy as a system: subspecialty access + surge/overflow + nights/weekends/holidays planning.
Cyber continuity: imaging downtime workflows and vendor access governance.

Where Vesta Teleradiology fits in a “do more with less” reality

For hospitals and imaging centers, one of the most immediate ways to de-risk 2026 is to strengthen coverage—especially when staffing shortages collide with growing imaging demand. Vesta Teleradiology supports facilities with 24/7/365 coverage (including nights, weekends, and holidays) and subspecialty radiology interpretations designed to integrate with your existing technology and workflows.

If you’re planning for 2026 coverage resilience—overflow protection, consistent turnaround times, or expanded subspecialty reads—you can request a quote or schedule a test run here.

Breast Imaging 2025–26: Risk Models, CEM/MRI Momentum — RSNA Preview

RSNA 2025 is putting real energy behind risk-adjusted screening and the evolving roles of contrast-enhanced mammography (CEM) and breast MRI. For breast programs, the takeaway is practical: risk tools are moving from the research poster to the reading room, and CEM/MRI decisions are becoming operational levers you can plan around—especially for dense-breast pathways and overflow routing to subspecialists.

What’s new at RSNA: risk from the image itself

RSNA’s breast-imaging preview highlights sessions on image-only, 5-year breast cancer risk models, external validation work, and how MRI adds value in multi-modal AI. It also calls out global screening updates and a deeper look at background parenchymal enhancement (BPE) on MRI. RSNA

In parallel, the FDA granted De Novo authorization to the first image-only AI risk platform that predicts 5-year risk directly from a screening mammogram—an inflection point that makes risk-adjusted pathways far more scalable. Coverage from Radiology Business and BCRF explains the authorization and clinical intent. Radiology Business

Why it matters: average-risk guidance in the U.S. now begins screening at age 40 (USPSTF, 2024). Programs can layer image-based risk on top of that baseline to triage who needs annual vs. short-interval follow-up and who merits supplemental imaging. USPSTF

CEM is earning a seat next to MRI

Expect exhibits and sessions positioning CEM as a cost-effective, accessible adjunct—particularly for dense-breast populations and diagnostic workups. RSNA News recently framed CEM as a practical alternative to MRI in some screening/diagnostic scenarios, and new peer-review literature is refining technique (e.g., lower volume/higher-iodine contrast while preserving diagnostic performance). RSNA

On outcomes, the RACER trial in The Lancet Regional Health – Europe reported that using CEM as primary imaging for recalled women improved the accuracy and efficiency of the work-up compared with conventional imaging—evidence that will influence protocols beyond the show floor. The Lancet

MRI still leads for sensitivity—BPE is your underused signal

Breast MRI remains the sensitivity champion for high-risk patients and for problem solving. This year’s RSNA content spotlights BPE—how the level of background enhancement relates to tumor biology and outcomes. Recent reviews (2024–2025) synthesize BPE’s predictive/prognostic value, including associations with pathologic complete response after neoadjuvant therapy and survival in certain subtypes. SpringerLink

Practical move: standardize how you document BPE and incorporate it into structured reports and risk conferences; it’s becoming more than a descriptive footnote.

What to ask vendors at RSNA

Risk engine proof: “Show external validation and calibration plots by density and race; how does your image-only model integrate into our mammography worklist and letters?”
CEM logistics: “Demonstrate CEM acquisition workflows, contrast protocols, and how your viewer handles subtraction/kinetics alongside priors.”
MRI + BPE analytics: “Can we standardize BPE capture in structured reports and trend it across treatment?”

As risk-first screening, CEM, and MRI gain real traction, the winners will be the programs that operationalize them quickly and consistently. If you’re planning your 2026 breast-imaging playbook, stop by Vesta at RSNA to see how our subspecialists, standardized templates, and overflow routing make risk-adjusted pathways usable on day one.

Imaging the Individual — In the Trenches: AI, Personalization & Equity at RSNA 2025

RSNA’s 2025 theme, Imaging the Individual, isn’t just about futuristic science—it’s about doing the basics better for each patient, every day. The official Trending Topics preview highlights three threads cutting across subspecialties: AI you can deploy, personalized care you can operationalize, and equity you can measure. This guide translates those themes into practical checkpoints hospitals and imaging centers can use right now. RSNA

1) AI that graduates from pilot to practice

This year’s agenda emphasizes real outcomes over proofs of concept: reader-in-the-loop tools, bias monitoring, and governance. In breast imaging alone, RSNA previews spotlight external validation for image-only risk models and integration of MRI signals into multimodal AI—clear signals that “personalization” is landing in routine workflows. Bring vendor questions that force specifics: external validation cohorts, drift detection, and how metrics (TAT, recalls, rework) appear in your dashboard. RSNA

What to set up before RSNA: define 3–5 outcome metrics and insist every demo shows pre/post performance tied to those measures. Use QIBA concepts to push for standardized inputs/outputs so results are reproducible across scanners and sites. QIBA Wiki

2) Personalization that reaches the reading room

Personalization isn’t only radiogenomics. RSNA’s preview points to risk-stratified pathways you can actually run: e.g., image-only 5-year breast cancer risk at the point of screening to route patients into annual vs. short-interval follow-up or supplemental imaging (CEM/MRI). That pairs well with updated U.S. recommendations: screening beginning at age 40 for average-risk women, then adjusting based on risk and local policy. Build routing rules, templates, and letters now, so RSNA demos can plug into your plan.

Operational checklist:

Map risk thresholds → next steps (annual vs. short-interval, CEM/MRI).
Standardize templates so risk outputs appear consistently in reports and patient letters.
Decide who reviews outlier risk flags and how quickly (SLA).

3) Equity you can instrument—not just endorse

RSNA is foregrounding health equity, with sessions on encoding equity in AI and addressing access gaps for underserved communities. Equity becomes real when you can see it in your data: turnaround times by language, missed-appointment patterns by zip code, recall rates by screening site, and AI performance by subgroup. Build those slices into your analytics now; then ask vendors to show subgroup performance in their dashboards.

Practical moves:

Add demographic and language filters to your TAT and recall reports.
Require AI vendors to show calibration and error analysis by subgroup.
Stand up multilingual patient letter templates to support new screening starts at 40. USPSTF

4) CEM/MRI momentum: choose the lever that fits your service line

RSNA coverage calls out CEM as an increasingly practical adjunct—especially useful for dense-breast populations and diagnostic workups where capacity or cost limits MRI. The RACER trial reported higher accuracy and efficiency for CEM as the primary exam for recalled women vs. conventional imaging—evidence that can justify protocol changes and equipment planning. Meanwhile, MRI retains the sensitivity crown, with renewed attention on background parenchymal enhancement (BPE) as a signal worth documenting consistently.

Action items:

Decide where CEM fits: diagnostic recall pathway, dense-breast supplemental strategy, or both.
Add BPE level to structured MRI reports and trend it during therapy response clinics.

5) Governance, not guesswork

If personalization is the “what,” governance is the “how.” Use QIBA ideas—claim definitions, acquisition standards, and profile adherence—to control variability across devices and shifts. Tie RSNA learnings to a written governance plan with three parts: 1) protocol book (who owns it, update cadence), 2) quality book (metrics, subgroup views), and 3) AI book (approval process, monitoring, rollback).

6) Where teleradiology extends your capacity

Personalization increases complexity at peaks (recalls, dense-breast seasons, MR backlogs). A teleradiology partner helps you keep individualized pathways moving: standardized templates, subspecialty over-reads, and after-hours coverage that adheres to your risk rules and equity metrics—so “Imaging the Individual” doesn’t stop at 5 p.m.

Headed to RSNA?

Visit Vesta at Booth 1346 (South Hall) to see how we make “Imaging the Individual” work in real clinics—then enter to win a 1-year Medality CME subscription. Don’t wait: email “RSNA CME Entry” to info@vestarad.com now for a reserved entry, and show your confirmation at the booth for a bonus entry.