radiologists Archives - The Imaging Wire

Doctors Adopt ‘Shadow AI’ for Efficiency Gains

Posted on January 25, 2026January 23, 2026 by Brian Casey

Doctors under pressure to work more efficiently are looking for help from “shadow AI” – artificial intelligence applications adopted outside a formal hospital approval process. A new survey of U.S. healthcare personnel found that many administrators have encountered unauthorized AI tools in their organizations, including some used for direct patient care.

U.S. healthcare providers are struggling under rising patient volumes in the midst of an ongoing workforce shortage, a situation that’s leading to burnout among clinicians.

AI is often touted as a possible solution by enabling providers to do more with less, but the jury is still out on whether this works in the real world.

The new survey was conducted by Wolters Kluwer Health to assess usage of what the report described as “shadow AI,” or AI that’s adopted without proper hospital authorization processes.

Shadow AI introduces risk to data, security, and privacy, and providers should better understand the need for an enterprise approach to AI with appropriate controls.

It’s worth noting that the report’s use of the term “authorization” applies primarily to an institution’s internal approval and governance processes for AI rather than formal FDA regulatory authorization.

AI algorithms that aren’t used for direct patient care don’t require FDA authorization, as the agency pointed out in a guidance just a few weeks ago.

Researchers surveyed 518 health professionals, finding…

41% were aware of colleagues using unauthorized AI tools.
17% said they had personally used an unauthorized tool.
10% said they had used an unauthorized AI tool for direct patient care.

While the report’s recommendation for stronger AI governance is valid, there could be a competitive subtext to the findings. Wolters Kluwer offers healthcare clinical decision support solutions, and the company is currently locked in a fierce battle with OpenEvidence for dominance in the CDS space.

OpenEvidence’s CDS solution is wildly popular with clinicians, many of whom install and consult with the software on their own, outside an enterprise-level governance – exactly the kind of “unauthorized” model the new report criticizes.

The Takeaway

The Wolters Kluwer report could be shedding light on a concerning new trend, or it could represent an effort by an established player to shut out a competitive threat. Either way, its warning on the need for appropriate enterprise-level AI governance should not be ignored.

Risk-Based Mammography Screening Returns

Posted on January 21, 2026January 21, 2026 by Brian Casey

The idea of risk-based mammography screening is back with the publication of a new study in JAMA Network Open claiming that some risk-based strategies averted more breast cancer deaths with fewer false positives than age-based criteria. But like a previous paper on risk-based screening, the new findings raise concerns.

The idea behind risk-based screening is to focus healthcare resources on the people who need them most while sparing low-risk individuals from unnecessary medical interventions.

But risk-based breast cancer screening needs more clinical validation before it can be adopted broadly. This was tried with the WISDOM study, but researchers found no statistically significant difference in biopsy rates and only a modest reduction in mammograms performed.

A slightly different tack was taken with the new study, which compared conventional age-based biennial screening to a package of risk-based approaches based on a patient’s five-year breast cancer risk as calculated by widely accepted techniques like the Gail model and BCSC calculator.

Out of 50 risk-based strategies, nine averted more deaths than biennial age-based screening for women aged 40-74 (both were compared to no screening), and resulted in fewer false-positive recalls.

One such strategy highlighted by the authors used no screening for younger low-risk women, biennial screening for average-risk women, and annual screening for intermediate- and high-risk women, with the following results…

6% more breast cancer deaths averted per 1k women versus conventional screening (7.2 vs. 6.8).
8% fewer false-positive recalls (1,257 vs. 1,365).
While other risk-based strategies saw death reductions as high as 7.5 deaths per 1k women and false-positive reductions of 8-23%.

One key thing to note with the new study is its use of biennial screening as the control group, in line with current USPSTF recommendations for women aged 40-74.

But many clinical organizations like ACR, ACOG, SBI, and NCCN recommend annual screening, and the new study’s findings may have been very different if compared to an annual model.

The Takeaway

This week’s findings are generally more supportive of risk-based screening than those of last year’s WISDOM study. But the new paper’s marginal improvement in cancer deaths averted might disappear when compared with annual age-based mammography. And like WISDOM, its use of clinical models for risk prediction may soon be obsolete given rapid developments in AI-based risk assessment.

Breast Density’s Impact on Mammography

Posted on January 14, 2026January 14, 2026 by Brian Casey

Breast density has a well-known effect on the accuracy of mammography screening – and it’s not a positive one. But a new study in Academic Radiology sheds light on density’s impact thanks to a massive patient population and its use of digital breast tomosynthesis, the most current breast screening technology.

Breast density is known to reduce the effectiveness of X-ray mammography by obscuring suspicious areas and making cancers harder to find.

Women with dense breast tissue are typically directed to other imaging modalities for screening, such as ultrasound, breast MRI, and contrast-enhanced mammography.

The problem posed by breast density is significant enough that in 2024 the FDA implemented new MQSA rules requiring women getting screening mammograms to be notified of their density status.

It’s particularly important because having dense breast tissue is also a risk factor for breast cancer.

In the new study, MGH researchers aimed to quantify exactly how much breast density affects mammography screening through a large patient population screened with DBT, the state of the art in the U.S.

Researchers included 111.1k women who got DBT exams from 2013 to 2019 at their institution.

They then calculated important metrics like sensitivity and specificity, as well as cancer detection and false-negative rates, across the four categories of dense breast tissue, from entirely fatty (A) to extremely dense (D), finding…

Sensitivity was lowest in extremely dense tissue compared to entirely fatty (62% vs. 93%).
Specificity was also lower for extremely dense and heterogeneously dense categories compared to entirely fatty (93% for both vs. 97%).
The false-negative rate for extremely dense tissue was over 8X that of entirely fatty based on adjusted odds ratio (aOR = 8.35).
While the abnormal interpretation rate was 57% higher for extremely dense versus entirely fatty tissue.

The Takeaway

The new findings are some of the most definitive yet on the negative effect breast density has on screening mammography’s accuracy and support the FDA’s 2024 notification requirement. They hopefully will spur development of new technologies to mitigate density’s impact.

Some Rads Are Working Harder – But Not All

Posted on January 11, 2026January 8, 2026 by Brian Casey

If you feel like you’re working harder than your colleagues, you might not be wrong. New data on changes in imaging volume in the U.S. before and after the COVID-19 pandemic show that while volume grew faster than the supply of radiologists, those reading the most imaging exams shouldered most of the burden.

Medical imaging volume has become a closely watched barometer as radiologists struggle to manage a rising tide of imaging exams with a workforce that’s largely stagnant.

Various technologies – especially AI – have been suggested as possible solutions by enabling radiologists to work more efficiently and churn out more cases per day.

The COVID-19 pandemic complicated efforts to track imaging volume over time, as exam volumes dropped dramatically in 2020 before eventually rebounding.

So how much is imaging volume growing, and how hard are radiologists working to meet demand?

The new JACR study compared imaging volumes, radiologist workforce growth, and corresponding workload for 1.6k radiologists from 167 U.S. practices before and after the pandemic (December 2017 to February 2024). The researchers found…

Imaging exam volume grew 31% over the entire seven-year period, at a 4.6% compound annual growth rate.
The number of working radiologists grew 24%, at a CAGR of 3.6%.
There was little change in the overall number of exams radiologists read per day over the study period (49.1 vs. 49.4 exams).
But the top quartile of radiologists by reading volume was reading 31% more exams/day by the end of the study (from 57 to 74 exams).
While bottom-quartile radiologists saw their productivity decline 32% (from 79 to 54 exams).

As a side note, researchers concluded that the COVID-19 pandemic ultimately had a “modest effect” on the number of working radiologists, although rates of part-time work were higher during the pandemic.

The Takeaway

The new findings on imaging volume and radiologist productivity have fascinating implications. In aggregate, it seems that radiologists are keeping pace with rising volumes. But a closer look shows that the burden is falling disproportionately on those radiologists who are most productive – a trend that contributes to burnout among the very professionals the discipline should be working hardest to keep.

Top 2026 Radiology Trends

Posted on January 7, 2026January 7, 2026 by Brian Casey

As we did in 2025, The Imaging Wire asked key opinion leaders in medical imaging to provide their predictions on the technologies, clinical applications, and regulatory developments that will shape the specialty for the next 12 months. Here’s what they said…

3 Key Radiology Trends for 2026: Three fundamental trends will drive the radiology industry in 2026: 1) AI-based workflow will become more widespread and harder to differentiate. 2) Technology and services will increasingly be bundled to drive care-pathway product solutions. 3) Intense competition will continue, with partnering and M&A growing at a faster pace as healthcare spending tightens and price pressures get worse. Steve Holloway, CEO of Signify Research

AI Consolidation Shifts to Multi-Product Platforms: Radiology AI consolidation will continue and accelerate the shift from point solutions to multi-product platforms. A few vendors will emerge as market leaders, leveraging deeper workflow integration to deliver more value, offer broad bundles at lower prices, and scale adoption. Pure intermediary platforms will compete with vertically integrated players that have become platforms. OEMs will embed more AI through partnerships or acquisitions and enter the race. Finally, in a sustained AI bull market, more startups will reach nine-figure valuations. Amine Korchi, MD, radiologist and founder of Singularity Consulting

AI Vision Language Models Impact Radiology Reporting: Use of AI vision language models for draft report generation will be a major trend. Chest X-ray models are already seeing growing real-world evaluation – VLMs for modalities like CT and MRI are the next wave. Also watch for advancements in volumetric foundation models. Winning solutions will seamlessly streamline radiologist review-and-correction workflows. The real differentiator: multimodal fusion that integrates longitudinal clinical context with imaging. Woojin Kim, MD, CSO/CMIO at HOPPR and CMO at ACR Data Science Institute

Breast Density Loopholes to Close: Dense breast reporting is now a national standard, and many states have expanded insurance coverage for breast imaging. The federal Find It Early Act would close state-specific loopholes and include federal plans. The next challenge is educating women and providers about increased or high-risk factors and guiding appropriate supplemental screening and clinical choices. JoAnn Pushkin, executive director, DenseBreast-info

Breast Imaging Moves to Risk-Based Screening: Breast imaging will continue to move toward risk-based screening, optimizing screening intervals and modalities personalized to the individual, based on risk models that combine breast density, family history, genetics, and AI-derived imaging biomarkers. AI-enhanced risk stratification will continue to gain traction, using mammographic features such as density patterns, texture, and parenchymal complexity to refine a woman’s future cancer risk. This will allow women to be triaged into personalized screening pathways: high-risk patients directed to MRI/abbreviated MRI, or intermediate-risk women to modalities such as ultrasound and contrast-enhanced mammography. Stamatia Destounis, MD, managing partner, Elizabeth Wende Breast Care

CT Lung Cancer Screening Will Save More Lives: In 2026, CT lung cancer screening will save more lives than ever before. More countries will start screening programs (e.g., Germany), and more healthcare systems will achieve the “intersection of the curves”: More early-stage than late-stage lung cancer at diagnosis. Sebastian Schmidt, head of strategy, innovation, and medical affairs for CT at Siemens Healthineers

What Will Make MRI Safer? Last year the fatal Long Island MRI accident showed us just how tenuous our safety gains are. In 2026, more conversations should take place about which specific practices would make MRI safer, and how we go about making those standard across our profession, through regulation, licensure, or accreditation. Tobias Gilk, founder of Gilk Radiology Consultants

Opportunistic Screening Adds Value: 2026 will witness a rapid expansion of published studies demonstrating the added clinical value of AI-enabled opportunistic CT screening. Furthermore, the increasing clinical availability of these automated AI tools for cardiometabolic assessment should ultimately herald their routine use in value-added patient care. Perry Pickhardt, MD, chief of gastrointestinal imaging at the University of Wisconsin

Radiation Dose Management Tools: Practices will continue to become more comfortable using dose management tools to evaluate their dose data, benchmarking their doses for a given task against their peers. Diagnostic medical physicists play a crucial role in investigating and addressing dose outliers, and their important role in dose management will continue to grow. Cynthia McCollough, PhD, professor of medical physics and biomedical engineering at Mayo Clinic

Radiologist Shortage Will Continue: Looking into 2026, the radiologist shortage remains acute. Imaging demand will continue to outpace training output, burnout will drive attrition, and AI won’t offset capacity gaps fast enough. Workforce pressure shifts from volume coverage to subspecialist scarcity, keeping recruitment and retention firmly center stage. Jay Gurney, director of radiology for Projectus

Regulation and Reimbursement: As hospital-based interventional procedures face their steepest revenue declines, groups with a strong IR background are recognizing the value of expanding into office-based labs as a necessary step to protect and diversify their revenue streams. Sandy Coffta, VP of client services at Healthcare Administrative Partners

Theranostics Emerges as Primary Treatment Option: Theranostics will continue to shed its reputation as a last-ditch treatment option, and dosimetry will become more routine. This upstream migration will be accelerated by emerging medium axial-field-of-view PET/CT scanners (~24-48 cm), which will increasingly deliver the sensitivity needed to reveal micrometastases missed by standard PET/CT systems, justifying earlier deployment of molecular therapies. Eliot Siegel, MD, professor, University of Maryland and co-founder of United Theranostics

The Takeaway

As healthcare’s most dynamic medical specialty, radiology is sure to continue its rapid pace of evolution in 2026. Rest assured that you can read about all the year’s top radiology trends in The Imaging Wire.

Canon Celebrates 50 Years of CT Innovation: Redefining Healthcare with Meaningful AI

Posted on January 7, 2026January 7, 2026 by Partner Content

This year marks a historic milestone for Canon – five decades of pioneering CT innovation that has transformed the landscape of healthcare. From introducing industry-first technologies to setting new standards in diagnostic imaging, Canon continues to lead the way in delivering solutions that matter.

Canon’s legacy is built on breakthroughs such as its three-time award-winning wide-area CT systems, deep learning reconstruction that brings 1K resolution to CT imaging, and automation improving workflow.

These innovations have consistently elevated diagnostic confidence, patient safety, and operational efficiency.

In today’s world, AI is everywhere – but Canon’s AI is Meaningful AI. It’s not about AI for the sake of technology; it’s about creating real-world impact on patient care.

Canon’s portfolio of scanner-integrated AI applications is designed to enhance image quality, streamline workflows, and improve consistency – ultimately delivering better care, better experience, and better efficiency for patients and providers alike.

Canon is redefining CT by making AI a core component across its portfolio. Key innovations include…

AI-Assisted Scanner Workflow Automation. Canon’s INSTINX platform introduces intuitive, intelligent, and integrated AI technologies that enable autonomous CT operations. By simplifying complex workflows, INSTINX helps technologists focus on patient care while improving throughput and reducing variability.
AI-Assisted Post-Processing. Canon’s Automation Platform offers a zero-click, AI-driven solution that accelerates image post-processing. By delivering fast, actionable insights, this platform ensures time-critical results reach care teams when they need them most.

AI-Assisted Reconstruction. Advanced algorithms such as AiCE DLR and PIQE DLR leverage deep learning to reveal critical diagnostic information – contrast and resolution – while optimizing dose efficiency. These tools empower clinicians to make confident diagnoses and reduce the need for additional downstream studies. Additionally, CLEARMotion, a DCNN-based algorithm, compensates for patient motion, reducing blur and delivering high-quality results even in challenging cases.

The Takeaway

As Canon celebrates 50 years of CT innovation, its commitment remains clear: harnessing AI to make imaging smarter, faster, and more meaningful. With these advancements, Canon is not just shaping the future of CT – it’s setting a new benchmark for patient-centered care.

VC Radiology Funding Drops

Posted on January 4, 2026January 2, 2026 by Brian Casey

Venture capital investment in radiology peaked in 2021 at just over $2B and has been on a slow decline since then. That’s according to a study in JACR that documents the ebb and flow of VC investment, in particular its shift to companies developing AI algorithms.

VC investment is the lifeblood of any industry built on innovation, and healthcare is no exception.

Venture capital funding helps many innovators bring their ideas to fruition and helps fund them until revenue from product sales can start rolling in.

So it stands to reason that changes in VC funding levels can have ripple effects, with declines potentially affecting the rate of new technology development.

Indeed, some studies have found that every 1% increase in interest rates can cause a 3% decline in R&D spending and a 9% drop in patent filings.

The new research tracks VC funding specifically in radiology, with researchers from Emory and Harvard universities using PitchBook to track VC investments from 2000 to 2023.

In particular, researchers found…

A total of $11.4B was invested in 646 radiology companies during the entire study period.
The average investment was $6.3M with an average $51M post-investment valuation.
VC investment activity in radiology peaked in 2021 at $2.18B.
Medical devices attracted 28% of investment, followed by AI healthcare software (22%), non-AI healthcare software (18%), healthcare services (14%), and biotechnology and drug discovery (18%).

The new data track with research from other sources – like Signify Research – that have also documented a slowdown in radiology VC investment, particularly in AI.

Most sources attribute the declines to the end of the “cheap money” era during the COVID-19 pandemic as governments began dialing back on stimulus payments and started raising interest rates to tamp down inflation. On the other hand, other research has found that the recent declines are occurring at a rate that’s not proportional to inflation or interest rates alone.

The Takeaway

The new JACR research comes as the investment and healthcare worlds are set to begin their annual courtship ritual next week at the J.P. Morgan Healthcare Conference in San Francisco. Undoubtedly these new findings will be a point of discussion as radiology companies look to secure the capital that will fuel the next innovations in medical imaging.

Risk-Based Mammo Screening – Ready for Prime Time?

Posted on December 14, 2025December 13, 2025 by Brian Casey

Is mammography screening based on patient risk ready to take over for age-based screening? Results from the WISDOM study presented at last week’s San Antonio Breast Cancer Symposium and published simultaneously in JAMA suggest that while risk-based screening has its merits, more work may need to be done.

Cancer screening exams like mammography have reduced disease-specific mortality, but (with the exception of lung cancer screening) all use exclusively age-based criteria to determine who should get screened.

Age isn’t a great tool for determining who’s at higher risk of getting cancer, but it’s the best tool we’ve had – up to now.

New cancer risk prediction tools are now becoming available, prompting debate over whether these techniques could make screening more precise by directing it to those most at risk.

Higher-risk people could get more frequent screening, while lower-risk individuals might be directed to longer screening intervals.

The WISDOM study presented at SABCS 2025 investigates this question. WISDOM is a randomized clinical trial that compared risk-based breast screening to age-based annual screening in 28.4k women followed for five years.

Risk categorization was performed with genetic testing, polygenic risk scores, and BCSC scores, which incorporate family history and imaging results.

Women in the risk-based screening group were directed into one of four screening strategies, from alternating mammography and MRI every six months for high-risk women to no screening until age 50 for low-risk women.

The study’s primary outcomes were detection rates for breast cancers rated as stage IIB or higher and effectiveness in reducing biopsy rates – a proxy for screening-caused morbidity.

Across the study population, researchers found…

The rate of mammograms per 100k person-years was lower in the risk-based cohort compared to age-based screening (43.1k vs. 46.9k).
The rate of stage IIB or higher cancers per 100k person-years was also lower in the risk-based cohort (30 vs. 48).
But there was no statistically significant difference in biopsy rates, with a rate difference of 99 per 100k person-years (p = 0.10).

One problem with the WISDOM trial was that the actual screening exams were performed outside the study, and some patients did not comply with screening recommendations, potentially confounding results.

The Takeaway

The WISDOM authors concluded that a risk-based screening approach is safe, but the lack of a difference in biopsy rates makes one wonder if veering from established age-based criteria is worth it. In any event, the coming arrival of risk stratification based on AI mammogram analysis could make the genetic testing-based approach used in WISDOM obsolete.

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