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The Danger of Incidental Findings, Imaging TAT Slows, and AI Punditry
April 2, 2026
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Together with
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“I think they should replace CEO’s with AI.”
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Silent_Law6552, commenting on statements by hospital CEOs that AI could replace their radiologists.
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Revenue cycle management can be a challenging issue for any radiology operation, but it’s important to master to keep your business running smoothly. In this edition of The Imaging Wire Show, we talk to Hank Freeman, MD, of Edison Radiology Group about how they turned to Healthcare Administrative Partners for help.
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CT lung cancer screening is gaining momentum around the world, but one of the challenges providers face is how to manage incidental findings. It’s especially important given that a new study in JAMA Network Open suggests that incidental findings on screening exams are associated with a higher risk of cancer occurring outside the lung.
Incidental findings are suspicious areas discovered outside the target region being imaged, and are especially a concern with cancer screening exams.
- Incidental findings turn out to be normal most of the time, but pathology occurs often enough that most clinicians agree they’re worth investigating.
The problem is that many providers don’t have a robust system in place for alerting referring physicians to incidental findings and ensuring that patients get the follow-up exams they need.
The new study addresses incidental findings within the context of CT lung cancer screening, specifically in the National Lung Screening Trial, the landmark study that established low-dose CT’s lifesaving benefit.
- It’s an important question, because chasing down a large number of benign incidental findings would be a resource-intensive task that could alter the cost-benefit ratio of lung screening.
Researchers analyzed significant incidental findings unrelated to lung cancer in 26.4k people across three rounds of LDCT screening who were followed for a year, revealing…
- Cancer findings outside the lung occurred in 6.8% of people, and 13% of them had multiple cancers.
- Patients with significant incidental findings had a higher absolute risk of being diagnosed with extrapulmonary cancer within a year (16 per 1k participants).
- Study participants with incidental findings tended to be slightly older (62 vs. 61 years) and more likely to have a history of smoking-related disease (69% vs. 66%).
The findings confirm that having a plan to manage incidental findings should be an important part of any CT lung cancer screening program, especially given previous research showing that 23% of deaths in NLST were due to cancers outside the lung.
- In fact, an effective incidental finding program could enhance LDCT screening’s value, especially given that people eligible for screening have heavy smoking histories.
The Takeaway
The new study shows that incidental findings on CT lung screening exams are common and serious enough to warrant further investigation. Screening programs that are able to do so effectively will deliver even more value to their patients than lung screening alone.
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Leveraging AI-Powered Discovery for Image Exchange
Southwest Medical Imaging, a premier physician-owned radiology practice in the southwestern U.S., partnered with Medicom to streamline their workflow. Discover how SMIL utilized Medicom’s AI-powered Smart Search, which leverages an LLM to automatically detect and surface imaging data, to eliminate manual searching and accelerate patient care.
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Experience Dynamic Simplicity in Fluoroscopy
Still on the fence about upgrading to the latest technology that fluoroscopy has to offer? Hear from your peers about their experiences with the first-ever installed LUMINOS Q.namix R system from Siemens Healthineers.
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The World’s Happiest Customers – 13 Straight Years
Sectra continues to top the charts when it comes to customer satisfaction. The company recently won seven Best in KLAS awards, including the 13th straight for its Sectra PACS enterprise imaging solution. Find out why on this page.
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- Lung Screening’s Stage Shift: A review of CT lung cancer screening in the U.K.’s NHS system found evidence of a stage shift toward earlier cancer detection. The study in Nature Medicine noted that 2.5M invitations to screening-eligible people were extended from 2019 to 2025, with 49% attending an appointment and 21% getting scanned. In all, 1.4% of participants were diagnosed with lung cancer, and 76% of cases were stage 1 or 2. The proportion of early-stage cancers is rising as screening uptake grows.
- Better Survival for LDCT Participants: People who underwent low-dose CT lung cancer screening had better 10-year survival and fewer comorbidities in a new study from Poland. In a population of 43.7k people aged 50 to 75, those who got screening had higher survival rates than those who didn’t (87% vs. 81%) and had lower rates of hypertension and high cholesterol. The study suggests that participating in LDCT screening could reduce all-cause mortality, a trend not found for other cancer screening tests.
- Chest X-Ray AI Doesn’t Speed CT Referrals: In patients with chest X-rays suspicious for lung cancer, researchers using Qure.ai’s algorithm for prioritization didn’t see faster care pathways. In the LungIMPACT trial in Nature Medicine, U.K. researchers tested an AI prioritization protocol in a study with 93.k patients, finding there was no difference between AI and non-AI prioritization in time to CT (eight days for both) and no statistically significant difference in time to diagnosis (44 and 46 days, respectively). AI may have complicated clinical workflow.
- Incidental Findings in Breast Screening: Incidental findings are also a challenge in breast cancer screening. In a prepublication paper from Lifepoint Health and Eon, women with breast abnormalities detected incidentally – like through chest CT or abdominal scans – were 6X more likely to be diagnosed with breast cancer than patients getting routine screening mammography. Patients diagnosed with cancer identified on incidental findings were more likely to be at high risk than screening mammography patients (63% vs. 47%), and over half of cancers occurred in women not eligible for mammography.
- Imaging Turnaround Times Double: The turnaround time for radiology reports more than doubled over the past 10 years, with most of the growth occurring in the last few years. A new study in JACR by Neiman HPI describes a “hockey stick” in TAT starting in 2022, when times grew 68% after 19% growth in 2021, with overall 113% growth between 2014 and 2023. TAT growth was particularly high for CT (318%), MRI (256%), and ultrasound (140%). The study renews concerns about a mismatch between imaging volume and radiologist staffing.
- FDA Clears GE’s Next-Generation DL Recon: The FDA last month signed off on GE HealthCare’s True Definition DL, which represents the next generation of GE’s deep learning-based CT image reconstruction technology. An improvement on TrueFidelity (which itself was cleared in 2019), True Definition DL is designed for the company’s conventional CT scanners using energy-integrating detectors (rather than photon-counting CT), and delivers better spatial resolution than TrueFidelity.
- AI of CAC Measures Heart Fat: AI can be used to analyze CT-derived coronary artery calcium scans to assess pericardial adipose tissue (or fat surrounding the heart), a potential biomarker for future cardiovascular disease. In a paper presented at ACC 2026, researchers used their homegrown AI model to measure pericardial adipose tissue in 11.9k people with no symptoms or history of heart problems. After a median follow-up of 16.4 years, patients with the highest levels of AI-calculated PAT volume had 30% higher risk of cardiovascular events after adjusting for CAC scores (HR = 1.30).
- Angio-Based FFR Compares Well: CT-based fractional flow reserve has been getting attention as a less-invasive alternative to pressure-wire FFR, but a new study published in NEJM and presented at ACC 2026 suggests angiography-derived FFR also works well. Researchers used Pie Medical Imaging’s CAAS vessel FFR software in the FAST III trial to guide revascularization in 1.1k patients, finding that after a year they had similar rates of death, revascularization, or adverse events as procedures guided by pressure-wire FFR (7.5%).
- Bayer’s Ambrogio to Lead U.S. Pharma Biz: The chief executive of Bayer’s global Radiology division, Nelson Ambrogio, has been tapped to lead the company’s U.S. Pharmaceutical operations. Ambrogio led the Radiology business for the past two years, and in his new role will oversee commercial operations for pharmaceuticals addressing prostate cancer, cardiovascular care, and women’s healthcare, as well as the company’s coming entry into secondary stroke prevention.
- FDA Clears Butterfly’s ‘Blind Sweep’ Tool: The FDA cleared a “blind sweep” ultrasound algorithm from Butterfly Network for estimating gestational age with its point-of-care ultrasound scanners. Blind sweeps are freehand ultrasound scans performed by minimally trained personnel and are often guided by AI, enabling imaging to be used in resource-poor areas. Butterfly’s GA Tool can be performed in under two minutes in an automated process that minimizes user variability. The company notes that nearly half of rural counties lack hospital obstetric services.
- Lucida Raises Funds: Prostate MRI software developer Lucida Medical raised $11.5M in an investment round to fund further commercialization of its flagship Pi algorithm in Europe and the U.K., where it is already in use at 15 NHS hospitals. Lucida also plans to pursue regulatory authorization in the U.S., and expand its AI platform to different cancer types.
- Hospital CEOs Open to Replacing Radiologists with AI: This month’s Geoffrey Hinton Prize for AI Punditry goes to a trio of health system CEOs who said they would be open to replacing their radiologists with AI – if the government allowed it. Their comments during a roundtable discussion last week in New York City sparked heated discussion on the r/Radiology Reddit forum about AI’s impact on radiologist employment, but we have a feeling it’s the CEOs who may be looking for work sooner than any of their radiologists.
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Transform Imaging Data into Actionable Predictions
When you choose Quibim, you get more than a partner for detecting and diagnosing prostate cancer on MRI scans. Learn how they can help you transform imaging data into actionable predictions by booking a demo today.
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Radiology Automation Simplified
CARPL is an enterprise-grade radiology AI validation and deployment platform with 250+ AI applications across 85+ AI vendors that empowers healthcare providers to access, assess, and securely integrate imaging AI in their practice. Book a demo today.
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Radiology Case Report
A man in his 40s presented with a known metastasis within his abdomen. Learn how contrast-enhanced MRI helped to diagnose the extent of his disease.
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