Francis Deng, MD, and Linda Moy, MD, in a new paper on radiology’s surging popularity with medical students.

CT lung cancer screening has been proven to reduce lung cancer mortality, but lung screening has struggled to achieve widespread acceptance. In this Imaging Wire Show, we discuss how to overcome the challenges setting up CT lung screening – and some of the technologies that are available to help – with Dr. Chip Gilkeson of University Hospitals Cleveland Medical Center and Steve Worrell of Riverain Technologies.

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Radiologists

Radiology’s Enduring Popularity

Radiology is seeing a resurgence of interest from medical students picking the specialty in the National Resident Matching Program (NRMP). While radiology’s popularity is at historically high levels, the new analysis shows how vulnerable the field is to macro-economic trends in healthcare. 

Radiology’s popularity has always ebbed and flowed. In general the field is seen as one of the more attractive medical specialties due to the perception that it combines high salaries with lifestyle advantages. But there have been times when medical students shunned radiology.

The new paper offers insights into these trends. Published in Radiology by Francis Deng, MD, and Linda Moy, MD, the paper fleshes out an earlier analysis that Deng posted as a Twitter thread after the 2023 Match, showing that diagnostic radiology saw the highest growth in applicants to medical specialties over a three-year period.

Deng and Moy analyze trends in the Match over almost 25 years in the new study, finding…

• The 2023 Match in radiology was the most competitive since 2001 based on percentage of applicants matching (81.1% vs. 73.3%)
• 5.9% of seniors in US MD training programs applied to diagnostic radiology in the 2023 Match, the highest level since 2010
• Fewer radiology residency slots per applicant were available in 2023 compared to the historical average (0.67 vs. 0.81) 

Interest in radiology hit its lowest levels in 1996 and 2015, when the number of applicants fell short of available radiology residency positions in the Match. It’s perhaps no surprise that these lows followed two major seismic healthcare shifts that could have negatively affected job prospects for radiologists: the “Hillarycare” healthcare reform effort in the early 1990s and the emergence of AI for healthcare in the mid-2010s. 

Hillarycare never happened, and Deng and Moy noted that outreach efforts to medical students about AI helped reverse the perspective that the technology would be taking radiologists’ jobs. Another advantage for radiology is its early adoption of teleradiology, which enables remote work and more flexible work options – a major lifestyle perk. 

The Takeaway

The new paper provides fascinating insights that support why radiology remains one of medicine’s most attractive specialties. Radiology’s appeal could even grow, given recent studies showing that work-life balance is a major priority for today’s medical students.

A Perfect Balance of Utility and Nirvana

The One Viewer philosophy from Visage offers end users from across the enterprise the chance to get access to Visage 7’s powerful tools based on their clinical need, with the same #1 rated viewer for multiple workflows. Find out today how it works.

Reducing the Risk of Medical Errors and Misreads

What are the factors that contribute to errors and misreads in radiology – and how can they be prevented? Find out how to improve your practice’s quality and accuracy in this white paper from Medality.

The Wire

• AI’s Top Influencers: Radiologist Keith Dreyer, MD, landed on Time magazine’s new list of top 100 influencers in AI. Dreyer is chief data science officer at Mass General Brigham and has long been known as a pioneer in imaging informatics, including AI. Another clinician on the list is Ziad Obermeyer, MD, an emergency medicine physician who gave a keynote address at SIIM 2023. Also making the cut? Geoffrey Hinton, PhD, who in 2016 delivered an infamous quote on AI and radiologist job prospects. 

• AI Confirms Tracheal Tube Position: An AI algorithm from Lunit performed well in confirming the position of endotracheal tubes on chest X-rays. Researchers in AJR describe how they used the algorithm to confirm tube insertion and position in 1,722 X-rays acquired in 892 patients during 2020 at three sites. The algorithm posted high sensitivity for detecting improper tube position (range of 73-84%) as well as high specificity 92-100%). In clinical use, AI could alert clinicians to malpositioned tubes faster than if humans reviewed chest X-rays.

• Incidental CAC Predicts Long-Term Risks: Stanford-led researchers applied a deep learning model to identify patients with high CAC scores using non-ECG-gated CTs, finding that AI-based CAC scores accurately predicted long-term risk. The researchers analyzed routine chest CTs from 5,678 adults (51% women, 51% >0 CAC) finding that participants with ≥100 incidental CAC scores had a 24% 10-year risk of developing ASCVD, even though only a quarter of them were on statins. After adjustments, patients with DL-CAC ≥100 had far higher risks of death, death/MI/stroke, and death/MI/stroke/revascularization (HRs: 1.51, 1.57, 1.69).

• CT-FFR Helps Predict Risk: In a related vein, Danish researchers writing in Radiology described how patients with high CAC scores might be at lower risk for adverse cardiac events if they have normal FFR-CT results. In a group of 900 patients with stable angina, those with both high CAC scores (>400) and abnormal FFR-CT based on HeartFlow’s FFRCT Analysis software had a higher rate of adverse events at three years than those with high CAC but normal FFR-CT (9% vs. 2.2%). 

• Echo AI Partnership: Us2.ai is partnering with Duke University to co-develop and commercialize AI applications for echocardiography. The goal of the partnership is to enable earlier detection, better diagnosis, and more efficient management of patients with heart disease. Us2.ai and Duke note that echo image interpretation is subject to variability between readers; by partnering they hope to reduce variability and possibly enable echo’s use as a screening tool. Us2.ai’s impact on heart failure screening was recently validated in the OPERA study in Scotland. 

• NIH Grant for Subtle Medical: Subtle Medical has been awarded a $2.3M Small Business Innovation Research (SBIR) grant from the NIH to advance the development of its SubtleSYNTH software. SubtleSYNTH uses deep learning to create synthetic MR images from other sequences produced during the same exam, such as STIR images from T1 and T2 acquisitions, cutting up to 70% of acquisition time. SubtleSYNTH works with the company’s SubtleMR algorithm and is pending FDA clearance. 

• Pandemic Drove Down Breast Screening: Another study is confirming the damage that the COVID-19 pandemic wreaked on breast cancer screening. In the open-access journal eLife, US and Scottish researchers performed a literature review covering 26 studies with 106M women in five countries with population-based screening, finding that from January to December 2020 screening volumes fell by between 13% and 31%. The two countries that relied most on opportunistic screening – Mexico and Brazil – saw even bigger declines (61% and 41%). Screening uptake rates also declined in most countries.

• Auto-Enrolling for Mammography: Automatically enrolling eligible women to receive mammography screening didn’t boost compliance compared to requiring them opt in manually. In a study of 883 veterans in the VHA system in JAMA Internal Medicine, there was no statistically significant difference in the number of completed mammography exams at 100 days between women who were automatically referred to screening and got a scheduling call versus those who got a phone recording to opt in manually (67 vs. 66, P=0.90). 

• Qure.ai Lands FDA 510(k): Qure.ai received FDA 510(k) clearance for two new clinical applications for its qXR software for analyzing chest X-rays. The company can now market qXR to triage pneumothorax and pleural effusion, which can be challenging in emergency and intensive care settings. Qure already has clearance for qXR-BT for breathing tube placement, qER for emergency head CT, and qER-Quant for head CT quantification. Qure is also touting results from a study in Vietnam using its chest X-ray algorithm to detect tuberculosis. 

• Canon Adds High-Def Angio: Canon Medical Systems expanded its Alphenix Sky family of interventional angiography systems with a new option for high-definition imaging. Alphenix Sky 12 HD adds a 12 x 12-inch option with the company’s HD 76 Hi-Def digital detector, joining the 12 x 16-inch configuration already available. Canon believes the new option will be suited for interventional procedures in cardiology, neurology, oncology, and radiology, including pediatric applications. 

• Annalise Brain CT Triage AI Cleared: Annalise.ai got 510(k) clearance for its algorithm for triage and notification of obstructive hydrocephalus (OHCP) on non-contrast brain CT. In OHCP, cerebrospinal fluid accumulates in the cranial vault, and the Annalise algorithm provides both passive and active notification from unenhanced CT, enabling these cases to be prioritized. The algorithm was designated as part of the FDA’s Breakthrough Devices Program before getting clearance; it is the 10th FDA-cleared algorithm in Annalise’s portfolio, which now includes five chest X-ray and five head CT applications.

• FDA to Review PET Tracer Rules: The FDA plans to review its regulation of PET radioisotope production in a meeting on November 13-14 at its campus in Silver Spring, Maryland. The meeting is designed to bring industry, researchers, and regulators together to discuss regulatory compliance for PET tracer manufacturing and pathways for regulatory applications. Topics will include inspections and compliance, product quality assurance, lifecycle management of PET drug applications, and more. 

• Thirona Raises $8M: Lung AI software developer Thirona raised $8M that the Dutch company plans to use to advance development of its products, including its flagship LungQ suite. Thirona’s software analyzes lung CT scans to enhance bronchoscopic and surgical lung interventions, and its offerings include the PRAGMA-CF cystic fibrosis automated quantification application. Thirona has carved out a niche in image-supported research and clinical trials for pharmaceutical development, with its software used to analyze 15M images to date.

Echo AI Hits the High Notes in OPERA Study

New results from the OPERA study show how Us2.ai’s echo AI solution improved heart failure screening in the NHS, reducing echo waiting times from 12 months to under 6 weeks. Find out more in this article.

Becoming Imaging AI Adopters

We talk a lot about radiology practices’ AI adoption, but usually don’t have much evidence to back it up. That changes with this Arterys report detailing how and why 30 US radiology groups became imaging AI adopters.

Monitoring AI Solutions in Healthcare

Clinical applications for healthcare AI are rapidly expanding, but many barriers are still preventing widespread adoption. This Nuance post explores a critical set of questions: what happens after an AI model goes into production, and how to know if it continues to perform as expected?

The Resource Wire

• Synthetic imaging is poised to reshape medical imaging by speeding up image acquisition time. Learn how Subtle Medical’s SubtleSYNTH software will revolutionize the MRI experience in this September 21 webinar. 

• How did Capital Health in New Jersey approach its investment in AI for radiology? For one, it’s necessary to have a comprehensive solution that goes beyond single-feature detection, according to this discussion between Dr. Ajay Choudhri and Annalise Chief Medical Officer Dr. Rick Abramson. 

• Did you know there are four main indicators that show informed patients have better clinical outcomes? Check out this analysis from PocketHealth on why empowered patients make better patients. 

• Bayer’s cloud-based Calantic Digital Solutions AI platform features a suite of disease-specific AI apps that integrate into radiologist workflows, helping radiology teams scale AI deployment and improve efficiency and quality of care.

• Interested in learning more on cardiac CT protocols? Hear from Luis Landeras, MD, and technologist Michael Mason from the University of Chicago as they share common challenges, clinical cases, and customized CT protocols they utilize with cardiac patients on their GE HealthCare Revolution Apex CT scanner.

• Healthcare providers can’t feel confident in the impact they make for their patients without feeling their IT environments are resilient and reliable. This eBook from Merge by Merative breaks down 3 essential ingredients of a resilient imaging IT environment: hybrid cloud, reliable uptime, and zero-trust security. 

• Data standardization has emerged as a key issue for both clinical and research aspects of medical imaging. Learn about standardization’s pivotal role in healthcare in this Enlitic webinar on October 25 featuring Cheryl Petersilge, MD, founder and CEO of Vidagos. 

• What is CPACS in Cardiology? It stands for Cardiovascular Picture Archive and Communication System, and it’s used to store, manage, and share cardiology images. Learn how CPACS can improve patient care in this Intelerad blog post. 

• How is Siemens Healthineers helping imaging providers meet their clinical and operational needs while maintaining high-quality care? Find out in this panel discussion with representatives from AdventHealth and WakeMed. 

• Faced with the task of monitoring the thousands of exams its algorithms analyze each day, Qure.ai leveraged CARPL.ai’s validation workflow to create a real-time performance dashboard. See how they did it here.

• How is Clearpath improving the healthcare experience for patients? Learn more about the company and its solutions for ditching the disc when sharing images and records with patients. 

• Is your organization ready to move enterprise imaging to the cloud? Check out this Change Healthcare and ACHE webinar detailing cloud-native imaging’s benefits, best practices, and ROI.

• The quality and appearance of CT scans can vary considerably. In this white paper from Riverain Technologies, find out how image normalization can standardize CT images, making them easier to analyze and interpret. 

• Trying to figure out how your IT resources can handle increased AI adoption? This Blackford paper details how the cloud is helping radiology organizations scale their computing resources to support multiple AI applications or algorithms.

• Explore how United Imaging is reinventing the medical imaging business, including downtime rebates, lifetime upgrades, and making sure their customers truly are successful.