Since the mid 1900s, lung cancer has been the leading cause of cancer deaths among both men and women and each year. More people die of lung cancer than of colon, breast and prostate cancers combined, even as the number of deaths from lung cancer has fallen thanks to fewer people smoking and new technologies for early detection and treatment.
Recent studies and industry insights highlight both the progress we’ve made and the challenges that remain, particularly around long-term risk, AI adoption and program sustainability.
Keep reading for a roundup of the latest developments shaping lung cancer screening today, along with practical considerations for imaging leaders preparing for what comes next.
Long Term Risks from Negative CT Screenings
A negative baseline low-dose computed tomography (LDCT) test does not eliminate long-term lung cancer risk. A recent study suggests that LDCT improves early detection and can reduce mortality for high-risk individuals, but about 80% of baseline screens are negative, leaving long-term lung cancer risk trajectories unclear.
The same study followed more than 30,000 individuals with negative initial scans and found that risk remained elevated for years, especially among current and former smokers.
Here’s what they found:
These findings reinforce the importance of personalized screening and more inclusive risk assessment frameworks. Radiologists and imaging teams should maintain strong follow-up pathways, even for patients who begin their screening journey with a negative result.
Gaps in Current Screening Guidelines
Recent national reporting by a study highlighted by The Washington Post raised concerns that today’s lung cancer screening criteria may still be too narrow. Even after the 2022 expansion, a significant amount of individuals who develop lung cancer still do not qualify for screening under current U.S. Preventive Services Task Force guidelines.
Experts suggest that if we keep current guidelines, we’d only catch about one-third of new lung cancers. The research also suggests that switching to universal age-based screening could save thousands of lives every year. Furthermore, the study found that if age-based screening caught only 30% of cases at Stage 1, we could save nearly $25 billion a year in treatment costs.
For imaging teams, these trends signal the need to prepare for evolving guidelines and potentially higher screening volumes.
AI in Lung Cancer Screening
Artificial intelligence (AI) keeps turning imagination into reality in the healthcare industry, and new real-world data supports its role in lung cancer screening workflows. A recent radiology study evaluated more than 900 LDCT exams and compared radiologist-alone reads with AI-assisted reads.
Here are the results:
Researchers described their findings as “pragmatic evidence” that AI can enhance screening performance without slowing down radiologists.
For imaging teams already incorporating AI into their workflows, this study reinforces that AI is indeed a practical tool that can strengthen early detection, support consistency and help teams handle rising screening volumes.
What High Performing Screening Programs Have in Common
Clinical studies and evidence are only one part of the equation. Successful lung cancer screening programs also require strong operational foundations through education, consulting and strong partnerships.
Here are several best practices for imaging teams to follow:
Together, these practices and more form the backbone of high-performing screening programs and help ensure patients receive timely, consistent and compassionate care.
Technology That Supports Early Detection and Screenings
As times change, imaging teams need technology that moves at the same pace while continuing to support accuracy, efficiency and patient safety. For lung cancer screening and early detection, the most notable systems include:
SOMATOM go.Up
SOMATOM go.Up is a CT scanner designed for daily routine that helps you adhere to clinical guidelines. Handle high throughput and challenging cases with ease.
You can benefit from:
Cios Spin Mobile 2D/3D C-arm
The Cios Spin Mobile C-arm offers 2D fluoroscopy and true cone-beam CT (3D) imaging, providing real-time visualization of pulmonary lesions and precise tool-in-lesion confirmation.
Designed to support lung cancer procedures, it enables accurate targeting and verification during transbronchial biopsies and other interventional pulmonology techniques.
These advanced systems help imaging teams detect lung cancer earlier, reduce dosage, streamline workflows, support follow up exams/procedures and prepare for the next round of screening guidelines.
Staying Prepared
There is still a lot of improvement to be done with lung screening, as suggested by the new evidence above surrounding long-term risk, the role of AI and the operational realities of running a high-performance program.
I highly encourage imaging teams to stay informed, invest in workflow improvements and adopt technology that supports early detection. In this way, you’ll be best positioned to meet rising demand and improve patient outcomes.
At Cassling, we remain committed to supporting imaging professionals through education, technology and partnerships. If you’re interested in learning how we can support your team, contact us today.