New research presented this week at the European Congress of Radiology (ECR 2026) suggests that a patient’s body composition, as measured by CT scans, can offer valuable insights into their risk profile during lung cancer screening. The findings highlight the interplay between age, smoking history, and the distribution of muscle and fat in the chest, potentially paving the way for more personalized and effective screening strategies.
Lung cancer remains a leading cause of cancer-related deaths worldwide, and early detection is crucial for improving outcomes. Current screening methods primarily rely on identifying suspicious nodules on low-dose CT scans. However, these scans too provide a wealth of information about a patient’s overall body composition, which researchers are now exploring as a potential predictor of risk. This emerging field of research, focused on lung cancer screening, could refine risk assessment and improve patient care.
The study, conducted by researchers analyzing data from the Netherlands-Lung Cancer Intervention Screening (NELSON) trial, involved 4,435 male participants with an average age of 59.4 years and a mean smoking history of 42.2 pack-years. Using artificial intelligence-based automated systems, researchers quantified skeletal muscle area (SMA) and subcutaneous adipose tissue area (SAT) at multiple levels of the chest – T5, T8, and T10 – to calculate a fat-to-muscle ratio (FMR). The goal was to determine if variations in these measurements correlated with age and smoking status.
Body Composition Differences Linked to Smoking Status
The analysis revealed significant differences in body composition between current and former smokers. Current smokers, representing 55% of the study cohort, exhibited notably lower levels of both SAT and SMA compared to former smokers (45%). Specifically, current smokers had an average SAT of 372 cm² versus 441 cm² in former smokers (p<0.001), and SMA measured 501 cm² compared to 507 cm² (p<0.001). The fat-to-muscle ratio was also lower in current smokers, at 0.74 compared to 0.87 in former smokers (p<0.001). These findings suggest that smoking impacts body composition in ways that may influence lung cancer risk.
Age-Related Changes in Muscle and Fat
Beyond smoking status, the study also documented age-related changes in body composition. Skeletal muscle area steadily declined with age, decreasing from an average of 515 cm² in men aged 50–54 years to 472 cm² in those 70 years and older (p<0.001). Conversely, subcutaneous adipose tissue increased with age, rising from 376 cm² to 443 cm² over the same period (p<0.001). The fat-to-muscle ratio also increased from 0.70 to 0.90 (p<0.001). These associations remained statistically significant even after accounting for smoking history and cumulative smoking exposure.
These findings align with broader research on age-related muscle loss, known as sarcopenia, and its potential impact on overall health. Maintaining muscle mass is crucial for physical function and metabolic health, and its decline with age may contribute to increased vulnerability to various diseases, including cancer. Cost-effectiveness of lung cancer screening is also being evaluated with these new metrics in mind.
Implications for Lung Cancer Screening
The researchers emphasize that establishing standardized reference values for CT-based body composition measures could enhance risk stratification in lung cancer screening programs. By incorporating these metrics alongside traditional risk factors, clinicians may be able to identify individuals who would benefit most from more intensive screening or preventative interventions. However, the authors caution that further research is needed to determine how these body composition markers correlate with actual clinical outcomes, such as lung cancer incidence and mortality.
The development of deep learning models to estimate cancer risk from lung nodules is also progressing, offering another avenue for improving early detection. These advancements, combined with a deeper understanding of body composition, hold promise for a more personalized approach to lung cancer prevention and treatment.
As research continues, the integration of CT-based body composition analysis into routine lung cancer screening could turn into a valuable tool for identifying high-risk individuals and tailoring interventions to improve outcomes. The next steps involve prospective studies to validate these findings and determine the optimal way to incorporate these measurements into clinical practice.
Disclaimer: This article is for informational purposes only and should not be considered medical advice. Please consult with a qualified healthcare professional for any health concerns or before making any decisions related to your health or treatment.
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