New research finds increased patient BMI can negatively impact AI performance on low-dose CT scans.
Key Details
- 1Study published in the European Journal of Radiology examines BMI impact on chest LDCTs.
- 2Higher BMI causes increased X-ray attenuation and image noise, degrading image quality.
- 3Researchers compared AI and human lung nodule detection in cohorts with highest and lowest BMI (top and bottom 1.5%).
- 4AI's diagnostic accuracy is limited by the diversity of its training datasets, particularly in BMI distribution.
- 5Prior literature shows conflicting findings about BMI influence on human performance; data on AI's vulnerability to BMI-related artifacts is growing.
Why It Matters
This study highlights a potential bias and limitation of current imaging AI tools, especially those trained on less diverse patients. Understanding performance differences across BMI ranges is essential for ensuring equitable and accurate lung cancer screening in clinical settings.
Source
Radiology Business
Related News
•AuntMinnie
Toronto Study: LLMs Must Cite Sources for Radiology Decision Support
University of Toronto researchers found that large language models (LLMs) such as DeepSeek V3 and GPT-4o offer promising support for radiology decision-making in pancreatic cancer when their recommendations cite guideline sources.
•AuntMinnie
AI Model Using Mammograms Enhances Five-Year Breast Cancer Risk Assessment
A new image-only AI model more accurately predicts five-year breast cancer risk than breast density alone, according to multinational research presented at RSNA 2025.
•Radiology Business
AI Model Uses CT Scans to Reveal Biomarker for Chronic Stress
Researchers developed an AI model to measure chronic stress using adrenal gland volume on routine CT scans.