Effects of Intra-patient Lung Volume Variability on CT-Based Emphysema Quantification: A Virtual Imaging Study

Area of Science:

• Pulmonary Imaging and Diagnostics
• Computational Modeling in Medicine
• Radiomics and Quantitative Imaging

Background:

• Computed tomography (CT) scans are crucial for diagnosing and quantifying emphysema.
• Variability in patient lung volume during CT acquisition affects measurement consistency.
• Ethical constraints and radiation risks limit studies requiring repeated patient imaging at different lung volumes.

Purpose of the Study:

• To isolate and quantify the impact of lung volume variability on CT-based emphysema measurements.
• To evaluate the effectiveness of different total lung volume (TLV) correction methods in mitigating these variabilities.
• To utilize a virtual imaging trial approach to overcome limitations of human subject studies.

Main Methods:

• Creation of 20 emphysema human models at varying inspiration levels (70%-100% full inspiration).
• Generation of simulated CT images using a scanner-specific simulator (DukeSim).
• Computation of emphysema biomarkers (LAA-950, Perc15) and global lung density; analysis using linear mixed-effects models with physiological and statistical TLV correction.

Main Results:

• Inspiration level significantly affected LAA-950 and Perc15 measurements (p<0.001).
• LAA-950 underestimated emphysema by 1.44±0.32% per liter deviation from full inspiration.
• Perc15 underestimated severity by 1.16±0.02% per 1% lower lung volume; TLV correction methods reduced these deviations.

Conclusions:

• Virtual imaging trials effectively isolate lung volume variability's impact on emphysema quantification.
• Physiological model-based TLV correction is superior to statistical models for mitigating volume-dependent variability.
• This study demonstrates a novel investigation method not feasible with human subjects or simple phantoms.