Abstract Rationale Efficient pulmonary gas exchange depends on balanced ventilation (V) and perfusion (Q). Imbalances between these processes impair respiratory function. A recently developed imaging technique (4DMedical™ CT:VQ) enables quantitative assessment of ventilation and perfusion using standard, non-contrast CT scans. This study presents a novel method to generate three-dimensional ventilation-perfusion (V/Q) images from CT:VQ data and investigates the relationship between V/Q-derived mismatch metrics and diffusing capacity for carbon monoxide (DLCO). Methods Forty-six participants were prospectively recruited and categorized into three groups: sub-acute pulmonary embolism (PE) (n = 9), chronic lung disease (n = 27; including COPD and bronchitis with GOLD 0, n = 11), and pulmonary intervention assessment (n = 5). All participants underwent spirometry, gas exchange testing, and a non-contrast paired inspiratory-expiratory CT scan.From the CT data, ventilation-perfusion (V/Q) maps were generated to quantify regional lung function. Lung regions were classified as: Dead space - low perfusion with preserved ventilation (high V/low Q) Shunt - low ventilation with preserved perfusion (low V/high Q) Matched defects - concurrent reductions in both ventilation and perfusion (low V/low Q) Results Across the entire cohort, both the percentage of lung classified as shunt (p 0.001) and dead space (p 0.001) showed significant correlations with DLCO (% predicted). The strongest association with DLCO was observed when all detected categories were combined into a total abnormal fraction of lung tissue (r² = 0.67, p 0.001; Figure 1D). The pulmonary intervention assessment group demonstrated significantly elevated levels of shunt (p 0.001), dead space (p 0.001), and matched defects (p 0.001) compared with the other groups Conclusions This study demonstrates that ventilation-perfusion (V/Q) matching can be derived from non-contrast CT scans. The proportion of V/Q mismatch was directly associated with gas exchange efficiency. Additionally, this imaging method enables spatial visualization of mismatch distribution within the lungs. Beyond structural assessment, CT-based V/Q mapping offers functional data that may support personalized treatment strategies and precision management of respiratory disease. Figure 1: Example from a subject with confirmed PE in the right upper lobe and right middle lobe (red arrows). Perfusion image from CT:VQ. Ventilation image from CT:VQ. VQ matching image derived from CT:VQ. Relationship between total mismatch defects and DLCO in the cohort This abstract is funded by: 4D Medical
Nilsen et al. (Fri,) studied this question.