What question did this study set out to answer?

This study investigates how novel CT imaging correlates ventilation-perfusion mismatch with gas transfer measurements.

May 20, 2026

C73-14 Defects From Novel Contrast-free CT 3d Ventilation- Perfusion Mismatch Imaging Are Related to Measurements of Gas Transfer

Key Points

This study investigates how novel CT imaging correlates ventilation-perfusion mismatch with gas transfer measurements.
Forty-six participants were categorized into three groups: pulmonary embolism, chronic lung disease, and pulmonary intervention.
All participants underwent spirometry, gas exchange testing, and non-contrast inspiratory-expiratory CT scans.
Ventilation-perfusion maps were generated to quantify regional lung function.
Significant correlations were found between gas transfer metrics (DLCO) and lung areas classified as shunt and dead space (p < 0.001 each).
The strongest association with DLCO occurred when combining all detected categories into an abnormal lung fraction (r² = 0.67, p < 0.001).
The pulmonary intervention group exhibited higher levels of shunt, dead space, and matched defects compared to other groups (p < 0.001 each).

Abstract

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

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