CT Ventilation Metrics Correlate With Spirometry in Healthy Adults

Quantifying Regional Lung Function Beyond Global Spirometry

Chronic respiratory diseases and lung malignancies represent a substantial portion of the global disease burden, with lung cancer remaining the leading cause of cancer-related mortality worldwide [1, 2]. While high-resolution computed tomography (CT) and pulmonary function tests are standard for monitoring fibrotic interstitial lung diseases, these modalities are often limited by inter-observer variability and a lack of localized functional data [3]. Meta-analytic evidence involving 3,320 participants indicates that while serum biomarkers like Krebs von den Lungen-6 (KL-6) offer a pooled specificity of 0.90 (95% confidence interval: 0.85 to 0.93) for identifying fibrosis, they cannot provide the spatial resolution necessary to map regional physiological changes [3]. Traditional spirometry provides a useful global assessment of lung capacity, yet it frequently fails to identify localized areas of impairment that may precede systemic decline [4]. As clinical focus shifts toward personalized phenotyping, a process of identifying specific observable traits to tailor individual treatment, there is an increasing demand for objective, spatially resolved metrics of lung ventilation. A recent study addresses this clinical necessity by defining standardized reference intervals for ventilation quantified through paired CT imaging, offering physicians a quantitative tool to detect early regional lung dysfunction.

Establishing Normative Baselines via Paired CT Imaging

To define the physiological range of regional lung function in a healthy population, researchers conducted a prospective, single-center investigation between December 2022 and April 2024. The team initially recruited 103 healthy adults who underwent a specialized imaging protocol consisting of paired inspiratory and expiratory CT scans. To ensure the scans captured maximum lung inflation and deflation, the imaging was spirometry-guided, requiring patients to perform breathing maneuvers into a device that synchronized the CT acquisition with specific lung volumes. After quality control, the final analysis included 91 participants with a mean age of 53 ± 12 years, comprising a nearly evenly split cohort that included 49 men. To map ventilation at a granular level, the researchers employed automated lobe segmentation using TotalSegmentator, an artificial intelligence tool that delineates the five pulmonary lobes without manual intervention. The core metric of the study was voxel-wise ventilation, which measures air volume changes at the level of tiny three-dimensional pixels. This was quantified as the relative air volume change between the inspiration and expiration phases. To accurately compare these two different states, the team used nonlinear registration, a computational method that aligns and warps the expiratory image to match the shape of the inspiratory lung. This technique allows for a direct point-to-point comparison of tissue expansion, which was then normalized to the total inspiratory lung volume to provide a standardized percentage of ventilation across the entire organ. Ultimately, the study established that the mean CT-derived ventilation across the cohort was 59.5% ± 8.5%, with a defined 5th to 95th percentile reference interval of 42.1% to 72.5%. For practicing clinicians, these normative values provide a quantitative baseline to objectively classify regional lung dysfunction, reducing the subjectivity often associated with visual scan interpretation.

Correlation and Divergence Between CT and Pulmonary Function Tests

The researchers compared CT-derived lung volumes against the established clinical standard of pulmonary function tests, specifically examining total lung capacity, residual volume, and vital capacity. While the CT-derived ventilation metrics correlate strongly with pulmonary function test indices, the data revealed a systematic underestimation of absolute volumes when using imaging. Specifically, CT-derived total lung capacity was 13.8% lower than values obtained via pulmonary function tests, though it maintained a high correlation coefficient of r = 0.89. Similarly, CT-derived residual volume was 2.5% lower than traditional test values (r = 0.80), and CT-derived vital capacity was 20.8% lower than standard measurements (r = 0.82). To provide a standardized framework for clinical interpretation alongside these volume differences, the study reiterated its reference intervals reported as mean ± standard deviation and 5th to 95th percentiles. The mean CT-derived ventilation across the cohort was 59.5% ± 8.5%, representing the average relative air volume change between the inspiratory and expiratory phases. The researchers defined the 5th to 95th percentile range for mean ventilation as 42.1% to 72.5%, establishing a normative baseline that allows clinicians to distinguish physiological variation from regional lung dysfunction. These findings demonstrate that although CT imaging yields lower absolute volume values than traditional spirometry, its strong correlation with established pulmonary function test metrics provides a reliable, spatially resolved assessment of pulmonary mechanics that can complement standard global measurements.

Impact of Demographics and Anatomy on Ventilation Distribution

To understand the drivers of physiological variation, the researchers employed multivariable analyses, a statistical method used to determine the independent effect of several variables on a single outcome, to assess the effects of sex, age, height, lung region, and gravitational orientation on ventilation. The results demonstrated that ventilation decreased significantly with increasing age (p < 0.001), while ventilation increased significantly with height (p < 0.05). These findings underscore that demographic and anatomical factors significantly influence the distribution of lung ventilation, suggesting that a uniform approach to interpreting regional lung function may overlook normal age-related or stature-related variations. The study also identified distinct patterns of regional heterogeneity within the lung parenchyma that clinicians must distinguish from true pathology. Ventilation was significantly higher in the lower lobes compared to other lobes (p < 0.003), a finding that aligns with the known physiological gradient of air distribution. Additionally, the researchers found that ventilation was significantly higher in posterior lung regions (p < 0.001), likely reflecting the impact of gravitational orientation on the dependent portions of the lungs. Establishing these specific regional baselines is critical for clinical practice, as it allows physicians to differentiate expected physiological heterogeneity from early signs of regional dysfunction, such as localized air trapping in chronic obstructive pulmonary disease or small airway disease in early interstitial fibrosis.

References

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2. Torre LA, Bray F, Siegel RL, Ferlay J, Lortet‐Tieulent J, Jemal A. Global cancer statistics, 2012. CA A Cancer Journal for Clinicians. 2015. doi:10.3322/caac.21262

3. Tzang C, Lin W, Huang ES, et al. Interstitial lung disease biomarkers: a systematic review and meta-analysis.. Clinica chimica acta; international journal of clinical chemistry. 2025. doi:10.1016/j.cca.2025.120473

4. Galiè N, Humbert M, Vachiéry J, et al. 2015 ESC/ERS Guidelines for the diagnosis and treatment of pulmonary hypertension. European Heart Journal. 2015. doi:10.1093/eurheartj/ehv317