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. 2025;2(1):25.
doi: 10.1038/s44385-025-00027-9. Epub 2025 Jul 4.

CT-derived functional imaging biomarkers combined with FEV1 for predicting 10-year all-cause mortality in COPDGene cohort

Girish Nair  1 , Yuying Judy Xing  2 , Aaron Luong  3 , Faiza Bashar  4 , Amanda Nowacki  3 , Craig Stevens  5 , Lili Zhao  6 , Edward Castillo  3
Affiliations

CT-derived functional imaging biomarkers combined with FEV1 for predicting 10-year all-cause mortality in COPDGene cohort

Girish Nair et al. NPJ Biomed Innov. 2025.

Abstract

This study evaluates the predictive power of CT-derived functional imaging (CTFI) combined with forced expiratory volume in 1 second (FEV1) for 10-year all-cause mortality in COPD patients. We analyzed 8583 participants from the COPDGene® cohort, focusing on 3550 participants with spirometric obstruction. CTFI metrics, including ventilation (CT-V) and perfusion (PBM), were computed from non-contrast CT scans at lobar resolution. Our findings show that regional and global CTFI scores decline with advancing GOLD stages. A Random Survival Forest model, adjusted for age, BMI, and scanner type, demonstrated significant improvement in mortality prediction when combining FEV1 with CTFI, compared to FEV1 alone, with an AUC increase from 0.71 to 0.76 over 10 years. The Net Reclassification Index further confirmed the added predictive value of CTFI. These results suggest that integrating CTFI with traditional lung function measures enhances mortality prediction in COPD, offering a promising tool for clinical risk assessment.

Keywords: Medical research; Predictive markers.

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Conflict of interest statement

Competing interestsEdward Castillo reports financial support was provided by National Heart Lung and Blood Institute. Girish Nair reports financial support was provided by National Heart Lung and Blood Institute. Lili Zhao reports financial support was provided by National Heart Lung and Blood Institute. Edward Castillo reports a relationship with 4D Medicine Ltd that includes: consulting or advisory and funding grants. Edward Castillo has patent #10932744 licensed to 4D Medical LTD. All other authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Figures

Fig. 1
Fig. 1
Survival probability in the population from baseline divided on GOLD stage. At six years GOLD I – IV are 0.92 (0.90, 0.94), 0.86 (0.84, 0.88), 0.75 (0.72, 0.78), 0.49 (0.44, 0.54) respectively.
Fig. 2
Fig. 2
AUC of Random Survival Forest model comparing CTFI + FEV1 without and after including for age, BMI and scanner type.
Fig. 3
Fig. 3. Violin plots for CTV (top) and PBM regional changes (bottom) with increasing GOLD stage by lobe.
The violin plot displays a rotated kernel density plot on each side and a box plot in the middle, which visualizes the distribution and summary statistics of the data.
Fig. 3
Fig. 3. Violin plots for CTV (top) and PBM regional changes (bottom) with increasing GOLD stage by lobe.
The violin plot displays a rotated kernel density plot on each side and a box plot in the middle, which visualizes the distribution and summary statistics of the data.
Fig. 4
Fig. 4
Net Reclassification Index for Random Survival Forest prediction model CTFI + FEV1 with age, BMI, and scanner type showed significant improvement in the mortality prediction over the model without CTFI.
Fig. 5
Fig. 5. PBM imaging in patients with increasing GOLD stages. Red areas showing higher CT-perfusion and blue regions low perfusion.
The global PBM decreases with advancing GOLD stages, but the regional distribution of PBM is characteristically different.
Fig. 6
Fig. 6
Consort diagram explaining inclusion and exclusion.
See this image and copyright information in PMC

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