Low morphometric complexity of emphysematous lesions predicts survival in chronic obstructive pulmonary disease patients

Objectives

To investigate whether morphometric complexity in the lung can predict survival and act as a new prognostic marker in patients with chronic obstructive pulmonary disease (COPD).

Methods

COPD (n = 302) patients were retrospectively reviewed. All patients underwent volumetric computed tomography and pulmonary function tests at enrollment (2005–2015). For complexity analysis, we applied power law exponent of the emphysema size distribution (D_size) as well as box-counting fractal dimension (D_box3D) analysis. Patients' survival at February 2017 was ascertained. Univariate and multivariate Cox proportional hazards analyses were performed, and prediction performances of various combinatorial models were compared.

Results

Patients were 66 ± 6 years old, had 41 ± 28 pack-years' smoking history and variable GOLD stages (n = 20, 153, 108 and 21 in stages I−IV). The median follow-up time was 6.1 years (range: 0.2−11.6 years). Sixty-three patients (20.9%) died, of whom 35 died of lung-related causes. In univariate Cox analysis, lower D_size and D_box3D were significantly associated with both all-cause and lung-related mortality (both p < 0.001). In multivariate analysis, the backward elimination method demonstrated that D_box3D, along with age and the BODE index, was an independent predictor of survival (p = 0.014; HR, 2.08; 95% CI, 1.16–3.71). The contributions of D_size and D_box3D to the combinatorial survival model were comparable with those of the emphysema index and lung-diffusing capacity.

Conclusions

Low morphometric complexity in the lung is a predictor of survival in patients with COPD.

Key Points

• A newly suggested method for quantifying lung morphometric complexity is feasible.

• Morphometric complexity measured on chest CT images predicts COPD patients’ survival.

• Complexity, diffusing capacity and emphysema index contribute similarly to the survival model.