Correlation between CT-based phenotypes and serum biomarker in interstitial lung diseases

The quantitative analysis of computed tomography (CT) and Krebs von den Lungen-6 (KL-6) serum level has gained importance in the diagnosis, monitoring, and prognostication of interstitial lung disease (ILD). However, the associations between quantitative analysis of CT and serum KL-6 level remain poorly understood.

In this retrospective observational study conducted at tertiary hospital between June 2020 and March 2022, quantitative analysis of CT was performed using the deep learning-based method including reticulation, ground glass opacity (GGO), honeycombing, and consolidation. We investigated the associations between CT-based phenotypes and serum KL-6 measured within three months of the CT scan. Furthermore, we evaluated the performance of the combined CT-based phenotypes and KL-6 levels in predicting hospitalizations due to respiratory reasons of ILD patients.

A total of 131 ILD patients (104 males) with a median age of 67 years were included in this study. Reticulation, GGO, honeycombing, and consolidation extents showed a positive correlation with KL-6 levels. [Reticulation, correlation coefficient (r) = 0.567, p < 0.001; GGO, r = 0.355, p < 0.001; honeycombing, r = 0.174, p = 0.046; and consolidation, r = 0.446, p < 0.001]. Additionally, the area under the ROC of the combined reticulation and KL-6 for hospitalizations due to respiratory reasons was 0.810 (p < 0.001).

Quantitative analysis of CT features and serum KL-6 levels ascertained a positive correlation between the two. In addition, the combination of reticulation and KL-6 shows potential for predicting hospitalizations of ILD patients due to respiratory causes. The combination of reticulation, focusing on phenotypic change in lung parenchyma, and KL-6, as an indicator of lung injury extent, could be helpful for monitoring and predicting the prognosis of various types of ILD.