Constructing Surrogate Lung Ventilation Maps From 4-Dimensional Computed Tomography-Derived Subregional Respiratory Dynamics.

Abstract

Purpose: To present a 2-stage framework that robustly extracts and maps reliable lung ventilation surrogates based on subregional respiratory dynamics (SRDs) measured from 4-dimensional computed tomography (4DCT) images, with comprehensive consideration of spatial and temporal heterogeneity in the ventilation process over the respiratory cycle.

Methods and materials: We retrospectively analyzed 3 subject cohorts from the Ventilation and Medical Pulmonary Image Registration Evaluation challenge containing 4DCT and reference ventilation imaging (RefVI) scans. Lung subregions were partitioned on the 4DCT end-of-exhale base phase using anatomically constrained simple linear iterative clustering, whereas sliding-preserved interphase image registrations were performed between the base and other phases. SRDs of breathing-induced volume and intensity changes were tracked across phases utilizing the displacement fields. Voxel-level representations integrating mechanical collapsibility and physiological tissue density (V_SRD) were accordingly constructed from SRDs. Imaging performance of V_SRD as the proposed surrogate ventilation map was studied against RefVI scans and compared with classical biphasic Jacobian maps. The dosimetric performance evaluation was also conducted to assess the clinical benefits of incorporating V_SRD maps into functional lung avoidance radiation therapy (FLA-RT) planning.

Results: The extracted SRD highlighted temporally varying subregional volume and computed tomography intensity changes related to underlying functional physiology and pathologies. For imaging performance, the median Spearman correlation coefficients between V_SRD and RefVI scans were 0.600, 0.582, and 0.561 for the 3 cohorts, whereas median Dice similarity coefficients against RefVI scans showing the high (low)-functioning lung regions' concordances were 0.611 (0.626), 0.592 (0.620), and 0.601 (0.611), superior to biphasic Jacobian maps for both metrics. For dosimetric performance, V_SRD-guided FLA-RT plans achieved significantly better dose sparing of high-functioning lung regions compared with FLA-RT plans based on biphasic Jacobian maps.

Conclusions: V_SRD maps captured spatial and temporal heterogeneity in the ventilation process, providing improved ventilation representations compared with classical algorithms. The capability to extract multidimensional ventilation-correlated image information from widely available 4DCT images showed promise in enhancing personalized FLA-RT implementations.