Constructing Surrogate Lung Ventilation Maps from 4DCT-derived Subregional Respiratory Dynamics.

Abstract

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

Materials and methods: We retrospectively analyzed three subject cohorts from the VAMPIRE 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, while 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 to 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 radiotherapy (FLA-RT) planning.

Results: The extracted SRD highlighted temporally varying subregional volume and CT 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 three cohorts, while 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 to 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 to classical algorithms. The capability to extract multidimensional ventilation-correlated image information from widely available 4DCT images showed promise in enhancing personalized FLA-RT implementations.