Mapping lung ventilation through stress maps derived from biomechanical models of the lung

Purpose Most existing computed tomography (CT)‐ventilation imaging techniques are based on deformable image registration (DIR) of different respiratory phases of a four‐dimensonal CT (4DCT) scan of the lung, followed by the quantification of local breathing‐induced changes in Hounsfield Units (HU) or volume. To date, only moderate correlations have been reported between these CT‐ventilation metrics and standard ventilation imaging modalities for adaptive lung radiation therapy. This study evaluates the use of stress maps derived from biomechanical model‐based DIR as an alternative CT‐ventilation metric. Materials and methods Six patients treated for lung cancer with conventional radiation therapy were retrospectively analyzed. For each patient, a 4DCT scan and Tc‐99m SPECT‐V image acquired for treatment planning were collected. Biomechanical model‐based DIR was applied between the inhale and exhale phase of the 4DCT scans and stress maps were calculated. The voxel‐wise correlation between the reference SPECT‐V image and map of the maximum principal stress was measured with a Spearman correlation coefficient. The overlap between high (above the 75th percentile) and low (below the 25th percentile) functioning volumes extracted from the reference SPECT‐V and the stress maps was measured with Dice similarity coefficients (DSC). The results were compared to those obtained when using two classical CT‐ventilation metrics: the change in HU and Jacobian determinant. Results The mean Spearman correlation coefficients were: 0.37 ± 18 and 0.39 ± 13 and 0.59 ± 0.13 considering the changes in HU, Jacobian and maximum principal stress, respectively. The corresponding mean DSC coefficients were 0.38 ± 0.09, 0.37 ± 0.07 and 0.52 ± 0.07 for the high ventilation function volumes and 0.48 ± 0.13, 0.44 ± 0.09 and 0.52 ± 0.07 for the low ventilation function volumes. Conclusion For presenting a significantly stronger and more consistent correlation with standard SPECT‐V images than previously proposed CT‐ventilation metrics, stress maps derived with the proposed method appear to be a promising tool for incorporation into functional lung avoidance strategies.