Keywords: Lung, Quantitative Imaging, COPD
Motivation: To develop dynamic ventilation metrics that are robust to breathing behaviour and can identify nonlinear responses of MR signal to lung expansion.
Goal(s): To extend Voxel-wise Lung Ventilation (VOLVE) analysis by incorporating cross-correlation metrics to account for phase shifts between the navigator (global) and lung parenchyma (local) respiratory signal representing delays in ventilation.
Approach: Prospective pilot study using VOLVE analysis incorporating cross-correlation of navigator and lung parenchyma signals.
Results: Significant differences between healthy and COPD groups in the cross-correlation metrics, with both a reduction in amplitude indicating reduced signal linearity and increase in phase shift (lag) indicating delayed ventilation.
Impact: Voxel-wise Lung Ventilation (VOLVE) analysis incorporating cross-correlation and lag enables the distinction between lung regions with delayed ventilation from regions where ventilation signal is static. This additional insight into nonlinear ventilation dynamics will improve understanding of changes in lung function.
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