Purpose: To generate a comprehensive map of regional lung function including both ventilation and perfusion in a single dynamic contrast-enhanced CT scan using a volumetric CT scanner.
Methods: Two patients with non-small cell lung cancer were imaged on a GE Revolution volumetric CT scanner before and 6 weeks after radiotherapy with standard fractionation. Images were acquired at a single couch position using the following parameters: cine mode, 0.28s/revolution, 100kV, 100mA, and 160mm axial field-of-view for 45-50s. Iodine-based contrast was injected 6s after the start of the acquisition. All images in the series were non-rigidly registered in Elastix using a b-splines transformation and a normalized mutual information metric. The lung volume was segmented on the registered images using a semi-automated density-based method. Blood flow maps were generated using GE’s prototype CT Perfusion software. End-inhale and end-exhale images were identified from the pre-contrast images and were used to calculate specific ventilation maps using an existing density-based method. Ventilation (V) and perfusion (Q) maps were normalized to the 99th percentile of the distribution to facilitate direct comparison, and V/Q maps were calculated as a ratio of the normalized maps.
Results: After radiotherapy, ventilation in the treated lung decreased for both patients and blood flow decreased in one patient but increased in the second. Tumour blood flow was heterogeneous in one patient, and uniformly low in the second. In both patients, regions of the lung that appear to have normal function based on ventilation or perfusion imaging alone are shown to have V/Q mismatch.
Conclusion: These results demonstrate the feasibility of generating both ventilation and perfusion imaging using volumetric CT in a single imaging protocol performed in under 1 minute. This method may facilitate the clinical translation of functional lung imaging in radiation treatment planning.
CT, Ventilation/perfusion, Image-guided Therapy
IM/TH- Image Analysis (Single Modality or Multi-Modality): Image processing