A novel method for generating a fused ventilation-perfusion map using CT-derived ventilation and FDG-PET for lung...

Pulmonary ventilation-perfusion function plays a crucial role in both radiotherapy planning and prognosis assessment in patients with lung cancer. However, there remains a lack of rapid and cost-effective imaging modalities capable of accurately capturing this functional parameter.

This study aimed to develop a lung functional image that reflects ventilation-perfusion characteristics by integrating computed tomography (CT) and (positron emission tomography) PET imaging techniques, with the objective of enhancing lung dose evaluation in radiotherapy planning.

A retrospective analysis was performed on twenty lung cancer patients using CT images acquired at two respiratory phases and FDG-PET/CT images. The Elastic Distortion algorithm was applied for deformable image registration, with the end-expiration phase CT serving as the baseline. Values derived from the determinant Jacobian matrices of ventilation CT (V-CT) images and the gray-value matrices of PET images were normalized to a range of 0 to 1. These normalized values were multiplied to generate a ventilation-perfusion matrix. Three types of lung functional images were produced from these matrices: ventilation-imaging (V-imaging), perfusion-imaging (P-imaging), and ventilation-perfusion- imaging (VP-imaging). The Dice Similarity Coefficient (DSC) and Bland-Altman plots were used to assess the correlations and discrepancies among the imaging modalities.

The DSC values for the entire lung, regions with low 30% functionality, and regions with high 40% functionality were 0.39 ± 0.05, 0.50 ± 0.03, and 0.20 ± 0.05 for V-P; 0.58 ± 0.03, 0.73 ± 0.03, and 0.32 ± 0.02 for V-VP; and 0.68 ± 0.04, 0.78 ± 0.04, and 0.34 ± 0.04 for P-VP, respectively. Notably, significant concordance was observed between V-VP and P-VP images within the delineated functional lung regions.#x02013;Altman analysis supported the DSC results, revealing high correlation coefficients in the low 30% functional lung region: 0.628 for V-P, 0.857 for V-VP, and 0.779 for P-VP. In contrast, similarity within the high 40% functional regions was markedly lower.

This study developed a novel method for generating a fused VP map by integrating CT-derived ventilation and FDG-PET data. The method demonstrated feasibility, and the resulting VP map provided a balanced representation of both ventilation and perfusion signals, particularly in regions with reduced lung function.