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Validation of Robust CT-Ventilation Methods

E Castillo1*, R Castillo2, Y Vinogradskiy3, G Nair1, I Grills1, T Guerrero1, C Stevens1, (1) Beaumont Health System, Royal Oak, MI, (2) Emory Univ, Atlanta, GA, (3) University of Colorado Denver, Aurora, CO

Presentations

(Sunday, 7/12/2020)   [Eastern Time (GMT-4)]

Room: AAPM ePoster Library

Purpose: Computed tomography (CT) derived ventilation imaging employs deformable image registration (DIR) to recover respiratory motion-induced voxel volume changes as a surrogate for pulmonary ventilation. The transformation-based Integrated Jacobian Formulation (IJF) and the intensity-based Mass Conserving Volume Change (MCVC) methods were recently shown to be robust to variations in DIR solution. Both methods are based on making subregional volume change measurements satisfying a specified uncertainty tolerance. However, smaller uncertainties come at the expense of lower measurement resolution. We determine the uncertainty parameters which yield the highest physiological fidelity for MCVC and IJF.

Methods: The single photon emission CT ventilation (SPECT-V) images and radiotherapy planning 4DCTs acquired prior to treatment for ten patients with non-small cell lung cancer were used to conduct a sweep of the uncertainty parameter. The parameter specifies the magnitude of the 95% confidence interval corresponding to the estimated mean Jacobian within each subregional volume. For each test case, IJF images were computed with seven different uncertainty parameters: [0.015, 0.02, 0.025, 0.05, 0.10, 0.15, 0.20]. Voxel-wise Spearman correlations between the resulting ventilation images and SPECT-V were computed. The process was repeated for MCVC.

Results: The median voxel-wise Spearman correlation corresponding to the seven uncertainty levels ranged between [0.459, 0.471] for IJF, and [0.224, 0.425] for MCVC. The optimal IJF uncertainty parameter was 0.05, which resulted in correlations ranging between [0.165, 0.578] across the 10 cases. The optimal MCVC uncertainty parameter was 0.015, which resulted in correlations ranging between [-0.096, 0.701] across the 10 cases.

Conclusion: Correlation variations across the parameter sweep were marginal for both methods, indicating robustness to uncertainty parameter. Moreover, the high overall correlations demonstrate that robust ventilation methods are both reproducible and physiologically accurate.

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Keywords

Ventilation/perfusion, CT, Image Processing

Taxonomy

IM/TH- Image Analysis (Single Modality or Multi-Modality): Image processing

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