SU-E-J-185: 4DCT Geometrical Eigenmode Model for Inter-Fraction Evaluation of Tumor Regression and Breathing Pattern Changes

Medical Physics
V KearneyLaura Cerviño

Abstract

Evaluate the feasibility of using intra-fractional respiratory dominant eigenmodes of lung deformation as a method to track inter-fractional tumor regression and other physiological changes. Geometrical evaluation by dominant eigenmodes during free-breathing may be implemented as an IGART tool for assessing inter-fractional non-respiratory anatomical variation. Intra-fractional deformable image registration (DIR) is performed on 4DCT scans of lung cancer patients. Principal component analysis is conducted on a set of 10 deformation vector fields for each patient both with and without a lung mask. Leave-one-out cross-validation (LOOCV) is used to assess intra-fractional modeling error among a subset of respiratory phases. The first two dominant eigenmodes of PCA are compared across patients in axial, sagittal, and coronal slices. Eigenvalues between the first and second dominant respiratory modes decay by a factor of ten for all patients. Intra-fractional LOOCV maximum error is on the order of 1mm inside the lung and 4-6mm for the whole thorax for all patients using the first two dominant eigenmodes. Eigenvalue decay is fastest for patients where diaphragm motion is relatively larger in magnitude. The first two eigenmodes genera...Continue Reading

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