Quantitative validation of deformable image registration (DIR) algorithms is extremely difficult because of the complexity involved in constructing a deformable phantom that can duplicate various clinical scenarios. The purpose of this study is to describe a framework to test the accuracy of DIR based on computational modeling and evaluating using inverse consistency and other methods. Three cl...

BACKGROUND Deformable image registration (DIR) is an attractive method for automatic propagation of regions of interest (ROIs) in adaptive lung radiotherapy. This study investigates DIR for automatic contour propagation in adaptive Non Small Cell Lung Carcinoma patients. METHODS Pre and mid-treatment fan beam 4D-kVCT scans were taken for 17 NSCLC patients. Gross tumour volumes (GTV), nodal-GT...

PURPOSE To establish the fundamental relationship between deformation and its causative physical force using a deformable bladder phantom. To ascertain if a threshold limit exists for DIR accuracy, beyond which its applicability in deformed anatomy may be clinically inappropriate. METHODS A tissue equivalent deformable bladder phantom with 21 implanted aluminum markers was developed using a v...

PURPOSE Deformable image registration (DIR) is necessary for accurate dose accumulation between multiple radiotherapy image sets. DIR algorithms can suffer from inverse and transitivity inconsistencies. When using deformation vector fields (DVFs) that exhibit inverse-inconsistency and are nontransitive, dose accumulation on a given image set via different image pathways will lead to different a...

BACKGROUND Commonly used methods of assessing the accuracy of deformable image registration (DIR) rely on image segmentation or landmark selection. These methods are very labor intensive and thus limited to relatively small number of image pairs. The direct voxel-by-voxel comparison can be automated to examine fluctuations in DIR quality on a long series of image pairs. METHODS A voxel-by-vox...

BACKGROUND The aim of this study is to develop a methodology to standardize the analysis and reporting of the patterns of loco-regional failure after IMRT of head and neck cancer. MATERIAL AND METHODS Twenty-one patients with evidence of local and/or regional failure following IMRT for head-and-neck cancer were retrospectively reviewed under approved IRB protocol. Manually delineated recurren...

Background/Aim: This study aimed to determine appropriate deformable image registration (DIR) algorithms for pancreatic cancer patients undergoing carbon ion radiotherapy (CIRT). Patients and Methods: The performance of three types DIR algorithms, including intensity-based (iDIR), contour-based (cDIR), hybrid (hDIR) were evaluated using seventy-one CT images from eight patients. Both the geomet...

Statistical models of deformations (SMD) capture the variability of deformations from the template image onto a group of sample images and can be used to constrain the traditional deformable registration algorithms to improve their robustness and accuracy. This paper employs a wavelet-PCA-based SMD to constrain the traditional deformable registration based on the Bayesian framework. The templat...

BACKGROUND Adaptive Radiotherapy aims to identify anatomical deviations during a radiotherapy course and modify the treatment plan to maintain treatment objectives. This requires regions of interest (ROIs) to be defined using the most recent imaging data. This study investigates the clinical utility of using deformable image registration (DIR) to automatically propagate ROIs. METHODS Target (...