Abstract
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 clinically relevant organ deformations were created in prostate (distended rectum and rectal gas), head and neck (large neck flexion), and lung (inhale and exhale lung volumes with variable contrast enhancement) study sets. DIR was performed using both B‐spline and diffeomorphic demons algorithms in the forward and inverse direction. A compositive accumulation of forward and inverse deformation vector fields was done to quantify the inverse consistency error (ICE). The anatomical correspondence of tumor and organs at risk was quantified by comparing the original RT structures with those obtained after DIR. Further, the physical characteristics of the deformation field, namely the Jacobian and harmonic energy, were computed to quantify the preservation of image topology and regularity of spatial transformation obtained in DIR. The ICE was comparable in prostate case but the B‐spline algorithm had significantly better anatomical correspondence for rectum and prostate than diffeomorphic demons algorithm. The ICE was 6.5 mm for demons algorithm for head and neck case when compared to 0.7 mm for B‐spline. Since the induced neck flexion was large, the average Dice similarity coefficient between both algorithms was only 0.87, 0.52, 0.81, and 0.67 for tumor, cord, parotids, and mandible, respectively. The B‐spline algorithm accurately estimated deformations between images with variable contrast in our lung study, while diffeomorphic demons algorithm led to gross errors on structures affected by contrast variation. The proposed framework offers the application of known deformations on any image datasets, to evaluate the overall accuracy and limitations of a DIR algorithm used in radiation oncology. The evaluation based on anatomical correspondence, physical characteristics of deformation field, and image characteristics can facilitate DIR verification with the ultimate goal of implementing adaptive radiotherapy. The suitability of application of a particular evaluation metric in validating DIR is dependent on the clinical deformation observed.PACS numbers: 87.57 nj, 87.55‐x,87.55 Qr
Highlights
Image-guided radiation therapy (IGRT) has become a widely used treatment modality in recent past with advanced treatment processes
Deformable image registration (DIR) studies have been advocated to more accurately quantify these anatomical and biological variations.[1]. Deformable registration is essential to map the position of each voxel to a reference CT image for dose tracking and to practice adaptive radiotherapy.[2,3] The accuracy of deformable registration is important in intensity-modulated radiation therapy (IMRT) and adaptive radiotherapy that deliver differential doses to different parts of the tumor and organs at risk, which sum to a uniform dose
As an example for the prostate case, the deformation vector field (DVF) from diffeomorphic demons algorithm is overlaid on the original kvCT image for forward, inverse, and compositive addition of forward and inverse DVFs is shown in Figs. 13, 14, and 15, respectively
Summary
Image-guided radiation therapy (IGRT) has become a widely used treatment modality in recent past with advanced treatment processes. IGRT requires daily or frequent imaging, which can lead to treatment planning modification decisions based on patient-specific anatomical variations as quantified by the imaging. Routine IGRT in most clinical departments uses only the vendor-supplied rigid registration matching between original treatment planning CT (kvCT) and the daily imaging study set. Deformable image registration (DIR) studies have been advocated to more accurately quantify these anatomical and biological variations.[1] Deformable registration is essential to map the position of each voxel to a reference CT image for dose tracking and to practice adaptive radiotherapy.[2,3] The accuracy of deformable registration is important in intensity-modulated radiation therapy (IMRT) and adaptive radiotherapy that deliver differential doses to different parts of the tumor and organs at risk, which sum to a uniform dose. It has been suggested that the presence of uniform intensity regions in the phantom images, as opposed to more intensity gradients in clinical CT images, may limit the applicability of phantom tests in DIR verification.[16]
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
