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Correlation of displacement vector fields calculated by different deformable image registration algorithms with motion parameters in helical, axial and cone beam CT imaging

Published online by Cambridge University Press:  16 September 2019

Nesreen Alsbou ,
Salahuddin Ahmad  and
Imad Ali Open the ORCID record for Imad Ali [Opens in a new window]
Nesreen Alsbou
Affiliation:
Department of Engineering and Physics, Howell Hall 221R, University of Central Oklahoma, Edmond, OK, USA
Salahuddin Ahmad
Affiliation:
Department of Radiation Oncology, University of Oklahoma Health Sciences Center, Oklahoma City, OK, USA
Imad Ali*
Affiliation:
Department of Radiation Oncology, University of Oklahoma Health Sciences Center, Oklahoma City, OK, USA
*
Author for correspondence: Imad Ali, Medical Physics, Department of Radiation Oncology, Stephenson Oklahoma Cancer Center, University of Oklahoma Health Sciences Center, 800 N.E. 10th Street, OKCC L100, Oklahoma City, OK 73104, USA. Tel: 405-271-8290. Fax: 405-271-8297. E-mail: iali@ouhsc.edu
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Abstract

Aim:

The purpose of this study is to investigate quantitatively the correlation of displacement vector fields (DVFs) from different deformable image registration (DIR) algorithms to register images from helical computed tomography (HCT), axial computed tomography (ACT) and cone beam computed tomography (CBCT) with motion parameters.

Materials and methods:

CT images obtained from scanning of the mobile phantom were registered with the stationary CT images using four DIR algorithms from the DIRART software: Demons, Fast-Demons, Horn–Schunck and Lucas–Kanade. HCT, ACT and CBCT imaging techniques were used to image a mobile phantom, which included three targets with different sizes (small, medium and large) that were manufactured from a water-equivalent material and embedded in low-density foam to simulate lung lesions. The phantom was moved with controlled cyclic motion patterns where a range of motion amplitudes (0–20 mm) and frequencies (0·125–0·5 Hz) were used.

Results:

The DVF obtained from different algorithms correlated well with motion amplitudes applied on the mobile phantom for CBCT and HCT, where the maximal DVF increased linearly with the motion amplitudes of the mobile phantom. In ACT, the DVF correlated less with motion amplitudes where motion-induced strong image artefacts and the DIR algorithms were not able to deform the ACT image of the mobile targets to the stationary targets. Three DIR algorithms produce comparable values and patterns of the DVF for certain CT imaging modality. However, DVF from Fast-Demons deviated strongly from other algorithms at large motion amplitudes.

Conclusions:

The local DVFs provide direct quantitative values for the actual internal tumour shifts that can be used to determine margins for the internal target volume that consider tumour motion during treatment planning. Furthermore, the DVF distributions can be used to extract motion parameters such as motion amplitude that can be extracted from the maximal or minimal DVF calculated by the different DIR algorithms and used in the management of the patient motion.

Keywords

CT imagesdeformable image registrationdisplacement vector fieldsmotion artefactsrespiratory motion
Type
Original Article
Information
Journal of Radiotherapy in Practice , Volume 19 , Issue 3 , September 2020 , pp. 219 - 225
Copyright
© Cambridge University Press 2019

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