Literature DB >> 31155990

Deformable image registration for radiation therapy: principle, methods, applications and evaluation.

Bastien Rigaud1, Antoine Simon1, Joël Castelli1, Caroline Lafond1, Oscar Acosta1, Pascal Haigron1, Guillaume Cazoulat2, Renaud de Crevoisier1.   

Abstract

Background: Deformable image registration (DIR) is increasingly used in the field of radiation therapy (RT) to account for anatomical deformations. The aims of this paper are to describe the main applications of DIR in RT and discuss current DIR evaluation methods.
Methods: Articles on DIR published from January 2000 to October 2018 were extracted from PubMed and Science Direct. Our search was restricted to articles that report data obtained from humans, were written in English, and address DIR methods for RT. A total of 207 articles were selected from among 2506 identified in the search process.
Results: At planning, DIR is used for organ delineation using atlas-based segmentation, deformation-based planning target volume definition, functional planning and magnetic resonance imaging-based dose calculation. In image-guided RT, DIR is used for contour propagation and dose calculation on per-treatment imaging. DIR is also used to determine the accumulated dose from fraction to fraction in external beam RT and brachytherapy, both for dose reporting and adaptive RT. In the case of re-irradiation, DIR can be used to estimate the cumulated dose of the two irradiations. Finally, DIR can be used to predict toxicity in voxel-wise population analysis. However, the evaluation of DIR remains an open issue, especially when dealing with complex cases such as the disappearance of matter. To quantify DIR uncertainties, most evaluation methods are limited to geometry-based metrics. Software companies have now integrated DIR tools into treatment planning systems for clinical use, such as contour propagation and fraction dose accumulation. Conclusions: DIR is increasingly important in RT applications, from planning to toxicity prediction. DIR is routinely used to reduce the workload of contour propagation. However, its use for complex dosimetric applications must be carefully evaluated by combining quantitative and qualitative analyses.

Entities:  

Year:  2019        PMID: 31155990     DOI: 10.1080/0284186X.2019.1620331

Source DB:  PubMed          Journal:  Acta Oncol        ISSN: 0284-186X            Impact factor:   4.089


  14 in total

1.  General and custom deep learning autosegmentation models for organs in head and neck, abdomen, and male pelvis.

Authors:  Asma Amjad; Jiaofeng Xu; Dan Thill; Colleen Lawton; William Hall; Musaddiq J Awan; Monica Shukla; Beth A Erickson; X Allen Li
Journal:  Med Phys       Date:  2022-02-07       Impact factor: 4.071

Review 2.  Adaptive proton therapy.

Authors:  Harald Paganetti; Pablo Botas; Gregory C Sharp; Brian Winey
Journal:  Phys Med Biol       Date:  2021-11-15       Impact factor: 3.609

3.  Detection of vessel bifurcations in CT scans for automatic objective assessment of deformable image registration accuracy.

Authors:  Guillaume Cazoulat; Brian M Anderson; Molly M McCulloch; Bastien Rigaud; Eugene J Koay; Kristy K Brock
Journal:  Med Phys       Date:  2021-08-25       Impact factor: 4.506

4.  Patient specific deep learning based segmentation for magnetic resonance guided prostate radiotherapy.

Authors:  Samuel Fransson; David Tilly; Robin Strand
Journal:  Phys Imaging Radiat Oncol       Date:  2022-06-03

5.  Relationship Between Radiation Pneumonitis Following Definitive Radiotherapy for Non-small Cell Lung Cancer and Isodose Line.

Authors:  Shigenobu Watanabe; Ichiro Ogino; Daisuke Shigenaga; Masaharu Hata
Journal:  In Vivo       Date:  2021 Nov-Dec       Impact factor: 2.155

6.  Accuracy of automatic deformable structure propagation for high-field MRI guided prostate radiotherapy.

Authors:  Rasmus Lübeck Christiansen; Lars Dysager; Anders Smedegaard Bertelsen; Olfred Hansen; Carsten Brink; Uffe Bernchou
Journal:  Radiat Oncol       Date:  2020-02-07       Impact factor: 3.481

7.  Dose-response of deformable radiochromic dosimeters for spot scanning proton therapy.

Authors:  Simon V Jensen; Lia B Valdetaro; Per R Poulsen; Peter Balling; Jørgen B B Petersen; Ludvig P Muren
Journal:  Phys Imaging Radiat Oncol       Date:  2020-11-20

8.  Quantitative assessment of intra- and inter-modality deformable image registration of the heart, left ventricle, and thoracic aorta on longitudinal 4D-CT and MR images.

Authors:  Alireza Omidi; Elisabeth Weiss; John S Wilson; Mihaela Rosu-Bubulac
Journal:  J Appl Clin Med Phys       Date:  2021-12-27       Impact factor: 2.102

9.  Automatic segmentation and applicator reconstruction for CT-based brachytherapy of cervical cancer using 3D convolutional neural networks.

Authors:  Daguang Zhang; Zhiyong Yang; Shan Jiang; Zeyang Zhou; Maobin Meng; Wei Wang
Journal:  J Appl Clin Med Phys       Date:  2020-09-29       Impact factor: 2.102

10.  Deforming to Best Practice: Key considerations for deformable image registration in radiotherapy.

Authors:  Jeffrey Barber; Johnson Yuen; Michael Jameson; Laurel Schmidt; Jonathan Sykes; Alison Gray; Nicholas Hardcastle; Callie Choong; Joel Poder; Amy Walker; Adam Yeo; Ben Archibald-Heeren; Kristie Harrison; Annette Haworth; David Thwaites
Journal:  J Med Radiat Sci       Date:  2020-08-02
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