Literature DB >> 28453911

Validation of biomechanical deformable image registration in the abdomen, thorax, and pelvis in a commercial radiotherapy treatment planning system.

Michael Velec1, Joanne L Moseley1, Stina Svensson2, Björn Hårdemark2, David A Jaffray1,3, Kristy K Brock4.   

Abstract

PURPOSE: The accuracy of deformable image registration tools can vary widely between imaging modalities and specific implementations of the same algorithms. A biomechanical model-based algorithm initially developed in-house at an academic institution was translated into a commercial radiotherapy treatment planning system and validated for multiple imaging modalities and anatomic sites.
METHODS: Biomechanical deformable registration (Morfeus) is a geometry-driven algorithm based on the finite element method. Boundary conditions are derived from the model-based segmentation of controlling structures in each image which establishes a point-to-point surface correspondence. For each controlling structure, material properties and fixed or sliding interfaces are assigned. The displacements of internal volumes for controlling structures and other structures implicitly deformed are solved with finite element analysis. Registration was performed for 74 patients with images (mean vector resolution) of thoracic and abdominal 4DCT (2.8 mm) and MR (5.3 mm), liver CT-MR (4.5 mm), and prostate MR (2.6 mm). Accuracy was quantified between deformed and actual target images using distance-to-agreement (DTA) for structure surfaces and the target registration error (TRE) for internal point landmarks.
RESULTS: The results of the commercial implementation were as follows. The mean DTA was ≤ 1.0 mm for controlling structures and 1.0-3.5 mm for implicitly deformed structures on average. TRE ranged from 2.0 mm on prostate MR to 5.1 mm on lung MR on average, within 0.1 mm or lower than the image voxel sizes. Accuracy was not overly sensitive to changes in the material properties or variability in structure segmentations, as changing these inputs affected DTA and TRE by ≤ 0.8 mm. Maximum DTA > 5 mm occurred for 88% of the structures evaluated although these were within the inherent segmentation uncertainty for 82% of structures. Differences in accuracy between the commercial and in-house research implementations were ≤ 0.5 mm for mean DTA and ≤ 0.7 mm for mean TRE.
CONCLUSIONS: Accuracy of biomechanical deformable registration evaluated on a large cohort of images in the thorax, abdomen and prostate was similar to the image voxel resolution on average across multiple modalities. Validation of this treatment planning system implementation supports biomechanical deformable registration as a versatile clinical tool to enable accurate target delineation at planning and treatment adaptation.
© 2017 American Association of Physicists in Medicine.

Entities:  

Keywords:  biomechanical models; deformable image registration; multimodality imaging

Mesh:

Year:  2017        PMID: 28453911      PMCID: PMC5535790          DOI: 10.1002/mp.12307

Source DB:  PubMed          Journal:  Med Phys        ISSN: 0094-2405            Impact factor:   4.071


  26 in total

1.  Modeling liver motion and deformation during the respiratory cycle using intensity-based nonrigid registration of gated MR images.

Authors:  Torsten Rohlfing; Calvin R Maurer; Walter G O'Dell; Jianhui Zhong
Journal:  Med Phys       Date:  2004-03       Impact factor: 4.071

2.  Semi-automatic deformable registration of prostate MR images to pathological slices.

Authors:  Yousef Mazaheri; Louisa Bokacheva; Dirk-Jan Kroon; Oguz Akin; Hedvig Hricak; Daniel Chamudot; Samson Fine; Jason A Koutcher
Journal:  J Magn Reson Imaging       Date:  2010-11       Impact factor: 4.813

3.  Factors influencing the accuracy of biomechanical breast models.

Authors:  Christine Tanner; Julia A Schnabel; Derek L G Hill; David J Hawkes; Martin O Leach; D Rodney Hose
Journal:  Med Phys       Date:  2006-06       Impact factor: 4.071

4.  Objective assessment of deformable image registration in radiotherapy: a multi-institution study.

Authors:  Rojano Kashani; Martina Hub; James M Balter; Marc L Kessler; Lei Dong; Lifei Zhang; Lei Xing; Yaoqin Xie; David Hawkes; Julia A Schnabel; Jamie McClelland; Sarang Joshi; Quan Chen; Weiguo Lu
Journal:  Med Phys       Date:  2008-12       Impact factor: 4.071

5.  Deformable image registration based automatic CT-to-CT contour propagation for head and neck adaptive radiotherapy in the routine clinical setting.

Authors:  Akila Kumarasiri; Farzan Siddiqui; Chang Liu; Raphael Yechieli; Mira Shah; Deepak Pradhan; Hualiang Zhong; Indrin J Chetty; Jinkoo Kim
Journal:  Med Phys       Date:  2014-12       Impact factor: 4.071

6.  The ANACONDA algorithm for deformable image registration in radiotherapy.

Authors:  Ola Weistrand; Stina Svensson
Journal:  Med Phys       Date:  2015-01       Impact factor: 4.071

7.  Prospective comparison of computed tomography and magnetic resonance imaging for liver cancer delineation using deformable image registration.

Authors:  Jon-Paul Voroney; Kristy K Brock; Cynthia Eccles; Masoom Haider; Laura A Dawson
Journal:  Int J Radiat Oncol Biol Phys       Date:  2006-11-01       Impact factor: 7.038

8.  Accumulated Delivered Dose Response of Stereotactic Body Radiation Therapy for Liver Metastases.

Authors:  Anand Swaminath; Christine Massey; James D Brierley; Rob Dinniwell; Rebecca Wong; John J Kim; Michael Velec; Kristy K Brock; Laura A Dawson
Journal:  Int J Radiat Oncol Biol Phys       Date:  2015-07-26       Impact factor: 7.038

9.  The evaluation of a deformable image registration segmentation technique for semi-automating internal target volume (ITV) production from 4DCT images of lung stereotactic body radiotherapy (SBRT) patients.

Authors:  Richard Speight; Jonathan Sykes; Rebecca Lindsay; Kevin Franks; David Thwaites
Journal:  Radiother Oncol       Date:  2011-01-21       Impact factor: 6.280

10.  Sliding characteristic and material compressibility of human lung: parametric study and verification.

Authors:  A Al-Mayah; J Moseley; M Velec; K K Brock
Journal:  Med Phys       Date:  2009-10       Impact factor: 4.071

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  12 in total

1.  Deformable MR-CBCT prostate registration using biomechanically constrained deep learning networks.

Authors:  Yabo Fu; Tonghe Wang; Yang Lei; Pretesh Patel; Ashesh B Jani; Walter J Curran; Tian Liu; Xiaofeng Yang
Journal:  Med Phys       Date:  2020-11-27       Impact factor: 4.071

2.  Automatic liver tumor localization using deep learning-based liver boundary motion estimation and biomechanical modeling (DL-Bio).

Authors:  Hua-Chieh Shao; Xiaokun Huang; Michael R Folkert; Jing Wang; You Zhang
Journal:  Med Phys       Date:  2021-11-19       Impact factor: 4.071

3.  Rigid and Deformable Image Registration for Radiation Therapy: A Self-Study Evaluation Guide for NRG Oncology Clinical Trial Participation.

Authors:  Yi Rong; Mihaela Rosu-Bubulac; Stanley H Benedict; Yunfeng Cui; Russell Ruo; Tanner Connell; Rojano Kashani; Kujtim Latifi; Quan Chen; Huaizhi Geng; Jason Sohn; Ying Xiao
Journal:  Pract Radiat Oncol       Date:  2021-03-02

4.  Associations between voxel-level accumulated dose and rectal toxicity in prostate radiotherapy.

Authors:  Leila E A Shelley; Michael P F Sutcliffe; Simon J Thomas; David J Noble; Marina Romanchikova; Karl Harrison; Amy M Bates; Neil G Burnet; Raj Jena
Journal:  Phys Imaging Radiat Oncol       Date:  2020-04

5.  Practical quantification of image registration accuracy following the AAPM TG-132 report framework.

Authors:  Kujtim Latifi; Jimmy Caudell; Geoffrey Zhang; Dylan Hunt; Eduardo G Moros; Vladimir Feygelman
Journal:  J Appl Clin Med Phys       Date:  2018-06-07       Impact factor: 2.102

6.  Automated Contouring of Contrast and Noncontrast Computed Tomography Liver Images With Fully Convolutional Networks.

Authors:  Brian M Anderson; Ethan Y Lin; Carlos E Cardenas; Dustin A Gress; William D Erwin; Bruno C Odisio; Eugene J Koay; Kristy K Brock
Journal:  Adv Radiat Oncol       Date:  2020-05-16

7.  MRI evaluation of normal tissue deformation and breathing motion under an abdominal compression device.

Authors:  Maureen Lee; Anna Simeonov; Teo Stanescu; Laura A Dawson; Kristy K Brock; Michael Velec
Journal:  J Appl Clin Med Phys       Date:  2021-01-15       Impact factor: 2.102

8.  Volumetric cine magnetic resonance imaging (VC-MRI) using motion modeling, free-form deformation and multi-slice undersampled 2D cine MRI reconstructed with spatio-temporal low-rank decomposition.

Authors:  Wendy Harris; Fang-Fang Yin; Jing Cai; Lei Ren
Journal:  Quant Imaging Med Surg       Date:  2020-02

9.  Quantitative analysis of respiration-induced motion of each liver segment with helical computed tomography and 4-dimensional computed tomography.

Authors:  Yu-Lun Tsai; Ching-Jung Wu; Suzun Shaw; Pei-Chieh Yu; Hsin-Hua Nien; Louis Tak Lui
Journal:  Radiat Oncol       Date:  2018-04-02       Impact factor: 3.481

Review 10.  Radiomics for liver tumours.

Authors:  Constantin Dreher; Philipp Linde; Judit Boda-Heggemann; Bettina Baessler
Journal:  Strahlenther Onkol       Date:  2020-04-15       Impact factor: 3.621

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