Deformable mesh registration for the validation of automatic target localization algorithms
Purpose: To evaluate deformable mesh registration (DMR) as a tool for validating automatic target registration algorithms used during image-guided radiation therapy. Methods: DMR was implemented in a hierarchical model, with rigid, affine, and B-spline transforms optimized in succession to register...
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| Vydáno v: | Medical physics (Lancaster) Ročník 40; číslo 7; s. 071721 - n/a |
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| Hlavní autoři: | , , |
| Médium: | Journal Article |
| Jazyk: | angličtina |
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United States
American Association of Physicists in Medicine
01.07.2013
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| ISSN: | 0094-2405, 2473-4209, 2473-4209, 0094-2405 |
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| Abstract | Purpose:
To evaluate deformable mesh registration (DMR) as a tool for validating automatic target registration algorithms used during image-guided radiation therapy.
Methods:
DMR was implemented in a hierarchical model, with rigid, affine, and B-spline transforms optimized in succession to register a pair of surface meshes. The gross tumor volumes (primary tumor and involved lymph nodes) were contoured by a physician on weekly CT scans in a cohort of lung cancer patients and converted to surface meshes. The meshes from weekly CT images were registered to the mesh from the planning CT, and the resulting registered meshes were compared with the delineated surfaces. Known deformations were also applied to the meshes, followed by mesh registration to recover the known deformation. Mesh registration accuracy was assessed at the mesh surface by computing the symmetric surface distance (SSD) between vertices of each registered mesh pair. Mesh registration quality in regions within 5 mm of the mesh surface was evaluated with respect to a high quality deformable image registration.
Results:
For 18 patients presenting with a total of 19 primary lung tumors and 24 lymph node targets, the SSD averaged 1.3 ± 0.5 and 0.8 ± 0.2 mm, respectively. Vertex registration errors (VRE) relative to the applied known deformation were 0.8 ± 0.7 and 0.2 ± 0.3 mm for the primary tumor and lymph nodes, respectively. Inside the mesh surface, corresponding average VRE ranged from 0.6 to 0.9 and 0.2 to 0.9 mm, respectively. Outside the mesh surface, average VRE ranged from 0.7 to 1.8 and 0.2 to 1.4 mm. The magnitude of errors generally increased with increasing distance away from the mesh.
Conclusions:
Provided that delineated surfaces are available, deformable mesh registration is an accurate and reliable method for obtaining a reference registration to validate automatic target registration algorithms for image-guided radiation therapy, specifically in regions on or near the target surfaces. |
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| AbstractList | To evaluate deformable mesh registration (DMR) as a tool for validating automatic target registration algorithms used during image-guided radiation therapy.PURPOSETo evaluate deformable mesh registration (DMR) as a tool for validating automatic target registration algorithms used during image-guided radiation therapy.DMR was implemented in a hierarchical model, with rigid, affine, and B-spline transforms optimized in succession to register a pair of surface meshes. The gross tumor volumes (primary tumor and involved lymph nodes) were contoured by a physician on weekly CT scans in a cohort of lung cancer patients and converted to surface meshes. The meshes from weekly CT images were registered to the mesh from the planning CT, and the resulting registered meshes were compared with the delineated surfaces. Known deformations were also applied to the meshes, followed by mesh registration to recover the known deformation. Mesh registration accuracy was assessed at the mesh surface by computing the symmetric surface distance (SSD) between vertices of each registered mesh pair. Mesh registration quality in regions within 5 mm of the mesh surface was evaluated with respect to a high quality deformable image registration.METHODSDMR was implemented in a hierarchical model, with rigid, affine, and B-spline transforms optimized in succession to register a pair of surface meshes. The gross tumor volumes (primary tumor and involved lymph nodes) were contoured by a physician on weekly CT scans in a cohort of lung cancer patients and converted to surface meshes. The meshes from weekly CT images were registered to the mesh from the planning CT, and the resulting registered meshes were compared with the delineated surfaces. Known deformations were also applied to the meshes, followed by mesh registration to recover the known deformation. Mesh registration accuracy was assessed at the mesh surface by computing the symmetric surface distance (SSD) between vertices of each registered mesh pair. Mesh registration quality in regions within 5 mm of the mesh surface was evaluated with respect to a high quality deformable image registration.For 18 patients presenting with a total of 19 primary lung tumors and 24 lymph node targets, the SSD averaged 1.3 ± 0.5 and 0.8 ± 0.2 mm, respectively. Vertex registration errors (VRE) relative to the applied known deformation were 0.8 ± 0.7 and 0.2 ± 0.3 mm for the primary tumor and lymph nodes, respectively. Inside the mesh surface, corresponding average VRE ranged from 0.6 to 0.9 and 0.2 to 0.9 mm, respectively. Outside the mesh surface, average VRE ranged from 0.7 to 1.8 and 0.2 to 1.4 mm. The magnitude of errors generally increased with increasing distance away from the mesh.RESULTSFor 18 patients presenting with a total of 19 primary lung tumors and 24 lymph node targets, the SSD averaged 1.3 ± 0.5 and 0.8 ± 0.2 mm, respectively. Vertex registration errors (VRE) relative to the applied known deformation were 0.8 ± 0.7 and 0.2 ± 0.3 mm for the primary tumor and lymph nodes, respectively. Inside the mesh surface, corresponding average VRE ranged from 0.6 to 0.9 and 0.2 to 0.9 mm, respectively. Outside the mesh surface, average VRE ranged from 0.7 to 1.8 and 0.2 to 1.4 mm. The magnitude of errors generally increased with increasing distance away from the mesh.Provided that delineated surfaces are available, deformable mesh registration is an accurate and reliable method for obtaining a reference registration to validate automatic target registration algorithms for image-guided radiation therapy, specifically in regions on or near the target surfaces.CONCLUSIONSProvided that delineated surfaces are available, deformable mesh registration is an accurate and reliable method for obtaining a reference registration to validate automatic target registration algorithms for image-guided radiation therapy, specifically in regions on or near the target surfaces. To evaluate deformable mesh registration (DMR) as a tool for validating automatic target registration algorithms used during image-guided radiation therapy. DMR was implemented in a hierarchical model, with rigid, affine, and B-spline transforms optimized in succession to register a pair of surface meshes. The gross tumor volumes (primary tumor and involved lymph nodes) were contoured by a physician on weekly CT scans in a cohort of lung cancer patients and converted to surface meshes. The meshes from weekly CT images were registered to the mesh from the planning CT, and the resulting registered meshes were compared with the delineated surfaces. Known deformations were also applied to the meshes, followed by mesh registration to recover the known deformation. Mesh registration accuracy was assessed at the mesh surface by computing the symmetric surface distance (SSD) between vertices of each registered mesh pair. Mesh registration quality in regions within 5 mm of the mesh surface was evaluated with respect to a high quality deformable image registration. For 18 patients presenting with a total of 19 primary lung tumors and 24 lymph node targets, the SSD averaged 1.3 ± 0.5 and 0.8 ± 0.2 mm, respectively. Vertex registration errors (VRE) relative to the applied known deformation were 0.8 ± 0.7 and 0.2 ± 0.3 mm for the primary tumor and lymph nodes, respectively. Inside the mesh surface, corresponding average VRE ranged from 0.6 to 0.9 and 0.2 to 0.9 mm, respectively. Outside the mesh surface, average VRE ranged from 0.7 to 1.8 and 0.2 to 1.4 mm. The magnitude of errors generally increased with increasing distance away from the mesh. Provided that delineated surfaces are available, deformable mesh registration is an accurate and reliable method for obtaining a reference registration to validate automatic target registration algorithms for image-guided radiation therapy, specifically in regions on or near the target surfaces. Purpose: To evaluate deformable mesh registration (DMR) as a tool for validating automatic target registration algorithms used during image‐guided radiation therapy. Methods: DMR was implemented in a hierarchical model, with rigid, affine, and B‐spline transforms optimized in succession to register a pair of surface meshes. The gross tumor volumes (primary tumor and involved lymph nodes) were contoured by a physician on weekly CT scans in a cohort of lung cancer patients and converted to surface meshes. The meshes from weekly CT images were registered to the mesh from the planning CT, and the resulting registered meshes were compared with the delineated surfaces. Known deformations were also applied to the meshes, followed by mesh registration to recover the known deformation. Mesh registration accuracy was assessed at the mesh surface by computing the symmetric surface distance (SSD) between vertices of each registered mesh pair. Mesh registration quality in regions within 5 mm of the mesh surface was evaluated with respect to a high quality deformable image registration. Results: For 18 patients presenting with a total of 19 primary lung tumors and 24 lymph node targets, the SSD averaged 1.3 ± 0.5 and 0.8 ± 0.2 mm, respectively. Vertex registration errors (VRE) relative to the applied known deformation were 0.8 ± 0.7 and 0.2 ± 0.3 mm for the primary tumor and lymph nodes, respectively. Inside the mesh surface, corresponding average VRE ranged from 0.6 to 0.9 and 0.2 to 0.9 mm, respectively. Outside the mesh surface, average VRE ranged from 0.7 to 1.8 and 0.2 to 1.4 mm. The magnitude of errors generally increased with increasing distance away from the mesh. Conclusions: Provided that delineated surfaces are available, deformable mesh registration is an accurate and reliable method for obtaining a reference registration to validate automatic target registration algorithms for image‐guided radiation therapy, specifically in regions on or near the target surfaces. Purpose: To evaluate deformable mesh registration (DMR) as a tool for validating automatic target registration algorithms used during image-guided radiation therapy. Methods: DMR was implemented in a hierarchical model, with rigid, affine, and B-spline transforms optimized in succession to register a pair of surface meshes. The gross tumor volumes (primary tumor and involved lymph nodes) were contoured by a physician on weekly CT scans in a cohort of lung cancer patients and converted to surface meshes. The meshes from weekly CT images were registered to the mesh from the planning CT, and the resulting registered meshes were compared with the delineated surfaces. Known deformations were also applied to the meshes, followed by mesh registration to recover the known deformation. Mesh registration accuracy was assessed at the mesh surface by computing the symmetric surface distance (SSD) between vertices of each registered mesh pair. Mesh registration quality in regions within 5 mm of the mesh surface was evaluated with respect to a high quality deformable image registration. Results: For 18 patients presenting with a total of 19 primary lung tumors and 24 lymph node targets, the SSD averaged 1.3 ± 0.5 and 0.8 ± 0.2 mm, respectively. Vertex registration errors (VRE) relative to the applied known deformation were 0.8 ± 0.7 and 0.2 ± 0.3 mm for the primary tumor and lymph nodes, respectively. Inside the mesh surface, corresponding average VRE ranged from 0.6 to 0.9 and 0.2 to 0.9 mm, respectively. Outside the mesh surface, average VRE ranged from 0.7 to 1.8 and 0.2 to 1.4 mm. The magnitude of errors generally increased with increasing distance away from the mesh. Conclusions: Provided that delineated surfaces are available, deformable mesh registration is an accurate and reliable method for obtaining a reference registration to validate automatic target registration algorithms for image-guided radiation therapy, specifically in regions on or near the target surfaces. |
| Author | Robertson, Scott Weiss, Elisabeth Hugo, Geoffrey D. |
| Author_xml | – sequence: 1 givenname: Scott surname: Robertson fullname: Robertson, Scott organization: Department of Radiation Oncology, Virginia Commonwealth University, Richmond, Virginia 23298 – sequence: 2 givenname: Elisabeth surname: Weiss fullname: Weiss, Elisabeth organization: Department of Radiation Oncology, Virginia Commonwealth University, Richmond, Virginia 23298 – sequence: 3 givenname: Geoffrey D. surname: Hugo fullname: Hugo, Geoffrey D. email: gdhugo@vcu.edu organization: Department of Radiation Oncology, Virginia Commonwealth University, Richmond, Virginia 23298 |
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| Keywords | localization lung cancer deformable registration image-guided radiation therapy |
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| Notes | Telephone: 804‐628‐3457; Fax: 804‐628‐0271. Author to whom correspondence should be addressed. Electronic mail gdhugo@vcu.edu ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23 ObjectType-Undefined-3 Author to whom correspondence should be addressed. Electronic mail: gdhugo@vcu.edu; Telephone: 804-628-3457; Fax: 804-628-0271. |
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To evaluate deformable mesh registration (DMR) as a tool for validating automatic target registration algorithms used during image-guided radiation... Purpose: To evaluate deformable mesh registration (DMR) as a tool for validating automatic target registration algorithms used during image‐guided radiation... To evaluate deformable mesh registration (DMR) as a tool for validating automatic target registration algorithms used during image-guided radiation therapy.... To evaluate deformable mesh registration (DMR) as a tool for validating automatic target registration algorithms used during image-guided radiation... Purpose: To evaluate deformable mesh registration (DMR) as a tool for validating automatic target registration algorithms used during image-guided radiation... |
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| SubjectTerms | Algorithms Automation Cancer Computed tomography Computerised tomographs computerised tomography deformable registration Digital computing or data processing equipment or methods, specially adapted for specific applications Humans Image data processing or generation, in general Image guided radiation therapy Image Processing, Computer-Assisted - methods image registration localization lung lung cancer Lung Neoplasms - diagnostic imaging Lung Neoplasms - pathology Lung Neoplasms - radiotherapy Lungs medical image processing Medical image quality Medical imaging Optimization radiation therapy Radiation Therapy Physics Radiation treatment Radiotherapy, Image-Guided - methods Registration Surface treatments Tomography, X-Ray Computed Tumor Burden tumours |
| Title | Deformable mesh registration for the validation of automatic target localization algorithms |
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