An adaptive MR-CT registration method for MRI-guided prostate cancer radiotherapy
Magnetic Resonance images (MRI) have superior soft tissue contrast compared with CT images. Therefore, MRI might be a better imaging modality to differentiate the prostate from surrounding normal organs. Methods to accurately register MRI to simulation CT images are essential, as we transition the u...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Zhong, Hualiang [verfasserIn] |
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| Format: |
Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2015 |
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| Schlagwörter: |
Magnetic Resonance Imaging - methods Radiotherapy Planning, Computer-Assisted - methods Tomography, X-Ray Computed - methods |
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| Systematik: |
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| Übergeordnetes Werk: |
Enthalten in: Physics in medicine and biology - Bristol : IOP Publ., 1956, 60(2015), 7, Seite 2837 |
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| Übergeordnetes Werk: |
volume:60 ; year:2015 ; number:7 ; pages:2837 |
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| 520 | |a Magnetic Resonance images (MRI) have superior soft tissue contrast compared with CT images. Therefore, MRI might be a better imaging modality to differentiate the prostate from surrounding normal organs. Methods to accurately register MRI to simulation CT images are essential, as we transition the use of MRI into the routine clinic setting. In this study, we present a finite element method (FEM) to improve the performance of a commercially available, B-spline-based registration algorithm in the prostate region. Specifically, prostate contours were delineated independently on ten MRI and CT images using the Eclipse treatment planning system. Each pair of MRI and CT images was registered with the B-spline-based algorithm implemented in the VelocityAI system. A bounding box that contains the prostate volume in the CT image was selected and partitioned into a tetrahedral mesh. An adaptive finite element method was then developed to adjust the displacement vector fields (DVFs) of the B-spline-based registrations within the box. The B-spline and FEM-based registrations were evaluated based on the variations of prostate volume and tumor centroid, the unbalanced energy of the generated DVFs, and the clarity of the reconstructed anatomical structures. The results showed that the volumes of the prostate contours warped with the B-spline-based DVFs changed 10.2% on average, relative to the volumes of the prostate contours on the original MR images. This discrepancy was reduced to 1.5% for the FEM-based DVFs. The average unbalanced energy was 2.65 and 0.38 mJ cm(-3), and the prostate centroid deviation was 0.37 and 0.28 cm, for the B-spline and FEM-based registrations, respectively. Different from the B-spline-warped MR images, the FEM-warped MR images have clear boundaries between prostates and bladders, and their internal prostatic structures are consistent with those of the original MR images. In summary, the developed adaptive FEM method preserves the prostate volume during the transformation between the MR and CT images and improves the accuracy of the B-spline registrations in the prostate region. The approach will be valuable for the development of high-quality MRI-guided radiation therapy. | ||
| 650 | 4 | |a Urinary Bladder - radiography | |
| 650 | 4 | |a Magnetic Resonance Imaging - methods | |
| 650 | 4 | |a Multimodal Imaging - methods | |
| 650 | 4 | |a Radiotherapy Planning, Computer-Assisted - methods | |
| 650 | 4 | |a Tomography, X-Ray Computed - methods | |
| 650 | 4 | |a Radiotherapy, Image-Guided - methods | |
| 650 | 4 | |a Prostatic Neoplasms - radiotherapy | |
| 700 | 1 | |a Wen, Ning |4 oth | |
| 700 | 1 | |a Gordon, James J |4 oth | |
| 700 | 1 | |a Elshaikh, Mohamed A |4 oth | |
| 700 | 1 | |a Movsas, Benjamin |4 oth | |
| 700 | 1 | |a Chetty, Indrin J |4 oth | |
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PQ20160617 (DE-627)OLC1966078005 (DE-599)GBVOLC1966078005 (PRQ)p1197-c562235d638530c076c2f52eb8f98b21ceca04bcbc6a5d8ef2d2541b840f87460 (KEY)0053250920150000060000702837adaptivemrctregistrationmethodformriguidedprostate DE-627 ger DE-627 rakwb eng 570 540 530 DNB BIODIV fid WA 15000 AVZ rvk 44.31 bkl 42.12 bkl Zhong, Hualiang verfasserin aut An adaptive MR-CT registration method for MRI-guided prostate cancer radiotherapy 2015 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier Magnetic Resonance images (MRI) have superior soft tissue contrast compared with CT images. Therefore, MRI might be a better imaging modality to differentiate the prostate from surrounding normal organs. Methods to accurately register MRI to simulation CT images are essential, as we transition the use of MRI into the routine clinic setting. In this study, we present a finite element method (FEM) to improve the performance of a commercially available, B-spline-based registration algorithm in the prostate region. Specifically, prostate contours were delineated independently on ten MRI and CT images using the Eclipse treatment planning system. Each pair of MRI and CT images was registered with the B-spline-based algorithm implemented in the VelocityAI system. A bounding box that contains the prostate volume in the CT image was selected and partitioned into a tetrahedral mesh. An adaptive finite element method was then developed to adjust the displacement vector fields (DVFs) of the B-spline-based registrations within the box. The B-spline and FEM-based registrations were evaluated based on the variations of prostate volume and tumor centroid, the unbalanced energy of the generated DVFs, and the clarity of the reconstructed anatomical structures. The results showed that the volumes of the prostate contours warped with the B-spline-based DVFs changed 10.2% on average, relative to the volumes of the prostate contours on the original MR images. This discrepancy was reduced to 1.5% for the FEM-based DVFs. The average unbalanced energy was 2.65 and 0.38 mJ cm(-3), and the prostate centroid deviation was 0.37 and 0.28 cm, for the B-spline and FEM-based registrations, respectively. Different from the B-spline-warped MR images, the FEM-warped MR images have clear boundaries between prostates and bladders, and their internal prostatic structures are consistent with those of the original MR images. In summary, the developed adaptive FEM method preserves the prostate volume during the transformation between the MR and CT images and improves the accuracy of the B-spline registrations in the prostate region. The approach will be valuable for the development of high-quality MRI-guided radiation therapy. Urinary Bladder - radiography Magnetic Resonance Imaging - methods Multimodal Imaging - methods Radiotherapy Planning, Computer-Assisted - methods Tomography, X-Ray Computed - methods Radiotherapy, Image-Guided - methods Prostatic Neoplasms - radiotherapy Wen, Ning oth Gordon, James J oth Elshaikh, Mohamed A oth Movsas, Benjamin oth Chetty, Indrin J oth Enthalten in Physics in medicine and biology Bristol : IOP Publ., 1956 60(2015), 7, Seite 2837 (DE-627)129503991 (DE-600)208857-5 (DE-576)014907305 0031-9155 nnns volume:60 year:2015 number:7 pages:2837 http://www.ncbi.nlm.nih.gov/pubmed/25775937 GBV_USEFLAG_A SYSFLAG_A GBV_OLC FID-BIODIV SSG-OLC-PHY SSG-OLC-CHE GBV_ILN_22 GBV_ILN_70 GBV_ILN_170 GBV_ILN_4012 GBV_ILN_4219 GBV_ILN_4306 WA 15000 44.31 AVZ 42.12 AVZ AR 60 2015 7 2837 |
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PQ20160617 (DE-627)OLC1966078005 (DE-599)GBVOLC1966078005 (PRQ)p1197-c562235d638530c076c2f52eb8f98b21ceca04bcbc6a5d8ef2d2541b840f87460 (KEY)0053250920150000060000702837adaptivemrctregistrationmethodformriguidedprostate DE-627 ger DE-627 rakwb eng 570 540 530 DNB BIODIV fid WA 15000 AVZ rvk 44.31 bkl 42.12 bkl Zhong, Hualiang verfasserin aut An adaptive MR-CT registration method for MRI-guided prostate cancer radiotherapy 2015 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier Magnetic Resonance images (MRI) have superior soft tissue contrast compared with CT images. Therefore, MRI might be a better imaging modality to differentiate the prostate from surrounding normal organs. Methods to accurately register MRI to simulation CT images are essential, as we transition the use of MRI into the routine clinic setting. In this study, we present a finite element method (FEM) to improve the performance of a commercially available, B-spline-based registration algorithm in the prostate region. Specifically, prostate contours were delineated independently on ten MRI and CT images using the Eclipse treatment planning system. Each pair of MRI and CT images was registered with the B-spline-based algorithm implemented in the VelocityAI system. A bounding box that contains the prostate volume in the CT image was selected and partitioned into a tetrahedral mesh. An adaptive finite element method was then developed to adjust the displacement vector fields (DVFs) of the B-spline-based registrations within the box. The B-spline and FEM-based registrations were evaluated based on the variations of prostate volume and tumor centroid, the unbalanced energy of the generated DVFs, and the clarity of the reconstructed anatomical structures. The results showed that the volumes of the prostate contours warped with the B-spline-based DVFs changed 10.2% on average, relative to the volumes of the prostate contours on the original MR images. This discrepancy was reduced to 1.5% for the FEM-based DVFs. The average unbalanced energy was 2.65 and 0.38 mJ cm(-3), and the prostate centroid deviation was 0.37 and 0.28 cm, for the B-spline and FEM-based registrations, respectively. Different from the B-spline-warped MR images, the FEM-warped MR images have clear boundaries between prostates and bladders, and their internal prostatic structures are consistent with those of the original MR images. In summary, the developed adaptive FEM method preserves the prostate volume during the transformation between the MR and CT images and improves the accuracy of the B-spline registrations in the prostate region. The approach will be valuable for the development of high-quality MRI-guided radiation therapy. Urinary Bladder - radiography Magnetic Resonance Imaging - methods Multimodal Imaging - methods Radiotherapy Planning, Computer-Assisted - methods Tomography, X-Ray Computed - methods Radiotherapy, Image-Guided - methods Prostatic Neoplasms - radiotherapy Wen, Ning oth Gordon, James J oth Elshaikh, Mohamed A oth Movsas, Benjamin oth Chetty, Indrin J oth Enthalten in Physics in medicine and biology Bristol : IOP Publ., 1956 60(2015), 7, Seite 2837 (DE-627)129503991 (DE-600)208857-5 (DE-576)014907305 0031-9155 nnns volume:60 year:2015 number:7 pages:2837 http://www.ncbi.nlm.nih.gov/pubmed/25775937 GBV_USEFLAG_A SYSFLAG_A GBV_OLC FID-BIODIV SSG-OLC-PHY SSG-OLC-CHE GBV_ILN_22 GBV_ILN_70 GBV_ILN_170 GBV_ILN_4012 GBV_ILN_4219 GBV_ILN_4306 WA 15000 44.31 AVZ 42.12 AVZ AR 60 2015 7 2837 |
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An adaptive MR-CT registration method for MRI-guided prostate cancer radiotherapy |
| abstract |
Magnetic Resonance images (MRI) have superior soft tissue contrast compared with CT images. Therefore, MRI might be a better imaging modality to differentiate the prostate from surrounding normal organs. Methods to accurately register MRI to simulation CT images are essential, as we transition the use of MRI into the routine clinic setting. In this study, we present a finite element method (FEM) to improve the performance of a commercially available, B-spline-based registration algorithm in the prostate region. Specifically, prostate contours were delineated independently on ten MRI and CT images using the Eclipse treatment planning system. Each pair of MRI and CT images was registered with the B-spline-based algorithm implemented in the VelocityAI system. A bounding box that contains the prostate volume in the CT image was selected and partitioned into a tetrahedral mesh. An adaptive finite element method was then developed to adjust the displacement vector fields (DVFs) of the B-spline-based registrations within the box. The B-spline and FEM-based registrations were evaluated based on the variations of prostate volume and tumor centroid, the unbalanced energy of the generated DVFs, and the clarity of the reconstructed anatomical structures. The results showed that the volumes of the prostate contours warped with the B-spline-based DVFs changed 10.2% on average, relative to the volumes of the prostate contours on the original MR images. This discrepancy was reduced to 1.5% for the FEM-based DVFs. The average unbalanced energy was 2.65 and 0.38 mJ cm(-3), and the prostate centroid deviation was 0.37 and 0.28 cm, for the B-spline and FEM-based registrations, respectively. Different from the B-spline-warped MR images, the FEM-warped MR images have clear boundaries between prostates and bladders, and their internal prostatic structures are consistent with those of the original MR images. In summary, the developed adaptive FEM method preserves the prostate volume during the transformation between the MR and CT images and improves the accuracy of the B-spline registrations in the prostate region. The approach will be valuable for the development of high-quality MRI-guided radiation therapy. |
| abstractGer |
Magnetic Resonance images (MRI) have superior soft tissue contrast compared with CT images. Therefore, MRI might be a better imaging modality to differentiate the prostate from surrounding normal organs. Methods to accurately register MRI to simulation CT images are essential, as we transition the use of MRI into the routine clinic setting. In this study, we present a finite element method (FEM) to improve the performance of a commercially available, B-spline-based registration algorithm in the prostate region. Specifically, prostate contours were delineated independently on ten MRI and CT images using the Eclipse treatment planning system. Each pair of MRI and CT images was registered with the B-spline-based algorithm implemented in the VelocityAI system. A bounding box that contains the prostate volume in the CT image was selected and partitioned into a tetrahedral mesh. An adaptive finite element method was then developed to adjust the displacement vector fields (DVFs) of the B-spline-based registrations within the box. The B-spline and FEM-based registrations were evaluated based on the variations of prostate volume and tumor centroid, the unbalanced energy of the generated DVFs, and the clarity of the reconstructed anatomical structures. The results showed that the volumes of the prostate contours warped with the B-spline-based DVFs changed 10.2% on average, relative to the volumes of the prostate contours on the original MR images. This discrepancy was reduced to 1.5% for the FEM-based DVFs. The average unbalanced energy was 2.65 and 0.38 mJ cm(-3), and the prostate centroid deviation was 0.37 and 0.28 cm, for the B-spline and FEM-based registrations, respectively. Different from the B-spline-warped MR images, the FEM-warped MR images have clear boundaries between prostates and bladders, and their internal prostatic structures are consistent with those of the original MR images. In summary, the developed adaptive FEM method preserves the prostate volume during the transformation between the MR and CT images and improves the accuracy of the B-spline registrations in the prostate region. The approach will be valuable for the development of high-quality MRI-guided radiation therapy. |
| abstract_unstemmed |
Magnetic Resonance images (MRI) have superior soft tissue contrast compared with CT images. Therefore, MRI might be a better imaging modality to differentiate the prostate from surrounding normal organs. Methods to accurately register MRI to simulation CT images are essential, as we transition the use of MRI into the routine clinic setting. In this study, we present a finite element method (FEM) to improve the performance of a commercially available, B-spline-based registration algorithm in the prostate region. Specifically, prostate contours were delineated independently on ten MRI and CT images using the Eclipse treatment planning system. Each pair of MRI and CT images was registered with the B-spline-based algorithm implemented in the VelocityAI system. A bounding box that contains the prostate volume in the CT image was selected and partitioned into a tetrahedral mesh. An adaptive finite element method was then developed to adjust the displacement vector fields (DVFs) of the B-spline-based registrations within the box. The B-spline and FEM-based registrations were evaluated based on the variations of prostate volume and tumor centroid, the unbalanced energy of the generated DVFs, and the clarity of the reconstructed anatomical structures. The results showed that the volumes of the prostate contours warped with the B-spline-based DVFs changed 10.2% on average, relative to the volumes of the prostate contours on the original MR images. This discrepancy was reduced to 1.5% for the FEM-based DVFs. The average unbalanced energy was 2.65 and 0.38 mJ cm(-3), and the prostate centroid deviation was 0.37 and 0.28 cm, for the B-spline and FEM-based registrations, respectively. Different from the B-spline-warped MR images, the FEM-warped MR images have clear boundaries between prostates and bladders, and their internal prostatic structures are consistent with those of the original MR images. In summary, the developed adaptive FEM method preserves the prostate volume during the transformation between the MR and CT images and improves the accuracy of the B-spline registrations in the prostate region. The approach will be valuable for the development of high-quality MRI-guided radiation therapy. |
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The B-spline and FEM-based registrations were evaluated based on the variations of prostate volume and tumor centroid, the unbalanced energy of the generated DVFs, and the clarity of the reconstructed anatomical structures. The results showed that the volumes of the prostate contours warped with the B-spline-based DVFs changed 10.2% on average, relative to the volumes of the prostate contours on the original MR images. This discrepancy was reduced to 1.5% for the FEM-based DVFs. The average unbalanced energy was 2.65 and 0.38 mJ cm(-3), and the prostate centroid deviation was 0.37 and 0.28 cm, for the B-spline and FEM-based registrations, respectively. Different from the B-spline-warped MR images, the FEM-warped MR images have clear boundaries between prostates and bladders, and their internal prostatic structures are consistent with those of the original MR images. In summary, the developed adaptive FEM method preserves the prostate volume during the transformation between the MR and CT images and improves the accuracy of the B-spline registrations in the prostate region. 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