Quantifying day-to-day variations in 4DCBCT-based PCA motion models
The aim of this paper is to quantify the day-to-day variations of motion models derived from pre-treatment 4-dimensional cone beam CT (4DCBCT) fractions for lung cancer stereotactic body radiotherapy (SBRT) patients. Motion models are built by 1) applying deformable image registration (DIR) on each...
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2020
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| Online Access: | https://hdl.handle.net/11073/25545 |
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| _version_ | 1864513434495746048 |
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| author | Dhou, Salam |
| author2 | Lewis, John Cai, Weixing Ionascu, Dan Williams, Christopher |
| author2_role | author author author author |
| author_facet | Dhou, Salam Lewis, John Cai, Weixing Ionascu, Dan Williams, Christopher |
| author_role | author |
| dc.creator.none.fl_str_mv | Dhou, Salam Lewis, John Cai, Weixing Ionascu, Dan Williams, Christopher |
| dc.date.none.fl_str_mv | 2020 2024-07-01T06:01:26Z 2024-07-01T06:01:26Z |
| dc.format.none.fl_str_mv | application/pdf |
| dc.identifier.none.fl_str_mv | Dhou S, Lewis J, Cai W, Ionascu D, Williams C. Quantifying day-to-day variations in 4DCBCT-based PCA motion models. Biomed Phys Eng Express. 2020 Apr 9;6(3):035020. doi: 10.1088/2057-1976/ab817e. PMID: 33438665. 2057-1976 https://hdl.handle.net/11073/25545 10.1088/2057-1976/ab817e |
| dc.language.none.fl_str_mv | en_US |
| dc.publisher.none.fl_str_mv | IOP Science |
| dc.relation.none.fl_str_mv | https://iopscience.iop.org/article/10.1088/2057-1976/ab817e |
| dc.subject.none.fl_str_mv | Four-dimensional cone beam CT (4DCBCT) PCA motion model Stereotactic body radiation therapy (SBRT) Inter-fraction variations |
| dc.title.none.fl_str_mv | Quantifying day-to-day variations in 4DCBCT-based PCA motion models |
| dc.type.none.fl_str_mv | Peer-Reviewed Postprint info:eu-repo/semantics/publishedVersion info:eu-repo/semantics/article |
| description | The aim of this paper is to quantify the day-to-day variations of motion models derived from pre-treatment 4-dimensional cone beam CT (4DCBCT) fractions for lung cancer stereotactic body radiotherapy (SBRT) patients. Motion models are built by 1) applying deformable image registration (DIR) on each 4DCBCT image with respect to a reference image from that day, resulting in a set of displacement vector fields (DVFs), and 2) applying principal component analysis (PCA) on the DVFs to obtain principal components representing a motion model. Variations were quantified by comparing the PCA eigenvectors of the motion model built from the first day of treatment to the corresponding eigenvectors of the other motion models built from each successive day of treatment. Three metrics were used to quantify the variations: root mean squared (RMS) difference in the vectors, directional similarity, and an introduced metric called the Euclidean Model Norm (EMN). EMN quantifies the degree to which a motion model derived from the first fraction can represent the motion models of subsequent fractions. Twenty-one 4DCBCT scans from five SBRT patient treatments were used in this retrospective study. Experimental results demonstrated that the first two eigenvectors of motion models across all fractions have smaller RMS (0.00017), larger directional similarity (0.528), and larger EMN (0.678) than the last three eigenvectors (RMS: 0.00025, directional similarity: 0.041, and EMN: 0.212). The study concluded that, while the motion model eigenvectors varied from fraction to fraction, the first few eigenvectors were shown to be more stable across treatment fractions than others. This supports the notion that a pre-treatment motion model built from the first few PCA eigenvectors may remain valid throughout a treatment course. Future work is necessary to quantify how day-to-day variations in these models will affect motion reconstruction accuracy for specific clinical tasks. |
| format | article |
| id | aus_13517b05c6cbdcb83dd0690e7fdf3bf5 |
| identifier_str_mv | Dhou S, Lewis J, Cai W, Ionascu D, Williams C. Quantifying day-to-day variations in 4DCBCT-based PCA motion models. Biomed Phys Eng Express. 2020 Apr 9;6(3):035020. doi: 10.1088/2057-1976/ab817e. PMID: 33438665. 2057-1976 10.1088/2057-1976/ab817e |
| language_invalid_str_mv | en_US |
| network_acronym_str | aus |
| network_name_str | aus |
| oai_identifier_str | oai:repository.aus.edu:11073/25545 |
| publishDate | 2020 |
| publisher.none.fl_str_mv | IOP Science |
| repository.mail.fl_str_mv | |
| repository.name.fl_str_mv | |
| repository_id_str | |
| spelling | Quantifying day-to-day variations in 4DCBCT-based PCA motion modelsDhou, SalamLewis, JohnCai, WeixingIonascu, DanWilliams, ChristopherFour-dimensional cone beam CT (4DCBCT)PCA motion modelStereotactic body radiation therapy (SBRT)Inter-fraction variationsThe aim of this paper is to quantify the day-to-day variations of motion models derived from pre-treatment 4-dimensional cone beam CT (4DCBCT) fractions for lung cancer stereotactic body radiotherapy (SBRT) patients. Motion models are built by 1) applying deformable image registration (DIR) on each 4DCBCT image with respect to a reference image from that day, resulting in a set of displacement vector fields (DVFs), and 2) applying principal component analysis (PCA) on the DVFs to obtain principal components representing a motion model. Variations were quantified by comparing the PCA eigenvectors of the motion model built from the first day of treatment to the corresponding eigenvectors of the other motion models built from each successive day of treatment. Three metrics were used to quantify the variations: root mean squared (RMS) difference in the vectors, directional similarity, and an introduced metric called the Euclidean Model Norm (EMN). EMN quantifies the degree to which a motion model derived from the first fraction can represent the motion models of subsequent fractions. Twenty-one 4DCBCT scans from five SBRT patient treatments were used in this retrospective study. Experimental results demonstrated that the first two eigenvectors of motion models across all fractions have smaller RMS (0.00017), larger directional similarity (0.528), and larger EMN (0.678) than the last three eigenvectors (RMS: 0.00025, directional similarity: 0.041, and EMN: 0.212). The study concluded that, while the motion model eigenvectors varied from fraction to fraction, the first few eigenvectors were shown to be more stable across treatment fractions than others. This supports the notion that a pre-treatment motion model built from the first few PCA eigenvectors may remain valid throughout a treatment course. Future work is necessary to quantify how day-to-day variations in these models will affect motion reconstruction accuracy for specific clinical tasks.IOP Science2024-07-01T06:01:26Z2024-07-01T06:01:26Z2020Peer-ReviewedPostprintinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfDhou S, Lewis J, Cai W, Ionascu D, Williams C. Quantifying day-to-day variations in 4DCBCT-based PCA motion models. Biomed Phys Eng Express. 2020 Apr 9;6(3):035020. doi: 10.1088/2057-1976/ab817e. PMID: 33438665.2057-1976https://hdl.handle.net/11073/2554510.1088/2057-1976/ab817een_UShttps://iopscience.iop.org/article/10.1088/2057-1976/ab817eoai:repository.aus.edu:11073/255452024-08-22T12:07:47Z |
| spellingShingle | Quantifying day-to-day variations in 4DCBCT-based PCA motion models Dhou, Salam Four-dimensional cone beam CT (4DCBCT) PCA motion model Stereotactic body radiation therapy (SBRT) Inter-fraction variations |
| status_str | publishedVersion |
| title | Quantifying day-to-day variations in 4DCBCT-based PCA motion models |
| title_full | Quantifying day-to-day variations in 4DCBCT-based PCA motion models |
| title_fullStr | Quantifying day-to-day variations in 4DCBCT-based PCA motion models |
| title_full_unstemmed | Quantifying day-to-day variations in 4DCBCT-based PCA motion models |
| title_short | Quantifying day-to-day variations in 4DCBCT-based PCA motion models |
| title_sort | Quantifying day-to-day variations in 4DCBCT-based PCA motion models |
| topic | Four-dimensional cone beam CT (4DCBCT) PCA motion model Stereotactic body radiation therapy (SBRT) Inter-fraction variations |
| url | https://hdl.handle.net/11073/25545 |