View-sharing for 4D magnetic resonance imaging with randomized projection-encoding enables improvements of respiratory motion imaging for treatment planning in abdominothoracic radiotherapy
Background and Purpose: The accuracy and precision of radiation therapy are dependent on the characterization of organ-at-risk and target motion. This work aims to demonstrate a 4D magnetic resonance imaging (MRI) method for improving spatial and temporal resolution in respiratory motion imaging for...
| Main Authors: | , , , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2023-01-01
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| Series: | Physics and Imaging in Radiation Oncology |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2405631622001075 |
| _version_ | 1797870496313769984 |
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| author | Ergys Subashi Li Feng Yilin Liu Scott Robertson Paul Segars Bastiaan Driehuys Christopher R. Kelsey Fang-Fang Yin Ricardo Otazo Jing Cai |
| author_facet | Ergys Subashi Li Feng Yilin Liu Scott Robertson Paul Segars Bastiaan Driehuys Christopher R. Kelsey Fang-Fang Yin Ricardo Otazo Jing Cai |
| author_sort | Ergys Subashi |
| collection | DOAJ |
| description | Background and Purpose: The accuracy and precision of radiation therapy are dependent on the characterization of organ-at-risk and target motion. This work aims to demonstrate a 4D magnetic resonance imaging (MRI) method for improving spatial and temporal resolution in respiratory motion imaging for treatment planning in abdominothoracic radiotherapy. Materials and Methods: The spatial and temporal resolution of phase-resolved respiratory imaging is improved by considering a novel sampling function based on quasi-random projection-encoding and peripheral k-space view-sharing. The respiratory signal is determined directly from k-space, obviating the need for an external surrogate marker. The average breathing curve is used to optimize spatial resolution and temporal blurring by limiting the extent of data sharing in the Fourier domain. Improvements in image quality are characterized by evaluating changes in signal-to-noise ratio (SNR), resolution, target detection, and level of artifact. The method is validated in simulations, in a dynamic phantom, and in-vivo imaging. Results: Sharing of high-frequency k-space data, driven by the average breathing curve, improves spatial resolution and reduces artifacts. Although equal sharing of k-space data improves resolution and SNR in stationary features, phases with large temporal changes accumulate significant artifacts due to averaging of high frequency features. In the absence of view-sharing, no averaging and detection artifacts are observed while spatial resolution is degraded. Conclusions: The use of a quasi-random sampling function, with view-sharing driven by the average breathing curve, provides a feasible method for self-navigated 4D-MRI at improved spatial resolution. |
| first_indexed | 2024-04-10T00:29:26Z |
| format | Article |
| id | doaj.art-09bc5bf9b1534f598d4085d87d78b36e |
| institution | Directory Open Access Journal |
| issn | 2405-6316 |
| language | English |
| last_indexed | 2024-04-10T00:29:26Z |
| publishDate | 2023-01-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Physics and Imaging in Radiation Oncology |
| spelling | doaj.art-09bc5bf9b1534f598d4085d87d78b36e2023-03-15T04:28:39ZengElsevierPhysics and Imaging in Radiation Oncology2405-63162023-01-0125100409View-sharing for 4D magnetic resonance imaging with randomized projection-encoding enables improvements of respiratory motion imaging for treatment planning in abdominothoracic radiotherapyErgys Subashi0Li Feng1Yilin Liu2Scott Robertson3Paul Segars4Bastiaan Driehuys5Christopher R. Kelsey6Fang-Fang Yin7Ricardo Otazo8Jing Cai9Department of Medical Physics, Memorial Sloan Kettering Cancer Center, New York, NY, United States; Corresponding author.Biomedical Engineering and Imaging Institute, Department of Radiology, Icahn School of Medicine at Mount Sinai, New York, NY, United StatesDepartment of Medical Physics, Memorial Sloan Kettering Cancer Center, New York, NY, United StatesMedical Physics Graduate Program, Duke University Medical Center, Durham, NC, United States; Department of Radiology, Duke University Medical Center, Durham, NC, United StatesMedical Physics Graduate Program, Duke University Medical Center, Durham, NC, United States; Department of Radiology, Duke University Medical Center, Durham, NC, United StatesMedical Physics Graduate Program, Duke University Medical Center, Durham, NC, United States; Department of Radiology, Duke University Medical Center, Durham, NC, United StatesDepartment of Radiation Oncology, Duke University Medical Center, Durham, NC, United StatesMedical Physics Graduate Program, Duke University Medical Center, Durham, NC, United States; Department of Radiation Oncology, Duke University Medical Center, Durham, NC, United StatesDepartment of Medical Physics, Memorial Sloan Kettering Cancer Center, New York, NY, United StatesDepartment of Health Technology and Informatics, The Hong Kong Polytechnic University, Kowloon, Hong KongBackground and Purpose: The accuracy and precision of radiation therapy are dependent on the characterization of organ-at-risk and target motion. This work aims to demonstrate a 4D magnetic resonance imaging (MRI) method for improving spatial and temporal resolution in respiratory motion imaging for treatment planning in abdominothoracic radiotherapy. Materials and Methods: The spatial and temporal resolution of phase-resolved respiratory imaging is improved by considering a novel sampling function based on quasi-random projection-encoding and peripheral k-space view-sharing. The respiratory signal is determined directly from k-space, obviating the need for an external surrogate marker. The average breathing curve is used to optimize spatial resolution and temporal blurring by limiting the extent of data sharing in the Fourier domain. Improvements in image quality are characterized by evaluating changes in signal-to-noise ratio (SNR), resolution, target detection, and level of artifact. The method is validated in simulations, in a dynamic phantom, and in-vivo imaging. Results: Sharing of high-frequency k-space data, driven by the average breathing curve, improves spatial resolution and reduces artifacts. Although equal sharing of k-space data improves resolution and SNR in stationary features, phases with large temporal changes accumulate significant artifacts due to averaging of high frequency features. In the absence of view-sharing, no averaging and detection artifacts are observed while spatial resolution is degraded. Conclusions: The use of a quasi-random sampling function, with view-sharing driven by the average breathing curve, provides a feasible method for self-navigated 4D-MRI at improved spatial resolution.http://www.sciencedirect.com/science/article/pii/S2405631622001075Respiratory imaging4D-MRIProjection-encodingView-sharing |
| spellingShingle | Ergys Subashi Li Feng Yilin Liu Scott Robertson Paul Segars Bastiaan Driehuys Christopher R. Kelsey Fang-Fang Yin Ricardo Otazo Jing Cai View-sharing for 4D magnetic resonance imaging with randomized projection-encoding enables improvements of respiratory motion imaging for treatment planning in abdominothoracic radiotherapy Physics and Imaging in Radiation Oncology Respiratory imaging 4D-MRI Projection-encoding View-sharing |
| title | View-sharing for 4D magnetic resonance imaging with randomized projection-encoding enables improvements of respiratory motion imaging for treatment planning in abdominothoracic radiotherapy |
| title_full | View-sharing for 4D magnetic resonance imaging with randomized projection-encoding enables improvements of respiratory motion imaging for treatment planning in abdominothoracic radiotherapy |
| title_fullStr | View-sharing for 4D magnetic resonance imaging with randomized projection-encoding enables improvements of respiratory motion imaging for treatment planning in abdominothoracic radiotherapy |
| title_full_unstemmed | View-sharing for 4D magnetic resonance imaging with randomized projection-encoding enables improvements of respiratory motion imaging for treatment planning in abdominothoracic radiotherapy |
| title_short | View-sharing for 4D magnetic resonance imaging with randomized projection-encoding enables improvements of respiratory motion imaging for treatment planning in abdominothoracic radiotherapy |
| title_sort | view sharing for 4d magnetic resonance imaging with randomized projection encoding enables improvements of respiratory motion imaging for treatment planning in abdominothoracic radiotherapy |
| topic | Respiratory imaging 4D-MRI Projection-encoding View-sharing |
| url | http://www.sciencedirect.com/science/article/pii/S2405631622001075 |
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