Analysing breast tissue composition with MRI using currently available short, simple sequences
© 2015 The Royal College of Radiologists. Aim: To determine the most robust commonly available magnetic resonance imaging (MRI) sequence to quantify breast tissue composition at 1.5 T. Materials and methods: Two-dimensional (2D) T1-weighted, Dixon fat, Dixon water and SPAIR images were obtained from...
| Main Authors: | , , |
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| Format: | Journal Article |
| Published: |
W.B. Saunders Ltd
2016
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| Online Access: | http://hdl.handle.net/20.500.11937/50785 |
| _version_ | 1848758535427457024 |
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| author | Chau, Anson Hua, J. Taylor, D. |
| author_facet | Chau, Anson Hua, J. Taylor, D. |
| author_sort | Chau, Anson |
| building | Curtin Institutional Repository |
| collection | Online Access |
| description | © 2015 The Royal College of Radiologists. Aim: To determine the most robust commonly available magnetic resonance imaging (MRI) sequence to quantify breast tissue composition at 1.5 T. Materials and methods: Two-dimensional (2D) T1-weighted, Dixon fat, Dixon water and SPAIR images were obtained from five participants and a breast phantom using a 1.5 T Siemens Aera MRI system. Manual segmentation of the breasts was performed, and an in-house computer program was used to generate signal intensity histograms. Relative trough depth and relative peak separation were used to determine the robustness of the images for quantifying the two breast tissues. Total breast volumes and percentage breast densities calculated using the four sequences were compared. Results: Dixon fat histograms had consistently low relative trough depth and relative peak separation compared to those obtained using other sequences. There was no significant difference in total breast volumes and percentage breast densities of the participants or breast phantom using Dixon fat and 2D T1-weighted histograms. Dixon water and SPAIR histograms were not suitable for quantifying breast tissue composition. Conclusion: Dixon fat images are the most robust for the quantification of breast tissue composition using a signal intensity histogram. |
| first_indexed | 2025-11-14T09:45:32Z |
| format | Journal Article |
| id | curtin-20.500.11937-50785 |
| institution | Curtin University Malaysia |
| institution_category | Local University |
| last_indexed | 2025-11-14T09:45:32Z |
| publishDate | 2016 |
| publisher | W.B. Saunders Ltd |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | curtin-20.500.11937-507852017-09-13T15:34:50Z Analysing breast tissue composition with MRI using currently available short, simple sequences Chau, Anson Hua, J. Taylor, D. © 2015 The Royal College of Radiologists. Aim: To determine the most robust commonly available magnetic resonance imaging (MRI) sequence to quantify breast tissue composition at 1.5 T. Materials and methods: Two-dimensional (2D) T1-weighted, Dixon fat, Dixon water and SPAIR images were obtained from five participants and a breast phantom using a 1.5 T Siemens Aera MRI system. Manual segmentation of the breasts was performed, and an in-house computer program was used to generate signal intensity histograms. Relative trough depth and relative peak separation were used to determine the robustness of the images for quantifying the two breast tissues. Total breast volumes and percentage breast densities calculated using the four sequences were compared. Results: Dixon fat histograms had consistently low relative trough depth and relative peak separation compared to those obtained using other sequences. There was no significant difference in total breast volumes and percentage breast densities of the participants or breast phantom using Dixon fat and 2D T1-weighted histograms. Dixon water and SPAIR histograms were not suitable for quantifying breast tissue composition. Conclusion: Dixon fat images are the most robust for the quantification of breast tissue composition using a signal intensity histogram. 2016 Journal Article http://hdl.handle.net/20.500.11937/50785 10.1016/j.crad.2015.11.020 W.B. Saunders Ltd restricted |
| spellingShingle | Chau, Anson Hua, J. Taylor, D. Analysing breast tissue composition with MRI using currently available short, simple sequences |
| title | Analysing breast tissue composition with MRI using currently available short, simple sequences |
| title_full | Analysing breast tissue composition with MRI using currently available short, simple sequences |
| title_fullStr | Analysing breast tissue composition with MRI using currently available short, simple sequences |
| title_full_unstemmed | Analysing breast tissue composition with MRI using currently available short, simple sequences |
| title_short | Analysing breast tissue composition with MRI using currently available short, simple sequences |
| title_sort | analysing breast tissue composition with mri using currently available short, simple sequences |
| url | http://hdl.handle.net/20.500.11937/50785 |