Thresholding approaches for estimating paraspinal muscle fat infiltration using T1‐ and T2‐weighted MRI: Comparative analysis using water–fat MRI
Abstract Background Paraspinal muscle fat infiltration is associated with spinal degeneration and low back pain, however, quantifying muscle fat using clinical magnetic resonance imaging (MRI) techniques continues to be a challenge. Advanced MRI techniques, including chemical‐shift encoding (CSE) ba...
| Main Authors: | , , , , , , , , , |
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| Format: | Article |
| Language: | English |
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Wiley
2024-03-01
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| Series: | JOR Spine |
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| Online Access: | https://doi.org/10.1002/jsp2.1301 |
| _version_ | 1797244311471915008 |
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| author | Jessica Ornowski Lucas Dziesinski Madeline Hess Roland Krug Maryse Fortin Abel Torres‐Espin Sharmila Majumdar Valentina Pedoia Noah B. Bonnheim Jeannie F. Bailey |
| author_facet | Jessica Ornowski Lucas Dziesinski Madeline Hess Roland Krug Maryse Fortin Abel Torres‐Espin Sharmila Majumdar Valentina Pedoia Noah B. Bonnheim Jeannie F. Bailey |
| author_sort | Jessica Ornowski |
| collection | DOAJ |
| description | Abstract Background Paraspinal muscle fat infiltration is associated with spinal degeneration and low back pain, however, quantifying muscle fat using clinical magnetic resonance imaging (MRI) techniques continues to be a challenge. Advanced MRI techniques, including chemical‐shift encoding (CSE) based water–fat MRI, enable accurate measurement of muscle fat, but such techniques are not widely available in routine clinical practice. Methods To facilitate assessment of paraspinal muscle fat using clinical imaging, we compared four thresholding approaches for estimating muscle fat fraction (FF) using T1‐ and T2‐weighted images, with measurements from water–fat MRI as the ground truth: Gaussian thresholding, Otsu's method, K‐mean clustering, and quadratic discriminant analysis. Pearson's correlation coefficients (r), mean absolute errors, and mean bias errors were calculated for FF estimates from T1‐ and T2‐weighted MRI with water–fat MRI for the lumbar multifidus (MF), erector spinae (ES), quadratus lumborum (QL), and psoas (PS), and for all muscles combined. Results We found that for all muscles combined, FF measurements from T1‐ and T2‐weighted images were strongly positively correlated with measurements from the water–fat images for all thresholding techniques (r = 0.70–0.86, p < 0.0001) and that variations in inter‐muscle correlation strength were much greater than variations in inter‐method correlation strength. Conclusion We conclude that muscle FF can be quantified using thresholded T1‐ and T2‐weighted MRI images with relatively low bias and absolute error in relation to water–fat MRI, particularly in the MF and ES, and the choice of thresholding technique should depend on the muscle and clinical MRI sequence of interest. |
| first_indexed | 2024-04-24T19:09:00Z |
| format | Article |
| id | doaj.art-fbb9fd18ab55473c9abd4195ca442afa |
| institution | Directory Open Access Journal |
| issn | 2572-1143 |
| language | English |
| last_indexed | 2024-04-24T19:09:00Z |
| publishDate | 2024-03-01 |
| publisher | Wiley |
| record_format | Article |
| series | JOR Spine |
| spelling | doaj.art-fbb9fd18ab55473c9abd4195ca442afa2024-03-26T14:08:39ZengWileyJOR Spine2572-11432024-03-0171n/an/a10.1002/jsp2.1301Thresholding approaches for estimating paraspinal muscle fat infiltration using T1‐ and T2‐weighted MRI: Comparative analysis using water–fat MRIJessica Ornowski0Lucas Dziesinski1Madeline Hess2Roland Krug3Maryse Fortin4Abel Torres‐Espin5Sharmila Majumdar6Valentina Pedoia7Noah B. Bonnheim8Jeannie F. Bailey9Department of Orthopaedic Surgery University of California San Francisco California USADepartment of Orthopaedic Surgery University of California San Francisco California USADepartment of Radiology and Biomedical Imaging University of California San Francisco California USADepartment of Radiology and Biomedical Imaging University of California San Francisco California USADepartment of Health, Kinesiology, and Applied Physiology Concordia University Montreal Québec CanadaSchool of Public Health Sciences Faculty of Health University of Waterloo Waterloo Ontario CanadaDepartment of Radiology and Biomedical Imaging University of California San Francisco California USADepartment of Radiology and Biomedical Imaging University of California San Francisco California USADepartment of Orthopaedic Surgery University of California San Francisco California USADepartment of Orthopaedic Surgery University of California San Francisco California USAAbstract Background Paraspinal muscle fat infiltration is associated with spinal degeneration and low back pain, however, quantifying muscle fat using clinical magnetic resonance imaging (MRI) techniques continues to be a challenge. Advanced MRI techniques, including chemical‐shift encoding (CSE) based water–fat MRI, enable accurate measurement of muscle fat, but such techniques are not widely available in routine clinical practice. Methods To facilitate assessment of paraspinal muscle fat using clinical imaging, we compared four thresholding approaches for estimating muscle fat fraction (FF) using T1‐ and T2‐weighted images, with measurements from water–fat MRI as the ground truth: Gaussian thresholding, Otsu's method, K‐mean clustering, and quadratic discriminant analysis. Pearson's correlation coefficients (r), mean absolute errors, and mean bias errors were calculated for FF estimates from T1‐ and T2‐weighted MRI with water–fat MRI for the lumbar multifidus (MF), erector spinae (ES), quadratus lumborum (QL), and psoas (PS), and for all muscles combined. Results We found that for all muscles combined, FF measurements from T1‐ and T2‐weighted images were strongly positively correlated with measurements from the water–fat images for all thresholding techniques (r = 0.70–0.86, p < 0.0001) and that variations in inter‐muscle correlation strength were much greater than variations in inter‐method correlation strength. Conclusion We conclude that muscle FF can be quantified using thresholded T1‐ and T2‐weighted MRI images with relatively low bias and absolute error in relation to water–fat MRI, particularly in the MF and ES, and the choice of thresholding technique should depend on the muscle and clinical MRI sequence of interest.https://doi.org/10.1002/jsp2.1301fat infiltrationlow back painMRImuscle qualityparaspinal musclesthresholding |
| spellingShingle | Jessica Ornowski Lucas Dziesinski Madeline Hess Roland Krug Maryse Fortin Abel Torres‐Espin Sharmila Majumdar Valentina Pedoia Noah B. Bonnheim Jeannie F. Bailey Thresholding approaches for estimating paraspinal muscle fat infiltration using T1‐ and T2‐weighted MRI: Comparative analysis using water–fat MRI JOR Spine fat infiltration low back pain MRI muscle quality paraspinal muscles thresholding |
| title | Thresholding approaches for estimating paraspinal muscle fat infiltration using T1‐ and T2‐weighted MRI: Comparative analysis using water–fat MRI |
| title_full | Thresholding approaches for estimating paraspinal muscle fat infiltration using T1‐ and T2‐weighted MRI: Comparative analysis using water–fat MRI |
| title_fullStr | Thresholding approaches for estimating paraspinal muscle fat infiltration using T1‐ and T2‐weighted MRI: Comparative analysis using water–fat MRI |
| title_full_unstemmed | Thresholding approaches for estimating paraspinal muscle fat infiltration using T1‐ and T2‐weighted MRI: Comparative analysis using water–fat MRI |
| title_short | Thresholding approaches for estimating paraspinal muscle fat infiltration using T1‐ and T2‐weighted MRI: Comparative analysis using water–fat MRI |
| title_sort | thresholding approaches for estimating paraspinal muscle fat infiltration using t1 and t2 weighted mri comparative analysis using water fat mri |
| topic | fat infiltration low back pain MRI muscle quality paraspinal muscles thresholding |
| url | https://doi.org/10.1002/jsp2.1301 |
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