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Ornowski J, Dziesinski L, Hess M, Krug R, Fortin M, Torres‐Espin A, Majumdar S, Pedoia V, Bonnheim NB, Bailey JF. Thresholding approaches for estimating paraspinal muscle fat infiltration using T1- and T2-weighted MRI: Comparative analysis using water-fat MRI. JOR Spine 2024; 7:e1301. [PMID: 38222819 PMCID: PMC10782057 DOI: 10.1002/jsp2.1301] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/30/2023] [Revised: 09/09/2023] [Accepted: 10/31/2023] [Indexed: 01/16/2024] Open
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.
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Affiliation(s)
- Jessica Ornowski
- Department of Orthopaedic SurgeryUniversity of CaliforniaSan FranciscoCaliforniaUSA
| | - Lucas Dziesinski
- Department of Orthopaedic SurgeryUniversity of CaliforniaSan FranciscoCaliforniaUSA
| | - Madeline Hess
- Department of Radiology and Biomedical ImagingUniversity of CaliforniaSan FranciscoCaliforniaUSA
| | - Roland Krug
- Department of Radiology and Biomedical ImagingUniversity of CaliforniaSan FranciscoCaliforniaUSA
| | - Maryse Fortin
- Department of Health, Kinesiology, and Applied PhysiologyConcordia UniversityMontrealQuébecCanada
| | - Abel Torres‐Espin
- School of Public Health SciencesFaculty of HealthUniversity of WaterlooWaterlooOntarioCanada
- Department of Physical TherapyUniversity of AlbertaEdmontonAlbertaCanada
- Department of Neurological SurgeryUniversity of CaliforniaSan FranciscoCaliforniaUSA
| | - Sharmila Majumdar
- Department of Radiology and Biomedical ImagingUniversity of CaliforniaSan FranciscoCaliforniaUSA
| | - Valentina Pedoia
- Department of Radiology and Biomedical ImagingUniversity of CaliforniaSan FranciscoCaliforniaUSA
| | - Noah B. Bonnheim
- Department of Orthopaedic SurgeryUniversity of CaliforniaSan FranciscoCaliforniaUSA
| | - Jeannie F. Bailey
- Department of Orthopaedic SurgeryUniversity of CaliforniaSan FranciscoCaliforniaUSA
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Nyayapati P, Booker J, Wu PIK, Theologis A, Dziesinski L, O'Neill C, Zheng P, Lotz JC, Matthew RP, Bailey JF. Compensatory biomechanics and spinal loading during dynamic maneuvers in patients with chronic low back pain. Eur Spine J 2022; 31:1889-1896. [PMID: 35604457 PMCID: PMC9252943 DOI: 10.1007/s00586-022-07253-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 08/15/2021] [Revised: 04/06/2022] [Accepted: 04/30/2022] [Indexed: 12/04/2022]
Abstract
Purpose This study explores the biomechanics underlying the sit-to-stand (STS) functional maneuver in chronic LBP patients to understand how different spinal disorders and levels of pain severity relate to unique compensatory biomechanical behaviors. This work stands to further our understanding of the relationship between spinal loading and symptoms in LBP patients. Methods We collected in-clinic motion data from 44 non-specific LBP (NS-LBP) and 42 spinal deformity LBP (SD-LBP) patients during routine clinical visits. An RGB-depth camera tracked 3D joint positions from the frontal view during unassisted, repeated STS maneuvers. Patient-reported outcomes (PROs) for back pain (VAS) and low back disability (ODI) were collected during the same clinical visit. Results Between patient groups, SD-LBP patients had 14.3% greater dynamic sagittal vertical alignment (dSVA) and 10.1% greater peak spine torque compared to NS-LBP patients (p < 0.001). SD-LBP patients also had 11.8% greater hip torque (p < 0.001) and 86.7% greater knee torque (p = 0.04) compared to NS-LBP patients. There were no significant differences between patient groups in regard to anterior or vertical torso velocities, but anterior and vertical torso velocities correlated with both VAS (r = − 0.38, p < 0.001) and ODI (r = − 0.29, p = 0.01). PROs did not correlate with other variables. Conclusion Patients with LBP differ in movement biomechanics during an STS transfer as severity of symptoms may relate to different compensatory strategies that affect spinal loading. Further research aims to establish relationships between movement and PROs and to inform targeted rehabilitation approaches.
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Affiliation(s)
- Priya Nyayapati
- Department of Orthopaedic Surgery, University of California, 95 Kirkham St., San Francisco, CA, 94122, USA.,Albany Medical College, Albany, NY, USA
| | - Jacqueline Booker
- Department of Orthopaedic Surgery, University of California, 95 Kirkham St., San Francisco, CA, 94122, USA.,School of Medicine, University of California, San Francisco, CA, USA
| | - Peter I-Kung Wu
- Department of Orthopaedic Surgery, University of California, 95 Kirkham St., San Francisco, CA, 94122, USA
| | - Alekos Theologis
- Department of Orthopaedic Surgery, University of California, 95 Kirkham St., San Francisco, CA, 94122, USA
| | - Lucas Dziesinski
- Department of Orthopaedic Surgery, University of California, 95 Kirkham St., San Francisco, CA, 94122, USA
| | - Conor O'Neill
- Department of Orthopaedic Surgery, University of California, 95 Kirkham St., San Francisco, CA, 94122, USA
| | - Patricia Zheng
- Department of Orthopaedic Surgery, University of California, 95 Kirkham St., San Francisco, CA, 94122, USA
| | - Jeffrey C Lotz
- Department of Orthopaedic Surgery, University of California, 95 Kirkham St., San Francisco, CA, 94122, USA
| | - Robert P Matthew
- Department of Orthopaedic Surgery, University of California, 95 Kirkham St., San Francisco, CA, 94122, USA
| | - Jeannie F Bailey
- Department of Orthopaedic Surgery, University of California, 95 Kirkham St., San Francisco, CA, 94122, USA.
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