Nico Sollmann1,2,3,4, Noah B Bonnheim5, Gabby B Joseph1, Ravi Chachad1, Jiamin Zhou1, Zehra Akkaya1, Amir M Pirmoazen1, Jeannie F Bailey5, Xiaojie Guo5, Ann A Lazar6, Thomas M Link1, Aaron J Fields5, Roland Krug1. 1. Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, California. 2. Department of Diagnostic and Interventional Radiology, University Hospital Ulm, Ulm, Germany. 3. Department of Diagnostic and Interventional Neuroradiology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany. 4. TUM-Neuroimaging Center, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany. 5. Department of Orthopaedic Surgery, University of California San Francisco, San Francisco, California, USA. 6. Department of Epidemiology and Biostatistics, University of California San Francisco, San Francisco, California, USA.
Abstract
BACKGROUND: Paraspinal musculature (PSM) is increasingly recognized as a contributor to low back pain (LBP), but with conventional MRI sequences, assessment is limited. Chemical shift encoding-based water-fat MRI (CSE-MRI) enables the measurement of PSM fat fraction (FF), which may assist investigations of chronic LBP. PURPOSE: To investigate associations between PSM parameters from conventional MRI and CSE-MRI and between PSM parameters and pain. STUDY TYPE: Prospective, cross-sectional. POPULATION: Eighty-four adults with chronic LBP (44.6 ± 13.4 years; 48 males). FIELD STRENGTH/SEQUENCE: 3-T, T1-weighted fast spin-echo and iterative decomposition of water and fat with echo asymmetry and least squares estimation sequences. ASSESSMENT: T1-weighted images for Goutallier classification (GC), muscle volume, lumbar indentation value, and muscle-fat index, CSE-MRI for FF extraction (L1/2-L5/S1). Pain was self-reported using a visual analogue scale (VAS). Intra- and/or interreader agreement was assessed for MRI-derived parameters. STATISTICAL TESTS: Mixed-effects and linear regression models to 1) assess relationships between PSM parameters (entire cohort and subgroup with GC grades 0 and 1; statistical significance α = 0.0025) and 2) evaluate associations of PSM parameters with pain (α = 0.05). Intraclass correlation coefficients (ICCs) for intra- and/or interreader agreement. RESULTS: The FF showed excellent intra- and interreader agreement (ICC range: 0.97-0.99) and was significantly associated with GC at all spinal levels. Subgroup analysis suggested that early/subtle changes in PSM are detectable with FF but not with GC, given the absence of significant associations between FF and GC (P-value range: 0.036 at L5/S1 to 0.784 at L2/L3). Averaged over all spinal levels, FF and GC were significantly associated with VAS scores. DATA CONCLUSION: In the absence of FF, GC may be the best surrogate for PSM quality. Given the ability of CSE-MRI to detect muscle alterations at early stages of PSM degeneration, this technique may have potential for further investigations of the role of PSM in chronic LBP. LEVEL OF EVIDENCE: 2 TECHNICAL EFFICACY STAGE: 2.
BACKGROUND: Paraspinal musculature (PSM) is increasingly recognized as a contributor to low back pain (LBP), but with conventional MRI sequences, assessment is limited. Chemical shift encoding-based water-fat MRI (CSE-MRI) enables the measurement of PSM fat fraction (FF), which may assist investigations of chronic LBP. PURPOSE: To investigate associations between PSM parameters from conventional MRI and CSE-MRI and between PSM parameters and pain. STUDY TYPE: Prospective, cross-sectional. POPULATION: Eighty-four adults with chronic LBP (44.6 ± 13.4 years; 48 males). FIELD STRENGTH/SEQUENCE: 3-T, T1-weighted fast spin-echo and iterative decomposition of water and fat with echo asymmetry and least squares estimation sequences. ASSESSMENT: T1-weighted images for Goutallier classification (GC), muscle volume, lumbar indentation value, and muscle-fat index, CSE-MRI for FF extraction (L1/2-L5/S1). Pain was self-reported using a visual analogue scale (VAS). Intra- and/or interreader agreement was assessed for MRI-derived parameters. STATISTICAL TESTS: Mixed-effects and linear regression models to 1) assess relationships between PSM parameters (entire cohort and subgroup with GC grades 0 and 1; statistical significance α = 0.0025) and 2) evaluate associations of PSM parameters with pain (α = 0.05). Intraclass correlation coefficients (ICCs) for intra- and/or interreader agreement. RESULTS: The FF showed excellent intra- and interreader agreement (ICC range: 0.97-0.99) and was significantly associated with GC at all spinal levels. Subgroup analysis suggested that early/subtle changes in PSM are detectable with FF but not with GC, given the absence of significant associations between FF and GC (P-value range: 0.036 at L5/S1 to 0.784 at L2/L3). Averaged over all spinal levels, FF and GC were significantly associated with VAS scores. DATA CONCLUSION: In the absence of FF, GC may be the best surrogate for PSM quality. Given the ability of CSE-MRI to detect muscle alterations at early stages of PSM degeneration, this technique may have potential for further investigations of the role of PSM in chronic LBP. LEVEL OF EVIDENCE: 2 TECHNICAL EFFICACY STAGE: 2.
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