Quantitative multi-parameter assessment of age- and gender-related variation of back extensor muscles in healthy adults using Dixon MR imaging

Chen, Pinzhen; Zhou, Zhou; Sun, Lei; Yu, Xueke; Li, Kai; Li, Jin; He, Min; Zhou, Xiaoyue; Luo, Fei; Zhao, Jian; Chen, Wei

doi:10.1007/s00330-023-09954-w

Cited by 2 publications

(2 citation statements)

References 40 publications

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“…The observation of changing mean diffusivity over the span of the lumbar spine may draw into question the assumption of spatial uniformity, however we note that spatial consistency was assumed within one spinal segment, not across the entire spine. Indeed, differences in IVIM parameters across the spinal segments are likely to reflect differences in structure and physiology of the paraspinal muscles from cranial to caudal, including differences in size (including the relative contribution of erector spinae vs. multifidus), tissue composition, and metabolic capacity (41)(42)(43). We also note that the IVIM parameters were generally more variable at L1 and L5, potentially due to respiratory motion at the superior extent and coil sensitivity at the inferior extent.…”

Section: Discussionmentioning

confidence: 86%

Assessment of fitting methods and variability of IVIM parameters in muscles of the lumbar spine at rest

Englund,

Berry,

Behun

et al. 2024

Front. Musculoskelet. Disord.

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Intravoxel incoherent motion (IVIM) MRI provides insight into tissue diffusion and perfusion. Here, estimates of perfusion fraction (f), pseudo-diffusion coefficient (D*), and diffusion coefficient (D) obtained via different fitting methods are compared to ascertain (1) the optimal analysis strategy for muscles of the lumbar spine and (2) repeatability of IVIM parameters in skeletal muscle at rest. Diffusion-weighted images were acquired in the lumbar spine at rest in 15 healthy participants. Data were fit to the bi-exponential IVIM model to estimate f, D* and D using three variably segmented approaches based on non-linear least squares fitting, and a Bayesian fitting method. Assuming that perfusion and diffusion are temporally stable in skeletal muscle at rest, and spatially uniform within a spinal segment, the optimal analysis strategy was determined as the approach with the lowest temporal or spatial variation and smallest residual between measured and fit data. Inter-session repeatability of IVIM parameters was evaluated in a subset of 11 people. Finally, simulated IVIM signal at varying signal to noise ratio were evaluated to understand precision and bias. Experimental results showed that IVIM parameter values differed depending on the fitting method. A three-step non-linear least squares fitting approach, where D, f, and D* were estimated sequentially, generally yielded the lowest spatial and temporal variation. Solving all parameters simultaneously yielded the lowest residual between measured and fit data, however there was substantial spatial and temporal variability. Results obtained by Bayesian fitting had high spatial and temporal variability in addition to a large residual between measured and fit data. Simulations showed that all fitting methods can fit the IVIM data at signal to noise ratios >35, and that D* was the most challenging to accurately obtain. Overall, this study motivates use of a three-step non-linear least squares fitting strategy to quantify IVIM parameters in skeletal muscle.

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Section: Discussionmentioning

confidence: 86%

Assessment of fitting methods and variability of IVIM parameters in muscles of the lumbar spine at rest

Englund,

Berry,

Behun

et al. 2024

Front. Musculoskelet. Disord.

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“…Magnetic resonance imaging (MRI) enables fat fraction (FF) mapping through chemical shift encoding, and the FF is commonly defined as the percentage of proton density of fat molecules relative to the combined proton density of water and fat molecules ( 19 , 20 ). Compared with traditional imaging techniques such as dual-energy x-ray absorptiometry (DXA) and bioelectrical impedance analysis (BIA), FF mapping by MRI can provide fast and accurate evaluation of the fat composition of the whole body, and it has been widely applied in the assessment of abdominal muscle (AM) ( 21 – 24 ), BMAT ( 23 – 25 ), and ectopic fat deposition ( 25 , 26 ).…”

Section: Introductionmentioning

confidence: 99%

Association between type 2 diabetes mellitus and body composition based on MRI fat fraction mapping

An,

Zhang,

Wang

et al. 2024

Front. Public Health

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PurposeTo explore the association between type 2 diabetes mellitus (T2DM) and body composition based on magnetic resonance fat fraction (FF) mapping.MethodsA total of 341 subjects, who underwent abdominal MRI examination with FF mapping were enrolled in this study, including 68 T2DM patients and 273 non-T2DM patients. The FFs and areas of visceral adipose tissue (VAT), subcutaneous adipose tissue (SAT) and abdominal muscle (AM) were measured at the level of the L1-L2 vertebral. The FF of bone marrow adipose tissue (BMAT) was determined by the averaged FF values measured at the level of T12 and L1 vertebral, respectively. The whole hepatic fat fraction (HFF) and pancreatic fat fraction (PFF) were measured based on 3D semi-automatic segmentation on the FF mapping. All data were analyzed by GraphPad Prism and MedCalc.ResultsVAT area, VAT FF, HFF, PFF of T2DM group were higher than those of non-T2DM group after adjusting for age and sex (P < 0.05). However, there was no differences in SAT area, SAT FF, BMAT FF, AM area and AM FF between the two groups (P > 0.05). VAT area and PFF were independent risk factors of T2DM (all P < 0.05). The area under the curve (AUC) of the receiver operating characteristic (ROC) for VAT area and PFF in differentiating between T2DM and non-T2DM were 0.685 and 0.787, respectively, and the AUC of PFF was higher than VAT area (P < 0.05). Additionally, in seemingly healthy individuals, the SAT area, VAT area, and AM area were found to be significantly associated with being overweight and/or obese (BMI ≥ 25) (all P < 0.05).ConclusionsIn this study, it was found that there were significant associations between T2DM and VAT area, VAT FF, HFF and PFF. In addition, VAT area and PFF were the independent risk factors of T2DM. Especially, PFF showed a high diagnostic performance in discrimination between T2DM and non-T2DM. These findings may highlight the crucial role of PFF in the pathophysiology of T2DM, and it might be served as a potential imaging biomarker of the prevention and treatment of T2DM. Additionally, in individuals without diabetes, focusing on SAT area, VAT area and AM area may help identify potential health risks and provide a basis for targeted weight management and prevention measures.

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Quantitative multi-parameter assessment of age- and gender-related variation of back extensor muscles in healthy adults using Dixon MR imaging

Cited by 2 publications

References 40 publications

Assessment of fitting methods and variability of IVIM parameters in muscles of the lumbar spine at rest

Assessment of fitting methods and variability of IVIM parameters in muscles of the lumbar spine at rest

Association between type 2 diabetes mellitus and body composition based on MRI fat fraction mapping

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