Comparison between magnetic resonance imaging and electrical impedance myography for evaluating lumbar skeletal muscle composition

Abstract

Background To compare electrical impedance myography (EIM) and MRI in assessing lumbar skeletal muscle composition. Methods One hundred forty-one patients (78 females, mean age 57 ± 19 years) were prospectively enrolled and underwent lumbar spine MRI, EIM with Skulpt®, and clinical evaluation including the questionnaire SARC-F. MRIs were reviewed to assess the Goutallier score of paravertebral muscles at L3 level and to calculate the cross sectional area (CSA) of both psoas, quadratus lumborum, erector spinae, and multifidus muscles on a single axial slice at L3 level, in order to calculate the skeletal muscle index (SMI=CSA/height2). We tested the correlation between EIM-derived parameters [body fat percentage (BF%) and muscle quality] and body mass index (BMI), Goutallier score (1–4), SMI, and SARC-F scores (0–10) using the Pearson correlation coefficient. The strength of association was considered large (0.5 to 1.0), medium (0.3 to 0.5), small (0.1 to 0.3). Results Pearson’s correlation coefficient showed small (0.26) but significant (p < 0.01) positive correlation between BF% obtained with EIM and Goutallier score. Small negative correlation (− 0.22, p < 0.01) was found between EIM muscle quality and Goutallier Score. Large negative correlation (− 0.56, p < 0.01) was found between SMI and Goutallier Score, while SMI showed small negative correlation with SARC-F (− 0.29, p < 0.01). Medium positive correlation was found between Goutallier Score and SARC-F (0.41, p < 0.01). BMI showed medium positive correlation with SMI (r = 0.369, p < 0.01) and small correlation with EIM muscle quality (r = − 0.291, p < 0.05) and BF% (r = 0.227, p < 0.05). We found a substantial increase of the strength of associations of BF% and muscle quality with Goutallier in the 18–40 years (r = 0.485 and r = − 0.401, respectively) and in the 41–70 years group (r = 0.448 and r = − 0.365, respectively). Conclusions Muscle quality and BF% measured by EIM device showed only small strength of correlation with other quantitative parameters for assessing muscle mass and fat infiltration. Interesting results have been found in younger patients, but Skulpt Chisel™ should be applied cautiously to assess lumbar skeletal muscle composition. This point deserves further investigation and other studies are warranted. Trial registration The registration number of this study is 107/INT/2019.

Electrical impedance myography combined with quantitative assessment techniques in paretic muscle of stroke survivors: Insights and challenges

“…Furthermore, several studies have established the relationship between EIM variables and structural features of muscles, as measured by MRI, CT, and DXA. Those studies also further supported the potential value of EIM in muscle structure assessment ( Anderson et al, 2014 ; McLester et al, 2018 ; van Rassel et al, 2019 ; Czeck et al, 2020 ; Hamel et al, 2020 ; Albano et al, 2022b , a ). While aforementioned correlation was validated, not all findings are fully consistent, since different techniques are sensitive to different pathological features of muscle ( Roy et al, 2019 ).…”

Assessing paraspinal muscle atrophy with electrical impedance myography: Limitations and insights

“…Also, approaches such as machine learning, as previously described, 31 may be helpful for creating predictive models for determining muscle health based on EIM measurements across different frequencies. Though one commercially available EIM device providing a semiquantitative muscle health prediction was previously shown to have a weak correlation with PMA, 18 such machine learning models could be specifically trained for patients with PMA, potentially improving accuracy.…”

“…17 Meanwhile, another study reported only a weak correlation between the semiquantitative grading of PMA on MRI and the fat percentage and muscle quality estimates by a commercial EIM device. 18 Thus, the relationship between the EIM readings at different frequencies with quantitative measurements of PMA on MRI scans, such as the functional cross-sectional area (fCSA) and fatty infiltration (FI), is unclear. Furthermore, whether surrounding tissue parameters such as dermal and subcutaneous layer thickness or echogenicity, which were previously shown to affect EIM readings confound the results in paraspinal EIM has not been previously reported.…”

“…One study found that the EIM readings varied significantly between patients with chronic low back back pain and those without 17 . Meanwhile, another study reported only a weak correlation between the semiquantitative grading of PMA on MRI and the fat percentage and muscle quality estimates by a commercial EIM device 18 . Thus, the relationship between the EIM readings at different frequencies with quantitative measurements of PMA on MRI scans, such as the functional cross‐sectional area (fCSA) and fatty infiltration (FI), is unclear.…”

Identification of abdominal aortic aneurysm subtypes based on mechanosensitive genes

“…The GSE98278 study was chosen for the analysis because it categorized AAAs as "large-sized" and "intermediate-sized" subgroups during patient enrollment [33]. After testing multiple SVM models with different When the correlation coefficient is less than 0.3, the probability of correlation is considered small [34]. With this cutoff value, correlation analysis for the hub genes showed that TAGLN, VCL, and GAJ1 were positioned as the center nodes (Fig 3E).…”