Electrical Properties of Lumbar Paraspinal Muscles in Young Adults With and Without Chronic Low Back Pain Based on Electrical Impedance Myography: A Cross-Sectional Study

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

Paraspinal muscle atrophy is gaining attention in spine surgery due to its link to back pain, spinal degeneration and worse postoperative outcomes. Electrical impedance myography (EIM) is a noninvasive diagnostic tool for muscle quality assessment, primarily utilized for patients with neuromuscular diseases. However, EIM's accuracy for paraspinal muscle assessment remains understudied. In this study, we investigated the correlation between EIM readings and MRI-derived muscle parameters, as well as the influence of dermal and subcutaneous parameters on these readings. We retrospectively analyzed patients with lumbar spinal degeneration who underwent paraspinal EIM assessment between May 2023 to July 2023. Paraspinal muscle fatty infiltration (FI) and functional cross-sectional area (fCSA), as well as the subcutaneous thickness were assessed on MRI scans. Skin ultrasound imaging was assessed for dermal thickness and the echogenicities of the dermal and subcutaneous layers. All measurements were performed on the bilaterally. The correlation between EIM readings were compared with ultrasound and MRI parameters using Spearman's correlation analyses. A total of 20 patients (65.0% female) with a median age of 69.5 years (IQR, 61.3-73.8) were analyzed. The fCSA and FI did not significantly correlate with the EIM readings, regardless of frequency. All EIM readings across frequencies correlated with subcutaneous thickness, echogenicity, or dermal thickness. With the current methodology, paraspinal EIM is not a valid alternative to MRI assessment of muscle quality, as it is strongly influenced by the dermal and subcutaneous layers. Further studies are required for refining the methodology and confirming our results.

Machine learning and clinical neurophysiology

Clinical neurophysiology constructs a wealth of dynamic information pertaining to the integrity and function of both central and peripheral nervous systems. As with many technological fields, there has been an explosion of data in neurophysiology over recent years, and this requires considerable analysis by experts. Computational algorithms and especially advances in machine learning (ML) have the ability to assist with this task and potentially reveal hidden insights. In this update article, we will provide a brief overview where such technology is being applied in clinical neurophysiology and possible future directions.

Evaluating growth trends of residual sporadic vestibular schwannomas: a systematic review and meta-analysis

BACKGROUND

Gross total resection remains the gold-standard approach for vestibular schwannomas (VS) when surgery is indicated. In select cases, incomplete resection (IR) becomes a desired alternative to preserve the facial nerve function and the patient's quality of life. While a lot of earlier studies described incompletely resected sporadic VSs as dormant, more recent studies reported a higher growth rate following IR, therefore an evaluation of the residual VS growth rates could have important implications for the follow-up treatment protocols and provide relevant information for neurosurgeons, neuro-otologists, neuropathologists, and radiologists. Although prognostic factors predicting preoperative VS growth have been previously investigated, these factors have not been investigated following IR. Our review aims to examine the growth rate of residual sporadic VS following IR and to examine variables associated with the regrowth of residual VS.

METHODS

The review was conducted in accordance with the PRISMA guidelines. Six databases (MEDLINE (Ovid), Embase (Ovid), CINAHL Plus (EBSCO), Cochrane Central Register of Controlled Trials (CENTRAL), WHO International Clinical Trials Registry Platform and UK Clinical Trials Gateway (WHO ICTRP) were searched. Full-text articles analysing growth rates in at least ten patients who had residual VS after IR were assessed. We conducted a meta-analysis using a random-effects model via RevMan.

RESULTS

14 studies totalling 849 patients were included in the analysis. The mean planimetric growth rate was 1.57 mm/year (range 0.16-3.81 mm/year). The mean volumetric growth rate was 281.725 mm³/year (range 17.9-530.0 mm³/year). Age, sex, pre-operative tumour size/volume, cystic tumour sub-type, MIB-1 index, and intracanalicular tumour location were not associated with residual growth. Residual tumour size/volume was statistically significant to growth (OR = 0.65, 95% CI 0.47-0.90, p = 0.01). Radiological re-growth occurred in an average of 26.6% of cases (range 0-54.5%).

CONCLUSION

From our analysis, only the residual tumour volume/size was associated with residual VS growth. Therefore, close postoperative surveillance for the first year, followed by an annual MRI scan for at least 5 years, and subsequently extended interval surveillance remains of utmost importance to monitor disease progression and provide timely surgical and adjuvant interventions. Our study shows that future work should be aimed at molecular and histological characteristics of residual VSs to aid prognostic understanding of growth.