An Objective and Reliable Method for Identifying Sarcopenia in Lumbar Spine Surgery Patients: Using Morphometric Measurements on Computed Tomography Imaging

Does Paraspinal Muscle Mass Predict Lumbar Lordosis Before and After Decompression for Degenerative Spinal Stenosis?

STUDY DESIGN

Retrospective cohort study.

OBJECTIVE

The purpose of this study was to determine whether muscle mass and quality of the lumbar paraspinal muscles was associated with improvements in lumbar lordosis and other sagittal parameters after isolated posterior lumbar decompression surgery for lumbar spinal stenosis.

SUMMARY OF BACKGROUND DATA

Individuals may develop sagittal imbalance over time, either due to degenerative changes or other spinal conditions. In patients with lumbar spinal stenosis, sagittal imbalance can further exacerbate symptoms of pain and radiculopathy. Sarcopenia of paraspinal muscles has been implicated in previous spine research as a variable with influence on surgical outcomes.

METHODS

Sagittal parameters were measured on preoperative and postoperative lateral lumbar radiographs and included lumbar lordosis (LL), sacral slope (SS), and pelvic tilt (PT). Preoperative MRI images were evaluated at the base of the L4 vertebral body to assess muscles mass of the psoas muscle and paravertebral muscles (PVM) and the Goutallier grade of the PVM. Patients were divided into three muscle size groups based on PVM normalized for body size (PVM/BMI): Group A (smallest), Group B, and Group C (largest).

RESULTS

Patients in group C had greater LL preoperatively (51.5° vs. 47.9° vs. 43.2, P =0.005) and postoperatively (52.2° vs. 48.9° vs. 45.7°, P =0.043). There was no significant difference in the ∆LL values between groups ( P >0.05). Patients in group C had larger SS preoperatively (35.2° vs. 32.1° vs. 30.0°, P =0.010) and postoperatively (36.1° vs. 33.0° vs. 31.7°, P =0.030). Regression analysis showed that PVM/BMI was a significant predictor of LL preoperatively ( P =0.039) and postoperatively ( P =0.031), as well as SS preoperatively ( P =0.001) and postoperatively ( P <0.001).

CONCLUSIONS

Muscle mass of the paravertebral muscles significantly impacts lumbar lordosis and sacral slope in patients with lumbar spinal stenosis before and after posterior lumbar decompression. These findings highlight the need to address risk factors for poor muscle quality in patients with sagittal imbalance.

LEVEL OF EVIDENCE

Level III.

The Role of Frailty and Sarcopenia in Predicting Major Adverse Events, Length of Stay and Reoperation Following En Bloc Resection of Primary Tumours of the Spine

STUDY DESIGN

Retrospective observational cohort study.

OBJECTIVE

En bloc resection for primary tumours of the spine is associated with a high rate of adverse events (AEs). The objective was to explore the relationship between frailty/sarcopenia and major perioperative AEs, length of stay (LOS), and unplanned reoperation following en bloc resection of primary spinal tumours.

METHODS

This is a unicentre study consisting of adult patients undergoing en bloc resection for a primary spine tumor. Frailty was calculated with the modified frailty index (mFI) and spine tumour frailty index (STFI). Sarcopenia was quantified with the total psoas area/vertebral body area ratio (TPA/VB) at L3 and L4. Univariable regression analysis was used to quantify the association between frailty/sarcopenia and major perioperative AEs, LOS and unplanned reoperation.

RESULTS

95 patients met the inclusion criteria. The mFI and STFI identified a frailty prevalence of 3% and 18%. Mean CT TPA/VB ratios were 1.47 (SD ± .05) and 1.83 (SD ± .06) at L3 and L4. Inter-observer reliability was .93 and .99 for CT and MRI L3 and L4 TPA/VB ratios. Unadjusted analysis demonstrated sarcopenia and mFI did not predict perioperative AEs, LOS or unplanned reoperation. Frailty defined by an STFI score ≥2 predicted unplanned reoperation for surgical site infection (SSI) (P < .05).

CONCLUSIONS

The STFI was only associated with unplanned reoperation for SSI on unadjusted analysis, while the mFI and sarcopenia were not predictive of any outcome. Further studies are needed to investigate the relationship between frailty, sarcopenia and perioperative outcomes following en bloc resection of primary spinal tumors.

Radiographic Thigh Muscle Measurements Are a Reliable Predictor of Psoas Area and Sarcopenia

BACKGROUND

Sarcopenia is associated with falls, fractures, postoperative complications such as periprosthetic joint infections and dislocations, and early mortality. Although cross-sectional imaging is currently used to diagnose sarcopenia, inexpensive and widely available screening tests are needed. The goal of this study was to investigate whether measurements of thigh muscles made on radiographs can predict psoas muscle area and the presence of sarcopenia as determined on computed tomography (CT) scans.

METHODS

A retrospective radiographic review was performed to measure thigh muscle area in the coronal and sagittal planes using the differential in soft-tissue attenuation. Psoas muscle area on CT at L3 and L4 served as the gold standard for the diagnosis of sarcopenia. The correlation between thigh muscle and psoas muscle areas was determined, and multivariable models were developed to identify predictors of psoas muscle area and sarcopenia.

RESULTS

Four hundred and fourteen patients (252 male, 162 female) were identified. Seventy-six (18.4%) of the patients had an L4 psoas muscle area below the sex-specific cutoff value for sarcopenia. Patients with sarcopenia on abdominal CT had significantly smaller thigh muscle measurements on all radiographic views. The mean and standard deviation of the thigh muscle measurements were determined for the entire cohort and for patients with sarcopenia, as well as for adults aged 18 to 40 years without sarcopenia to provide normative reference values. The intraclass correlation coefficients were >0.8 for all radiographic measurements. The anteroposterior-view measurement of thigh muscle width and lateral-view measurement of quadriceps height were identified as independent predictors of both psoas muscle area and sarcopenia.

CONCLUSIONS

Measurements of thigh muscle size made on radiographs can predict both psoas muscle area and sarcopenia. These measurements are a reliable and readily available screening tool to aid in the diagnosis and treatment of sarcopenia in the orthopaedic population.

LEVEL OF EVIDENCE

Prognostic Level III . See Instructions for Authors for a complete description of levels of evidence.

The Value of Artificial Intelligence-Assisted Imaging in Identifying Diagnostic Markers of Sarcopenia in Patients with Cancer

Sarcopenia is defined as the loss of skeletal muscle mass and muscle function. It is common in patients with malignancies and often associated with adverse clinical outcomes. The presence of sarcopenia in patients with cancer is determined by body composition, and recently, radiologic technology for the accurate estimation of body composition is under development. Artificial intelligence- (AI-) assisted image measurement facilitates the detection of sarcopenia in clinical practice. Sarcopenia is a prognostic factor for patients with cancer, and confirming its presence helps to recognize those patients at the greatest risk, which provides a guide for designing individualized cancer treatments. In this review, we examine the recent literature (2017-2021) on AI-assisted image assessment of body composition and sarcopenia, seeking to synthesize current information on the mechanism and the importance of sarcopenia, its diagnostic image markers, and the interventions for sarcopenia in the medical care of patients with cancer. We concluded that AI-assisted image analysis is a reliable automatic technique for segmentation of abdominal adipose tissue. It has the potential to improve diagnosis of sarcopenia and facilitates identification of oncology patients at the greatest risk, supporting individualized prevention planning and treatment evaluation. The capability of AI approaches in analyzing series of big data and extracting features beyond manual skills would no doubt progressively provide impactful information and greatly refine the standard for assessing sarcopenia risk in patients with cancer.