Skeletal Muscle Depletion and Major Postoperative Complications in Locally-Advanced Head and Neck Cancer: A Comparison between Ultrasound of Rectus Femoris Muscle and Neck Cross-Sectional Imaging

SIMPLE SUMMARY: Skeletal muscle mass (SMM) depletion is gaining popularity as independent predictor of postoperative complications in many surgical scenarios, even in the field of head and neck oncology. In this study, we demonstrate the value of ultrasound scans of the rectus femoris muscle together with the neck CT/MRI at C3 level in terms of estimation of SMM (through muscle cross sectional area), the identification of sarcopenic patients and as a predictor of major surgical morbidity in a cohort of locally-advanced head and neck cancer patients submitted to surgical treatment. This provides important tools for the on-going re-assessment of patients with regards to any pre-habilitation strategy aimed at reducing postoperative complications. ABSTRACT: Skeletal muscle mass (SMM) depletion has been validated in many surgical fields as independent predictor of complications through cross-sectional imaging. We evaluated SMM depletion in a stage III-IV head and neck cancer cohort, comparing the accuracy of CT/MRI at C3 level with ultrasound (US) of rectus femoris muscle (RF) in terms of prediction of major complications. Patients submitted to surgery were recruited from 2016 to 2021. SMM was estimated on CT/MRI by calculating the sum of the cross-sectional area (CSA) of the sternocleidomastoid and paravertebral muscles at C3 level and its height-indexed value (cervical skeletal muscle index, CSMI) and on US by computing the CSA of RF. Specific thresholds were defined for both US and CT/MRI according to ROC curve in terms of best prediction of 30-day major complications to detect sarcopenic subjects (40–53%). Sixty-five patients completed the study. At univariate analysis, major complications were associated to lower RF CSA, lower CSA at C3 level and lower CSMI, together with previous radiotherapy, higher ASA score and higher modified frailty index (mFI). At multivariate analysis RF CSA (OR 7.07, p = 0.004), CSA at C3 level (OR 6.74, p = 0.005) and CSMI (OR 4.02, p = 0.025) were confirmed as independent predictors in three different models including radiotherapy, ASA score and mFI. This analysis proved the value of SMM depletion as predictor of major complications in a head and neck cancer cohort, either defined on cross-sectional imaging at C3 or on US of RF.