Cervical body composition on radiotherapy planning computed tomography scans predicts overall survival in glioblastoma patients.

ABSTRACT

Background and purpose: Glioblastoma (GBM) patients face a strongly unfavorable prognosis despite multimodal therapy regimens. However, individualized mortality prediction remains imprecise. Harnessing routine radiation planning cranial computed tomography (CT) scans, we assessed cervical body composition measures as novel biomarkers for overall survival (OS) in GBM patients. Materials and methods: We performed threshold-based semi-automated quantification of muscle and subcutaneous fat cross-sectional area (CSA) at the levels of the first and second cervical vertebral body. First, we tested this method's validity by correlating cervical measures to established abdominal body composition in an open-source whole-body CT cohort. We then identified consecutive patients undergoing radiation planning for recent GBM diagnosis at our institution from 2010 to 2020 and quantified cervical body composition on radiation planning CT scans. Finally, we performed univariable and multivariable time-to-event analyses, adjusting for age, sex, body mass index, comorbidities, performance status, extent of surgical resection, extent of tumor at diagnosis, and MGMT methylation. Results: Cervical body composition measurements were well-correlated with established abdominal markers (Spearman's rho greater than 0.68 in all cases). Subsequently, we included 324 GBM patients in our study cohort (median age 63 years, 60.8% male). 293 (90.4%) patients died during follow-up. Median survival time was 13 months. Patients with below-average muscle CSA or above-average fat CSA demonstrated shorter survival. In multivariable analyses, continuous cervical muscle measurements remained independently associated with OS. Conclusion: This exploratory study establishes novel cervical body composition measures routinely available on cranial radiation planning CT scans and confirms their association with OS in patients diagnosed with GBM.