Association of adipose tissue and skeletal muscle metrics with overall survival and postoperative complications in soft tissue sarcoma patients: an opportunistic study using computed tomography.

BACKGROUND

To determine the relationship between adipose tissue and skeletal muscle measurements on computed tomography (CT) and overall survival and major postoperative complications in patients with soft-tissue sarcoma (STS).

METHODS

The retrospective study included 137 STS patients (75 men, 62 women; mean age, 53 years, SD 17.7; mean BMI, 28.5, SD 6.6) who had abdominal CT exams. On a single CT image, at the L4 pedicle level, measurements of visceral adipose tissue (VAT), subcutaneous adipose tissue (SAT), and skeletal muscle area and attenuation were obtained using clinical PACS and specialized segmentation software. Clinical information was recorded, including STS characteristics (size, depth, grade, stage, and site), overall survival, and postoperative complications. The relationships between CT metrics and survival were analyzed using Cox proportional hazard models and those between CT metrics and postoperative complications using logistic regression models.

RESULTS

There were 33 deaths and 41 major postoperative complications. Measured on clinical PACS, the psoas area (P=0.003), psoas index (P=0.006), psoas attenuation (P=0.011), and total muscle attenuation (P=0.023) were associated with overall survival. Using specialized software, psoas attenuation was also associated with overall survival (P=0.018). Adipose tissue metrics were not associated with survival or postoperative complications.

CONCLUSIONS

In STS patients, CT-derived muscle size and attenuation are associated with overall survival. These prognostic biomarkers can be obtained using specialized segmentation software or routine clinical PACS.

Informations de copyright

2020 Quantitative Imaging in Medicine and Surgery. All rights reserved.

Déclaration de conflit d'intérêts

Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at http://dx.doi.org/10.21037/qims.2020.02.09). The special issue “Body Composition Imaging” was commissioned by the editorial office without any funding or sponsorship. The authors have no other conflicts of interest to declare.