Robert D Boutin1, Jeremy R Katz2, Abhijit J Chaudhari3, Jonathan G Yabes4, Jonah S Hirschbein5, Yves-Paul Nakache6, J Anthony Seibert3, Ramit Lamba3, Ghaneh Fananapazir3, Robert J Canter7, Leon Lenchik8. 1. Department of Radiology, Stanford University Medical Center, Stanford, CA, USA. 2. Integrated Imaging Associates, Oak Lawn, IL, USA. 3. Department of Radiology, University of California, Davis, School of Medicine, Sacramento, CA, USA. 4. Department of Biostatistics, University of Pittsburgh, Pittsburgh, PA, USA. 5. Emeryville Advanced Imaging, Emeryville, CA, USA. 6. Department of Internal Medicine, Santa Clara Valley Medical Center, San Jose, CA, USA. 7. Department of Surgery, University of California, Davis, School of Medicine, Sacramento, CA, USA. 8. Department of Radiology, Wake Forest School of Medicine, Winston-Salem, NC, USA.
Abstract
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. 2020 Quantitative Imaging in Medicine and Surgery. All rights reserved.
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. 2020 Quantitative Imaging in Medicine and Surgery. All rights reserved.
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