Opportunistic CT for Prediction of Adverse Postoperative Events in Patients with Spinal Metastases.
Neal D KapoorOlivier Quinten GrootColleen G BucklessPeter K TwiningMichiel E R BongersStein J JanssenJoseph H SchwabMartin TorrianiMiriam A BredellaPublished in: Diagnostics (Basel, Switzerland) (2024)
The purpose of this study was to assess the value of body composition measures obtained from opportunistic abdominal computed tomography (CT) in order to predict hospital length of stay (LOS), 30-day postoperative complications, and reoperations in patients undergoing surgery for spinal metastases. 196 patients underwent CT of the abdomen within three months of surgery for spinal metastases. Automated body composition segmentation and quantifications of the cross-sectional areas (CSA) of abdominal visceral and subcutaneous adipose tissue and abdominal skeletal muscle was performed. From this, 31% (61) of patients had postoperative complications within 30 days, and 16% (31) of patients underwent reoperation. Lower muscle CSA was associated with increased postoperative complications within 30 days (OR [95% CI] = 0.99 [0.98-0.99], p = 0.03). Through multivariate analysis, it was found that lower muscle CSA was also associated with an increased postoperative complication rate after controlling for the albumin, ASIA score, previous systemic therapy, and thoracic metastases (OR [95% CI] = 0.99 [0.98-0.99], p = 0.047). LOS and reoperations were not associated with any body composition measures. Low muscle mass may serve as a biomarker for the prediction of complications in patients with spinal metastases. The routine assessment of muscle mass on opportunistic CTs may help to predict outcomes in these patients.
Keyphrases
- body composition
- computed tomography
- end stage renal disease
- patients undergoing
- skeletal muscle
- adipose tissue
- newly diagnosed
- ejection fraction
- chronic kidney disease
- spinal cord
- cross sectional
- minimally invasive
- resistance training
- healthcare
- type diabetes
- deep learning
- magnetic resonance imaging
- acute coronary syndrome
- mesenchymal stem cells
- metabolic syndrome
- contrast enhanced
- image quality