Clinical outcomes associated with computed tomography-based body composition measures in lung transplantation: a systematic review.
Dmitry RozenbergCamila E OrssoKaran ChohanAni Orchanian-CheffSahar NourouzpourJohn Michael NicholsonBrenawen ElangeswaranAndrei VagaonLee FidlerLianne G SingerSunita MathurPublished in: Transplant international : official journal of the European Society for Organ Transplantation (2020)
Computed tomography (CT) is gaining increased recognition in the assessment of body composition in lung transplant (LTx) candidates as a prognostic marker of post-transplant outcomes. This systematic review was conducted to describe the methodology of CT measures of body composition used in LTx patients and its association with post-transplant outcomes. Six databases were searched (inception-April 2020) for studies of adult LTx patients with thoracic or abdominal CT measures [muscle cross-sectional area (CSA) and/or adiposity]. Thirteen articles were included with 1911 LTx candidates, 58% males, mean age range (48-61 years) and body mass index of 21.0-26.1 kg/m2 . Several methods were utilized using thoracic or abdominal CT scans to assess skeletal muscle (n = 11) and adiposity (n = 4) at various anatomic locations (carina, thoracic, and lumbar vertebrae), differing muscle groups, and adipose tissue compartments. Low muscle mass was associated with adverse outcomes in 6/11 studies, including longer mechanical ventilation days (n = 2), intensive care (n = 2) and hospital stay (n = 2), and mortality (n = 4). Greater subcutaneous and mediastinal fat were associated with increased risk of primary graft dysfunction (n = 2), but implications of adiposity on survival were variable across four studies. Further standardization of CT body composition assessments is needed to assess the prognostic utility of these measures on LTx outcomes.
Keyphrases
- pet ct
- body composition
- computed tomography
- positron emission tomography
- dual energy
- image quality
- contrast enhanced
- skeletal muscle
- resistance training
- insulin resistance
- bone mineral density
- adipose tissue
- systematic review
- mechanical ventilation
- body mass index
- magnetic resonance imaging
- spinal cord
- cross sectional
- weight gain
- case control
- end stage renal disease
- machine learning
- oxidative stress
- cardiovascular disease
- minimally invasive
- patient reported outcomes
- emergency department
- lymph node
- magnetic resonance
- randomized controlled trial
- chronic kidney disease
- deep learning
- ultrasound guided
- big data
- young adults
- metabolic syndrome
- prognostic factors
- coronary artery disease
- risk factors
- respiratory failure