Quantitative computed tomography analysis of body composition changes in paediatric patients with acute lymphoblastic leukaemia.
Kunanya SuwannayingAdrian A OngRikeenkumar DhadukDeqing PeiMayuko IijimaEric MerkleTony Z ZhuangChelsea G GoodenoughJoren BrownEmily K BrowneBruce WolcottCheng ChengCarmen L WilsonChing-Hon PuiKirsten K NessSue C KasteHiroto InabaPublished in: British journal of haematology (2024)
Children with acute lymphoblastic leukaemia (ALL) are at risk for obesity and cardiometabolic diseases. To gain insight into body composition changes among children with ALL, we assessed quantitative computed tomography (QCT) data for specific body compartments (subcutaneous adipose tissue [SAT], visceral adipose tissue [VAT], total adipose tissue [TAT], lean tissue [LT], LT/TAT and VAT/SAT at lumbar vertebrae L1 and L2) at diagnosis and at off-therapy for 189 children with ALL and evaluated associations between body mass index (BMI) Z-score and clinical characteristics. BMI Z-score correlated positively with SAT, VAT and TAT and negatively with LT/TAT and VAT/SAT. At off-therapy, BMI Z-score, SAT, VAT and TAT values were higher than at diagnosis, but LT, LT/TAT and VAT/SAT were lower. Patients aged ≥10 years at diagnosis had higher SAT, VAT and TAT and lower LT and LT/TAT than patients aged 2.0-9.9 years. Female patients had lower LT and LT/TAT than male patients. Black patients had less VAT than White patients. QCT analysis showed increases in adipose tissue and decreases in LT during ALL therapy when BMI Z-scores increased. Early dietary and physical therapy interventions should be considered, particularly for patients at risk for obesity.
Keyphrases
- end stage renal disease
- adipose tissue
- body mass index
- body composition
- ejection fraction
- computed tomography
- newly diagnosed
- chronic kidney disease
- peritoneal dialysis
- stem cells
- emergency department
- young adults
- type diabetes
- physical activity
- machine learning
- mesenchymal stem cells
- electronic health record
- postmenopausal women
- high intensity
- big data
- resistance training
- patient reported