The Australian government has honored Dr. Lizbeth Kenny, who is an honorary member of several European radiological associations, including the European Society of Radiology (ESR).
Kenny has been appointed an officer of the Order of Australia, one of the highest honors awarded by the Australian government.
She received honorary membership of the ESR in 2008 in recognition of her exceptional achievements in emphasizing the clinical role of radiology in cancer care. She is currently an adjunct professor at the University of Queensland School of Medicine in Australia and has been the medical director of the Central Integrated Regional Cancer Service since 2005.
Kenny is an honorary fellow of other radiology organizations, such as the British Institute of Radiology, the Royal College of Radiologists, the American College of Radiology, and the Radiological Society of North America.
She has published numerous papers and has been the principal investigator in a number of trials.
![Overview of the study design. (A) The fully automated deep learning framework was developed to estimate body composition (BC) (defined as subcutaneous adipose tissue [SAT] in liters; visceral adipose tissue [VAT] in liters; skeletal muscle [SM] in liters; SM fat fraction [SMFF] as a percentage; and intramuscular adipose tissue [IMAT] in deciliters) from MRI. The fully automated framework comprised one model (model 1) to quantify different BC measures (SAT, VAT, SM, SMFF, and IMAT) as three-dimensional (3D) measures from whole-body MRI scans. The second model (model 2) was trained to identify standardized anatomic landmarks along the craniocaudal body axis (z coordinate field), which allowed for subdividing the whole-body measures into different subregions typically examined on clinical routine MRI scans (chest, abdomen, and pelvis). (B) BC was quantified from whole-body MRI in over 66,000 individuals from two large population-based cohort studies, the UK Biobank (UKB) (36,317 individuals) and the German National Cohort (NAKO) (30,291 individuals). Bar graphs show age distribution by sex and cohort. BMI = body mass index. (C) After the performance assessment of the fully automated framework, the change in BC measures, distributions, and profiles across age decades were investigated. Age-, sex-, and height-adjusted body composition reference curves were calculated and made publicly available in a web-based z-score calculator (https://circ-ml.github.io).](https://img.auntminnieeurope.com/mindful/smg/workspaces/default/uploads/2026/05/body-comp.XgAjTfPj1W.jpg?auto=format%2Ccompress&dpr=2&fit=crop&h=167&q=70&w=250)
