A senior U.K. National Health Service (NHS) doctor failed to identify lymphoma on a chest x-ray from a 13-year-old girl who died two days later, according to a report from the Daily Mail newspaper on a medical inquest held at Salisbury Coroner's Court.
The patient, Tanisha Narraway-Baverstock, was a talented footballer who had a recurring cough for 10 weeks. Pediatrician Dr. Jim Baird reviewed a chest x-ray and diagnosed her with a chest infection or pneumonia and asked her mother to return in two weeks.
The inquest also heard how the teenager's x-ray review "fell through the cracks" due to a poor NHS logging system and was not properly chased up, the Daily Mail reported. When medics did review the x-ray, they correctly identified rapidly progressing non-Hodgkin lymphoma.
Had the cancer been caught in time, the patient would have had an approximately 75% chance of survival, an oncologist told the inquest.
![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)
