The European Organization for Research and Treatment of Cancer (EORTC) has commenced a clinical trial to qualify imaging biomarkers for non-small cell lung cancer (NSCLC).
EORTC trial 1217 is designed to evaluate the use of PET with a F-18 fluorothymidine (FLT-PET) radiotracer and diffusion-weighted MR (DWI-MRI) in patients with early-stage NSCLC treated with preoperative chemotherapy followed by surgery. Researchers plan to enroll 40 patients at a total of eight institutions in Italy, the Netherlands, and the U.K.
Study coordinator Dr. Nandita deSouza of the Royal Marsden Hospital-Sutton in the U.K. said FLT-PET will be used to monitor tumor cell proliferation and DWI-MRI will monitor tumor cell death. Values obtained from the scans at the beginning of treatment will be compared with those obtained two weeks later, as well as with pathological results, such as the percentage of viable residual tumor cells measured in surgical specimens.
The analysis could help researchers determine whether imaging can help qualify tumor cell proliferation and tumor cell death in patients with operable non-small cell lung cancer.
![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)
