
Whole-body MRI with diffusion-weighted imaging (DWI) is a viable alternative to F-18 FDG-PET/CT imaging for lung cancer staging, according to research presented at the recent ECR meeting in Vienna.
"Whole-body MRI is an ideal radiation-free imaging tool for the staging of lung cancer with good diagnostic accuracy," said presenter Dr. Ajith Antony of All India Institute of Medical Sciences (AIIMS) in New Delhi, India.
Lung cancer is the second most commonly diagnosed cancer around the world, and the leading cause of cancer-related death, Antony noted. The current gold standard for staging the disease is either contrast-enhanced CT of the chest and upper abdomen or F-18 FDG PET/CT imaging. But both of these exams expose patients to high doses of radiation.
Whole-body MRI shows promise as an attractive alternative for lung cancer staging because it does not impart radiation, but there have been few studies evaluating its performance for this indication, Antony said. To compare the two exams, he and colleagues conducted a study that included 31 patients with biopsy-proven lung cancer.
The whole-body MRI protocol consisted of the following sequences:
- Axial fluid attenuation inversion recovery (FLAIR)
- Axial short tau inversion recovery (STIR)
- Axial dual fast field echo (FFE) T1-weighted
- Axial diffusion-weighted imaging
- Contrast enhanced axial T1-weighted mDIXON (fat suppression technique)
The F-18 FDG PET/CT protocol consisted of patient fasting for four hours before radiopharmaceutical injection; a whole-body scan taken about an hour after injection, with a low-dose CT scan first followed by a PET scan. Images were reconstructed using iterative techniques.
Antony and colleagues found that whole-body MRI -- particularly when used with diffusion-weighted imaging (DWI) -- showed high performance across a variety of measures for staging different levels of lung cancer.
| Overall staging with whole body MRI | |||
| Measure | Stage I and II | Stage III | Stage IV |
| Sensitivity | |||
| With DWI | 100% | 93.3% | 100% |
| Without DWI | 96.6% | 80% | 100% |
| Specificity | |||
| With DWI | 100% | 100% | 94.1% |
| Without DWI | 100% | 100% | 88.2% |
| AUC | |||
| With DWI | 1 | 0.97 | 0.98 |
| Without DWI | 0.98 | 0.90 | 0.94 |
Antony conceded that one of the study's limitations was its small sample size and that pathological confirmation of suspicious lung nodes wasn't available. Yet the study results remain promising, he said.
"Whole-body [MRI] can be used for [lung cancer] staging with comparable accuracy to the present gold standard," he concluded.












![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&fit=crop&h=112&q=70&w=112)





