BRUSSELS (Reuters), Aug 29 - Belgian authorities have restricted consumption of vegetables and milk produced near a nuclear medicine institute after a leakage of radioactive iodine, the European Commission said on Friday.
The institute in Fleurus in southern Belgium produces radioisotopes used to treat cancer.
"Belgian authorities ... have now decided to implement protective actions, in particular restrictions on the consumption of local food produce (vegetables and milk), up to a distance of 5 km (sector northeast)," the EU executive said in a statement.
The measures were taken after samples of local grass showed higher-than-expected contamination.
A Commission spokesman said that he was unaware of anyone being contaminated. Belgian authorities said there was no need to distribute iodine pills to the population as would typically be done after a major leak.
The Belgian nuclear control agency said on Thursday that the incident, which took place last weekend, was "serious" and rated it three out of seven on the International Nuclear Incident Scale (INES).
Incidents are classified at seven levels -- levels one to three are considered "incidents," while levels four to seven are termed "accidents."
Chernobyl is the only level seven accident to date and the vast majority of events are classified below level three.
Belgian authorities have drawn heavy criticism for the handling of the crisis.
"What do we do with people who have eaten vegetables? Why wait so many days before announcing measures?" the Belga news agency quoted Green member of parliament Jean-Marc Nollet as saying. Nollet asked for an independent investigation.
Last Updated: 2008-08-29 10:00:16 -0400 (Reuters Health)
Related Reading
Higher thyroid cancer rate from Chernobyl confirmed, July 7, 2006
Copyright © 2008 Reuters Limited. All rights reserved. Republication or redistribution of Reuters content, including by framing or similar means, is expressly prohibited without the prior written consent of Reuters. Reuters shall not be liable for any errors or delays in the content, or for any actions taken in reliance thereon. Reuters and the Reuters sphere logo are registered trademarks and trademarks of the Reuters group of companies around the world.
![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)
