Canadian isotope supplier Atomic Energy of Canada (AECL) is ready to increase production to cover a potential shortfall in isotope supply after the recent shutdown of a nuclear reactor in the Netherlands.
In addition, the Canadian government has initiated talks with isotope suppliers in South Africa, France, and Belgium to secure other isotope sources should the need arise. There was no immediate word on how long the Dutch reactor may be offline.
According to a prepared statement issued August 25 by Canada's Natural Resources agency and the Ministry of Health, the Canadian government "is monitoring this developing situation, and is working closely with Atomic Energy of Canada Limited and suppliers in an effort to help ensure a consistent supply of medical isotopes for Canadians."
Even with a planned five-day shutdown for maintenance later this week, the statement confirmed that AECL "will be able to increase its normal production schedule to help close the supply gap should a global shortage arise."
Related Reading
SNM draft report shows U.S. Mo-99 production years away, July 22, 2008
MDS sues AECL for $1.6 billion over Maple reactors, July 9, 2008
SNM cites regulatory, reimbursement, and research as top priorities, June 18, 2008
MDS to press AECL on Chalk River reactors, June 6, 2008
SNM explores feasibility of U.S. medical isotope source, May 22, 2008
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![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)
