Metal-containing radiopharmaceuticals are highly effective at detecting early markers of Alzheimer's disease, and they are synchrotron-independent and long-lived, according to a review by Russian researchers published in the International Journal of Molecular Sciences.
The development of imaging agents for Alzheimer's is limited due to the presence of the blood-brain barrier (BBB), which restricts the substance from reaching the cerebral target. This makes it difficult to develop new treatments for brain diseases or new radiopharmaceuticals for neuroimaging of the brain.
But the use of metal-containing radiopharmaceuticals could improve the accessibility of diagnostic imaging for Alzheimer's disease patients, according to a team of researchers from Laboratory of Biophysics at NUST MISIS, Lomonosov Moscow State University, and D. Mendeleev University of Chemical Technology of Russia.
Copper-based coordination compounds for PET, gallium-based coordination compounds for MRI, and technetium-based coordination compounds for SPECT showed the most promising results, according to the review.
![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)
