Giananthony Rizzo[email protected]Nuclear MedicineIs the U.S. due for a shortage of SPECT tracers? Part 2In the second part of our series on the coming shortage of SPECT radiopharmaceuticals, Giananthony Rizzo of Decision Resources Group examines other factors in the U.S. healthcare industry that could affect isotope prices in the future.November 17, 2016Nuclear MedicineIs the U.S. due for a shortage of SPECT tracers? Part 1A perfect storm is brewing in the global SPECT market that could see the prices of radiopharmaceuticals skyrocket over the next five years. A number of factors are coalescing that could lead to a shortage of SPECT tracers for years to come, according to this article by Giananthony Rizzo of Decision Resources Group.November 16, 2016Page 1 of 1Top StoriesDigital X-RayLLMs excel at scoliosis detection on spine x-raysFor scoliosis detection, Grok 4 led with 94.2% accuracy.HomeExpanding opportunities for interventional radiology practiceCTWelding fumes linked to distinct lung CT changes, functionMolecular ImagingPSMA-PET linked to higher use of systemic therapiesSponsor ContentRadiology is Under Pressure
![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.auntminnie.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)
