The GE HealthCare (GEHC) Foundation has given $3 million for the creation of a professorship at the University of Wisconsin (UW) School of Medicine and Public Health Department of Radiology.
Tom Grist, MD.
Honoring Tom Grist, MD, who served 18 years as chair of the UW Department of Radiology, the endowment and the new professorship will support an incoming vice chair of research and continued growth and innovation in the field, UW said in a statement issued October 31.
"We intend to recruit a vice chair of research sometime in the next year, and this professorship will provide sustained resources for that individual, not only to support their own research but also to further the department’s mission," stated Scott Reeder, MD, who now leads the UW Department of Radiology.
An initial $600,000 award will “further Dr. Grist’s legacy of innovation in clinical care, imaging research and education,” according to Victoria Glazar, managing director of the GE HealthCare Foundation.
Grist pushed the boundaries of knowledge in the fields of MRI and CT. Grist's work led to innovations in the form of clinical applications for GE HealthCare’s MRI and CT scanners, and protocols for using the machines, from minimizing radiation levels to maintaining high image quality, UW said.
Now led by Reeder, who held the vice chair of research position before succeeding Grist earlier this year, UW's radiology department is in a period of growth, according to the university, with 157 current faculty and more than two dozen searches underway for new clinical and research positions.
For the occasion, Reeder cited the advancement of AI and theranostics, which leverages molecular targeting agents for both imaging and therapeutic uses, as examples of developments that boost radiology’s relevance and importance.
















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


