The Veterans Affairs (VA) Office of Inspector General (OIG) has sharply criticized the VA Waco Center of Excellence for a "waste of taxpayers' funds" with its purchase of a $3.6 million MRI scanner nearly a decade ago.
According to a June 24 report in Stars and Stripes, the OIG cited "poor stewardship" in not using the MRI for the intended purpose of researching traumatic brain and other war injuries experienced by troops from the Fort Hood military base in Texas before and after their deployments to Iraq.
The OIG report also found that the Waco center spent approximately $1.1 million on maintenance during the nearly five and a half years the scanner wasn't being used between 2008 and 2015.
The VA has since hired new leadership at the center, and in April 2015 it once again began using the scanner for brain MRI research. The VA is also in the process of redesigning its supply chain and how it buys and manages high-tech medical equipment, according to the article.
![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)