Amanda Gearhart.
Gearhart has previously served in senior roles at GE HealthCare (GEHC) and Philips Healthcare. In her new role at Ezra, she will lead the company's planned expansion into U.S. clinics and markets to make its AI-enhanced full body MRI scans more accessible to patients.
Ezra’s proprietary AI technology, Ezra Flash, received 510(k) clearance by the U.S. Food and Drug Administration (FDA) in May. The technology improves the quality of MR images, with the company saying this can decrease the time needed to complete a high-quality scan and reduce MRI costs. The company used Ezra Flash to launch the world's first 30-minute full body MRI scan.
In 2023, Ezra expanded from 15 clinics in the U.S. to 19 clinics, adding new locations in New Jersey and Los Angeles. Ezra currently offers AI-enhanced, FDA-cleared scans for breast, lung, and prostate alongside the company’s full body scan. Ezra’s full-body MRI technology is currently available in New York, New Jersey, Los Angeles, San Francisco, Miami, and Las Vegas.
![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)
