A man who entered an MRI suite while wearing a 20-lb weight training metal chain around his neck has died.
Keith McAllister, 61, entered the room at Nassau Open MRI in Long Island, NY, where his wife was undergoing an MRI exam on July 17. He was drawn by the magnet's force into the machine, according to a report published July 19 by Associated Press (AP), and although he was taken to a local hospital, he died on the same day.
McAllister's wife, Adrienne Jones-McAllister, was getting the exam to image her knee and asked the technician to call her husband once it was over to help her off the table, according to AP. The technician did so.
In an interview with News 12 Long Island, Jones-McAllister said that when her husband got close to her, "at that instant, the machine switched him around, pulled him in and he hit the MRI," AP reported.
![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)
