
The U.S. Food and Drug Administration (FDA) has issued a safety alert regarding the reliability of MR thermometry with MRI-guided laser interstitial thermal therapy (MRgLITT) devices.
MRgLITT devices are used in neurosurgical procedures for the ablation of brain tumors, epileptic foci, or radiation necrosis. Changes in temperature at the treatment site are monitored with MR thermometry.
The agency has reviewed medical device and literature reports that describe adverse events when these devices were used to treat intracranial lesions. It is evaluating data that suggest potentially inaccurate MR thermometry information can be displayed during treatment, and that MRgLITT devices may not account for the continued thermal spread of energy to the surrounding tissue, which may result in an underestimation of thermal damage.
The FDA recommends that healthcare providers discuss with patients the benefits and risks of these devices. More information is available on the FDA's website.














![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)
