Seoul, South Korea-based AI developer Neurophet has received clearance from the U.S. Food and Drug Administration (FDA) for an updated version of its brain MRI analysis software.
Neurophet Aqua AD Plus is an upgraded version of the existing Neurophet Aqua AD and features an added capability to automatically detect the location and number of suspected microbleed lesions in patients with Alzheimer’s disease, the company said. The software can also identify high-intensity lesion areas related to brain edema, which can help medical professionals evaluate risk factors associated with anti-amyloid antibody therapy and establish personalized treatment plans for individual patients, according to the firm.
"With this FDA clearance, we are now fully showcasing Neurophet's technological competitiveness in the Alzheimer's treatment sector to the U.S. market," said Bin Jun-gil, co-chief executive officer, in a news release.
![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)
