Seoul, South Korea-based AI developer Neurophet has signed a memorandum of understanding with the Alzheimer's Network for Treatment and Diagnostics (ALZ-NET) to offer its brain imaging AI devices across the network's participating medical institutions.
Under the agreement, ALZ-NET sites will receive discounted access to Neurophet Aqua, an MRI brain neurodegeneration imaging analysis tool; Neurophet Scale PET, a quantitative PET imaging analysis tool; and Neurophet Aqua AD Plus, an integrated brain imaging platform designed to support treatment decisions for Alzheimer's disease therapies, the company said. All three products have received clearance from the U.S. Food and Drug Administration (FDA).
The partnership will also focus on raising awareness of the importance of monitoring amyloid-related imaging abnormalities, Neurophet said.
Sponsored by the Alzheimer's Association and managed by the American College of Radiology, ALZ-NET collects and analyzes clinical and imaging data from patients receiving FDA-approved Alzheimer's therapies at voluntarily participating institutions.














![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)
