Ultrasound technology developer Misonix has signed a three-year distribution agreement with Italian mobile lithotripsy services distributor Alliance LithoMobile.
Alliance LithoMobile of Milan will market the Farmingdale, NY-based vendor's Sonablate 500 high-intensity focused ultrasound (HIFU) system as a mobile, fee-for-use service to Italian hospitals. The distributor will also be responsible for capital sales of Sonablate, Misonix said.
Related Reading
Misonix signs Greek distribution deal, October 31, 2008
Misonix inks Italian distribution deal, June 6, 2008
Misonix wins Chile contract, February 22, 2008
Sonora gets patent, October 17, 2007
Misonix reports fiscal 2007 results, September 21, 2007
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![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.auntminnieeurope.com/mindful/smg/workspaces/default/uploads/2026/05/body-comp.XgAjTfPj1W.jpg?auto=format%2Ccompress&fit=crop&h=112&q=70&w=112)








