PROS® CT: MQ segments and quantifies fat and muscle quality by leveraging abdominal CT images.
Automatic extraction of L3 Slice
The deep learning algorithm automatically identifies and extracts the L3 slice, the key cross-sectional image that best represents muscle and fat distribution on CT.
Segmentation and measurement of muscle/fat area
AI precisely segments muscle and fat based on quality and provides quantified data. |
Intuitive and accessible analysis is provided through various structured reports and patient-focused explanatory materials. |
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96% Muscle/fat
segmentation alignment
Model performance was validated using 21,708 abdominal CT scans, showing a high level of concordance.
Explore the association between metabolic diseases and
PROS® CT: MQ index.
Type 2 diabetes mellitus
Higher VFA and VSR at baseline were independent risk factors for the development of T2DM.
NAFLD
(Non-alcoholic fatty liver disease)
A higher proportion of good quality muscle was associated with lower risks of NAFLD and fibrosis. |

Sarcopenia
BMI-adjusted index(SMA/BMI) was the best index of CT-measured SMA to reflects the age-related muscle changes and to maximize the diagnostic yield for sarcopenia.
Myosteatosis
The NAMA/TAMA index developed in this study was useful for assessing myosteatosis
Have questions?Check out our FAQ for more information. |
