Intelligent ultrasonic assessment of muscle quality for a functionally healthy elderly life
Grant Data
Project Title
Intelligent ultrasonic assessment of muscle quality for a functionally healthy elderly life
Principal Investigator
Professor Lee, Wei-Ning
(Principal Investigator (PI))
Co-Investigator(s)
Mr. GUAN Haotian
(Co-Investigator)
Dr Dong Jinping
(Co-Investigator)
Duration
12
Start Date
2022-10-31
Amount
389000
Conference Title
Intelligent ultrasonic assessment of muscle quality for a functionally healthy elderly life
Keywords
Elasticity, Neural network, Ultrasound imaging, Machine learning, Skeletal muscle
Discipline
Biomedical Engineering
HKU Project Code
HLCA/M-706/22
Grant Type
Healthy Longevity Catalyst Awards (Hong Kong) 2022
Funding Year
2022
Status
On-going
Objectives
Maintaining functional ability is central to physical and mental well-being in older age. Motility, which is endowed by skeletal muscle, is an intrinsic capacity pertinent to functional ability. Despite a multitude of available measurement tools of muscular function in clinical settings, skeletal muscles exhibit intricate architecture, complex dynamics, individual compositional differences, and adaptive coordination, thus presenting diagnostic discrepancies and therapeutic challenges.The goal of this project is therefore to develop a personalized data-driven model enabled by a physics-informed neural network (PINN) and noninvasive ultrasonic measures for assessment of muscle quality, which is herein defined by muscle stiffness and movement. More specifically, we will develop a scientific machine learning model, PINN, which is governed by muscle mechanics, instead of treating the model as a black box. This model, coined as mus-PINN, will learn from muscle stiffness and kinematics, which will be quantified by our recently developed ultrasound elastography method. We will evaluate the feasibility of mus-PINN on excised porcine muscle samples and in vivo human calf muscles, which are regarded as the second heart.This project is foreseen to ultimately 1) provide a new mathematical formulation of the skeletal muscle mechanics in vivo, 2) establish an unprecedented quantitative tool for personalized examination of muscle conditions, and 3) promote a sustainable healthy lifestyle powered by high-quality skeletal muscle as we age.