Image processing and analysis of muscle of frail elderly using MRI

• Main Author: Nanda Meenachi Sundram
• Other Authors: Poh Chueh Loo
• Format: Final Year Project
• Language: English
• Published: 2013
• Subjects: DRNTU::Engineering
• Online Access: http://hdl.handle.net/10356/53706
• Institution: Nanyang Technological University

Sarcopenia is a syndrome associated with aging, characterized as the loss of muscle mass and function. Despite studies pointing to Sarcopenia’s prevalence congruent with loss of muscle mass, using this as the only indicator could be futile. Therefore, in this project, MRI images of normal and frail subjects’ lower extremities were analyzed for muscle and adipose tissues. In addition to absolute muscle volume, other volumetric parameters such as fat infiltrates and intermuscular fat, along with many other defined ratios, were studied to identify if they could be utilized as potential indicators to distinguish between frail and normal subjects. There are two parts to this project. First, a method was devised to, as accurately as possible, extract the fat infiltrates evident in the subjects’ MRI images. After various accuracy and reliability tests, k-means clustering was identified as the optimal technique. After which, volumetric quantification reflected that the muscle to bone ratio in the quadriceps, hamstring and total muscle groups, muscle volume normalized with BMI values across all muscle groups, and the muscle to fascia ratio in the quadriceps and total muscle groups to be the parameters that could be used as indicators to distinguish between frail and normal subjects. As one ages, muscle mass loss, degradation, and loss of function are inevitable. However, Sarcopenia could be prevented and controlled through early detection. By being able to identify the parameters that could distinguish between the frail and normal subjects, this process would be facilitated.