Proactive Health Monitoring Using Individualized Analysis
of Tissue Elasticity
PI:
Ming C. Lin
Co-PI: Ronald Chen and Vladimir Jojic
Senior Investigators:: Jun Lian and Hongtu Zhu
Research Assisants: Shan (Alex) Yang, Junbang (William) Liang, and Tanya Amert
University of North Carolina at Chapel Hill
System Overview: (a) elasticity parameter
estimation using medical image analysis and biomedical modeling; (b)
longitudinal analysis of patient data against clinical criteria to establish
predictive models; and (c) clinical classifier using machine learning and
individual tissue elasticity.
To develop a novel computational framework for proactively
monitoring the wellbeing of at-risk groups through individualized analysis of
tissue elasticity, taking into account of other explanatory variables,
including ages, family history, genetic disposition, chronic conditions, and
other factors.
Efficient algorithms for non-invasive, image-based techniques for automatic extraction of tissue elasticity;
New predictive models for cancer staging and grading based on patient-specific parameters;
Novel regression models and inference procedures for survival analysis;
A health monitoring system for at-risk groups based on individual tissue elasticity along with other variables.
Synthetic
Experiment for Multi-Region Elasticity Parameter Reconstruction
Tumor-to-Region
ratio |
0.022 |
0.14 |
0.30 |
0.49 |
0.65 |
0.76 |
0.85 |
Region
with tumor |
30.63 |
31.54 |
39.18 |
43.93 |
51.23 |
61.16 |
71.01 |
Region
with normal tissue |
29.15 |
28.89 |
31.22 |
30.17 |
31.49 |
29.31 |
30.46 |
As the
volume ratio of tumor to the embedded region increases, so does the average
stiffness value for the tumor embedded region.
Tumor
Elasticity Parameter (kPa) |
70 |
140 |
210 |
280 |
350 |
420 |
490 |
Region 1
with tumor |
51.23 |
112.92 |
157.44 |
186.78 |
202.22 |
254.20 |
272.58 |
Region 2
with normal tissue |
31.49 |
28.28 |
30.04 |
28.56 |
27.62 |
29.61 |
25.18 |
As the
tumor becomes more stiff, the average elasticity value in the tumor region increase
as well.
Real
Patient Cancer Stage Correlation Experiment
1. "Simulation-Based Estimation of
Elasticity Parameters for Multi-Body Deformation", Janunary 2014.
2. "MaterialCloning: Acquiring
Elasticity Parameters from Images", November 2014.
This project is supported in part by the joint
NSF-NIH Smart and Connected Health Program: