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Published on: July 7, 2017
Surface density mapping of natural tissue by a scanning haptic microscope (SHM)
Takeshi Moriwaki1, Tomonori Oie, Keiichi Takamizawa
1Division of Medical Engineering and Materials, National Cerebral and Cardiovascular Center Research Institute, Fujishiro-dai, Osaka, Japan.
Journal of Medical Engineering & Technology
|January 31, 2013
Summary
Scanning haptic microscopy (SHM) now maps tissue density. By analyzing frequency changes at different resonance frequencies, SHM distinguishes density from stiffness, enabling detailed imaging of natural tissues.
Area of Science:
- Biomedical Engineering
- Materials Science
- Microscopy
Background:
- The scanning haptic microscope (SHM) traditionally maps elastic modulus and topography.
- Expanding SHM capabilities requires new measurement theories for complex biological samples.
Purpose of the Study:
- To develop and validate a surface density mapping technique using SHM.
- To differentiate between elastic modulus and density contributions to SHM sensor signals.
Main Methods:
- Applied SHM measurement theory utilizing a microtactile sensor (MTS) vibrating at specific oscillation frequencies.
- Tested the method on agar and silicone organogels with varying densities but similar elastic moduli.
- Performed measurements near second-order (elastic modulus-dependent) and third-order (density and elastic modulus-dependent) resonance frequencies.
Main Results:
- Frequency change was primarily stiffness-dependent at low oscillation frequencies and density-dependent at high oscillation frequencies.
- Silicone gels showed a significant frequency change near the third-order resonance, indicating density dependence.
- A density image of canine aortic wall was successfully generated by subtracting second-order from third-order resonance data.
Conclusions:
- SHM can be adapted for surface density mapping of natural tissues.
- The method effectively distinguishes density from elastic modulus in biological samples.
- Density imaging revealed higher density in elastin-rich regions compared to collagen-rich regions of the canine aortic wall.
