Skip to content

Latest commit

 

History

History
17 lines (12 loc) · 1.75 KB

Thermal_memory_PAT.md

File metadata and controls

17 lines (12 loc) · 1.75 KB

Junjie yao - Prof at Duke University and used to be Post Doc in Prof. Lihong Wang's Lab at WashU.

Key Points

  • Based on the Grüneisen parameter’s temperature dependence, photoacoustic (PA) imaging can provide relative temperature measurement, but it has been traditionally challenging to measure absolute temperatures without knowing the baseline temperature, particularly in deep tissues with unknown optical and acoustic properties
  • By illuminating the tissue with a burst of nanosecond laser pulses, TEMPT exploits the temperature dependence of the thermal energy lingering, which is probed by the corresponding PA signals acquired within the thermal confinement
  • A self-normalized ratiometric measurement cancels out temperature-irrelevant quantities and estimates the Grüneisen parameter
  • The temperature can then be evaluated, given the tissue’s temperature-dependent Grüneisen parameter, mass density, and specific heat capacity. Unlike conventional PA thermometry, TEMPT does not require knowledge of the tissue’s baseline temperature, nor the optical properties
  • We have developed a mathematical model to describe the temperature dependence in TEMPT
  • We have demonstrated the feasibility of the temperature evaluation on tissue phantoms at 1.5 cm depth within a clinically relevant temperature range

My Notes

This gives a new perspective for coming up with a new imaging modality. Based on the heatng and cooling profile we can extract better images of the tissue. Temperature profile can act like a signature. This is kind of combining the physical model as non linearity paramater into proper imaging framework for imaging.