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Generalized solution and estimation method for cooling performance of downscaled cryoprobe.

Junnosuke Okajima1

  • 1Institute of Fluid Science, Tohoku University, 2-1-1, Katahira, Aoba-ku, Sendai, Miyagi, 980-8577, Japan.

Journal of Thermal Biology
|May 27, 2019
PubMed
Summary

This study presents dimensionless analytical solutions for cryosurgery, clarifying the relationship between tissue freezing and cryoprobe cooling power. These findings establish a freezing limit to guide the design of smaller, more effective cryoprobes.

Keywords:
Biot numberCryoprobeCryosurgeryDimensionless solutionDimensionless temperature

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Area of Science:

  • Biomedical Engineering
  • Therapeutic Technologies
  • Cryosurgery

Background:

  • Minimizing surgical invasion in cryosurgery necessitates the downscaling of cryoprobes.
  • Understanding the thermal dynamics of tissue freezing is crucial for optimizing cryoprobe performance.

Purpose of the Study:

  • To derive dimensionless analytical solutions for the freezing phenomenon around a cryoprobe.
  • To establish the relationship between a cryoprobe's cooling power and its freezing ability in biological tissues.
  • To introduce the concept of a 'freezing limit' for cryoprobe design.

Main Methods:

  • A one-dimensional axisymmetric, steady-state model was employed.
  • Analytical solutions were derived and transformed into a dimensionless form.
  • The solutions were validated against existing numerical simulation results.

Main Results:

  • Dimensionless solutions were obtained, describing the general trend between the frozen region size and cryoprobe cooling power.
  • The steady-state cryoprobe surface temperature was identified as a direct factor influencing the frozen region size.
  • The derived solutions demonstrated independence from organ type, fluid temperature, and heat transfer coefficient.

Conclusions:

  • The established freezing limit provides essential guidelines for designing downscaled cryoprobes.
  • The dimensionless solutions offer a universal framework for predicting tissue freezing in cryosurgery.
  • Optimized cryoprobe design can be achieved by considering the derived thermal relationships.