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Cryo-electron Microscopy

Cryo-electron Microscopy

Conventional electron microscopy (EM) involves dehydration, fixation, and staining of biological samples, which distorts the native state of biological molecules and results in several artifacts. Also, the high-energy electron beam damages the sample and makes it difficult to obtain high-resolution images. These issues can be addressed using cryo-EM, which uses frozen samples and gentler electron beams. The technique was developed by Jacques Dubochet, Joachim Frank, and Richard Henderson, for...

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Updated: Jun 17, 2025

Thermal Ablation for the Treatment of Abdominal Tumors

Thermal Ablation for the Treatment of Abdominal Tumors

Published on: March 7, 2011

Cryosurgery process applications - a mathematical review.

L Famhawite¹, S Tanwar², P R Verma³

¹Department of Mathematics, University of Delhi, Delhi, India. lfamhawite@maths.du.ac.in.

|August 10, 2024

Summary

This summary is machine-generated.

This study reviews mathematical models for cryosurgery, a tumor treatment using controlled freezing. Numerical simulations aid physicians in planning cryosurgery, optimizing probe placement and freezing duration for effective tumor destruction with minimal healthy tissue impact.

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Area of Science:

Biomedical Engineering
Mathematical Modeling
Oncology

Background:

Cryosurgery is a minimally invasive treatment for tumors.
Accurate simulation is crucial for effective cryosurgery planning.
Minimizing damage to surrounding healthy tissue is a key challenge.

Purpose of the Study:

To review prominent mathematical models for cryosurgery simulation.
To highlight the role of numerical simulations in treatment planning.
To discuss numerical techniques for bio-heat transfer in cryosurgery.

Main Methods:

Review of existing mathematical models for cryosurgery.
Discussion of numerical simulation techniques.
Analysis of bio-heat transfer processes in tumor tissues.

Main Results:

Identified key mathematical models for cryosurgery simulation.
Emphasized the utility of numerical simulations in treatment design.
Highlighted the suitability of finite element, meshfree, and finite volume methods.

Conclusions:

Mathematical models and numerical simulations are vital for cryosurgery.
Effective planning frameworks can be developed using these simulations.
Optimized treatment strategies enhance tumor destruction and preserve healthy tissue.