Affiliations 

  • 1 School of Engineering, Monash University Malaysia, Jalan Lagoon Selatan, 47500 Bandar Sunway, Selangor, Malaysia
  • 2 School of Engineering, Monash University Malaysia, Jalan Lagoon Selatan, 47500 Bandar Sunway, Selangor, Malaysia. Electronic address: ooi.ean.hin@monash.edu
Cryobiology, 2016 12;73(3):304-315.
PMID: 27789380 DOI: 10.1016/j.cryobiol.2016.10.006

Abstract

Advancement in biomedical simulation and imaging modality have catalysed the development of in silico predictive models for cryoablation. However, one of the main challenges in ensuring the accuracy of the model prediction is the use of proper thermal and biophysical properties of the patient. These properties are difficult to measure clinically and thus, represent significant uncertainty that can affect the model prediction. Motivated by this, a sensitivity analysis is carried out to identify the model parameters that have the most significant impact on the lesion size during cryoablation. The study is initially carried out using the Morris method to screen for the most dominant parameters. Once determined, analysis of variance (ANOVA) is performed to quantitatively rank the order of importance of each parameter and their interactions. Results from the sensitivity analysis revealed that blood perfusion, water transport and ice nucleation parameters are critical in predicting the lesion size, suggesting that the acquisition of these parameters should be prioritised to ensure the accuracy of the model prediction.

* Title and MeSH Headings from MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine.