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Statistical analysis of temperature rise in passive medical implants in a magnetic resonance imaging environment

Cox, M G; Jagan, K; Rajan, S (2021) Statistical analysis of temperature rise in passive medical implants in a magnetic resonance imaging environment. NPL Report. MS 28

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Purpose: Data records from test laboratories had been gathered for small passive medical implants immersed in gel phantoms in an MRI environment. The data had been analyzed by the Food and Drug Administration of the USA (FDA) in order to understand the extent to which temperature rise around the implant is correlated with implant primary length. This paper extends that work to other factors that may influence RF heating.

Methods: Parametric models are constructed to try to understand which factors have most influence on temperature rise. Explanatory models can be used to predict heating rise for implants whose characteristics lie within the span of the data on which the models are based.

Results: Models were analyzed that yield temperature rise as a function of various geometric parameters and test laboratory, taking measurement uncertainties into consideration. A main result is that there is dependence on the primary length parameter but secondary and tertiary length parameters have little effect. Also, the test laboratory appears not to be a significant influencing factor.

Conclusions: Since the data set is small, our conclusions are inevitably tentative. Our analyses should be regarded as preliminary to a more extensive treatment involving more data, which will be required to make more concrete statements. Those statements can be strengthened, and measurement traceability issues handled when there is access to uncertainties associated with all measured quantities. Currently quoted uncertainties are too small by a factor of about two.

Item Type: Report/Guide (NPL Report)
NPL Report No.: MS 28
Keywords: medical implants, MRI heating, statistical analysis
Subjects: Mathematics and Scientific Computing > Modelling
Divisions: Data Science
Identification number/DOI: 10.47120/npl.MS28
Last Modified: 12 Jul 2021 14:47
URI: http://eprintspublications.npl.co.uk/id/eprint/9086

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