ISO/TR 21900:2018

TECHNICAL ISO/TR
REPORT 21900
First edition
2018-09
Guidance for uncertainty analysis
regarding the application of ISO/TS
Lignes directrices pour l’analyse de l’incertitude concernant
l’application de l’ISO/TS 10974
Reference number
©
ISO 2018
© ISO 2018
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ii © ISO 2018 – All rights reserved

Contents Page
Foreword .iv
Introduction .v
1 Scope . 1
2 Normative references . 1
3 Terms and definitions . 1
4 Uncertainty background . 1
4.1 General . 1
4.2 Method 1 Evaluation . 2
4.3 Method 2 Evaluation . 3
5 Experiment Uncertainty (u ) . 3
exp
5.1 General . 3
5.2 Measurement tool uncertainty (probe) . 3
5.3 Probe position uncertainty . 3
5.4 Tissue simulating phantom . 4
5.5 RF field source . 4
5.6 Phantom position uncertainty . 4
5.7 AIMD influence . 4
5.8 Overall u consideration . 4
exp
6 AIMD model uncertainty (u ) . 5
Predict
6.1 Piecewise excitation method for deriving AIMD model . 5
6.2 AIMD model uncertainty (u ): Method 1 . 6
Predict
6.3 AIMD model uncertainty (u ): Method 2 .11
Predict
7 Clinical uncertainty (u ) .12
Clinical
8 Uncertainty in conversion to power (u ) .13
power
9 Final uncertainty (combination and application) .13
Bibliography .14
Foreword
ISO (the International Organization for Standardization) is a worldwide federation of national standards
bodies (ISO member bodies). The work of preparing International Standards is normally carried out
through ISO technical committees. Each member body interested in a subject for which a technical
committee has been established has the right to be represented on that committee. International
organizations, governmental and non-governmental, in liaison with ISO, also take part in the work.
ISO collaborates closely with the International Electrotechnical Commission (IEC) on all matters of
electrotechnical standardization.
The procedures used to develop this document and those intended for its further maintenance are
described in the ISO/IEC Directives, Part 1. In particular, the different approval criteria needed for the
different types of ISO documents should be noted. This document was drafted in accordance with the
editorial rules of the ISO/IEC Directives, Part 2 (see www .iso .org/directives).
Attention is drawn to the possibility that some of the elements of this document may be the subject of
patent rights. ISO shall not be held responsible for identifying any or all such patent rights. Details of
any patent rights identified during the development of the document will be in the Introduction and/or
on the ISO list of patent declarations received (see www .iso .org/patents).
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.org/iso/foreword .html.
This document was prepared by Technical Committee ISO/TC 150, Implants for surgery, Subcommittee
SC 6, Active implants.
Any feedback or questions on this document should be directed to the user’s national standards body. A
complete listing of these bodies can be found at www .iso .org/members .html.
iv © ISO 2018 – All rights reserved

Introduction
Clause 8 of ISO/TS 10974:2018 describes methods (Tiers) for analyzing the RF power deposition for
active implantable medical device (AIMD). EM evaluations in a complex near-field exposure scenario
can be difficult and involve many uncertainty sources. Simulations requiring a model of the DUT and
clinical incident field have uncertainties that need to be carefully assessed.
The objective of the uncertainty analysis is to determine the confidence interval of the RF-induced
power deposition with respect to its true value. The acceptable level of uncertainty for an AIMD model
is relative to the safety margin afforded by the AIMD’s RF performance. For instance, if the expected
MRI RF induced AIMD power deposition in vivo is very low, it is less critical to have a highly accurate
model and more uncertainty can be tolerated in the model predictions.
TECHNICAL REPORT ISO/TR 21900:2018(E)
Guidance for uncertainty analysis regarding the
application of ISO/TS 10974
1 Scope
This document provides guidance for some methods that could be used to evaluate the sources of
uncertainty. It is important to note that there are many legitimate methods for analyzing the overall
uncertainty and that the methods in this document are illustrative only.
2 Normative references
The following documents are referred to in the text in such a way that some or all of their content
constitutes requirements of this document. For dated references, only the edition cited applies. For
undated references, the latest edition of the referenced document (including any amendments) applies.
ISO/TS 10974:2018, Assessment of the safety of magnetic resonance imaging for patients with an active
implantable medical device
3 Terms and definitions
For the purposes of this document, the terms and definitions given in ISO/TS 10974 apply.
ISO and IEC maintain terminological databases for use in standardization at the following addresses:
— ISO Online browsing platform: available at https: //www .iso .org/obp
— IEC Electropedia: available at http: //www .electropedia .org/
4 Uncertainty background
4.1 General
The uncertainties are divided into random and systematic uncertainties.
Random errors result in measured values being distributed about the mean value. Measurement
variations are often well approximated by normal or lognormal distributions. Many of the sources
n
of uncertainty for the measurements described in this document are the result of exponential or r
functions, e.g., the decay of power levels as a function of distance from the AIMD, and therefore can be
approximated by lognormal distributions.
In addition to random errors, systematic errors should also be considered. Systematic error is the
error remaining once the random error is removed as shown in Figure 1. Systematic errors should be
eliminated wherever possible.
Key
X range of values Y range of occurrence
1 mean value 4 random error
2 individual value 5 systematic error
3 true value 6 distribution of values
Figure 1 — Relationship of measured, mean, and true values and association of random and
systematic errors
Uncertainty assessments of systems such as these can be dominated in magnitude by a small subset of
uncertainty sources. When independent uncertainty sources are combined smaller uncertainty sources
often contribute negligibly to the overall budget.
A variety of factors contribute to the uncertainty described in Clause 8 of ISO/TS 10974:2018. The
dominant sources of uncertainty are specific to the equipment, measurement methods, and numerical
simulation tools used for the assessment. Clause 8 of ISO/TS 10974:2018 requires an uncertainty
assessment for the measurement system (u ) and AIMD model (u ). There are two additional
exp Predict
sources of uncertainty being clinical uncertainty (from 8.6 of ISO/TS 10974:2018) and power to
temperature uncertainty (8.4.3 of ISO/TS 10974:2018). Techniques for evaluating these uncertainty
terms (u , u , u , u ) are described. As Clause 8 of ISO/TS 10974:2018 has multiple tiers
exp Predict Clinical Power
for evaluation of power deposition, the evaluation of each uncertainty source is specified per tier.
Two methods of uncertainty evaluations are developed in this document. In both methods, the
uncertainty of the entire assembly is determined. In one method, many of the components of the
assembly are grouped and a single uncertainty determination is made for many of them. In the second,
the sources of uncertainty in a system are identified and individually evaluated a priori and the
dominant sources are combined to obtain the system uncertainty.
[1]
GUM has provided approaches for evaluating the uncertainty of assemblies, regardless of component
count, and called their approaches Type A and Type B. Either or both Type A and Type B evaluations for
each method is appropriate.
4.2 Method 1 Evaluation
Method 1 determines the uncertainty of a complex measurement system by considering the variability
of the system as a whole. Method 1 is based on the assumption that a probability distribution of the
random variation of the evaluation results can be deduced from approximation of the measurement or
modelling system where the uncertainty is determined for an assembly or collection of many parts of
the system. In this approach, multiple elements of the system are assembled or ‘lumped’ together and
2 © ISO 2018 – All rights reserved

their combined uncertainty is assessed. Estimates of the standard deviation of this distribution are
obtained by repeated evaluations and statistical analysis of the obtained values.
4.3 Method 2 Evaluation
Method 2 generally dissects the assembly into its constituent parts, determines the uncertainty of each
individually, and then determines the uncertainty of the group by combining the uncertainty of each
of the components. Method 2 is based on reasonably assumed probability distributions that account
for the available information about the quantities concerned, a
...