Estimating cumulated absorbed doses and associated health risks due to occupational exposure to ionising radiation

1. Estimating cumulated absorbed doses and associated
health risks due to occupational exposure to ionising
radiation
David Moriña, James Grellier, Adela Carnicer, Eileen Pernot and
Elisabeth Cardis
May 28th 2015, Barcelona, ICRA 6

2. Contents
1 Introduction
2 Methods
3 Risk estimation
4 Example
5 Further work
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3. Introduction
Occupational exposure
• Interventional cardiology (IC) comprises a variety of minimally invasive
procedures used in the diagnosis and treatment of cardiovascular
disease
• Interventional radiology (IR) forms a key component of the work of the
interventional cardiologist
• Used appropriately to support a variety of procedures, IR represents
enormous clinical benefits like minimal invasiveness, reduced pain and
risk, shorter hospital stay and lower cost
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4. Introduction
Occupational exposure
• Interventional cardiologists and electrophysiologists are occupationally
exposed to ionising radiation
• The clinical benefits of using catheterisation techniques instead of open
surgery have resulted in a considerable increase in workload over the
past two decades
• There is concern that present cumulated doses may result in increased
risk of brain cancer and cataracts to surgeons
• Effective use of radiation protection measures can reduce these risks by
reducing doses to the brain and eye lens
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5. Introduction
Occupational exposure
• There are some tools for radiation risk assessment already available, but
focused essentially on acute exposures and on cancer related diseases
• Our goal is to estimate doses and associated health risks for
occupational chronic exposures also for other radiation related diseases
like cataracts
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6. Introduction
Occupational exposure
• We designed a tool that employs robust estimators of parameters based
on a multiple linear regression of predictors of dose including radiation
protection measures, catheterisation access route, tube configuration
and operator experience (derived from data collected in the ORAMED
project and from the literature) and a user-defined occupational history
to produce distributions of annual and total cumulated absorbed doses
to the targets of interest
• Potential sources of uncertainty are taken into account by means of
Monte Carlo simulation
• Occupational histories can be reconstructed by the user using general
data derived from existing databases
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7. Introduction
Occupational exposure
• Changes in imaging equipment available to interventional cardiologists
over the past four decades were taken into account by fitting a
metaregression model using results from a literature review, and the
computed doses are adjusted using these values
• Probability distributions of risk are then calculated on the basis of the
resulting cumulated absorbed doses, using estimates of dose-response
and related uncertainties derived from the literature
• In direct support of radiation protection, the tool allows the user to
compare their doses and associated risks with those expected under a
scenario where protective equipment is employed to the fullest extent
and under a scenario where no protective equipment is employed at all
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8. Introduction
Occupational exposure
• Outputs of the tool allow population attributable risks of health outcomes
to be calculated for specific populations of these health professionals, for
whom group-level occupational histories are reconstructed
• By extension, it allows for estimation of the expected health benefits for
that population associated with use of a variety of radiation protection
measures
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9. Methods
The tool
• The webtool has been developed in R using the shiny package, which
allows to build interactive web applications from R
• The left panel on the website allows the user to enter specific data
concerning their career (profession, working dates range and number of
annual procedures), while the results are automatically updated and
presented on the right side of the web
• The output part is divided in four tabs, allowing the user to compare the
expected doses in a “standard” career, the expected doses under the
use of all available protection measures and the expected doses under
the usage of none protection measure
• The fourth tab shows the typical behaviour regarding usage of protection
methods and procedure type distribution per decade
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10. Methods
The tool
Figure: Screenshot of the tool
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11. Methods
Underlying model
• The main model considered was a robust linear regression model using
protection measures as RadPad, table, cabin and screen, the type of
procedure, the tube configuration and operator experience (high after 4
years of work) as predictors of the absorbed dose
• The reduction on the lens dose due to the usage of lead glasses is
assumed to follow a PERT distribution with minimal, modal and maximal
values of 1, 3 and 10 respectively, based on expert opinions
• The obtained estimates were
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12. Methods
Underlying model
Protection method ˆβ (95% CI)
Table 0.746 (0.543; 1.026)
RadPad 0.828 (0.485; 1.415)
Screen 0.826 (0.604; 1.130)
Cabin 0.168 (0.055; 0.518)
Procedure ˆβ (95% CI)
CA PTCA Ref.
DSA PTA C 0.392 (0.193; 0.794)
DSA PTA LL 0.920 (0.612; 1.384)
DSA PTA R 0.600 (0.392; 0.906)
Embolisation 0.778 (0.565; 1.070)
ERCP 2.166 (1.445; 3.246)
PM/ICD 1.827 (1.265; 2.639)
RF ablation 0.965 (0.620; 1.500)
Tube configuration ˆβ (95% CI)
Above Ref.
Below 0.244 (0.164; 0.363)
Biplane 0.230 (0.142; 0.372)
Experience ˆβ (95% CI)
High Ref.
Low 1.063 (0.836; 1.351)
Table: Parameter estimates and confidence intervals
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13. Methods
Risk estimation
The PERT distribution is a particular case of the Beta distribution,
characterized by the density function
f(x) =
xα−1
(1−x)β−1
B(α,β)
: 0 ≤ x ≤ 1
0 : Otherwise
where B(α, β) is the beta function, defined by
B(α, β) =
1
0
tα−1
(1 − t)β−1
dt.
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14. Methods
Risk estimation
• Sampling from the beta distribution requires minimum and maximum
values (scale) and two shape parameters, α and β
• The PERT distribution uses the mode or most likely parameter to
generate the shape parameters α and β
• An additional scale parameter λ scales the height of the distribution; the
default value for this parameter is 4
• In the PERT distribution, the mean µ is calculated as
µ =
min + max + λmode
λ + 2
• And it can be used to compute the Beta parameters α and β:
α = (µ−min)·(2mode−min−max)
(mode−µ)·(max−min)
β = α·(max−µ)
µ−min
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15. Risk estimation
Risk estimation
• Instead of dosimetry, users may be interested in estimate the cumulated
absorbed dose has increased their risk of cataracts
• Once the dose is estimated as described before, the associated health
risk is estimated by means of the PERT distribution with minimal, modal
and maximal values derived from the literature
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16. Risk estimation
Risk estimation
• Instead of dosimetry, users may be interested in estimate the cumulated
absorbed dose has increased their risk of cataracts
• Once the dose is estimated as described before, the associated health
risk is estimated by means of the PERT distribution with minimal, modal
and maximal values derived from the literature
Cataract kind Minimal value Modal value Maximal value
Stage 1-5 1.22 1.70 2.38
Early PSC 1.25 1.89 2.84
Stage 1 PSC 1.01 1.42 2.00
Table: Minimal, modal and maximal values for cataract risk
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17. Risk estimation
Report
Figure: Total dose distribution
The user can download a re-
port including all the informa-
tion regarding estimated doses
and associated risks in a pdf
document
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18. Example
Example
For example, we can see how the cumulated absorbed lens doses and
associated health risks changes comparing a “standard” interventional
cardiologist working from 1985 to 2014 and doing about 300 procedures
annually from 1985 to 2000 and then 350 until 2014 to the same working
profile incorporating the effect of the usage of all available protection methods
or incorporating the effect of the usage of no protection methods at all
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19. Example
Total dose distributions
Standard career
Dose (mGy)
Density
0 10000 20000 30000 40000
0.000000.000020.000040.000060.000080.000100.00012
All available protection methods
Dose (mGy)
Density
0 2000 4000 6000 8000 10000
0.00000.00050.00100.0015
No protection method
Dose (mGy)
Density
10000 20000 30000 40000
0.000000.000020.000040.000060.000080.000100.00012
Figure: Total dose distribution
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20. Example
Annual dose
The annual absorbed dose for each scenario is also graphically represented
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21. Example
Annual dose0100200300400500600
Standard career
Year
Dose(mGy)
1985 1989 1993 1997 2001 2005 2009 2013
050100150
All available protection methods
Year
Dose(mGy)
1985 1989 1993 1997 2001 2005 2009 2013
200300400500600700800
No protection method
Year
Dose(mGy)
1985 1989 1993 1997 2001 2005 2009 2013
Figure: Annual dose
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22. Example
Results
• In the case of this example, the total cumulated absorbed lens dose
estimated is 4932.79 mGy (685.18, 15046.38) under a “standard”
scenario
• If no protection methods are used, these values are increased to
11112.62 mGy (6063.63, 22715.79)
• In the scenario under the usage of all available protection methods, the
estimated dose is 575.58 mGy (198.02, 1844.93)
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23. Example
Results
• Regarding the risk of cataracts, the differences between the scenarios
are
Cataract kind Scenario Median RR (95% UI)
Stage 1-5
Standard
All available protection methods
No protection methods
8.6 (1.2, 27.1)
1.0 (0.3, 3.1)
18.3 (9.4, 39.0)
Early PSC
Standard
All available protection methods
No protection methods
9.6 (1.3, 30.8)
1.1 (0.4, 3.5)
20.4 (10.3, 44.3)
Stage 1 PSC
Standard
All available protection methods
No protection methods
9.6 (1.3, 30.7)
1.1 (0.4, 3.5)
20.4 (10.3, 43.9)
Table: Cataract risk for the different considered scenarios
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24. Example
Results
• Obviously, the effect of the protection methods is very relevant for the
cumulated absorbed lens dose and for the risk of cataracts as well
• This comparison can also be done to the dose received if no protection
methods were used at all
• The user can also see the difference between the different protection
methods usage scenarios on the cataract risk. For example, we can see
the difference in the distribution of relative risk of stage 1-5 cataracts
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25. Example
Risk of stage 1-5 cataracts
Standard career
RR
Density
0 20 40 60 80
0.000.020.040.06
All available protection methods
RR
Density
0 5 10 15
0.00.20.40.60.8
No protection method
RR
Density
20 40 60 80 100
0.000.010.020.030.040.050.060.07
Figure: RR of stage 1-5 cataracts distribution
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26. Further work
Further work
• Estimate doses and associated risk for other organs/diseases (in
particular, brain/CNS tumours)
• Use of other health impact measures as
• Population attributable fraction
• Attributable cases
• Lifetime excess risk of cancer
• Years of life lost (YLL)
• Disability-adjusted life years (DALYs)
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27. Further work
Live example
The tool is already available on
http://crealradiation.shinyapps.io/radtool
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29. Centre for Research
in Environmental
Epidemiology
Parc de Recerca Biomèdica de Barcelona
Doctor Aiguader, 88
08003 Barcelona (Spain)
Tel. (+34) 93 214 70 00
Fax (+34) 93 214 73 02
info@creal.cat
www.creal.cat