estimating cumulated absorbed doses and associated health risks due to occupational exposure to...

Estimating cumulated absorbed doses and associatedhealth risks due to occupational exposure to ionising

radiation

David Moriña, James Grellier, Adela Carnicer, Eileen Pernot andElisabeth Cardis

May 28th 2015, Barcelona, ICRA 6

Contents

1 Introduction

2 Methods

3 Risk estimation

4 Example

5 Further work

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Introduction

Occupational exposure

• Interventional cardiology (IC) comprises a variety of minimally invasiveprocedures used in the diagnosis and treatment of cardiovasculardisease

• Interventional radiology (IR) forms a key component of the work of theinterventional cardiologist

• Used appropriately to support a variety of procedures, IR representsenormous clinical benefits like minimal invasiveness, reduced pain andrisk, shorter hospital stay and lower cost

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Introduction


• Interventional cardiologists and electrophysiologists are occupationallyexposed to ionising radiation

• The clinical benefits of using catheterisation techniques instead of opensurgery have resulted in a considerable increase in workload over thepast two decades

• There is concern that present cumulated doses may result in increasedrisk of brain cancer and cataracts to surgeons

• Effective use of radiation protection measures can reduce these risks byreducing doses to the brain and eye lens

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Introduction


• There are some tools for radiation risk assessment already available, butfocused essentially on acute exposures and on cancer related diseases

• Our goal is to estimate doses and associated health risks foroccupational chronic exposures also for other radiation related diseaseslike cataracts

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Introduction


• We designed a tool that employs robust estimators of parameters basedon a multiple linear regression of predictors of dose including radiationprotection measures, catheterisation access route, tube configurationand operator experience (derived from data collected in the ORAMEDproject and from the literature) and a user-defined occupational historyto produce distributions of annual and total cumulated absorbed dosesto the targets of interest

• Potential sources of uncertainty are taken into account by means ofMonte Carlo simulation

• Occupational histories can be reconstructed by the user using generaldata derived from existing databases

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Introduction


• Changes in imaging equipment available to interventional cardiologistsover the past four decades were taken into account by fitting ametaregression model using results from a literature review, and thecomputed doses are adjusted using these values

• Probability distributions of risk are then calculated on the basis of theresulting cumulated absorbed doses, using estimates of dose-responseand related uncertainties derived from the literature

• In direct support of radiation protection, the tool allows the user tocompare their doses and associated risks with those expected under ascenario where protective equipment is employed to the fullest extentand under a scenario where no protective equipment is employed at all

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Introduction


• Outputs of the tool allow population attributable risks of health outcomesto be calculated for specific populations of these health professionals, forwhom group-level occupational histories are reconstructed

• By extension, it allows for estimation of the expected health benefits forthat population associated with use of a variety of radiation protectionmeasures

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Methods

The tool

• The webtool has been developed in R using the shiny package, whichallows to build interactive web applications from R

• The left panel on the website allows the user to enter specific dataconcerning their career (profession, working dates range and number ofannual procedures), while the results are automatically updated andpresented on the right side of the web

• The output part is divided in four tabs, allowing the user to compare theexpected doses in a “standard” career, the expected doses under theuse of all available protection measures and the expected doses underthe usage of none protection measure

• The fourth tab shows the typical behaviour regarding usage of protectionmethods and procedure type distribution per decade

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Methods

The tool

Figure: Screenshot of the tool

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Methods

Underlying model

• The main model considered was a robust linear regression model usingprotection measures as RadPad, table, cabin and screen, the type ofprocedure, the tube configuration and operator experience (high after 4years of work) as predictors of the absorbed dose

• The reduction on the lens dose due to the usage of lead glasses isassumed to follow a PERT distribution with minimal, modal and maximalvalues of 1, 3 and 10 respectively, based on expert opinions

• The obtained estimates were

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Methods

Underlying model

Protection method β̂ (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 β̂ (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 β̂ (95% CI)Above Ref.Below 0.244 (0.164; 0.363)

Biplane 0.230 (0.142; 0.372)Experience β̂ (95% CI)

High Ref.Low 1.063 (0.836; 1.351)

Table: Parameter estimates and confidence intervals

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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

0tα−1(1 − t)β−1dt .

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Methods

Risk estimation

• Sampling from the beta distribution requires minimum and maximumvalues (scale) and two shape parameters, α and β

• The PERT distribution uses the mode or most likely parameter togenerate the shape parameters α and β

• An additional scale parameter λ scales the height of the distribution; thedefault 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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Risk estimation

Risk estimation

• Instead of dosimetry, users may be interested in estimate the cumulatedabsorbed dose has increased their risk of cataracts

• Once the dose is estimated as described before, the associated healthrisk is estimated by means of the PERT distribution with minimal, modaland maximal values derived from the literature

Cataract kind Minimal value Modal value Maximal valueStage 1-5 1.22 1.70 2.38Early 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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Risk estimation

Report

Figure: Total dose distribution

The user can download a re-port including all the informa-tion regarding estimated dosesand associated risks in a pdfdocument

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Example

Example

For example, we can see how the cumulated absorbed lens doses andassociated health risks changes comparing a “standard” interventionalcardiologist working from 1985 to 2014 and doing about 300 proceduresannually from 1985 to 2000 and then 350 until 2014 to the same workingprofile incorporating the effect of the usage of all available protection methodsor incorporating the effect of the usage of no protection methods at all

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Example

Total dose distributions

Standard career

Dose (mGy)

Den

sity

0 10000 20000 30000 40000

0.00

000

0.00

002

0.00

004

0.00

006

0.00

008

0.00

010

0.00

012

All available protection methods

Dose (mGy)

Den

sity

0 2000 4000 6000 8000 10000

0.00

000.

0005

0.00

100.

0015

No protection method

Dose (mGy)

Den

sity

10000 20000 30000 40000

0.00

000

0.00

002

0.00

004

0.00

006

0.00

008

0.00

010

0.00

012

Figure: Total dose distribution

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Example

Annual dose

The annual absorbed dose for each scenario is also graphically represented

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Example

Annual dose0

100

200

300

400

500

600

Standard career

Year

Dos

e (m

Gy)

1985 1989 1993 1997 2001 2005 2009 2013

050

100

150


Year

Dos

e (m

Gy)

1985 1989 1993 1997 2001 2005 2009 2013

200

300

400

500

600

700

800


Year

Dos

e (m

Gy)

1985 1989 1993 1997 2001 2005 2009 2013

Figure: Annual dose

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Example

Results

• In the case of this example, the total cumulated absorbed lens doseestimated is 4932.79 mGy (685.18, 15046.38) under a “standard”scenario

• If no protection methods are used, these values are increased to11112.62 mGy (6063.63, 22715.79)

• In the scenario under the usage of all available protection methods, theestimated dose is 575.58 mGy (198.02, 1844.93)

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Example

Results

• Regarding the risk of cataracts, the differences between the scenariosare

Cataract kind Scenario Median RR (95% UI)

Stage 1-5Standard

All available protection methodsNo protection methods

8.6 (1.2, 27.1)1.0 (0.3, 3.1)18.3 (9.4, 39.0)

Early PSCStandard


9.6 (1.3, 30.8)1.1 (0.4, 3.5)20.4 (10.3, 44.3)

Stage 1 PSCStandard


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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Example

Results

• Obviously, the effect of the protection methods is very relevant for thecumulated absorbed lens dose and for the risk of cataracts as well

• This comparison can also be done to the dose received if no protectionmethods were used at all

• The user can also see the difference between the different protectionmethods usage scenarios on the cataract risk. For example, we can seethe difference in the distribution of relative risk of stage 1-5 cataracts

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Example

Risk of stage 1-5 cataracts

Standard career

RR

Den

sity

0 20 40 60 80

0.00

0.02

0.04

0.06


RR

Den

sity

0 5 10 15

0.0

0.2

0.4

0.6

0.8


RR

Den

sity

20 40 60 80 100

0.00

0.01

0.02

0.03

0.04

0.05

0.06

0.07

Figure: RR of stage 1-5 cataracts distribution

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Further work

Further work

• Estimate doses and associated risk for other organs/diseases (inparticular, 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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Further work

Live example

The tool is already available onhttp://crealradiation.shinyapps.io/radtool

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http://crealradiation.shinyapps.io/radtool

Centre for Researchin EnvironmentalEpidemiology

Parc de Recerca Biomèdica de BarcelonaDoctor Aiguader, 8808003 Barcelona (Spain)Tel. (+34) 93 214 70 00Fax (+34) 93 214 73 02

[email protected]