Dosimetry in digital mammography

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Dosimetry in digital mammography Professor David Dance NCCPM, Royal Surrey County Hospital, Guildford, United kingdom

Outline Why do dosimetry? History Essentials of European breast dosimetry protocol Practical breast dosimetry Uncertainties and limitations Key points

Why do dosimetry? To control the dose no higher than necessary BUT high enough to ensure that adequate image quality is obtained essential part of quality control optimise equipment selection, design and use To estimate risk comparison of risk and benefit

History

UK DOSE SURVEY 1981 5 cm phantom Entrance surface dose TLD Dose range 0.9 to 45 mgy (!) kv range 24-49 kv HVL range 0.2 mm Al to 1.7 mm Al! Entrance dose is a poor measure of risk!

Transmission Transmission through 5 cm breast 1 0.1 0.01 Adipose Gland 0.001 15 20 25 30 35 Energy kev

Alternative dose measures Mid-breast dose Mean breast dose Average glandular dose (Mean glandular dose) Karlsson in 1976 Recommended by ICRP in 1987

Essentials of European breast dosimetry protocol

Original dosimetry requirements in UK AGD: risk related dose measure Easy to implement Applicable for patient and phantom dosimetry Standard phantom for QC Equivalent to a typical compressed breast

Average glandular dose Cannot measure AGD on patients Incident air kerma K (without backscatter) can be easily measured or estimated Need conversion coefficients which relate K to AGD AGD = K g Used in: IPSM Report 59 1989 European Protocol 1996

Focal spot Calculation of g using Monte Carlo model (Dance 1990) Calculate energy deposited in breast tissues Compression plate Simple breast phantom Breast support etc

Simple breast model Hammerstein 1979 5 mm adipose shield region Central region with mixture of glandular and adipose tissues Fraction by weight of glandular tissue in central region is known as the glandularity Hammerstein et al suggested the use of 50% glandularity for dosimetry

g-factors g-factor is for 50% glandularity In principle g-factors depend upon target/filtration and kv Simplification Tables of g-factor just based on HVL & breast thickness For spectra in use at that time worked within ± 5%

g-factor mgy/mgy g-factors 0.8 0.6 0.4 HVL 0.3 mm HVL 0.6 mm 0.2 0 2 4 6 8 Breast thickness cm

Improved formulation in 2000 Dance et al 2000, 2009, 2010, 2014 Real breasts don t all have 50% glandularity factors calculated for 0.1-100% Wider range of spectra used AGD = Kgcs

AGD = Kgcs c corrects for glandularity =1 for 50% glandularity s corrects for X-ray spectrum =1 for Mo/Mo Used in: UK (IPEM report 89 2005) European Guidelines (latest supplement is 2013) IAEA Code of Practice (TRS457)

c-factors Tabulated against HVL, breast thickness and glandularity c-factor 1.4 1.2 1.0 5 cm breast 0.1% 25% 50% 75% 0.8 100% 0.6 0.30 0.35 0.40 0.45 0.50 0.55 0.60 HVL (mm Al) But what glandularity should be used?

Breast glandularity (UK)

s-factors S Max Error Mo/Mo 1.000 3.1% Mo/Rh 1.017 2.2% Rh/Rh 1.061 3.6% Rh/Al 1.044 2.4% W/Rh 1.042 2.1% W/Ag 1.042 4.6% W/Al s-table needed

Standard breasts For quality control and inter-system comparison need a simple phantom or phantoms Cheap and easily reproducible (PMMA) Should be approximately equivalent to typical compressed breast(s)

Breast/PMMA equivalence Same incident air kerma at PMMA surface and breast surface Obtained by Monte Carlo simulation Validated by measurements with breast tissue equivalent phantoms

PMMA for standard breast dosimetry PMMA mm 20 30 40 45 50 60 70 Breast mm 21 32 45 53 60 75 90 Gland y % 97 67 41 29 20 9 4

PMMA equivalence age 50-64 Dance et al, 2000

Practical breast dosimetry

European Guidelines Fourth Edition Supplements 2013 Method: Section 2b2.3 g,c and s factors: Appendix 5

Practical dosimetry using blocks of PMMA (6 monthly) Objective is to simulate exposure of standard breasts Stage 1: determine exposure settings using blocks of PMMA Stage 2: determine incident air kerma & HVL Stage 3: calculate AGD Stage 4: review results

Stage 1 - Exposure parameters for blocks of PMMA Use usual clinical exposure settings Record mas, kv and target/filter Repeat for 20, 30, 40, 45, 50, 60, 70 mm blocks

Exposure parameters for blocks of PMMA Notes I PMMA blocks Thickness correct within ± 0.5 mm PMMA and breast equiv thicknesses are different If AEC works on thickness, add expanded polystyrene spacer to adjust total thickness (do not cover chamber with spacer) If AEC works on attenuation, spacer should not be necessary

Exposure parameters for blocks of PMMA Notes II Apply standard compression AEC on mid-line and closest to chest wall If digital AEC looks at densest region of breast, exposures may not be a good match to those obtained clinically

Stage 2 - Determination of incident air kerma and HVL AGD = Kgcs g, c and s depend upon the HVL K and HVL are determined with the compression paddle in place

Determination of incident air kerma - I Incident air kerma at upper surface of PMMA Measurement of tube output at a known distance from tube focus Apply inverse square law to calculate air kerma at top surface of PMMA Measurement is made with paddle in contact with the dosimeter

Determination of incident air kerma - II Use a calibrated dosimeter suitable for mammography Position dosimeter on line joining focal spot to a point on the mid-line of the breast support 6 cm from chest wall edge.

Determination of incident air kerma - II For dosimeters with backscatter rejection position dosimeter on breast support For dosimeters without backscatter rejection position the dosimeter higher up to avoid or reduce the effect of backscatter

Stage 3 AGD = Kgcs Tables A5.1 & A5.2 give g and c vs PMMA cm & HVL Table A5.4 gives s

AGD mgy Stage 4: review results 7 6 5 4 3 2 acceptable achievable 1 0 2 3 4 4.5 5 6 7 PMMA thickness cm

AGD: 53 mm breast (45 mm PMMA) Number of systems 35 30 25 20 15 10 5 0 0.5 1 1.5 2 2.5 3 MGD (mgy) 98% < 2.5 mgy

Patient dosimetry Measure tube output and HVL with paddle in place Record exposure parameters for patient series (e.g.50 or more) kv & target/filter mas compressed breast thickness Calculate AGD

Patient dosimetry Note Accuracy of displayed thickness should be checked by applying a typical force (e.g. 100 N) to rigid material of known thickness Accuracy of ±2 mm or better required

AGD = Kgcs Tables A5.5 A5.7 give g and c vs breast cm & HVL c for age 50-64 or 40-49 Table A5.4 gives s

Average patient AGD for different digital systems: 2010 UK data 2.5 2.0 Oduko et al IWDM 2010 AGD (mgy) 1.5 1.0 0.5 0.0 DR CR FS Image receptor type

Uncertainties & Limitations

Uncertainties in AGD using PMMA (typical) Dosimeter calibration 5% AEC and dosimeter reproducibility 2% Uncertainty in g due to 3% uncertainty in HVL 2% Chamber positioning (2mm) 1% Phantom thickness (0.5mm) 2% s-factor approximation 4% Overall 7%

Errors in using tabulated equivalent PMMA thickness Exact PMMA thickness required for equivalence varies with beam quality. Error is largest for highest kvs and thickest breasts. 0-60 mm breast: up to 1.0 mm PMMA 80 mm breast: up to 1.7 mm PMMA 100 mm breast: up to 2.4 mm PMMA

Errors in AGD associated with nonequivalence of tabulated PMMA thickness (W/Al spectrum) 15 30 kv 35 kv 40 kv Error % 10 5 0 20 30 40 50 60 70 Breast thickness (mm) 80 90 100

Air kerma measurement Measurements should be made with the dosimeter in contact with paddle (to mirror MC model) Scatter contributes e.g. ~7% to air kerma for 2.4 mm polycarbonate paddle Some semi-conductor dosimeters are collimated and will not record scatter Correction is then needed (Hemdal, Rad Prot Dosim. 2011)

Uncertainties in patient AGD typical and assuming breast model is correct Dosimeter calibration 5% Dosimeter etc. reproducibility 2% Uncertainty in g due to 3% uncertainty in HVL 2% Patient thickness (2 mm) impact on g and ISL 3% s-factor approximation 4% Overall, for one exposure 7% PLUS Standard error on mean from sample of 50 patients about 7%

Some limitations of the model Heel effect ignored Simple breast geometry Breast composition data (Hammerstein) based on 4 samples glandular tissue 8 samples adipose tissue 6 samples skin tissue results show considerable variability in composition

Effect of adipose shield thickness on g g / g(standard) 1.20 1.15 1.10 1.05 1.00 2.5 mm adipose shield 0.95 2 4 6 8 Thickness (cm)

g / g(standard) Effect of glandular tissue composition on g 1.10 1.05 1.00 0.95 0.90 High O Low O 0.85 2 4 6 8 Thickness (cm)

Real distributions of glandular tissue The distribution of glandular tissue in patients will not be uniform and large differences in conversion factors can be expected. Modelled using breast phantoms from Predrag Bakic (Dance et al, RPD 2005) Differences in AGD of up to ~40% found

European vs USA breast model (Wu) Adipose shield replaced by 4mm skin Different initial attenuation Different volume containing glandular tissue to share energy absorbed Unclear if dose from photons scattered in paddle included Different cross section compilation Differences of up to 16% in conversion coefficients

Key points

Key points The conversion factors are influenced by the model parameters. Whatever breast model is chosen for QC dosimetry, it need only be an approximate representation of the true situation. The present European and American models give standard procedures and are fine for QC. Large errors can occur if either model is used to estimate AGD for individual patients. But the models are fine for QC of patient doses.

Acknowledgements Recent work has been funded under the EU 6th Framework Programme the HighRex project and the UK funded OPTIMAM and OPTIMAM2 projects I am grateful to my colleagues at NCCPM for provision of data, and for discussions