Defining and assessing a delineation uncertainty margin for modern radiotherapy

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Transcript of Defining and assessing a delineation uncertainty margin for modern radiotherapy

Page 1: Defining and assessing a delineation uncertainty margin for modern radiotherapy
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1 Centre for Medical Radiation Physics, University of Wollongong, Australia.2 Liverpool & Macarthur Cancer Therapy Centres & Ingham Institute, Liverpool, Australia. 3 SWSCS, University of New South Wales, Australia.4 Institute of Medical Physics, University of Sydney, Australia.

Defining and Assessing a Delineation Margin for Modern Radiation Therapy

L.R.Bell1,2, E.M.Pogson1,2, P.Metcalfe1,2, L.Holloway1,2,3,4

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~50% patients have an indication for RT 1

Conform ionising radiation to cancer

Radiation Therapy

2

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Motion Set up Delineation errors

Random uncertainties BLUR the dose distribution

Systematic uncertainties SHIFT the dose distribution

Uncertainties

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New technologies and imaging reduces impact of motion and set up errors◦ High precision

Set up and motion margins can be/are being/have been be reduced

Uncertainty Margins

Delineation ErrorsSet up ErrorsMotion Errors

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Delineation uncertainty is a current limiting factor in radiotherapy accuracy- weakest link!

We need precision AND accuracy for most effective radiotherapy

Delineation Uncertainty

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Based on first systematic term of margin recipes◦ Average SD in contour delineation multiplied by a weighting

factor ANISOTROPIC to account for spatially varying

uncertainty

Delineation Uncertainty Margin

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21 CT whole breast datasets 3

CTVs delineated by 8 observers

Small, medium and large volume categories for both left and right breast patients

Dataset

Small 0-700 cm3

Medium 701-1400 cm3

Large 1401-2100 cm3

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Defined in cylindrical and spherical coordinates for anisotropic approach; and cartesian to compare to current practice

Origin defined average COM of CTVs

Margin=2*SDav ◦ ‘Leave one out approach’

Margin Definition

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1. Generated consensus contour (STAPLE) for each patient

2. Applied margin to STAPLE, smallest CTV and largest CTV

3. Assessed encompassment of CTVs (% Overlap)

4. Assessed extra and missed tissue

Margin Assessment

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Overlap: >90%

Non-critical MT: <10% of CTV union Critical MT: 0% of CTV union Non-critical EIT: No limit Critical EIT: <1/3 union of CTVs

Margin Assessment

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<90% overlap in ◦ 35/504 (6.9%) cases for cylindrically defined margin◦ 17/504 (3.4%) cases for spherically defined margin◦ 72/504 (14.3%) cases for the clinically defined margin

Results

Small STAPLE

Large

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Critical ET within tolerance

Non-Critical ET small (<11%)

Negligible critical MT

Non-critical MT exceeds tolerance in 52/54 (96.3%) cases

Extra and Missed TissueSmall STAPLE

Large

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Anisotropic margin has greater encompassment in all cases

Anisotropic margin includes less EIT for large target volumes

Anisotropic margin misses more non-critical tissue– potentially due to coordinate system failures

Anisotropic margin is necessary to account for the weak link in RT that is delineation uncertainty

Conclusions

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References

1. Barton, M.B., S. Jacob, J. Shafiq, K. Wong, S.R. Thompson, T.P. Hanna and G.P. Delaney, Estimating the demand for radiotherapy from the evidence: A review of changes from 2003 to 2012. Radiother. Onc., 2014.

2. Njeh, C.F., Tumor delineation: The weakest link in the search for accuracy in radiotherapy. Journal of Medical Physics / Association of Medical Physicists of India, 2008. 33(4): p. 136-140.

3. Jameson, M.G., et al., Correlation of contouring variation with modeled outcome for conformal non-small cell lung cancer radiotherapy. Radiotherapy and Oncology, 2014. 112(3): p. 332-336.

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Hemi-spherical shape of breast CTVs means cylindrical/spherical coordinates are not always suitable

SD limited to ½ max hausdorff distance

Coordinate System Failures