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TU‐C‐M100F‐07: Detecting Dose Reconstruction Errors
Author(s) -
Zhong Hualiang,
Weiss Elisabeth,
Siebers Jeffrey
Publication year - 2007
Publication title -
medical physics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.473
H-Index - 180
eISSN - 2473-4209
pISSN - 0094-2405
DOI - 10.1118/1.2761348
Subject(s) - image registration , image warping , voxel , image guided radiation therapy , medical imaging , mathematics , convolution (computer science) , dosimetry , nuclear medicine , divergence (linguistics) , displacement (psychology) , radiation treatment planning , artificial intelligence , standard deviation , interpolation (computer graphics) , computer vision , computer science , radiation therapy , image (mathematics) , medicine , statistics , artificial neural network , radiology , psychology , linguistics , philosophy , psychotherapist
Purpose In radiation therapy, delivered doses can be accumulated over fractions for adaptive treatment planning. However, the dose reconstruction fidelity can be compromised by image registration errors. The resultant dose discrepancy is hard to measure. This paper proposes a new method to assess the difference between the delivered dose and the warped dose. Method and Materials: The dose warping discrepancy is dominated by deformable image registration errors and source‐dose distributions. Registration errors can be specified within a finite element framework as an unbalanced energy δ R , which is defined at element j by δ R( j ) = ∑ i = 1 , … , 4| d i( j )F ̃ i|, F ̃ i = E 0∑ j Φ j( di 1( j ), di 2( j ), … , di 4( j )) where E 0 and d i are Young's modulus and the displacement vector fields of the registration R . E 0 Φ j is an assembly of all the element forces relating to the node i . Consequently the dose warping discrepancy at voxel k can be defined as the convolution of the dose divergence Div ( D ) and δ R : ε D , R( k ) = ∫ Div ( D ( k ) ) * δ R( k − τ ) d τ . The effectiveness of the dose‐discrepancy‐convolution (DDC) defined above is demonstrated through applying it to dose computed on ten prostate‐CT images. An IMRT treatment plan is developed on the planning image. In nine subsequent treatments, images are acquired to calculate the corresponding delivered doses. Their mean and standard‐deviation in C i , a target contour automatically expanded from prostate delineated on the time‐of‐treatment image i , are compared with those of their warped doses measured on the planning target volume. The differences in their means and standard‐deviations are denoted by E ε and E σ , respectively. Results δ R , ε D,R , E ε and E σ are computed for the nine treatment fractions. Fraction one and eight have the largest warping discrepancies identified in all the four evaluation criterions. Conclusion Defined in terms of the deformable registration error, the voxel‐based DDC can be employed for the automatic evaluation of dose reconstruction in the whole dosing domain. Its measurement is consistent to the contour‐based dose warping evaluation performed in the planning target volume.