SU‐EE‐A3‐05: Accuracy Testing of Deformable Registration Using Dosimetric End‐Points

K. Langen, S. Meeks, A. Limaye, O. Zeidan, P. Kupelian, R. Manon, G. Olivera, K. Ruchala, J. Haimerl, W. lu

Research output: Contribution to journalArticle

Abstract

Purpose: To develop a dose‐based evaluation method to assess deformable image registration accuracy Method and Materials: An algorithm developed for deformable registration of MVCT to kVCT images was evaluated. The algorithm allows the generation of automatic contours on MVCT images by transferring the kVCT contours using the deformation map. The automatically generated MVCT contours can thus be used to test the deformation algorithm by comparing these contours with manual contours. Instead of a geographic contour comparison, dosimetric endpoints were evaluated after the dose distribution was calculated in the MVCT images. Three dosimetric endpoints (Dmax, Dmean, and Dose to the hottest 2 cc (Dmax (2cc)) were compared for spinal cord contours. The evaluation of geometric end‐points is directly related to the clinical information that needs to be evaluated if daily images are used for adaptive radiation therapy. A total of 93 daily megavoltage CT (MVCT) images from three patients treated for cancers in the head and neck region were evaluated. Results: Averaged over all images the calculated Dmax differed between the automatic and manual contours by 1.1 % with a standard deviation of 3.5 %. The respective values for Dmean and Dmax(2cc) are 0.1 ± 2.5 % and 1.8 ± 2.4 %. Maximum deviations between the dosimetric endpoints were 12 % for Dmax, 8% for Dmean, and 13 % for Dmax(2cc). Conclusions: Using deformable image registration, dosimetric end‐points can be generated from automatic contours in the spinal cord region that differ from manual contours by 1–2 % on average with a standard deviation of 2.5 to 3.5 %. In the spinal cord region the developed deformable image registration appears to provide sufficient accuracy to support clinical decisions. Conflict of interest: Research supported by the vendor that is commercializing the algorithm. Several co‐authors are vendor employees.

Original languageEnglish (US)
Pages (from-to)1994-1995
Number of pages2
JournalMedical Physics
Volume33
Issue number6
DOIs
StatePublished - 2006

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Spinal Cord
Clinical Decision Support Systems
Conflict of Interest
Head and Neck Neoplasms
Radiotherapy
Research

ASJC Scopus subject areas

  • Biophysics
  • Radiology Nuclear Medicine and imaging

Cite this

SU‐EE‐A3‐05 : Accuracy Testing of Deformable Registration Using Dosimetric End‐Points. / Langen, K.; Meeks, S.; Limaye, A.; Zeidan, O.; Kupelian, P.; Manon, R.; Olivera, G.; Ruchala, K.; Haimerl, J.; lu, W.

In: Medical Physics, Vol. 33, No. 6, 2006, p. 1994-1995.

Research output: Contribution to journalArticle

Langen, K, Meeks, S, Limaye, A, Zeidan, O, Kupelian, P, Manon, R, Olivera, G, Ruchala, K, Haimerl, J & lu, W 2006, 'SU‐EE‐A3‐05: Accuracy Testing of Deformable Registration Using Dosimetric End‐Points', Medical Physics, vol. 33, no. 6, pp. 1994-1995. https://doi.org/10.1118/1.2240230
Langen, K. ; Meeks, S. ; Limaye, A. ; Zeidan, O. ; Kupelian, P. ; Manon, R. ; Olivera, G. ; Ruchala, K. ; Haimerl, J. ; lu, W. / SU‐EE‐A3‐05 : Accuracy Testing of Deformable Registration Using Dosimetric End‐Points. In: Medical Physics. 2006 ; Vol. 33, No. 6. pp. 1994-1995.
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abstract = "Purpose: To develop a dose‐based evaluation method to assess deformable image registration accuracy Method and Materials: An algorithm developed for deformable registration of MVCT to kVCT images was evaluated. The algorithm allows the generation of automatic contours on MVCT images by transferring the kVCT contours using the deformation map. The automatically generated MVCT contours can thus be used to test the deformation algorithm by comparing these contours with manual contours. Instead of a geographic contour comparison, dosimetric endpoints were evaluated after the dose distribution was calculated in the MVCT images. Three dosimetric endpoints (Dmax, Dmean, and Dose to the hottest 2 cc (Dmax (2cc)) were compared for spinal cord contours. The evaluation of geometric end‐points is directly related to the clinical information that needs to be evaluated if daily images are used for adaptive radiation therapy. A total of 93 daily megavoltage CT (MVCT) images from three patients treated for cancers in the head and neck region were evaluated. Results: Averaged over all images the calculated Dmax differed between the automatic and manual contours by 1.1 {\%} with a standard deviation of 3.5 {\%}. The respective values for Dmean and Dmax(2cc) are 0.1 ± 2.5 {\%} and 1.8 ± 2.4 {\%}. Maximum deviations between the dosimetric endpoints were 12 {\%} for Dmax, 8{\%} for Dmean, and 13 {\%} for Dmax(2cc). Conclusions: Using deformable image registration, dosimetric end‐points can be generated from automatic contours in the spinal cord region that differ from manual contours by 1–2 {\%} on average with a standard deviation of 2.5 to 3.5 {\%}. In the spinal cord region the developed deformable image registration appears to provide sufficient accuracy to support clinical decisions. Conflict of interest: Research supported by the vendor that is commercializing the algorithm. Several co‐authors are vendor employees.",
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AB - Purpose: To develop a dose‐based evaluation method to assess deformable image registration accuracy Method and Materials: An algorithm developed for deformable registration of MVCT to kVCT images was evaluated. The algorithm allows the generation of automatic contours on MVCT images by transferring the kVCT contours using the deformation map. The automatically generated MVCT contours can thus be used to test the deformation algorithm by comparing these contours with manual contours. Instead of a geographic contour comparison, dosimetric endpoints were evaluated after the dose distribution was calculated in the MVCT images. Three dosimetric endpoints (Dmax, Dmean, and Dose to the hottest 2 cc (Dmax (2cc)) were compared for spinal cord contours. The evaluation of geometric end‐points is directly related to the clinical information that needs to be evaluated if daily images are used for adaptive radiation therapy. A total of 93 daily megavoltage CT (MVCT) images from three patients treated for cancers in the head and neck region were evaluated. Results: Averaged over all images the calculated Dmax differed between the automatic and manual contours by 1.1 % with a standard deviation of 3.5 %. The respective values for Dmean and Dmax(2cc) are 0.1 ± 2.5 % and 1.8 ± 2.4 %. Maximum deviations between the dosimetric endpoints were 12 % for Dmax, 8% for Dmean, and 13 % for Dmax(2cc). Conclusions: Using deformable image registration, dosimetric end‐points can be generated from automatic contours in the spinal cord region that differ from manual contours by 1–2 % on average with a standard deviation of 2.5 to 3.5 %. In the spinal cord region the developed deformable image registration appears to provide sufficient accuracy to support clinical decisions. Conflict of interest: Research supported by the vendor that is commercializing the algorithm. Several co‐authors are vendor employees.

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