Deformable image registration based automatic CT-to-CT contour propagation for head and neck adaptive radiotherapy in the routine clinical setting

Akila Kumarasiri, Farzan Siddiqui, Chang Liu, Raphael Yechieli, Mira Shah, Deepak Pradhan, Hualiang Zhong, Indrin J. Chetty, Jinkoo Kim

Research output: Contribution to journalArticle

32 Citations (Scopus)

Abstract

Purpose: To evaluate the clinical potential of deformable image registration (DIR)-based automatic propagation of physician-drawn contours from a planning CT to midtreatment CT images for head and neck (H&N) adaptive radiotherapy.

Methods: Ten H&N patients, each with a planning CT (CT1) and a subsequent CT (CT2) taken approximately 3-4 week into treatment, were considered retrospectively. Clinically relevant organs and targets were manually delineated by a radiation oncologist on both sets of images. Four commercial DIR algorithms, two B-spline-based and two Demons-based, were used to deform CT1 and the relevant contour sets onto corresponding CT2 images. Agreement of the propagated contours with manually drawn contours on CT2 was visually rated by four radiation oncologists in a scale from 1 to 5, the volume overlap was quantified using Dice coefficients, and a distance analysis was done using center of mass (CoM) displacements and Hausdorff distances (HDs). Performance of these four commercial algorithms was validated using a parameter-optimized Elastix DIR algorithm.

Results: All algorithms attained Dice coefficients of >0.85 for organs with clear boundaries and those with volumes >9 cm3. Organs with volumes <3 cm3 and/or those with poorly defined boundaries showed Dice coefficients of ∼0.5-0.6. For the propagation of small organs (<3 cm3), the B-splinebased algorithms showed higher mean Dice values (Dice = 0.60) than the Demons-based algorithms (Dice = 0.54). For the gross and planning target volumes, the respective mean Dice coefficients were 0.8 and 0.9. There was no statistically significant difference in the Dice coefficients, CoM, or HD among investigated DIR algorithms. The mean radiation oncologist visual scores of the four algorithms ranged from 3.2 to 3.8, which indicated that the quality of transferred contours was "clinically acceptable with minor modification or major modification in a small number of contours".

Conclusions: Use of DIR-based contour propagation in the routine clinical setting is expected to increase the efficiency of H&N replanning, reducing the amount of time needed for manual target and organ delineations.

Original languageEnglish (US)
Article number121712
JournalMedical Physics
Volume41
Issue number12
DOIs
StatePublished - Dec 1 2014
Externally publishedYes

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Neck
Radiotherapy
Head
Organ Size
Physicians
Radiation Oncologists

Keywords

  • adaptive radiotherapy
  • automatic contouring
  • contour evaluation
  • contour propagation
  • deformable image registration

ASJC Scopus subject areas

  • Biophysics
  • Radiology Nuclear Medicine and imaging

Cite this

Deformable image registration based automatic CT-to-CT contour propagation for head and neck adaptive radiotherapy in the routine clinical setting. / Kumarasiri, Akila; Siddiqui, Farzan; Liu, Chang; Yechieli, Raphael; Shah, Mira; Pradhan, Deepak; Zhong, Hualiang; Chetty, Indrin J.; Kim, Jinkoo.

In: Medical Physics, Vol. 41, No. 12, 121712, 01.12.2014.

Research output: Contribution to journalArticle

Kumarasiri, Akila ; Siddiqui, Farzan ; Liu, Chang ; Yechieli, Raphael ; Shah, Mira ; Pradhan, Deepak ; Zhong, Hualiang ; Chetty, Indrin J. ; Kim, Jinkoo. / Deformable image registration based automatic CT-to-CT contour propagation for head and neck adaptive radiotherapy in the routine clinical setting. In: Medical Physics. 2014 ; Vol. 41, No. 12.
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AU - Yechieli, Raphael

AU - Shah, Mira

AU - Pradhan, Deepak

AU - Zhong, Hualiang

AU - Chetty, Indrin J.

AU - Kim, Jinkoo

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