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. 2001 Sep 1;51(1):255-60.
doi: 10.1016/s0360-3016(01)01659-5.

Multimodality image registration quality assurance for conformal three-dimensional treatment planning

S Mutic  1 , J F Dempsey, W R Bosch, D A Low, R E Drzymala, K S Chao, S M Goddu, P D Cutler, J A Purdy
Affiliations

Multimodality image registration quality assurance for conformal three-dimensional treatment planning

S Mutic et al. Int J Radiat Oncol Biol Phys. .

Abstract

Purpose: We present a quality assurance methodology to determine the accuracy of multimodality image registration and fusion for the purpose of conformal three-dimensional and intensity-modulated radiation therapy treatment planning. Registration and fusion accuracy between any combination of computed tomography (CT), magnetic resonance (MR), and positron emission computed tomography (PET) imaging studies can be evaluated.

Methods and materials: A commercial anthropomorphic head phantom filled with water and containing CT, MR, and PET visible targets was modified to evaluate the accuracy of multimodality image registration and fusion software. For MR and PET imaging, the water inside the phantom was doped with CuNO(3) and 18F-fluorodeoxyglucose (18F-FDG), respectively. Targets consisting of plastic spheres and pins were distributed throughout the cranium section of the phantom. Each target sphere had a conical-shaped bore with its apex at the center of the sphere. The pins had a conical extension or indentation at the free end. The contours of the spheres, sphere centers, and pin tips were used as anatomic landmark models for image registration, which was performed using affine coordinate-transformation tools provided in a commercial multimodality image registration/fusion software package. Four sets of phantom image studies were obtained: primary CT, secondary CT with different phantom immobilization, MR, and PET study. A novel CT, MR, and PET external fiducial marking system was also tested.

Results: The registration of CT/CT, CT/MR, and CT/PET images allowed correlation of anatomic landmarks to within 2 mm, verifying the accuracy of the registration software and spatial fidelity of the four multimodality image sets.

Conclusions: This straightforward phantom-based quality assurance of the image registration and fusion process can be used in a routine clinical setting or for providing a working image set for development of the image registration and fusion process and new software.

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