Volume 37, Issue 5 p. 2101-2109
Radiation imaging physics

MR-based attenuation correction for hybrid PET-MR brain imaging systems using deformable image registration

Eduard Schreibmann

Eduard Schreibmann

Department of Radiation Oncology, School of Medicine, Emory University, Atlanta, Georgia 30322

Author to whom correspondence should be addressed. Electronic mail: [email protected]; Telephone: 404.778.5667; Fax: 404.778.4139.

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Jonathon A. Nye

Jonathon A. Nye

Department of Radiology, School of Medicine, Emory University, Atlanta, Georgia 30322

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David M. Schuster

David M. Schuster

Department of Radiology, School of Medicine, Emory University, Atlanta, Georgia 30322

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Diego R. Martin

Diego R. Martin

Department of Radiology, School of Medicine, Emory University, Atlanta, Georgia 30322

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John Votaw

John Votaw

Department of Radiology, School of Medicine, Emory University, Atlanta, Georgia 30322

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Tim Fox

Tim Fox

Department of Radiation Oncology, School of Medicine, Emory University, Atlanta, Georgia 30322

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First published: 21 April 2010
Citations: 87

0094-2405/2010/37(5)/2101/9/$30.00

Abstract

Purpose:

Realization of combined positron emission tomography (PET)—magnetic resonance (MR) scanners has the potential to significantly change healthcare and revolutionize clinical practice as it allows, simultaneously, visualization of molecular imaging and anatomical imaging. PET-MR, acquired in one imaging study, will likely become the advanced imaging modality of choice for neurological studies, certain forms of cancer, stroke, and the emerging study of stem cell therapy. A challenge toward the implementation and operation of combined PET-MR scanners is that attenuation corrections maps are not directly available due to space and cost constraints. This article presents a method to obtain accurate patient-specific PET attenuation coefficients maps in head imaging by warping an atlas computed tomography (CT) data set to the patient-specific MR data set using a deformable registration model.

Methods:

A multimodality optical flow deformable model has been developed that establishes a voxel-to-voxel correspondence between the CT atlas and patient MR images. Once the mapping is established, the atlas is warped with the deformation field obtained by the registration to create a simulated CT image study that matches the patient anatomy, which could be used for attenuation correction.

Results:

To evaluate the accuracy of the deformable-based attenuation correction, 17 clinical brain tumor cases were studied using acquired MR-CT images. A simulated CT was compared to the patient's true CT to assess geometrical accuracy of the deformation module as well as voxel-to-voxel comparison of Hounsfield units (HUs). In all cases, mapping from the atlas CT to the individual MR was achieved with geometrical accuracy as judged using quantitative inspection tools. The mean distance between simulated and true CT external contour and bony anatomy was 1.26 and 2.15 mm, respectively. In terms of HU unit comparison, the mean voxel-to-voxel difference was less than 2 HU for all cases.

Conclusions:

Attenuation correction for hybrid PET-MR scanners was easily achieved by individualizing an atlas CT to the MR data set using a deformable model without requiring user interaction. The method provided clinical accuracy while eliminating the need for an additional CT scan for PET attenuation correction.