Investigation of a method for generating synthetic CT models from MRI scans of the head and neck for radiation therapy

Shu Hui Hsu, Yue Cao, Ke Huang, Mary Feng, James M. Balter

Research output: Contribution to journalArticle

70 Citations (Scopus)

Abstract

Magnetic resonance (MR) images often provide superior anatomic and functional information over computed tomography (CT) images, but generally are not used alone without CT images for radiotherapy treatment planning and image guidance. This study aims to investigate the potential of probabilistic classification of voxels from multiple MRI contrasts to generate synthetic CT ('MRCT') images. The method consists of (1) acquiring multiple MRI volumes: T1-weighted, T2-weighted, two echoes from a ultra-short echo time (UTE) sequence, and calculated fat and water image volumes using a Dixon method, (2) classifying tissues using fuzzy c-means clustering with a spatial constraint, (3) assigning attenuation properties with weights based on the probability of individual tissue classes being present in each voxel, and (4) generating a MRCT image volume from the sum of attenuation properties in each voxel. The capability of each MRI contrast to differentiate tissues of interest was investigated based on a retrospective analysis of ten patients. For one prospective patient, the correlation of skull intensities between CT and MR was investigated, the discriminatory power of MRI in separating air from bone was evaluated, and the generated MRCT image volume was qualitatively evaluated. Our analyses showed that one MRI volume was not sufficient to separate all tissue types, and T2-weighted images was more sensitive to bone density variation compared to other MRI image types. The short echo UTE image showed significant improvement in contrasting air versus bone, but could not completely separate air from bone without false labeling. Generated MRCT and CT images showed similar contrast between bone and soft/solid tissues. These results demonstrate the potential of the presented method to generate synthetic CT images to support the workflow of radiation oncology treatment planning and image guidance.

Original languageEnglish (US)
Pages (from-to)8419-8435
Number of pages17
JournalPhysics in Medicine and Biology
Volume58
Issue number23
DOIs
StatePublished - Dec 7 2013

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Neck
Radiotherapy
Head
Tomography
Magnetic Resonance Imaging
Bone and Bones
Air
Magnetic Resonance Spectroscopy
Radiation Oncology
Workflow
Skull
Bone Density
Cluster Analysis
Fats
Weights and Measures
Water
Therapeutics

ASJC Scopus subject areas

  • Radiology Nuclear Medicine and imaging
  • Radiological and Ultrasound Technology

Cite this

Investigation of a method for generating synthetic CT models from MRI scans of the head and neck for radiation therapy. / Hsu, Shu Hui; Cao, Yue; Huang, Ke; Feng, Mary; Balter, James M.

In: Physics in Medicine and Biology, Vol. 58, No. 23, 07.12.2013, p. 8419-8435.

Research output: Contribution to journalArticle

Hsu, Shu Hui ; Cao, Yue ; Huang, Ke ; Feng, Mary ; Balter, James M. / Investigation of a method for generating synthetic CT models from MRI scans of the head and neck for radiation therapy. In: Physics in Medicine and Biology. 2013 ; Vol. 58, No. 23. pp. 8419-8435.
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