Attenuation correction for PET/MRI using MRI-based pseudo CT

Tonghe Wang; Yang Lei; Xue Dong; Kristin Higgins; Tian Liu; Walter J. Curran; Hui Mao; Jonathon A. Nye; Xiaofeng Yang

doi:10.1117/12.2548158

16 March 2020 Attenuation correction for PET/MRI using MRI-based pseudo CT

Tonghe Wang, Yang Lei, Xue Dong, Kristin Higgins, Tian Liu, Walter J. Curran, Hui Mao, Jonathon A. Nye, Xiaofeng Yang

Proceedings Volume 11312, Medical Imaging 2020: Physics of Medical Imaging; 1131248 (2020) https://doi.org/10.1117/12.2548158
Event: SPIE Medical Imaging, 2020, Houston, Texas, United States

Abstract

Deriving accurate attenuation maps for PET/MRI remains a challenging problem because MRI voxel intensities are not related to properties of photon attenuation and bone/air interfaces have similarly low signal. This work presents a learning-based method to derive patient-specific pseudo computed tomography (PCT) maps from routine T1-weighted MRI in their native space for attenuation correction of brain PET. We developed a machine-learning-based method using a sequence of alternating random forests under the framework of an iterative refinement model. Anatomical feature selection is included in both training and predication stages to achieve excellent performance. To evaluate its accuracy, we retrospectively investigated 17 patients, each of which has been scanned by PET/CT and MR for brain. The PET images were corrected for attenuation on CT images as ground truth, as well as on PCT images generated from MR images. The side-by-side image comparisons and joint histograms demonstrated very good agreement of PET images after correction by PCT and CT. The mean differences of voxel values in selected VOIs were less than 4%, the mean absolute difference of all active area is around 2.5%. This work demonstrates a novel learning-based approach to automatically generate CT images from routine T1-weighted MR images based on a random forest regression with patch-based anatomical signatures to effectively capture the relationship between the CT and MR images. Reconstructed PET images using the PCT exhibit errors well below accepted test/retest reliability of PET/CT indicating high quantitative equivalence.

Citation Download Citation

Tonghe Wang, Yang Lei, Xue Dong, Kristin Higgins, Tian Liu, Walter J. Curran, Hui Mao, Jonathon A. Nye, and Xiaofeng Yang "Attenuation correction for PET/MRI using MRI-based pseudo CT", Proc. SPIE 11312, Medical Imaging 2020: Physics of Medical Imaging, 1131248 (16 March 2020); https://doi.org/10.1117/12.2548158

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