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. 2016 Jan;57(1):136-43.
doi: 10.2967/jnumed.115.156299. Epub 2015 Oct 22.

Fast Patch-Based Pseudo-CT Synthesis from T1-Weighted MR Images for PET/MR Attenuation Correction in Brain Studies

Angel Torrado-Carvajal  1 , Joaquin L Herraiz  2 , Eduardo Alcain  3 , Antonio S Montemayor  3 , Lina Garcia-Cañamaque  4 , Juan A Hernandez-Tamames  5 , Yves Rozenholc  6 , Norberto Malpica  5
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Free article

Fast Patch-Based Pseudo-CT Synthesis from T1-Weighted MR Images for PET/MR Attenuation Correction in Brain Studies

Angel Torrado-Carvajal et al. J Nucl Med. 2016 Jan.
Free article

Abstract

Attenuation correction in hybrid PET/MR scanners is still a challenging task. This paper describes a methodology for synthesizing a pseudo-CT volume from a single T1-weighted volume, thus allowing us to create accurate attenuation correction maps.

Methods: We propose a fast pseudo-CT volume generation from a patient-specific MR T1-weighted image using a groupwise patch-based approach and an MRI-CT atlas dictionary. For every voxel in the input MR image, we compute the similarity of the patch containing that voxel to the patches of all MR images in the database that lie in a certain anatomic neighborhood. The pseudo-CT volume is obtained as a local weighted linear combination of the CT values of the corresponding patches. The algorithm was implemented in a graphical processing unit (GPU).

Results: We evaluated our method both qualitatively and quantitatively for PET/MR correction. The approach performed successfully in all cases considered. We compared the SUVs of the PET image obtained after attenuation correction using the patient-specific CT volume and using the corresponding computed pseudo-CT volume. The patient-specific correlation between SUV obtained with both methods was high (R(2) = 0.9980, P < 0.0001), and the Bland-Altman test showed that the average of the differences was low (0.0006 ± 0.0594). A region-of-interest analysis was also performed. The correlation between SUVmean and SUVmax for every region was high (R(2) = 0.9989, P < 0.0001, and R(2) = 0.9904, P < 0.0001, respectively).

Conclusion: The results indicate that our method can accurately approximate the patient-specific CT volume and serves as a potential solution for accurate attenuation correction in hybrid PET/MR systems. The quality of the corrected PET scan using our pseudo-CT volume is comparable to having acquired a patient-specific CT scan, thus improving the results obtained with the ultrashort-echo-time-based attenuation correction maps currently used in the scanner. The GPU implementation substantially decreases computational time, making the approach suitable for real applications.

Keywords: GPU; PET/MR; attenuation correction; image synthesis; pseudo-CT.

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