• Andrew P Leynes, Jaewon Yang, Florian Wiesinger, Sandeep S Kaushik, Dattesh D Shanbhag, Youngho Seo, Thomas A Hope, and LarsonPeder E ZPEZDepartment of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, California.UC Berkeley-UCSF Graduate Program in Bioengineering, UC Berkeley, Berkeley, California, and UCSF, San Francisco, California.
• Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, California andrew.leynes@ucsf.edu.
• J. Nucl. Med. 2018 May 1; 59 (5): 852-858.

AbstractAccurate quantification of uptake on PET images depends on accurate attenuation correction in reconstruction. Current MR-based attenuation correction methods for body PET use a fat and water map derived from a 2-echo Dixon MRI sequence in which bone is neglected. Ultrashort-echo-time or zero-echo-time (ZTE) pulse sequences can capture bone information. We propose the use of patient-specific multiparametric MRI consisting of Dixon MRI and proton-density-weighted ZTE MRI to directly synthesize pseudo-CT images with a deep learning model: we call this method ZTE and Dixon deep pseudo-CT (ZeDD CT). Methods: Twenty-six patients were scanned using an integrated 3-T time-of-flight PET/MRI system. Helical CT images of the patients were acquired separately. A deep convolutional neural network was trained to transform ZTE and Dixon MR images into pseudo-CT images. Ten patients were used for model training, and 16 patients were used for evaluation. Bone and soft-tissue lesions were identified, and the SUVmax was measured. The root-mean-squared error (RMSE) was used to compare the MR-based attenuation correction with the ground-truth CT attenuation correction. Results: In total, 30 bone lesions and 60 soft-tissue lesions were evaluated. The RMSE in PET quantification was reduced by a factor of 4 for bone lesions (10.24% for Dixon PET and 2.68% for ZeDD PET) and by a factor of 1.5 for soft-tissue lesions (6.24% for Dixon PET and 4.07% for ZeDD PET). Conclusion: ZeDD CT produces natural-looking and quantitatively accurate pseudo-CT images and reduces error in pelvic PET/MRI attenuation correction compared with standard methods.© 2018 by the Society of Nuclear Medicine and Molecular Imaging.

22 keywords...

hide…