Abstract
Objectives
This study evaluates the phantom attenuation correction (PAC) method as an alternative to maximum-likelihood attenuation correction factor (ML-ACF) correction in time-of-flight (TOF) brain positron emission tomography (PET) studies.
Methods
In the PAC algorithm, a template emission image \({\lambda }_{Ref}\) and a template attenuation coefficient image \({\mu }_{Ref}\) are prepared as a data set based on phantom geometry. Position-aligned attenuation coefficient image \({\mu }_{Acq}\) is derived by aligning \({\mu }_{Ref}\) using parameters that match the template emission image \({\lambda }_{Ref}\) to measured emission image \({\lambda }_{Acq}\). Then, attenuation coefficient image \({\mu }_{Acq}\) combined with a headrest image is used for scatter and attenuation correction in the image reconstruction. To evaluate the PAC algorithm as an alternative to ML-ACF, Hoffman 3D brain and cylindrical phantoms were measured to obtain the image quality indexes of contrast and uniformity. These phantoms were also wrapped with a radioactive sheet to obtain attenuation coefficient images using ML-ACF. Emission images were reconstructed with attenuation correction by PAC and ML-ACF, and the results were compared using contrast and uniformity as well as visual assessment. CT attenuation correction (CT-AC) was also applied as a reference.
Results
The contrast obtained by ML-ACF was slightly overestimated due to its unique experimental condition for applying ML-ACF in Hoffman 3D brain phantom but the uniformity was almost equivalent among ML-ACF, CT-AC, and PAC. PAC showed reasonable result without overestimation compared to ML-ACF and CT-AC.
Conclusions
PAC is an attenuation correction method that can ensure the performance in phantom test, and is considered to be a reasonable alternative to clinically used ML-ACF-based attenuation correction.
References
Summary of PET imaging facility certification. Japanese Society of Nuclear Medicine website. http://jsnm.org/wp_jsnm/wp-content/uploads/2021/06/JPEQi_Overview_20210624.pdf. Accessed 24 June 2021.
Standard PET imaging protocols and phantom test procedures and criteria: executive summary. http://jsnm.org/wp_jsnm/wp-content/themes/theme_jsnm/doc/StandardPETProtocolPhantom20170201.pdf. Accessed 1 Feb 2017.
Ikari Y, Akamatsu G, Nishio T, et al. Phantom criteria for qualification of brain FDG and amyloid PET across different cameras. EJNMMI Phys. 2016;3(23):2.
Phantom test procedures and criteria for brain FDG and amyloid PET imaging [in Japanese]. Japanese Society of Nuclear Medicine website. http://jsnm.org/wp_jsnm/wp-content/uploads/2021/02/Dementia_PhantomTest_20210208.pdf. Accessed 8 Feb 2021.
Rezaei A, Defrise M, Nuyts J. ML-reconstruction for TOF-PET with simultaneous estimation of the Attenuation Factors. IEEE Trans Med Imag. 2014;33(7):1563–72.
Mizuta T, Kobayashi T, Yamakawa Y, et al. Initial evaluation of a new maximum-likelihood attenuation correction factor-based attenuation correction for time-of-flight brain PET. Ann Nucl Med. 2022;36(4):420–6.
Ishii K, Hanaoka K, Watanabe S, et al. High-resolution silicon photomultiplier time-of-flight dedicated head PET system for clinical brain studies. J Nucl Med. 2022. https://doi.org/10.2967/jnumed.122.264080.
Larkin RS. Accelerated image reconstruction using ordered subsets of projection data. IEEE Trans Med Imaging. 1994;13(4):601–9.
Nakayama T, Kudo H, Derivation and implementation of ordered-subsets algorithms for list-mode PET data. IEEE NSS&MIC Conf. Rec 2005
Rapisarda E, Bettinardi V, Thielemans K, et al. Image-based point spread function implementation in a fully 3D OSEM reconstruction algorithm for PET. Phys Med Biol. 2010;55(14):4131–51.
Hoffman EJ, Culer PD, Digby WM, et al. 3-D phantom to simulate cerebral blood flow and metabolic images for PET. IEEE Trans Nucl Sci. 1990;37(2):616–20.
Matsumoto K, Endo K. Development of analysis software package for the two kinds of Japanese Fluoro-D-glucose-positron emission tomography guideline. Japanese J Radiol Technol. 2013;69:648–54.
Acknowledgements
The authors wish to thank reviewers of this manuscript for their helpful comments and suggestions. We also thank Dr. Hiroshi Ito from Fukushima Medical University and Dr. Keiichi Matsumoto from Kyoto College of Medical Science for discussion on experimental design. We thank Kimberly Moravec, PhD, from Edanz (https://jp.edanz.com/ac) for editing a draft of this manuscript.
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The part of authors are employees of Shimadzu Corporation. No other potential conflicts of interest relevant to this article exist.
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Mizuta, T., Yamakawa, Y., Minagawa, S. et al. Attenuation correction for phantom tests: an alternative to maximum-likelihood attenuation correction factor-based correction for clinical studies in time-of-flight PET. Ann Nucl Med 36, 998–1006 (2022). https://doi.org/10.1007/s12149-022-01788-8
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DOI: https://doi.org/10.1007/s12149-022-01788-8