Skip to main content
Erschienen in: Annals of Nuclear Medicine 4/2022

09.02.2022 | Short Communication

Initial evaluation of a new maximum-likelihood attenuation correction factor-based attenuation correction for time-of-flight brain PET

verfasst von: Tetsuro Mizuta, Tetsuya Kobayashi, Yoshiyuki Yamakawa, Kohei Hanaoka, Shota Watanabe, Daisuke Morimoto-Ishikawa, Takahiro Yamada, Hayato Kaida, Kazunari Ishii

Erschienen in: Annals of Nuclear Medicine | Ausgabe 4/2022

Einloggen, um Zugang zu erhalten

Abstract

Aim

The aim of this study was to evaluate an image reconstruction algorithm, including a new maximum-likelihood attenuation correction factor (ML-ACF) for time of flight (TOF) brain positron emission tomography (PET).

Methods

The implemented algorithm combines an ML-ACF method that simultaneously estimates both the emission image and attenuation sinogram from TOF emission data, and a scaling method based on anatomical features. To evaluate the algorithm’s quantitative accuracy, three-dimensional brain phantom images were acquired and soft-tissue attenuation coefficients and emission values were analyzed.

Results

The heterogeneous distributions of attenuation coefficients in soft tissue, skull, and nasal cavity were sufficiently visualized. The attenuation coefficient of soft tissue remained within 5% of theoretical value. Attenuation-corrected emission showed no lateral differences, and significant differences among soft tissue were within the error range.

Conclusion

The ML-ACF-based attenuation correction implemented for TOF brain PET worked well and obtained practical levels of accuracy.
Literatur
1.
Zurück zum Zitat Defrise M, Rezaei A, Nuyts J. Time-of-flight PET data determine the attenuation sinogram up to a constant. Phys Med Biol. 2012;57:885–99.CrossRef Defrise M, Rezaei A, Nuyts J. Time-of-flight PET data determine the attenuation sinogram up to a constant. Phys Med Biol. 2012;57:885–99.CrossRef
2.
Zurück zum Zitat 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.CrossRef 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.CrossRef
3.
Zurück zum Zitat Frey KA, Lodge MA, Meltzer CC, Peller PJ, Wong TZ, Hess CP, et al. ACR-ASNR practice parameter for brain PET/CT imaging dementia. Clin Nucl Med. 2016;41(2):118–25.CrossRef Frey KA, Lodge MA, Meltzer CC, Peller PJ, Wong TZ, Hess CP, et al. ACR-ASNR practice parameter for brain PET/CT imaging dementia. Clin Nucl Med. 2016;41(2):118–25.CrossRef
4.
Zurück zum Zitat Nuyts J, et al. Simultaneous maximum a posteriori reconstruction of attenuation and activity distributions from emission sinograms. IEEE Trans Med Imag. 1999;18(5):393–403.CrossRef Nuyts J, et al. Simultaneous maximum a posteriori reconstruction of attenuation and activity distributions from emission sinograms. IEEE Trans Med Imag. 1999;18(5):393–403.CrossRef
5.
Zurück zum Zitat Berkera Y, Li Y. Attenuation correction in emission tomography using the emission data—A review. Med Phys. 2016;43(2):807–32.CrossRef Berkera Y, Li Y. Attenuation correction in emission tomography using the emission data—A review. Med Phys. 2016;43(2):807–32.CrossRef
6.
Zurück zum Zitat Kobayashi T, Kitamura K. A solution for scaling problem in joint estimation of activity and attenuation. In: IEEE NSS&MIC Conf. Rec. 2017. Kobayashi T, Kitamura K. A solution for scaling problem in joint estimation of activity and attenuation. In: IEEE NSS&MIC Conf. Rec. 2017.
7.
Zurück zum Zitat Li Y, Matej S, Karp JS. Practical joint reconstruction of activity and attenuation with autonomous scaling for time-of-flight PET. Phys Med Biol. 2020;65:235037.CrossRef Li Y, Matej S, Karp JS. Practical joint reconstruction of activity and attenuation with autonomous scaling for time-of-flight PET. Phys Med Biol. 2020;65:235037.CrossRef
8.
Zurück zum Zitat Hudson HM, Larkin RS. Accelerated image reconstruction using ordered subsets of projection data. IEEE Trans Med Imaging. 1994;13(4):601–9.CrossRef Hudson HM, Larkin RS. Accelerated image reconstruction using ordered subsets of projection data. IEEE Trans Med Imaging. 1994;13(4):601–9.CrossRef
9.
Zurück zum Zitat Watson CC, Newport D, Casey ME. A single scatter simulation technique for scatter correction in 3D PET. Three-dimensional image reconstruction in radiology and nuclear medicine. IEEE Trans Med Imaging. 1996;1996:255–68. Watson CC, Newport D, Casey ME. A single scatter simulation technique for scatter correction in 3D PET. Three-dimensional image reconstruction in radiology and nuclear medicine. IEEE Trans Med Imaging. 1996;1996:255–68.
10.
Zurück zum Zitat Nakayama T, Kudo H. Derivation and implementation of ordered-subsets algorithms for list-mode PET data. In: IEEE NSS&MIC Conf. Rec. 2005. Nakayama T, Kudo H. Derivation and implementation of ordered-subsets algorithms for list-mode PET data. In: IEEE NSS&MIC Conf. Rec. 2005.
11.
Zurück zum Zitat Iida H, Hori Y, Ishida K, Imabayashi E, Matsuda H, Takahashi M, et al. Three-dimensional brain phantom containing bone and grey matter structures with a realistic head contour. Ann Nucl Med. 2013;27:25–36.CrossRef Iida H, Hori Y, Ishida K, Imabayashi E, Matsuda H, Takahashi M, et al. Three-dimensional brain phantom containing bone and grey matter structures with a realistic head contour. Ann Nucl Med. 2013;27:25–36.CrossRef
Metadaten
Titel
Initial evaluation of a new maximum-likelihood attenuation correction factor-based attenuation correction for time-of-flight brain PET
verfasst von
Tetsuro Mizuta
Tetsuya Kobayashi
Yoshiyuki Yamakawa
Kohei Hanaoka
Shota Watanabe
Daisuke Morimoto-Ishikawa
Takahiro Yamada
Hayato Kaida
Kazunari Ishii
Publikationsdatum
09.02.2022
Verlag
Springer Singapore
Erschienen in
Annals of Nuclear Medicine / Ausgabe 4/2022
Print ISSN: 0914-7187
Elektronische ISSN: 1864-6433
DOI
https://doi.org/10.1007/s12149-022-01721-z

Weitere Artikel der Ausgabe 4/2022

Annals of Nuclear Medicine 4/2022 Zur Ausgabe