Literature DB >> 28837045

Subject-specific bone attenuation correction for brain PET/MR: can ZTE-MRI substitute CT scan accurately?

Maya Khalifé1, Brice Fernandez, Olivier Jaubert, Michael Soussan, Vincent Brulon, Irène Buvat, Claude Comtat.   

Abstract

In brain PET/MR applications, accurate attenuation maps are required for accurate PET image quantification. An implemented attenuation correction (AC) method for brain imaging is the single-atlas approach that estimates an AC map from an averaged CT template. As an alternative, we propose to use a zero echo time (ZTE) pulse sequence to segment bone, air and soft tissue. A linear relationship between histogram normalized ZTE intensity and measured CT density in Hounsfield units ([Formula: see text]) in bone has been established thanks to a CT-MR database of 16 patients. Continuous AC maps were computed based on the segmented ZTE by setting a fixed linear attenuation coefficient (LAC) to air and soft tissue and by using the linear relationship to generate continuous μ values for the bone. Additionally, for the purpose of comparison, four other AC maps were generated: a ZTE derived AC map with a fixed LAC for the bone, an AC map based on the single-atlas approach as provided by the PET/MR manufacturer, a soft-tissue only AC map and, finally, the CT derived attenuation map used as the gold standard (CTAC). All these AC maps were used with different levels of smoothing for PET image reconstruction with and without time-of-flight (TOF). The subject-specific AC map generated by combining ZTE-based segmentation and linear scaling of the normalized ZTE signal into [Formula: see text] was found to be a good substitute for the measured CTAC map in brain PET/MR when used with a Gaussian smoothing kernel of [Formula: see text] corresponding to the PET scanner intrinsic resolution. As expected TOF reduces AC error regardless of the AC method. The continuous ZTE-AC performed better than the other alternative MR derived AC methods, reducing the quantification error between the MRAC corrected PET image and the reference CTAC corrected PET image.

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Year:  2017        PMID: 28837045     DOI: 10.1088/1361-6560/aa8851

Source DB:  PubMed          Journal:  Phys Med Biol        ISSN: 0031-9155            Impact factor:   3.609


  9 in total

1.  Attenuation correction for brain PET imaging using deep neural network based on Dixon and ZTE MR images.

Authors:  Kuang Gong; Jaewon Yang; Kyungsang Kim; Georges El Fakhri; Youngho Seo; Quanzheng Li
Journal:  Phys Med Biol       Date:  2018-06-13       Impact factor: 3.609

2.  MR-based PET attenuation correction using a combined ultrashort echo time/multi-echo Dixon acquisition.

Authors:  Paul Kyu Han; Debra E Horng; Kuang Gong; Yoann Petibon; Kyungsang Kim; Quanzheng Li; Keith A Johnson; Georges El Fakhri; Jinsong Ouyang; Chao Ma
Journal:  Med Phys       Date:  2020-05-11       Impact factor: 4.071

3.  ZTE MR-based attenuation correction in brain FDG-PET/MR: performance in patients with cognitive impairment.

Authors:  Brian Sgard; Maya Khalifé; Arthur Bouchut; Brice Fernandez; Marine Soret; Alain Giron; Clara Zaslavsky; Gaspar Delso; Marie-Odile Habert; Aurélie Kas
Journal:  Eur Radiol       Date:  2019-11-20       Impact factor: 5.315

4.  MR-based Attenuation Correction for Brain PET Using 3D Cycle-Consistent Adversarial Network.

Authors:  Kuang Gong; Jaewon Yang; Peder E Z Larson; Spencer C Behr; Thomas A Hope; Youngho Seo; Quanzheng Li
Journal:  IEEE Trans Radiat Plasma Med Sci       Date:  2020-07-03

Review 5.  MR Image-Based Attenuation Correction of Brain PET Imaging: Review of Literature on Machine Learning Approaches for Segmentation.

Authors:  Imene Mecheter; Lejla Alic; Maysam Abbod; Abbes Amira; Jim Ji
Journal:  J Digit Imaging       Date:  2020-10       Impact factor: 4.056

6.  Accuracy and precision of zero-echo-time, single- and multi-atlas attenuation correction for dynamic [11C]PE2I PET-MR brain imaging.

Authors:  João M Sousa; Lieuwe Appel; Inés Merida; Rolf A Heckemann; Nicolas Costes; Mathias Engström; Stergios Papadimitriou; Dag Nyholm; Håkan Ahlström; Alexander Hammers; Mark Lubberink
Journal:  EJNMMI Phys       Date:  2020-12-28

7.  Clinical validation of the novel HDAC6 radiotracer [18F]EKZ-001 in the human brain.

Authors:  Michel Koole; Donatienne Van Weehaeghe; Kim Serdons; Marissa Herbots; Christopher Cawthorne; Sofie Celen; Frederick A Schroeder; Jacob M Hooker; Guy Bormans; Jan de Hoon; Janice E Kranz; Koen Van Laere; Tonya M Gilbert
Journal:  Eur J Nucl Med Mol Imaging       Date:  2020-07-08       Impact factor: 9.236

8.  Evaluation of three methods for delineation and attenuation estimation of the sinus region in MR-based attenuation correction for brain PET-MR imaging.

Authors:  Jani Lindén; Jarmo Teuho; Mika Teräs; Riku Klén
Journal:  BMC Med Imaging       Date:  2022-03-17       Impact factor: 1.930

9.  Attenuation correction using 3D deep convolutional neural network for brain 18F-FDG PET/MR: Comparison with Atlas, ZTE and CT based attenuation correction.

Authors:  Paul Blanc-Durand; Maya Khalife; Brian Sgard; Sandeep Kaushik; Marine Soret; Amal Tiss; Georges El Fakhri; Marie-Odile Habert; Florian Wiesinger; Aurélie Kas
Journal:  PLoS One       Date:  2019-10-07       Impact factor: 3.240

  9 in total

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