Literature DB >> 26936700

Vision 20/20: Magnetic resonance imaging-guided attenuation correction in PET/MRI: Challenges, solutions, and opportunities.

Abolfazl Mehranian1, Hossein Arabi1, Habib Zaidi2.   

Abstract

Attenuation correction is an essential component of the long chain of data correction techniques required to achieve the full potential of quantitative positron emission tomography (PET) imaging. The development of combined PET/magnetic resonance imaging (MRI) systems mandated the widespread interest in developing novel strategies for deriving accurate attenuation maps with the aim to improve the quantitative accuracy of these emerging hybrid imaging systems. The attenuation map in PET/MRI should ideally be derived from anatomical MR images; however, MRI intensities reflect proton density and relaxation time properties of biological tissues rather than their electron density and photon attenuation properties. Therefore, in contrast to PET/computed tomography, there is a lack of standardized global mapping between the intensities of MRI signal and linear attenuation coefficients at 511 keV. Moreover, in standard MRI sequences, bones and lung tissues do not produce measurable signals owing to their low proton density and short transverse relaxation times. MR images are also inevitably subject to artifacts that degrade their quality, thus compromising their applicability for the task of attenuation correction in PET/MRI. MRI-guided attenuation correction strategies can be classified in three broad categories: (i) segmentation-based approaches, (ii) atlas-registration and machine learning methods, and (iii) emission/transmission-based approaches. This paper summarizes past and current state-of-the-art developments and latest advances in PET/MRI attenuation correction. The advantages and drawbacks of each approach for addressing the challenges of MR-based attenuation correction are comprehensively described. The opportunities brought by both MRI and PET imaging modalities for deriving accurate attenuation maps and improving PET quantification will be elaborated. Future prospects and potential clinical applications of these techniques and their integration in commercial systems will also be discussed.

Mesh:

Year:  2016        PMID: 26936700     DOI: 10.1118/1.4941014

Source DB:  PubMed          Journal:  Med Phys        ISSN: 0094-2405            Impact factor:   4.071


  36 in total

1.  Novel adversarial semantic structure deep learning for MRI-guided attenuation correction in brain PET/MRI.

Authors:  Hossein Arabi; Guodong Zeng; Guoyan Zheng; Habib Zaidi
Journal:  Eur J Nucl Med Mol Imaging       Date:  2019-07-01       Impact factor: 9.236

2.  Direct attenuation correction of brain PET images using only emission data via a deep convolutional encoder-decoder (Deep-DAC).

Authors:  Isaac Shiri; Pardis Ghafarian; Parham Geramifar; Kevin Ho-Yin Leung; Mostafa Ghelichoghli; Mehrdad Oveisi; Arman Rahmim; Mohammad Reza Ay
Journal:  Eur Radiol       Date:  2019-06-21       Impact factor: 5.315

3.  Attenuation correction using deep learning for brain perfusion SPECT images.

Authors:  Kenta Sakaguchi; Hayato Kaida; Shuhei Yoshida; Kazunari Ishii
Journal:  Ann Nucl Med       Date:  2021-03-09       Impact factor: 2.668

4.  Impact of Tissue Classification in MRI-Guided Attenuation Correction on Whole-Body Patlak PET/MRI.

Authors:  Mingzan Zhuang; Nicolas A Karakatsanis; Rudi A J O Dierckx; Habib Zaidi
Journal:  Mol Imaging Biol       Date:  2019-12       Impact factor: 3.488

5.  One registration multi-atlas-based pseudo-CT generation for attenuation correction in PET/MRI.

Authors:  Hossein Arabi; Habib Zaidi
Journal:  Eur J Nucl Med Mol Imaging       Date:  2016-06-03       Impact factor: 9.236

Review 6.  Towards enhanced PET quantification in clinical oncology.

Authors:  Habib Zaidi; Nicolas Karakatsanis
Journal:  Br J Radiol       Date:  2017-11-22       Impact factor: 3.039

Review 7.  Applications of artificial intelligence in nuclear medicine image generation.

Authors:  Zhibiao Cheng; Junhai Wen; Gang Huang; Jianhua Yan
Journal:  Quant Imaging Med Surg       Date:  2021-06

Review 8.  Advances in simultaneous PET/MR for imaging neuroreceptor function.

Authors:  Christin Y Sander; Hanne D Hansen; Hsiao-Ying Wey
Journal:  J Cereb Blood Flow Metab       Date:  2020-03-13       Impact factor: 6.200

9.  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

10.  Deep-JASC: joint attenuation and scatter correction in whole-body 18F-FDG PET using a deep residual network.

Authors:  Isaac Shiri; Hossein Arabi; Parham Geramifar; Ghasem Hajianfar; Pardis Ghafarian; Arman Rahmim; Mohammad Reza Ay; Habib Zaidi
Journal:  Eur J Nucl Med Mol Imaging       Date:  2020-05-15       Impact factor: 9.236

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