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

  • Brian SgardEmail author
  • Maya Khalifé
  • Arthur Bouchut
  • Brice Fernandez
  • Marine Soret
  • Alain Giron
  • Clara Zaslavsky
  • Gaspar Delso
  • Marie-Odile Habert
  • Aurélie Kas
Nuclear Medicine
  • 30 Downloads

Abstract

Objective

One of the main challenges of integrated PET/MR is to achieve an accurate PET attenuation correction (AC), especially in brain acquisition. Here, we evaluated an AC method based on zero echo time (ZTE) MRI, comparing it with the single-atlas AC method and CT-based AC, set as reference.

Methods

Fifty patients (70 ± 11 years old, 28 men) underwent FDG-PET/MR examination (SIGNA PET/MR 3.0 T, GE Healthcare) as part of the investigation of suspected dementia. They all had brain computed tomography (CT), 2-point LAVA-flex MRI (for atlas-based AC), and ZTE-MRI. Two AC methods were compared with CT-based AC (CTAC): one based on a single atlas, one based on ZTE segmentation. Impact on brain metabolism was evaluated using voxel and volumes of interest–based analyses. The impact of AC was also evaluated through comparisons between two subgroups of patients extracted from the whole population: 15 patients with mild cognitive impairment and normal metabolic pattern, and 22 others with metabolic pattern suggestive of Alzheimer disease, using SPM12 software.

Results

ZTE-AC yielded a lower bias (3.6 ± 3.2%) than the atlas method (4.5 ± 6.1%) and lowest interindividual (4.6% versus 6.8%) and inter-regional (1.4% versus 2.6%) variabilities. Atlas-AC resulted in metabolism overestimation in cortical regions near the vertex and cerebellum underestimation. ZTE-AC yielded a moderate metabolic underestimation mainly in the occipital cortex and cerebellum. Voxel-wise comparison between the two subgroups of patients showed that significant difference clusters had a slightly smaller size but similar locations with PET images corrected with ZTE-AC compared with those corrected with CT, whereas atlas-AC images showed a notable reduction of significant voxels.

Conclusion

ZTE-AC performed better than atlas-AC in detecting pathologic areas in suspected neurodegenerative dementia.

Key Points

• The ZTE-based AC improved the accuracy of the metabolism quantification in PET compared with the atlas-AC method.

• The overall uptake bias was 21% lower when using ZTE-based AC compared with the atlas-AC method.

• ZTE-AC performed better than atlas-AC in detecting pathologic areas in suspected neurodegenerative dementia.

Keywords

PET/MR ZTE MRI Attenuation correction Fluoro-2-deoxy-d-glucose (FDG) Neurodegenerative dementia 

Abbreviations

AAL

Automated anatomical labeling

AC

Attenuation correction

AC-PC line

Anterior commissure–posterior commissure line

AD

Alzheimer disease

CNN

Convolutional neural networks

DL

Deep learning

FDG

2-Fluoro-2-deoxy-d-glucose

FWE

Family-wise error

HU

Hounsfield unit

MNI

Montreal Neurological Institute

MR

Magnetic resonance

MRAC

Magnetic resonance–based attenuation correction

MRI

Magnetic resonance imaging

PET

Positron emission tomography

PSF

Point spread function

SPM

Statistical parametric mapping

SUV

Standard uptake value

TOF

Time of flight

UTE

Ultrashort time

ZTE

Zero time echo

Notes

Acknowledgements

The authors would like to thank GE Healthcare for providing access to research tools and prototype pulse sequences.

The authors also would like to thank ARC foundation which allowed Dr. SGARD to get a fellowship for a year of research during which he was able to carry out this study.

Funding information

The authors state that this work has not received any funding.

Compliance with ethical standards

Guarantor

The scientific guarantor of this publication is Aurélie Kas, MD, PhD, Department of Nuclear Medicine, Pitié-Salpêtrière C. Foix Hospital, APHP, Paris, France. Phone: 33 1 42 17 62 80. Fax: 33 1 42 17 62 92. Email: aurelie.kas@gmail.com

Conflict of interest

The authors of this manuscript declare relationships with the following companies:

Maya Khalifé received a research grant from GE Healthcare.

Brice Fernandez and Gaspar Delso are GE Healthcare employees. Only non-GE employees had control of inclusion of data and information that might present a conflict of interest for authors who are employees of GE Healthcare. No other potential conflict of interest relevant to this article was reported.

Aurélie Kas received honoria for lectures from GE Healthcare and Piramal.

Marie-Odile Habert received honoraria for lectures from Lilly.

Statistics and biometry

One of the authors has significant statistical expertise.

No complex statistical methods were necessary for this paper.

Informed consent

Written informed consent was obtained from all subjects (patients) in this study.

Ethical approval

Data of this study were extracted from the PET/MR examinations database of the Pitié-Salpêtrière Hospital, Paris, France, which was approved by the French authority for the protection of privacy and personal data in clinical research (CNIL, approval no. 2111722). All procedures performed in this study were in accordance with the ethical standards of the institutional research committee and with the 1964 Helsinki Declaration and its later amendments.

Methodology

• Retrospective

• Experimental

• Performed at one institution

Supplementary material

330_2019_6514_MOESM1_ESM.docx (120 kb)
ESM 1 (DOCX 119 kb)

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Copyright information

© European Society of Radiology 2019

Authors and Affiliations

  • Brian Sgard
    • 1
    • 2
    Email author
  • Maya Khalifé
    • 3
  • Arthur Bouchut
    • 3
  • Brice Fernandez
    • 4
  • Marine Soret
    • 1
    • 2
  • Alain Giron
    • 2
  • Clara Zaslavsky
    • 5
  • Gaspar Delso
    • 6
  • Marie-Odile Habert
    • 1
    • 2
  • Aurélie Kas
    • 1
    • 2
  1. 1.Department of Nuclear MedicineGroupe Hospitalier Pitié-Salpêtrière Charles FoixParisFrance
  2. 2.Laboratoire d’Imagerie Biomédicale (LIB)Sorbonne Université, CNRS, INSERMParisFrance
  3. 3.Centre de NeuroImagerie de Recherche (CENIR)Institut du Cerveau et de la Moelle épinière (ICM)ParisFrance
  4. 4.Applications and WorkflowGE HealthcareOrsayFrance
  5. 5.Department of BiophysicsSorbonne UniversitéParisFrance
  6. 6.Applications and WorkflowGE HealthcareCambridgeUK

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