Abstract

Simultaneous PET-MR imaging has shown potential for the comprehensive assessment of myocardial health from a single examination. Furthermore, MR-derived respiratory motion information has been shown to improve PET image quality by incorporating this information into the PET image reconstruction. Separately, MR-based anatomically guided PET image reconstruction has been shown to perform effective denoising, but this has been so far demonstrated mainly in brain imaging. To date the combined benefits of motion compensation and anatomical guidance have not been demonstrated for myocardial PET-MR imaging. This work addresses this by proposing a single cardiac PET-MR image reconstruction framework which fully utilises MR-derived information to allow both motion compensation and anatomical guidance within the reconstruction. Methods: Fifteen patients underwent a 18F-FDG cardiac PET-MR scan with a previously introduced acquisition framework. The MR data processing and image reconstruction pipeline produces respiratory motion fields and a high-resolution respiratory motion-corrected MR image with good tissue contrast. This MR-derived information was then included in a respiratory motion-corrected, cardiac-gated, anatomically guided image reconstruction of the simultaneously acquired PET data. Reconstructions were evaluated by measuring myocardial contrast and noise and compared to images from several comparative intermediate methods using the components of the proposed framework separately. Results: Including respiratory motion correction, cardiac gating, and anatomical guidance significantly increased contrast. In particular, myocardium-to-blood pool contrast increased by 143% on average (p<0.0001) compared to conventional uncorrected, non-guided PET images. Furthermore, anatomical guidance significantly reduced image noise compared to non-guided image reconstruction by 16.1% (p<0.0001). Conclusion: The proposed framework for MR-derived motion compensation and anatomical guidance of cardiac PET data was shown to significantly improve image quality compared to alternative reconstruction methods. Each component of the reconstruction pipeline was shown to have a positive impact on the final image quality. These improvements have the potential to improve clinical interpretability and diagnosis based on cardiac PET-MR images.

Highlights

  • Simultaneous positron emission tomography (PET)-magnetic resonance(MR) imaging allows the comprehensive assessment of cardiovascular disease

  • With a correctly aligned -map, increasing the number of maximum likelihood expectation maximisation (MLEM) iterations from 63 to 200 was seen to increase myocardium standard deviation (SD) and contrast recovery coefficient (CRC) in all cases. These effects are due to the convergence of the MLEM algorithm; improved contrast represents convergence towards true regional means, while increased noise at convergence is a well-known characteristic of MLEM reconstructions

  • MR-based motion compensation and MR-guided reconstruction have been demonstrated to improve PET image quality. These developments are integrated into a single PET-MR framework that produces high quality, diagnostic coronary MR angiography (CMRA) images alongside improved 18F-FDG cardiac PET images

Read more

Summary

Introduction

Simultaneous positron emission tomography (PET)-magnetic resonance(MR) imaging allows the comprehensive assessment of cardiovascular disease. Accurate attenuation correction is fundamental to clinical interpretability and quantification of cardiac PET data; attenuation maps ( -maps) are typically acquired under breath-hold before the actual PET acquisition, resulting in a potential misalignment between the -map and the PET image position. This may lead to artefacts that appear as reduced myocardial uptake and could be mistaken for myocardial defects [4]. To improve the correspondence between attenuation and emission data, specialised MR acquisitions schemes have been proposed to enable free-breathing [5] or respiratory-resolved -maps [6]

Objectives
Methods
Results
Discussion
Conclusion
Full Text
Published version (Free)

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call