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Journal of Nuclear Cardiology
Erschienen in: Journal of Nuclear Cardiology 2/2023

14.06.2022 | Theme Articles

Automated nonlinear registration of coronary PET to CT angiography using pseudo-CT generated from PET with generative adversarial networks

verfasst von: Ananya Singh, MS, Jacek Kwiecinski, MD, PhD, Sebastien Cadet, MS, Aditya Killekar, MS, Evangelos Tzolos, MD, Michelle C Williams, MBChB, PhD, Marc R. Dweck, MD, PhD, David E. Newby, MD, PhD, Damini Dey, PhD, Piotr J. Slomka, PhD

Erschienen in: Journal of Nuclear Cardiology | Ausgabe 2/2023

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Abstract

Background

Coronary 18F-sodium-fluoride (18F-NaF) positron emission tomography (PET) showed promise in imaging coronary artery disease activity. Currently image processing remains subjective due to the need for manual registration of PET and computed tomography (CT) angiography data. We aimed to develop a novel fully automated method to register coronary 18F-NaF PET to CT angiography using pseudo-CT generated by generative adversarial networks (GAN).

Methods

A total of 169 patients, 139 in the training and 30 in the testing sets were considered for generation of pseudo-CT from non-attenuation corrected (NAC) PET using GAN. Non-rigid registration was used to register pseudo-CT to CT angiography and the resulting transformation was used to align PET with CT angiography. We compared translations, maximal standard uptake value (SUVmax) and target to background ratio (TBRmax) at the location of plaques, obtained after observer and automated alignment.

Results

Automatic end-to-end registration was performed for 30 patients with 88 coronary vessels and took 27.5 seconds per patient. Difference in displacement motion vectors between GAN-based and observer-based registration in the x-, y-, and z-directions was 0.8 ± 3.0, 0.7 ± 3.0, and 1.7 ± 3.9 mm, respectively. TBRmax had a coefficient of repeatability (CR) of 0.31, mean bias of 0.03 and narrow limits of agreement (LOA) (95% LOA: − 0.29 to 0.33). SUVmax had CR of 0.26, mean bias of 0 and narrow LOA (95% LOA: − 0.26 to 0.26).

Conclusion

Pseudo-CT generated by GAN are perfectly registered to PET can be used to facilitate quick and fully automated registration of PET and CT angiography.
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Metadaten
Titel
Automated nonlinear registration of coronary PET to CT angiography using pseudo-CT generated from PET with generative adversarial networks
verfasst von
Ananya Singh, MS
Jacek Kwiecinski, MD, PhD
Sebastien Cadet, MS
Aditya Killekar, MS
Evangelos Tzolos, MD
Michelle C Williams, MBChB, PhD
Marc R. Dweck, MD, PhD
David E. Newby, MD, PhD
Damini Dey, PhD
Piotr J. Slomka, PhD
Publikationsdatum
14.06.2022
Verlag
Springer International Publishing
Erschienen in
Journal of Nuclear Cardiology / Ausgabe 2/2023
Print ISSN: 1071-3581
Elektronische ISSN: 1532-6551
DOI
https://doi.org/10.1007/s12350-022-03010-8

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