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Data Driven Surrogate Signal Extraction for Dynamic PET Using Selective PCA

Whitehead, Alexander; Su, Kuan-Hao; Emond, Elise; Biguri, Ander; Machado, Maria; Porter, Joanna; Garthwaite, Helen; ... Thielemans, Kris; + view all (2022) Data Driven Surrogate Signal Extraction for Dynamic PET Using Selective PCA. In: Proceedings of the IEEE Nuclear Science Symposium and Medical Imaging Conference (NSS/MIC) 2022. (pp. pp. 1-4). Institute of Electrical and Electronics Engineers (IEEE) Green open access

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Abstract

Respiratory motion correction is beneficial in PET. Methods of motion correction include gated reconstruction, where the acquisition is binned, based on a respiratory trace. To acquire these respiratory traces, an external device, like the Real Time Position Management System, or a data driven method, such as PCA, can be used. Data driven methods have the advantage that they are non-invasive, and can be performed post-acquisition. However, data driven methods have the disadvantage that they are adversely affected by the tracer kinetics of a dynamic acquisition. This work seeks to evaluate several adaptions of the PCA method, through which it can be used with dynamic data. The methods explored in this work include, using a moving window (similar to the KRG method of Schleyer et al. (PMB 2014)), extrapolation of the principal component from later time points to earlier time points, as well as a method to select and combine multiple respiratory components. The respiratory traces acquired, were evaluated on 21 patients, by calculating their correlation with a Real Time Position Management System surrogate signal. The results indicate that all methods produce better surrogate signals than when applying static PCA to dynamic data. Extrapolating a late principal component, produced more promising results than using a moving window, and selecting and combining components held benefits for all methods.

Type: Proceedings paper
Title: Data Driven Surrogate Signal Extraction for Dynamic PET Using Selective PCA
Event: IEEE Nuclear Science Symposium and Medical Imaging, NSS/MIC 2022
Location: Milano, Italy
Dates: 5th-12th November 2022
ISBN-13: 978-1-6654-8872-3
Open access status: An open access version is available from UCL Discovery
DOI: 10.1109/NSS/MIC44845.2022.10399196
Publisher version: https://doi.org/10.1109/NSS/MIC44845.2022.10399196
Language: English
Additional information: This version is the author accepted manuscript. For information on re-use, please refer to the publisher's terms and conditions.
Keywords: positron emission tomography, respiratory motion, data-driven gating
UCL classification: UCL
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences
UCL > Provost and Vice Provost Offices > UCL BEAMS
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Medical Sciences
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Medical Sciences > Div of Medicine
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Chemical Engineering
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Med Phys and Biomedical Eng
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Medical Sciences > Div of Medicine > Respiratory Medicine
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Medical Sciences > Div of Medicine > Department of Imaging
URI: https://discovery.ucl.ac.uk/id/eprint/10188983
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