Abstract
Background and purpose
In clinical applications of Positron Emission Tomography (PET)-based treatment verification
in ion beam therapy (PT-PET), detection and interpretation of inconsistencies between
Measured PET and Expected PET are mostly limited by Measured PET noise, due to low
count statistics, and by Expected PET bias, especially due to inaccurate washout modelling
in off-line implementations. In this work, a recently proposed 4D Maximum Likelihood
(ML) reconstruction algorithm which considers Measured PET and Expected PET as two
different motion phases of a 4D dataset is assessed on clinical 4D PET-CT datasets
acquired after carbon ion therapy.
Material and methods
The 4D ML reconstruction algorithm estimates: (1) Measured PET of enhanced image quality
with respect to the conventional Measured PET, thanks to the exploitation of Expected
PET; (2) the deformation field mapping the Expected PET onto the Measured PET as a
measure of the occurred displacements.
Results
Results demonstrate the desired sensitivity to inconsistencies due to breathing motion
and/or setup modification, robustness to noise in different count statistics scenarios,
but a limited sensitivity to Expected PET washout inaccuracy.
Conclusions
The 4D ML reconstruction algorithm supports clinical 4D PT-PET in ion beam therapy.
The limited sensitivity to washout inaccuracy can be detected and potentially overcome.
Keywords
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Article info
Publication history
Published online: May 03, 2017
Accepted:
April 16,
2017
Received in revised form:
March 17,
2017
Received:
August 26,
2016
Identification
Copyright
© 2017 Elsevier B.V. All rights reserved.
