Improved PET/MRI attenuation correction in the pelvic region using a statistical decomposition method on T2-weighted images

Elin Wallstén,Anne Larsson,Camilla Thellenberg Karlsson,Joakim Jonsson,Tufve Nyholm,Jan Axelsson

doi:10.1186/s40658-020-00336-5

Elin Wallstén, Anne Larsson + Show 4 more

Open Access

https://doi.org/10.1186/s40658-020-00336-5

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Journal: EJNMMI physics	Publication Date: Nov 23, 2020
Citations: 4	License type: open-access

Affiliation: Umeå University

Abstract

BackgroundAttenuation correction of PET/MRI is a remaining problem for whole-body PET/MRI. The statistical decomposition algorithm (SDA) is a probabilistic atlas-based method that calculates synthetic CTs from T2-weighted MRI scans. In this study, we evaluated the application of SDA for attenuation correction of PET images in the pelvic region.Materials and methodTwelve patients were retrospectively selected from an ongoing prostate cancer research study. The patients had same-day scans of [11C]acetate PET/MRI and CT. The CT images were non-rigidly registered to the PET/MRI geometry, and PET images were reconstructed with attenuation correction employing CT, SDA-generated CT, and the built-in Dixon sequence-based method of the scanner. The PET images reconstructed using CT-based attenuation correction were used as ground truth.ResultsThe mean whole-image PET uptake error was reduced from − 5.4% for Dixon-PET to − 0.9% for SDA-PET. The prostate standardized uptake value (SUV) quantification error was significantly reduced from − 5.6% for Dixon-PET to − 2.3% for SDA-PET.ConclusionAttenuation correction with SDA improves quantification of PET/MR images in the pelvic region compared to the Dixon-based method.

Highlights

Attenuation correction of Positron emission tomography (PET)/Magnetic resonance imaging (MRI) is a remaining problem for wholebody PET/MRI
The prostate standardized uptake value (SUV) quantification error was significantly reduced from − 5.6% for Dixon-PET to − 2.3% for statistical decomposition algorithm (SDA)-PET
Attenuation correction with SDA improves quantification of PET/MR images in the pelvic region compared to the Dixon-based method

Summary

Introduction

Attenuation correction of PET/MRI is a remaining problem for wholebody PET/MRI. The statistical decomposition algorithm (SDA) is a probabilistic atlasbased method that calculates synthetic CTs from T2-weighted MRI scans. MR images are based on proton spin relaxation and contain no information about attenuation, which is caused by electron interactions This causes difficulties using MR images for calculation of attenuation maps and leads to quantification errors in PET images. The present model for attenuation correction (AC) of PET images of the body on the SIGNA PET/MRI (GE Healthcare, USA) is based on the 2-echo Dixon MRI sequence that produces images of water and fat separately. These images are used for segmentation into soft tissue, fat, lung and air, which are translated to attenuation coefficient values [2]. The major problem with this method is that bone of different densities is misclassified as fat, which leads to underestimated attenuation coefficients of bone and an underestimation of the PET tracer uptake

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