PET/MR attenuation correction: where have we come from and where are we going?

Abstract

The advent of clinical multimodality imaging with the development of PET/CT scanners [1] has presented us with ample opportunities to harvest the benefits of combining functional and anatomical imaging. These benefits concern improved PET quantitative accuracy and overall patient management (improved diagnostic accuracy and therapy response assessment), but also increased patient throughput. It is indeed the last of these points that has substantially contributed to the rapid acceptance of PET/CT imaging in clinical practice eclipsing PET-only systems. Indeed, one of the major reasons behind the improved patient throughput achieved with PET/ CT has been the use of CT images for attenuation correction (AC) of the acquired PET emission datasets. In this context, CT images possess two desirable properties. Firstly, CT acquisitions are very fast, removing the need for long radionuclide-based transmission imaging that was traditionally used in PET (about 50 % of the overall acquisition times). Secondly, CT intensity values represent the attenuation properties of the tissues in the imaging field of view, albeit at X-ray photon energies. The necessary transformation of CT images into attenuation maps at 511 keV can be achieved by bilinear transformation [2]. Although such a transformation represents a certain approximation, CT-based AC of PET datasets using such attenuation maps has been shown to lead to the same level of quantitative accuracy and superior contrast in the reconstructed PET images compared to radionuclide-based transmission scanning [3].In the last couple of years clinical PET/MR devices have become a reality and the first results concerning the potential of this modality in terms of patient management are beginning to emerge. However, different issues persist with respect to the quantitative accuracy of this new modality, concerning in particular the question of PET AC based on the use of MRderived attenuation maps. A recent study published in this journal clearly reinforces these issues for neurological imaging [4]. In contrast to CT imaging, MRI does not provide direct information concerning tissue attenuation properties, and there is therefore no direct way to obtain the required information for PET AC purposes. Most of the approaches currently proposed in clinical PET/MR systems for PET AC are based on the combination of specific MR sequences and subsequent image segmentation.Amongst these, the approach implemented in the first generation of clinical systems is based on the two-point Dixon gradient echo sequence [5]. This sequence, which involves a few seconds of acquisition time, allows the separation of water and fat tissue by using the chemical shift of fat relative to that of water. This information facilitates in turn the segmentation of MR images into four to five different classes (lung, fat tissue, nonfat tissue, mixture of fat/nonfat tissue, air) [6]. It is important to highlight that once segmented, fixed 511 keV linear attenuation coefficients (LACs) are assigned to each of the considere...

Fast Patch-Based Pseudo-CT Synthesis from T1-Weighted MR Images for PET/MR Attenuation Correction in Brain Studies

“…Therefore, small deviations in the AC map will have a modest impact on scatter correction, especially as the scaling factor used to fit the estimated scatter distribution to the experimental data would remove any overall bias that might be introduced. Our study also neglected the effect of possible errors in modeling the attenuation of the MR coils (12). However, this effect can be controlled in clinical practice with appropriate scanner modeling, calibrations, and acquisition protocols.…”

“…They differ mainly in the type of semantic representation used to describe the image data, based on mathematic morphology (6), deformable models (7), MRI Dixon (8) or ultrashort-echo-time (TE) sequences (9,10), and multiatlas segmentation using label fusion (11). However, most of these methods showed limited accuracy when used to create AC maps (12). Hofmann et al combined local pattern recognition with image registration to generate pseudo-CT images (13).…”

An improved MR sequence for attenuation correction in PET/MR hybrid imaging

“…Instead, PET/MR uses stepwise attenuation correction from the tissue segmentation map. Several methods for MR-based attenuation correction have been reported thus far [4][5][6], and the combined use of signal intensities and anatomical information in MR imaging has been the primary method for constructing a tissue segmentation map [5,7].…”

“…In whole-body PET/MR imaging, three-dimensional (3D) T 1 -weighted A C C E P T E D M A N U S C R I P T ACCEPTED MANUSCRIPT 5 images (T1WIs) of the whole body are acquired for attenuation correction prior to PET imaging. On the basis of the signal intensities and anatomical information from the T1WIs, an attenuation map of the entire body is generated to partition the entire field of view (FOV) into three segments: soft tissue, lungs, and air.…”

Sensitivity estimation in time‐of‐flight list‐mode positron emission tomography

“…In the last few years, the new combined PET and magnetic resonance (MR) scanners [10][11][12] and their lack of a CT scan have made nonCT-based attenuation correction methods to be revisited. 13,14 MR-derived images give a lot of useful anatomical information, but they are not fully related to the attenuation parameters, and therefore, they cannot be used for attenuation correction in a straightforward way. For instance, MR Dixon fat-water images can be segmented into four tissue classes (air, lung, fat, and water) and then assigned predetermined attenuation coefficients to each class.…”