Challenges and current methods for attenuation correction in PET/MR

Abstract

Quantitative PET imaging requires an attenuation map to correct for attenuation. In stand-alone PET or PET/CT, the attenuation map is usually derived from a transmission scan or CT image, respectively. In PET/MR, these methods will most likely not be used. Therefore, attenuation correction has long been regarded as one of the major challenges in the development of PET/MR. In the past few years, much progress has been made in this field. In this review, the challenges faced in attenuation correction for PET/MR are discussed. Different methods have been proposed to overcome these challenges. An overview of the MR-based (template-based and voxel-based), transmission-based and emission-based methods and the results that have been obtained is provided. Although several methods show promising results, no single method fulfils all of the requirements for the ideal attenuation correction method for PET/MR. Therefore, more work is still necessary in this field. To allow implementation in routine clinical practice, extensive evaluation of the proposed methods is necessary to demonstrate robustness and automation.

Qualitative and Quantitative Performance of18F-FDG-PET/MRI versus18F-FDG-PET/CT in Patients with Head and Neck Cancer

“…Attenuation-correction solutions based on MR imaging data are one of the major challenges for PET/MR imaging. 22 Attenuation correction has an impact on both SUV max and SUV mean . According to our experience with PET/MR imaging, workflow and associated time constraints frequently pose a challenge in PET/MR imaging.…”

Vision 20/20: Magnetic resonance imaging‐guided attenuation correction in PET/MRI: Challenges, solutions, and opportunities

“…Using Monte Carlo simulation studies, Keereman et al 9,18 also concluded that at least six-tissue classes (air, lung, soft tissue, fat, spongious, and cortical bones) should be identified in MRAC maps to reduce quantification errors to less than 5%. Similarly, Akbarzadeh et al 54 confirmed that the accuracy of segmentation-based MRAC improves as the number of tissue classes increases.…”

Attenuation correction in emission tomography using the emission data—A review

“…This review is not meant as a replacement or mere update of previous works: such as those recent ones summarizing the state of the art in PET AC based on transmission measurements, 1,17 based on MRI, [18][19][20] for neurological applications, 21 for PET/MRI, [22][23][24] or even more general ones. 25,26 By contrast, we specifically focus and expand on the literature for estimation of attenuation maps from PET (and SPECT) emission data, which is only briefly touched in other reviews, if at all.…”