Evaluation of 511 keV photon attenuation by a novel 32-channel phased array prospectively designed for cardiovascular hybrid PET/MRI imaging

Farag, Adam; Thompson, R. Terry; Thiessen, Jonathan D.; Biernaski, Heather; Prato, Frank S.; Théberge, Jean

doi:10.1186/s41824-020-00076-w

Cited by 6 publications

(7 citation statements)

References 22 publications

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“…MRI, with its superior soft tissue resolution and depth of penetration in a non-ionizing form of radiation, is continually expanding its reach. To keep up with inroads in pre-and post-natal care [67,68], pediatric MRI [69], specialty coils for the brain and cardiac imaging [46], as well as inserts for hybrid PET/ MRI [70], there is a continuing need to foster technological developments in MR-sensitive contrast agents. Cellular imaging is enabled by magnetic nanoparticles.…”

Section: Discussionmentioning

confidence: 99%

Molecular Imaging with Genetically Programmed Nanoparticles

Goldhawk¹

2022

Radiopharmaceuticals - Current Research for Better Diagnosis and Therapy

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Nanoparticle research has greatly benefitted medical imaging platforms by generating new signals, enhancing detection sensitivity, and expanding both clinical and preclinical applications. For magnetic resonance imaging, the fabrication of superparamagnetic iron oxide nanoparticles has provided a means of detecting cells and has paved the way for magnetic particle imaging. As the field of molecular imaging grows and enables the tracking of cells and their molecular activities so does the possibility of tracking genetically programmed biomarkers. This chapter discusses the advantages and challenges of gene-based contrast, using the bacterial magnetosome model to highlight the requirements of in vivo iron biomineralization and reporter gene expression for magnetic resonance signal detection. New information about magnetosome protein interactions in non-magnetic mammalian cells is considered in the light of design and application(s) of a rudimentary magnetosome-like nanoparticle for molecular imaging. Central to this is the hypothesis that a magnetosome root structure is defined by essential magnetosome genes, whose expression positions the biomineral in a given membrane compartment, in any cell type. The use of synthetic biology for programming multi-component structures not only broadens the scope of reporter gene expression for molecular MRI but also facilitates the tracking of cell therapies.

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Section: Discussionmentioning

confidence: 99%

Molecular Imaging with Genetically Programmed Nanoparticles

Goldhawk¹

2022

Radiopharmaceuticals - Current Research for Better Diagnosis and Therapy

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“…The idea was to employ this information to enable the MR-NLM approach to discriminate between noise and genuine signals more effectively. The ultimate objective is to employ this concept within a deep learning framework [ 16 ] to enhance PET image quality (denoising). This could be achieved using either an unsupervised or supervised training scheme.…”

Section: Discussionmentioning

confidence: 99%

Non-local mean denoising using multiple PET reconstructions

Arabi

Zaidi

2020

Ann Nucl Med

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Objectives Non-local mean (NLM) filtering has been broadly used for denoising of natural and medical images. The NLM filter relies on the redundant information, in the form of repeated patterns/textures, in the target image to discriminate the underlying structures/signals from noise. In PET (or SPECT) imaging, the raw data could be reconstructed using different parameters and settings, leading to different representations of the target image, which contain highly similar structures/signals to the target image contaminated with different noise levels (or properties). In this light, multiple-reconstruction NLM filtering (MR-NLM) is proposed, which relies on the redundant information provided by the different reconstructions of the same PET data (referred to as auxiliary images) to conduct the denoising process. Methods Implementation of the MR-NLM approach involved the use of twelve auxiliary PET images (in addition to the target image) reconstructed using the same iterative reconstruction algorithm with different numbers of iterations and subsets. For each target voxel, the patches of voxels at the same location are extracted from the auxiliary PET images based on which the NLM denoising process is conducted. Through this, the exhaustive search scheme performed in the conventional NLM method to find similar patches of voxels is bypassed. The performance evaluation of the MR-NLM filter was carried out against the conventional NLM, Gaussian and bilateral post-reconstruction approaches using the experimental Jaszczak phantom and 25 whole-body PET/CT clinical studies. Results The signal-to-noise ratio (SNR) in the experimental Jaszczak phantom study improved from 25.1 when using Gaussian filtering to 27.9 and 28.8 when the conventional NLM and MR-NLM methods were applied (p value < 0.05), respectively. Conversely, the Gaussian filter led to quantification bias of 35.4%, while NLM and MR-NLM approaches resulted in a bias of 32.0% and 31.1% (p value < 0.05), respectively. The clinical studies further confirm the superior performance of the MR-NLM method, wherein the quantitative bias measured in malignant lesions (hot spots) decreased from − 12.3 ± 2.3% when using the Gaussian filter to − 3.5 ± 1.3% and − 2.2 ± 1.2% when using the NLM and MR-NLM approaches (p value < 0.05), respectively. Conclusion The MR-NLM approach exhibited promising performance in terms of noise suppression and signal preservation for PET images, thus translating into higher SNR compared to the conventional NLM approach. Despite the promising performance of the MR-NLM approach, the additional computational burden owing to the requirement of multiple PET reconstruction still needs to be addressed.

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“…The same procedure as described above was performed to derive the hardware AC map of the rigid/fixed posterior part of the cardiac array. However, the hardware profile was derived from a 3D-CT map [ 12 ]. The posterior profile was created by transforming the maps into binary values where each voxel containing posterior information was assigned 1, otherwise 0.…”

Section: Methodsmentioning

confidence: 99%

“…One aspect that affects the accuracy of PET quantification is the attenuation of photons absorbed by fixed or mobile hardware present during scans, such as radio frequency (RF) arrays, the patient table, and headphones. The adverse effects of such hardware on PET quantifications has been reported numerously in publications; for example, the patient table of the PET/MRI system causes up to 18.7% loss of PET true-counts [ 14 ], while RF resonators, for the same system, caused true-count losses varying between 3 and 14% [ 2 , 11 , 12 , 19 , 25 , 31 , 35 ].…”

Section: Introductionmentioning

confidence: 99%

“…To overcome such hardware attenuation, it is often required to prospectively redesign some hardware (i.e. rigidly fixed RF arrays) for simultaneous PET/MRI, aiming to reduce their photon attenuation [ 12 ]. However, other hardware, such as the patient table, would be challenging to redesign, and hence, techniques to correct their attenuation are still a topic of study.…”

Section: Introductionmentioning

confidence: 99%

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Improved PET/MRI accuracy by use of static transmission source in empirically derived hardware attenuation correction

et al. 2021

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Background Accurate quantification of radioactivity, measured by an integrated positron emission tomography (PET) and magnetic resonance imaging (MRI) system, is still a challenge. One aspect of such a challenge is to correct for the hardware attenuation, such as the patient table and radio frequency (RF) resonators. For PET/MRI systems, computed tomography (CT) is commonly used to produce hardware attenuation correction (AC) maps, by converting Hounsfield units (HU) to a linear attenuation coefficients (LAC) map at the PET energy level 511 keV, using a bilinear model. The model does not address beam hardening, nor higher density materials, which can lead to inaccurate corrections. Purpose In this study, we introduce a transmission-based (TX-based) AC technique with a static Germanium-68 (Ge-68) transmission source to generate hardware AC maps using the PET/MRI system itself, without the need for PET or medical CT scanners. The AC TX-based maps were generated for a homogeneous cylinder, made of acrylic as a validator. The technique thereafter was applied to the patient table and posterior part of an RF-phased array used in cardiovascular PET/MRI imaging. The proposed TX-based, and the CT-based, hardware maps were used in reconstructing PET images of one cardiac patient, and the results were analysed and compared. Results The LAC derived by the TX-based method for the acrylic cylinder is estimated to be 0.10851 ± 0.00380 cm−1 compared to the 0.10698 ± 0.00321 cm−1 theoretical value reported in the literature. The PET photon counts were reduced by 8.7 ± 1.1% with the patient table, at the region used in cardiac scans, while the CT-based map, used for correction, over-estimated counts by 4.3 ± 1.3%. Reconstructed in vivo images using TX-based AC hardware maps have shown 4.1 ± 0.9% mean difference compared to those reconstructed images using CT-based AC. Conclusions The LAC of the acrylic cylinder measurements using the TX-based technique was in agreement with those in the literature confirming the validity of the technique. The over-estimation of photon counts caused by the CT-based model used for the patient table was improved by the TX-based technique. Therefore, TX-based AC of hardware using the PET/MRI system itself is possible and can produce more accurate images when compared to the CT-based hardware AC in cardiac PET images.

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Evaluation of 511 keV photon attenuation by a novel 32-channel phased array prospectively designed for cardiovascular hybrid PET/MRI imaging

Cited by 6 publications

References 22 publications

Molecular Imaging with Genetically Programmed Nanoparticles

Molecular Imaging with Genetically Programmed Nanoparticles

Non-local mean denoising using multiple PET reconstructions

Improved PET/MRI accuracy by use of static transmission source in empirically derived hardware attenuation correction

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