These joint practice guidelines, or procedure standards, were developed collaboratively by the European Association of Nuclear Medicine (EANM), the Society of Nuclear Medicine and Molecular Imaging (SNMMI), the European Association of Neurooncology (EANO), and the working group for Response Assessment in Neurooncology with PET (PET-RANO). Brain PET imaging is being increasingly used to supplement MRI in the clinical management of glioma. The aim of these standards/guidelines is to assist nuclear medicine practitioners in recommending, performing, interpreting and reporting the results of brain PET imaging in patients with glioma to achieve a high-quality imaging standard for PET using FDG and the radiolabelled amino acids MET, FET and FDOPA. This will help promote the appropriate use of PET imaging and contribute to evidence-based medicine that may improve the diagnostic impact of this technique in neurooncological practice. The present document replaces a former version of the guidelines published in 2006 (Vander Borght et al. Eur J Nucl Med Mol Imaging. 33:1374–80, 2006), and supplements a recent evidence-based recommendation by the PET-RANO working group and EANO on the clinical use of PET imaging in patients with glioma (Albert et al. Neuro Oncol. 18:1199–208, 2016). The information provided should be taken in the context of local conditions and regulations.
Closed circulatory systems (CCS) underlie the function of vertebrate organs, but in long bones their structure is unclear, although they constitute the exit route for bone marrow (BM) leukocytes. To understand neutrophil emigration from BM, we studied the vascular system of murine long bones. Here we show that hundreds of capillaries originate in BM, cross murine cortical bone perpendicularly along the shaft and connect to the periosteal circulation. Structures similar to these trans-cortical-vessels (TCVs) also exist in human limb bones. TCVs express arterial or venous markers and transport neutrophils. Furthermore, over 80% arterial and 59% venous blood passes through TCVs. Genetic and drug-mediated modulation of osteoclast count and activity leads to substantial changes in TCV numbers. In a murine model of chronic arthritic bone inflammation, new TCVs develop within weeks. Our data indicate that TCVs are a central component of the CCS in long bones and may represent an important route for immune cell export from the BM.
In routine whole-body PET/MR hybrid imaging, attenuation correction (AC) is usually performed by segmentation methods based on a Dixon MR sequence providing up to 4 different tissue classes. Because of the lack of bone information with the Dixon-based MR sequence, bone is currently considered as soft tissue. Thus, the aim of this study was to evaluate a novel model-based AC method that considers bone in whole-body PET/MR imaging. Methods The new method (“Model”) is based on a regular 4-compartment segmentation from a Dixon sequence (“Dixon”). Bone information is added using a model-based bone segmentation algorithm, which includes a set of prealigned MR image and bone mask pairs for each major body bone individually. Model was quantitatively evaluated on 20 patients who underwent whole-body PET/MR imaging. As a standard of reference, CT-based μ-maps were generated for each patient individually by nonrigid registration to the MR images based on PET/CT data. This step allowed for a quantitative comparison of all μ-maps based on a single PET emission raw dataset of the PET/MR system. Volumes of interest were drawn on normal tissue, soft-tissue lesions, and bone lesions; standardized uptake values were quantitatively compared. Results In soft-tissue regions with background uptake, the average bias of SUVs in background volumes of interest was 2.4% ± 2.5% and 2.7% ± 2.7% for Dixon and Model, respectively, compared with CT-based AC. For bony tissue, the −25.5% ± 7.9% underestimation observed with Dixon was reduced to −4.9% ± 6.7% with Model. In bone lesions, the average underestimation was −7.4% ± 5.3% and −2.9% ± 5.8% for Dixon and Model, respectively. For soft-tissue lesions, the biases were 5.1% ± 5.1% for Dixon and 5.2% ± 5.2% for Model. Conclusion The novel MR-based AC method for whole-body PET/MR imaging, combining Dixon-based soft-tissue segmentation and model-based bone estimation, improves PET quantification in whole-body hybrid PET/MR imaging, especially in bony tissue and nearby soft tissue.
As the field strength and, therefore, the operational frequency in MRI is increased, the wavelength approaches the size of the human head/body, resulting in wave effects, which cause signal decreases and dropouts. Several multichannel approaches have been proposed to try to tackle these problems, including RF shimming, where each element in an array is driven by its own amplifier and modulated with a certain (constant) amplitude and phase relative to the other elements, and Transmit SENSE, where spatially tailored RF pulses are used. In this article, a relatively inexpensive and easy to use imaging scheme for 7 Tesla imaging is proposed to mitigate signal voids due to B þ 1 field inhomogeneity. Two time-interleaved images are acquired using a different excitation mode for each. By forming virtual receive elements, both images are reconstructed together using GRAPPA to achieve a more homogeneous image, with only small SNR and SAR penalty in head and body imaging at 7 Tesla. Magn Reson Med 64:327-333, 2010. V C 2010 Wiley-Liss, Inc.Key words: 7 Tesla; ultra high field; body imaging; parallel transmissionSince the beginning of magnetic resonance imaging (MRI), there has been a steady drive to higher magnetic field strengths to increase signal-to-noise ratio (SNR) and to achieve new contrasts. As operational frequency is proportional to field strength, severe problems are often encountered with today's high-field systems regarding homogeneity of the transmission field (1,2). As the operational frequency is increased, the wavelength approaches the size of the human head/body, resulting in wave effects which cause signal decreases and dropouts.Several multichannel approaches have been proposed to try to tackle these problems. The most straightforward approach is static RF shimming (3,4). Each element in an array is driven by its own amplifier and modulated with a certain (constant) amplitude and phase relative to the other elements; the pulse profile for each element remains, however, identical. By choosing the amplitudes and phases properly, a more homogeneous transmit field or signal improvement in a certain region of interest can be achieved (5). For this approach, one needs to know the transmission profiles of each element; furthermore, many channels are needed to achieve a satisfactory result (4).A more complicated approach is Transmit SENSE (6,7), where spatially tailored RF pulses are used. Amplitude and phase vary during transmission and, thus, different pulse profiles are played out for each element. This approach yields excellent results, but presupposes exact knowledge of element transmission profiles as well as expensive and complicated hardware.In this article, we propose a new imaging scheme based on multimode excitation and GRAPPA (8) parallel imaging reconstruction to mitigate signal voids due to B þ 1 field inhomogeneity that is relatively inexpensive and easy to apply. We designate this acquisition scheme Time-Interleaved Acquisition of Modes (TIAMO). The basic premise is to excite two (or more) diff...
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
customersupport@researchsolutions.com
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.