SAFIR-I: Design and Performance of a High-Rate Preclinical PET Insert for MRI.

(1) Background: Small Animal Fast Insert for MRI detector I (SAFIR-I) is a preclinical Positron Emission Tomography (PET) insert for the Bruker BioSpec 70/30 Ultra Shield Refrigerated (USR) preclinical 7T Magnetic Resonance Imaging (MRI) system. It is designed explicitly for high-rate kinetic studies in mice and rats with injected activities reaching 500MBq, enabling truly simultaneous quantitative PET and Magnetic Resonance (MR) imaging with time frames of a few seconds in length. (2) Methods: SAFIR-I has an axial field of view of 54.2mm and an inner diameter of 114mm. It employs Lutetium Yttrium OxyorthoSilicate (LYSO) crystals and Multi Pixel Photon Counter (MPPC) arrays. The Position-Energy-Timing Application Specific Integrated Circuit, version 6, Single Ended (PETA6SE) digitizes the MPPC signals and provides time stamps and energy information. (3) Results: SAFIR-I is MR-compatible. The system's Coincidence Resolving Time (CRT) and energy resolution are between separate-uncertainty 209.0(3)ps and separate-uncertainty 12.41(02) Full Width at Half Maximum (FWHM) at low activity and separate-uncertainty 326.89(12)ps and separate-uncertainty 20.630(011) FWHM at 550MBq, respectively. The peak sensitivity is ∼1.6. The excellent performance facilitated the successful execution of first in vivo rat studies beyond 300MBq. Based on features visible in the acquired images, we estimate the spatial resolution to be ∼2mm in the center of the Field Of View (FOV). (4) Conclusion: The SAFIR-I PET insert provides excellent performance, permitting simultaneous in vivo small animal PET/MR image acquisitions with time frames of a few seconds in length at activities of up to 500MBq.

NEMA characterization of the SAFIR prototype PET insert.

BACKGROUND: The SAFIR prototype insert is a preclinical Positron Emission Tomography (PET) scanner built to acquire dynamic images simultaneously with a 7 T Bruker Magnetic Resonance Imaging (MRI) scanner. The insert is designed to perform with an excellent coincidence resolving time of 194 ps Full Width Half Maximum (FWHM) and an energy resolution of 13.8% FWHM. These properties enable it to acquire precise quantitative images at activities as high as 500 MBq suitable for studying fast biological processes within short time frames (< 5 s). In this study, the performance of the SAFIR prototype insert is evaluated according to the NEMA NU 4-2008 standard while the insert is inside the MRI without acquiring MRI data. RESULTS: Applying an energy window of 391-601 keV and a coincidence time window of 500 ps the following results are achieved. The average spatial resolution at 5 mm radial offset is 2.6 mm FWHM when using the Filtered Backprojection 3D Reprojection (FBP3DRP) reconstruction method, improving to 1.2 mm when using the Maximum Likelihood Expectation Maximization (MLEM) method. The peak sensitivity at the center of the scanner is 1.06%. The Noise Equivalent count Rate (NECR) is 799 kcps at the highest measured activity of 537 MBq for the mouse phantom and 121 kcps at the highest measured activity of 624 MBq for the rat phantom. The NECR peak is not yet reached for any of the measurements. The scatter fractions are 10.9% and 17.8% for the mouse and rat phantoms, respectively. The uniform region of the image quality phantom has a 3.0% STD, with a 4.6% deviation from the expected number of counts per voxel. The spill-over ratios for the water and air chambers are 0.18 and 0.17, respectively. CONCLUSIONS: The results satisfy all the requirements initially considered for the insert, proving that the SAFIR prototype insert can obtain dynamic images of small rodents at high activities ([Formula: see text] 500 MBq) with a high sensitivity and an excellent count-rate performance.

Implementation of cylindrical PET scanners with block detector geometry in STIR.

BACKGROUND: Software for Tomographic Image Reconstruction (STIR) is an open-source library for PET and SPECT image reconstruction, implementing iterative reconstruction as well as 2D- and 3D-filtered back projection. Quantitative reconstruction of PET data requires the knowledge of the scanner geometry. Typical scanners, clinical as well as pre-clinical ones, use a block-type geometry. Several rectangular blocks of crystals are arranged into regular polygons. Multiple of such polygons are arranged along the scanner axis. However, the geometrical representation of a scanner provided by STIR is a cylinder made of rings of individual crystals equally distributed in axial and transaxial directions. The data of realistic scanners are projected onto such virtual scanners prior to image reconstruction. This results in reduced quality of the reconstructed image. In this study, we implemented the above-described block geometry into the STIR library, permitting the image reconstruction without the interpolation step. In order to evaluate the difference in image quality, we performed Monte Carlo simulation studies of three different scanner designs: two scanners with multiple crystals per block and one with a single crystal per block. Simulated data were reconstructed using the standard STIR method and the newly implemented block geometry. RESULTS: Visual comparison between the images reconstructed by the two models for the block-type scanners shows that the new implementation enhances the image quality to the extent that the results before normalization correction are comparable with those after normalization correction. The simulation result of a uniform cylinder shows that the coefficient of variation decreases from 25.8% to 20.9% by using the new implementation in STIR. Spatial resolution is enhanced resulting in a lower partial loss of intensity in sources of small size, e.g., the spill-over ratio for spherical sources of 1.8 mm diameter is 0.19 in the block and 0.34 in the cylindrical model. CONCLUSIONS: Results indicate a significant improvement for the new model in comparison with the old one which mapped the polygonal geometry into a cylinder. The new implementation was tested and is available for use via the library of Swiss Federal Institute of Technology in Zurich (ETH).

Single STE-MR Acquisition in MR-Based Attenuation Correction of Brain PET Imaging Employing a Fully Automated and Reproducible Level-Set Segmentation Approach.

PURPOSE: The aim of this study is to introduce a fully automatic and reproducible short echo-time (STE) magnetic resonance imaging (MRI) segmentation approach for MR-based attenuation correction of positron emission tomography (PET) data in head region. PROCEDURES: Single STE-MR imaging was followed by generating attenuation correction maps (µ-maps) through exploiting an automated clustering-based level-set segmentation approach to classify head images into three regions of cortical bone, air, and soft tissue. Quantitative assessment was performed by comparing the STE-derived region classes with the corresponding regions extracted from X-ray computed tomography (CT) images. RESULTS: The proposed segmentation method returned accuracy and specificity values of over 90 % for cortical bone, air, and soft tissue regions. The MR- and CT-derived µ-maps were compared by quantitative histogram analysis. CONCLUSIONS: The results suggest that the proposed automated segmentation approach can reliably discriminate bony structures from the proximal air and soft tissue in single STE-MR images, which is suitable for generating MR-based µ-maps for attenuation correction of PET data.

Generation of a Four-Class Attenuation Map for MRI-Based Attenuation Correction of PET Data in the Head Area Using a Novel Combination of STE/Dixon-MRI and FCM Clustering.

PURPOSE: The aim of this study is to generate a four-class magnetic resonance imaging (MRI)-based attenuation map (µ-map) for attenuation correction of positron emission tomography (PET) data of the head area using a novel combination of short echo time (STE)/Dixon-MRI and a dedicated image segmentation method. PROCEDURES: MR images of the head area were acquired using STE and two-point Dixon sequences. µ-maps were derived from MRI images based on a fuzzy C-means (FCM) clustering method along with morphologic operations. Quantitative assessment was performed to evaluate generated MRI-based µ-maps compared to X-ray computed tomography (CT)-based µ-maps. RESULTS: The voxel-by-voxel comparison of MR-based and CT-based segmentation results yielded an average of more than 95 % for accuracy and specificity in the cortical bone, soft tissue, and air region. MRI-based µ-maps show a high correlation with those derived from CT scans (R (2) > 0.95). CONCLUSIONS: Results indicate that STE/Dixon-MRI data in combination with FCM-based segmentation yields precise MR-based µ-maps for PET attenuation correction in hybrid PET/MRI systems.