Significant improvements have made it possible to add the technology of time-of-flight (TOF) to improve PET, particularly for oncology applications. The goals of this work were to investigate the benefits of TOF in experimental phantoms and to determine how these benefits translate into improved performance for patient imaging. Methods: In this study we used a fully 3-dimensional scanner with the scintillator lutetium-yttrium oxyorthosilicate and a system timing resolution of ;600 ps. The data are acquired in list-mode and reconstructed with a maximum-likelihood expectation maximization algorithm; the system model includes the TOF kernel and corrections for attenuation, detector normalization, randoms, and scatter. The scatter correction is an extension of the model-based singlescatter simulation to include the time domain. Phantom measurements to study the benefit of TOF include 27-cm-and 35-cm-diameter distributions with spheres ranging in size from 10 to 37 mm. To assess the benefit of TOF PET for clinical imaging, patient studies are quantitatively analyzed. Results: The lesion phantom studies demonstrate the improved contrast of the smallest spheres with TOF compared with non-TOF and also confirm the faster convergence of contrast with TOF. These gains are evident from visual inspection of the images as well as a quantitative evaluation of contrast recovery of the spheres and noise in the background. The gains with TOF are higher for larger objects. These results correlate with patient studies in which lesions are seen more clearly and with higher uptake at comparable noise for TOF than with non-TOF. Conclusion: TOF leads to a better contrast-versus-noise trade-off than non-TOF but one that is difficult to quantify in terms of a simple sensitivity gain improvement: A single gain factor for TOF improvement does not include the increased rate of convergence with TOF nor does it consider that TOF may converge to a different contrast than non-TOF. The experimental phantom results agree with those of prior simulations and help explain the improved image quality with TOF for patient oncology studies. There has been considerable advancement of the technology and instrumentation in PET over the last 30 y since the first tomography ring systems were developed. Significant improvements have been made in detectors, hardware, and image processing that impact both image quality and accuracy of quantification. Some of the major achievements include (a) the development and incorporation of new scintillators and detector configurations for higher spatial resolution and sensitivity, (b) the evolution from 2-dimensional (2D) systems with septa to 3-dimensional (3D) systems with larger axial fields of view for improved sensitivity, (c) the transition from analytic filtered-backprojection reconstruction algorithms to fully 3D iterative techniques with data corrections included in the system model for improved image quality and quantification, and (d) the combination of a CT scanner with the PET instrument for both attenuation ...
The trend in the design of scanners for positron emission computed tomography has traditionally been to improve the transverse spatial resolution to several millimeters while maintaining relatively coarse axial resolution (1-2 cm). Several scanners are being built with fine sampling in the axial as well as transverse directions, leading to the possibility of the true volume imaging. The number of possible coincidence pairs in these scanners is quite large. The usual methods of image reconstruction cannot handle these data without making approximations. It is computationally most efficient to reduce the size of this large, sparsely populated array by back-projecting the coincidence data prior to reconstruction. While analytic reconstruction techniques exist for back-projected data, an iterative algorithm may be necessary for those cases where the point spread function is spatially variant. A modification of the maximum likelihood algorithm is proposed to reconstruct these back-projected data. The method, the iterative image space reconstruction algorithm (ISRA), is able to reconstruct data from a scanner with a spatially variant point spread function in less time than other proposed algorithms. Results are presented for single-slice data, simulated and actual, from the PENN-PET scanner.
We report on the development of the PennPET Explorer whole-body imager. Methods: The PennPET Explorer is a multiring system designed with a long axial field of view. The imager is scalable and comprises multiple 22.9-cm-long ring segments, each with 18 detector modules based on a commercial digital silicon photomultiplier. A prototype 3-segment imager has been completed and tested with an active 64-cm axial field of view. Results: The instrument design is described, and its physical performance measurements are presented. These include sensitivity of 55 kcps/MBq, spatial resolution of 4.0 mm, energy resolution of 12%, timing resolution of 256 ps, and a noise-equivalent count rate above 1,000 kcps beyond 30 kBq/mL. After an evaluation of lesion torso phantoms to characterize quantitative accuracy, human studies were performed on healthy volunteers. Conclusion: The physical performance measurements validated the system design and led to highquality human studies.
The PennPET Explorer, a prototype whole-body imager currently operating with a 64-cm axial field of view, can image the major body organs simultaneously with higher sensitivity than that of commercial devices. We report here the initial human imaging studies on the PennPET Explorer, with each study designed to test specific capabilities of the device. Methods: Healthy subjects were imaged with FDG on the PennPET Explorer. Subsequently, clinical subjects with disease were imaged with 18 F-FDG and 68 Ga-DOTATATE, and research subjects were imaged with experimental radiotracers. Results: We demonstrated the ability to scan for a shorter duration or, alternatively, with less activity, without a compromise in image quality. Delayed images, up to 10 half-lives with 18 F-FDG, revealed biologic insight and supported the ability to track biologic processes over time. In a clinical subject, the PennPET Explorer better delineated the extent of 18 F-FDG-avid disease. In a second clinical study with 68 Ga-DOTATATE, we demonstrated comparable diagnostic image quality between the PennPET scan and the clinical scan, but with one fifth the activity. Dynamic imaging studies captured relatively noise-free input functions for kinetic modeling approaches. Additional studies with experimental research radiotracers illustrated the benefits from the combination of large axial coverage and high sensitivity. Conclusion: These studies provided a proof of concept for many proposed applications for a PET scanner with a long axial field of view.
For modern Time-Of-Flight PET systems, in which the number of possible lines of response and TOF bins is much larger than the number of acquired events, the most appropriate reconstruction approaches are considered to be list-mode methods. However, their shortcomings are relatively high computational costs for reconstruction and for sensitivity matrix calculation. Efficient treatment of TOF data within the proposed DIRECT approach is obtained by 1) angular (azimuthal and co-polar) grouping of TOF events to a set of views as given by the angular sampling requirements for the TOF resolution, and 2) deposition (weighted-histogramming) of these grouped events, and correction data, into a set of “histo-images”, one histo-image per view. The histo-images have the same geometry (voxel grid, size and orientation) as the reconstructed image. The concept is similar to the approach involving binning of the TOF data into angularly sub-sampled histo-projections -projections expanded in the TOF directions. However, unlike binning into histo-projections, the deposition of TOF events directly into the image voxels eliminates the need for tracing and/or interpolation operations during the reconstruction. Together with the performance of reconstruction operations directly in image space, this leads to a very efficient implementation of TOF reconstruction algorithms. Furthermore, the resolution properties are not compromised either, since events are placed into the image elements of the desired size from the beginning. Concepts and efficiency of the proposed data partitioning scheme are demonstrated in this work by using the DIRECT approach in conjunction with the Row-Action Maximum-Likelihood (RAMLA) algorithm.
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