Positron Emission Tomography: Current Challenges and Opportunities for Technological Advances in Clinical and Preclinical Imaging Systems

Positron emission tomography (PET) imaging is based on detecting two time-coincident high-energy photons from the emission of a positronemitting radioisotope. The physics of the emission, and the detection of the coincident photons, give PET imaging unique capabilities for both very high sensitivity and accurate estimation of the in vivo concentration of the radiotracer. PET imaging has been widely adopted as an important clinical modality for oncological, cardiovascular, and neurological applications. PET imaging has also become an important tool in preclinical studies, particularly for investigating murine models of disease and other small-animal models. However, there are several challenges to using PET imaging systems. These include the fundamental trade-offs between resolution and noise, the quantitative accuracy of the measurements, and integration with X-ray computed tomography and magnetic resonance imaging. In this article, we review how researchers and industry are addressing these challenges.This work was supported in part by National Institutes of Health grants R01-CA042593, U01-CA148131, R01CA160253, R01CA169072, and R01CA164371; by Human Frontier Science Program grant RGP0004/2013; and by the Innovative Medicines Initiative under grant agreement 115337, which comprises financial contributions from the European Union’s Seventh Framework Program (FP7/2007–2013

Low-Dose Dual-Energy Computed Tomography for PET Attenuation Correction with Statistical Sinogram Restoration

Dual-energy (DE) X-ray computed tomography (CT) has been proposed as an useful tool in various applications. One promising application is DECT with low radiation doses used for attenuation correction in positron emission tomography (PET). In low-dose DECT, conventional methods for sinogram decomposition have been based on logarithmic transformations and ignored noise properties, leading to very noisy component sinogram estimates. In this paper, we propose two novel sinogram restoration methods that are statistically motivated; penalized weighted least square (PWLS) and penalized likelihood (PL), producing less noisy component sinogram estimates for low-dose DECT than the conventional approaches. The restored component sinograms can improve attenuation correction, thus allowing better image quality in PET. Experiments with a digital phantom indicate that the proposed methods produce less noisy sinograms, reconstructed images, and attenuation correction factors (ACF) than the conventional one, showing promise for CT-based attenuation correction in emission tomography.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/85933/1/Fessler230.pd

Statistical Sinogram Restoration in Dual-Energy CT for PET Attenuation Correction

Dual-energy (DE) X-ray computed tomography (CT) has been found useful in various applications. In medical imaging, one promising application is using low-dose DECT for attenuation correction in positron emission tomography (PET). Existing approaches to sinogram material decomposition ignore noise characteristics and are based on logarithmic transforms, producing noisy component sinogram estimates for low-dose DECT. In this paper, we propose two novel sinogram restoration methods based on statistical models: penalized weighted least square (PWLS) and penalized likelihood (PL), yielding less noisy component sinogram estimates for low-dose DECT than classical methods. The proposed methods consequently provide more precise attenuation correction of the PET emission images than do previous methods for sinogram material decomposition with DECT. We report simulations that compare the proposed techniques and existing approaches.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/85900/1/Fessler11.pd

Fast kVp-Switching Dual Energy CT for PET Attenuation Correction

X-ray CT images are used routinely for attenuation correction in PET/CT systems. However, conventional CT-based attenuation correction (CTAC) can be inaccurate in regions containing iodine contrast agent. Dual-energy (DE) CT has the potential to improve the accuracy of attenuation correction in PET, but conventional DECT can suffer from motion artifacts. Recent X-ray CT systems can collect DE sinograms by rapidly switching the X-ray tube voltage between two levels for alternate projection views, reducing motion artifacts. The goal of this work is to study statistical methods for image reconstruction from both fast kVp-switching DE scans and from conventional dual-rotate DE scans in the context of CTAC for PET.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/86003/1/Fessler244.pd

Cherenkov luminescence measurements with digital silicon photomultipliers: a feasibility study.

BackgroundA feasibility study was done to assess the capability of digital silicon photomultipliers to measure the Cherenkov luminescence emitted by a β source. Cherenkov luminescence imaging (CLI) is possible with a charge coupled device (CCD) based technology, but a stand-alone technique for quantitative activity measurements based on Cherenkov luminescence has not yet been developed. Silicon photomultipliers (SiPMs) are photon counting devices with a fast impulse response and can potentially be used to quantify β-emitting radiotracer distributions by CLI.MethodsIn this study, a Philips digital photon counting (PDPC) silicon photomultiplier detector was evaluated for measuring Cherenkov luminescence. The PDPC detector is a matrix of avalanche photodiodes, which were read one at a time in a dark count map (DCM) measurement mode (much like a CCD). This reduces the device active area but allows the information from a single avalanche photodiode to be preserved, which is not possible with analog SiPMs. An algorithm to reject the noisiest photodiodes and to correct the measured count rate for the dark current was developed.ResultsThe results show that, in DCM mode and at (10-13) °C, the PDPC has a dynamic response to different levels of Cherenkov luminescence emitted by a β source and transmitted through an opaque medium. This suggests the potential for this approach to provide quantitative activity measurements. Interestingly, the potential use of the PDPC in DCM mode for direct imaging of Cherenkov luminescence, as a opposed to a scalar measurement device, was also apparent.ConclusionsWe showed that a PDPC tile in DCM mode is able to detect and image a β source through its Cherenkov radiation emission. The detector's dynamic response to different levels of radiation suggests its potential quantitative capabilities, and the DCM mode allows imaging with a better spatial resolution than the conventional event-triggered mode. Finally, the same acquisition procedure and data processing could be employed also for other low light levels applications, such as bioluminescence

Quantitative Attenuation Correction for PET/CT Using Iterative Reconstruction of Low-Dose Dual-Energy CT

We present the results of using iterative reconstruction of dual-energy CT (DECT) to perform accurate CT-based attenuation correction (CTAC) for PET emission images. Current methods, such as bilinear scaling, introduce quantitative errors in the PET emission image for bone, metallic implants, and contrast agents. DECT has had limited use in the past for quantitative CT imaging due to increased patient dose and high noise levels in the decoupled CT basis-material images. Reconstruction methods that model the acquisition physics impose a significant computational burden due to the large image matrix size (typically 512 × 512). For CTAC, however, three factors make DECT feasible: (1) a smaller matrix is needed for the transmission image, which reduces the noise per pixel, (2) a smaller matrix significantly accelerates an iterative CT reconstruction algorithm, (3) the monoenergetic transmission image at 511 keV is the sum of the two decoupled basis-material images. Initial results using a 128 × 128 matrix size for a test object comprised of air, soft tissue, dense bone, and a mixture of tissue and bone demonstrate a significant reduction of bias using DECT (from 20% to ?0% for the tissue/bone mixture). FBP reconstructed images, however, have significant noise. Noise levels are reduced from ?8% to ?3% by the use of PWLS reconstruction.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/85861/1/Fessler203.pd

Performance assessment of a NaI(Tl) gamma counter for PET applications with methods for improved quantitative accuracy and greater standardization

BACKGROUND: Although NaI(Tl) gamma counters play an important role in many quantitative positron emission tomography (PET) protocols, their calibration for positron-emitting samples has not been standardized across imaging sites. In this study, we characterized the operational range of a gamma counter specifically for positron-emitting radionuclides, and we assessed the role of traceable (68)Ge/(68)Ga sources for standardizing system calibration. METHODS: A NaI(Tl) gamma counter was characterized with respect to count rate performance, adequacy of detector shielding, system stability, and sample volume effects using positron-emitting radionuclides (409- to 613-keV energy window). System efficiency was measured using (18)F and compared with corresponding data obtained using a long-lived (68)Ge/(68)Ga source that was implicitly traceable to a national standard. RESULTS: One percent count loss was measured at 450 × 10(3) counts per minute. Penetration of the detector shielding by 511-keV photons gave rise to a negligible background count rate. System stability tests showed a coefficient of variation of 0.13% over 100 days. For a sample volume of 4 mL, the efficiencies relative to those at 0.1 mL were 0.96, 0.94, 0.91, 0.78, and 0.72 for (11)C, (18)F, (125)I, (99m)Tc, and (51)Cr, respectively. The efficiency of a traceable (68)Ge/(68)Ga source was 30.1% ± 0.07% and was found to be in close agreement with the efficiency for (18)F after consideration of the different positron fractions. CONCLUSIONS: Long-lived (68)Ge/(68)Ga reference sources, implicitly traceable to a national metrology institute, can aid standardization of gamma counter calibration for (18)F. A characteristic feature of positron emitters meant that accurate calibration could be maintained over a wide range of sample volumes by using a narrow energy window centered on the 511-keV peak

Noise Characteristics of the FORE+OSEM(DB) Reconstruction Method for the MiCES PET Scanner

The FORE+OSEM(DB) image reconstruction method has been proposed for the fully-3D MiCES PET scanner under construction at the University of Washington. It is based on Fourier rebinning followed by 2D OSEM and an incorporated model of detector blurring (DB). As an extension, this paper presents the noise/resolution characteristics of this method. Multiple realizations were simulated to estimate the noise properties of the algorithm. The results are compared with OSEM followed by post reconstruction 3D Gaussian smoothing. The results show that the incorporation of detector blurring (OSEM(DB)) into the system matrix improves resolution compared to OSEM, while also inducing an increased variance at all radial locations. In addition, radially-varying noise characteristics are more apparent with OSEM(DB) than with OSEM.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/85836/1/Fessler204.pd

Semi-automated extraction of research topics and trends from NCI funding in radiological sciences from 2000-2020

Investigators, funders, and the public desire knowledge on topics and trends in publicly funded research but current efforts in manual categorization are limited in scale and understanding. We developed a semi-automated approach to extract and name research topics, and applied this to \$1.9B of NCI funding over 21 years in the radiological sciences to determine micro- and macro-scale research topics and funding trends. Our method relies on sequential clustering of existing biomedical-based word embeddings, naming using subject matter experts, and visualization to discover trends at a macroscopic scale above individual topics. We present results using 15 and 60 cluster topics, where we found that 2D projection of grant embeddings reveals two dominant axes: physics-biology and therapeutic-diagnostic. For our dataset, we found that funding for therapeutics- and physics-based research have outpaced diagnostics- and biology-based research, respectively. We hope these results may (1) give insight to funders on the appropriateness of their funding allocation, (2) assist investigators in contextualizing their work and explore neighboring research domains, and (3) allow the public to review where their tax dollars are being allocated.Comment: Presented at the American Society of Radiation Oncology annual meeting in 2021 ((doi: 10.1016/j.ijrobp.2021.07.263) and the Practical Big Data Workshop 202

Quantitative Imaging Network: Data Sharing and Competitive AlgorithmValidation Leveraging The Cancer Imaging Archive

AbstractThe Quantitative Imaging Network (QIN), supported by the National Cancer Institute, is designed to promote research and development of quantitative imaging methods and candidate biomarkers for the measurement of tumor response in clinical trial settings. An integral aspect of the QIN mission is to facilitate collaborative activities that seek to develop best practices for the analysis of cancer imaging data. The QIN working groups and teams are developing new algorithms for image analysis and novel biomarkers for the assessment of response to therapy. To validate these algorithms and biomarkers and translate theminto clinical practice, algorithms need to be compared and evaluated on large and diverse data sets. Analysis competitions, or “challenges,” are being conducted within the QIN as a means to accomplish this goal. The QIN has demonstrated, through its leveraging of The Cancer Imaging Archive (TCIA), that data sharing of clinical images across multiple sites is feasible and that it can enable and support these challenges. In addition to Digital Imaging and Communications in Medicine (DICOM) imaging data, many TCIA collections provide linked clinical, pathology, and “ground truth” data generated by readers that could be used for further challenges. The TCIA-QIN partnership is a successful model that provides resources for multisite sharing of clinical imaging data and the implementation of challenges to support algorithm and biomarker validation