Update on latest advances in time-of-flight PET

This paper provides an update on time-of-flight (TOF) PET with a focus on latest hardware developments leading to current commercial PET/CT instruments. We describe advances in scintillator development, new photosensors and associated electronics readout, and detector designs for utilization in complete systems. Next, we introduce the latest commercial PET/CT scanners based on the aforementioned technologies, and discuss the detector design choices made that are relevant to differences in the system performance. Finally, we end with a discussion of the latest performance benchmarks for improved timing in PET detectors, challenges in scaling this performance to a complete system, and the outlook towards achieving a sub-50 ps coincidence timing resolution (CTR) in a PET detector.     

Conceptual Design and Simulation Study of an ROI-Focused Panel-PET Scanner

Positron emission tomography (PET) is an important imaging modality for clincial use. Conventionally, the PET scanner is generally built to provide a roomy enough transverse field-of-view (FOV) for imaging most adults’ torsos. However, in many cases, the region-of-interest (ROI) for imaging is usually a small area inside the human body. Therefore, to fulfill a PET system which provides an FOV comparable in size to the target ROI seems appealing and more cost effective. Meanwhile, such a PET system has the potential for portable or bedside application with the reduced system size. In this work, we have investigated the feasibility of using dual-headed panel-detectors to build an ROI-focused PET scanner. A novel windowed list-mode ordered subset expectation maximization method was developed to perform the ROI image reconstruction. With this method, the ROI of the object can be reconstructed from the coincidences whose position determined by time-of-flight (TOF) measurements was inside the ROI. Monte Carlo simulation demonstrates the feasibility of detecting lesions not less than 1 cm in diameter, with a 300 ps full width at half maximum timing resolution. As a critical system performance, the impact of TOF information on image quality has been studied and the required TOF capability was assessed. With enhanced timing resolution, the distortions and artifacts were reduced effectively. The further improved TOF capability also shows a noticeable improvement of detection performance for low uptake lesions, as well as the recovery speed of lesion contrast, which is of practical significance in the lesion detection task.     

Simultaneous PET-MRI: a new approach for functional and morphological imaging

Noninvasive imaging at the molecular level is an emerging field in biomedical research. This paper introduces a new technology synergizing two leading imaging methodologies: positron emission tomography (PET) and magnetic resonance imaging (MRI). Although the value of PET lies in its high-sensitivity tracking of biomarkers in vivo, it lacks resolving morphology. MRI has lower sensitivity, but produces high soft-tissue contrast and provides spectroscopic information and functional MRI (fMRI). We have developed a three-dimensional animal PET scanner that is built into a 7-T MRI. Our evaluations show that both modalities preserve their functionality, even when operated isochronously. With this combined imaging system, we simultaneously acquired functional and morphological PET-MRI data from living mice. PET-MRI provides a powerful tool for studying biology and pathology in preclinical research and has great potential for clinical applications. Combining fMRI and spectroscopy with PET paves the way for a new perspective in molecular imaging.     

Role and Cost Effectiveness of PET/CT in Management of Patients with Cancer

PET/CT is a relatively new imaging technology, whose undoubted advantages are valuable in clinical oncology as well as in all fields of diagnosis, staging, and treatment. The hardware combination of anatomy and function has been the true evolution in imaging. PET using 18F-fluorodeoxyglucose (FDG) is increasingly used for the staging of solid malignancies, including colon, lung, etc., but anatomic information is limited. Integrated PET/CT enables optimal anatomic delineation of PET findings and identification of FDG-negative lesions on computed tomography (CT) images and might improve preoperative staging. However, controversy still exists in relation to the application of PET/CT in clinical practice, mainly because of its high cost. It is evident that apart from additional costs, potential savings also are associated with PET/CT as a result of avoiding additional imaging examinations or invasive procedures and by helping clinicians make the optimum treatment decisions. The authors review the literature on the role of PET/CT in management of various tumors and discuss the medicoeconomic usefulness.     

jClustering,an Open Framework for the Development of 4D Clustering Algorithms

We present jClustering, an open framework for the design of clustering algorithms in dynamic medical imaging. We developed this tool because of the difficulty involved in manually segmenting dynamic PET images and the lack of availability of source code for published segmentation algorithms. Providing an easily extensible open tool encourages publication of source code to facilitate the process of comparing algorithms and provide interested third parties with the opportunity to review code. The internal structure of the framework allows an external developer to implement new algorithms easily and quickly, focusing only on the particulars of the method being implemented and not on image data handling and preprocessing. This tool has been coded in Java and is presented as an ImageJ plugin in order to take advantage of all the functionalities offered by this imaging analysis platform. Both binary packages and source code have been published, the latter under a free software license (GNU General Public License) to allow modification if necessary.     

Computer-assisted sperm analysis (CASA): Capabilities and potential developments

Computer-assisted sperm analysis (CASA) systems have evolved over approximately 40 years, through advances in devices to capture the image from a microscope, huge increases in computational power concurrent with amazing reduction in size of computers, new computer languages, and updated/expanded software algorithms. Remarkably, basic concepts for identifying sperm and their motion patterns are little changed. Older and slower systems remain in use. Most major spermatology laboratories and semen processing facilities have a CASA system, but the extent of reliance thereon ranges widely. This review describes capabilities and limitations of present CASA technology used with boar, bull, and stallion sperm, followed by possible future developments. Each marketed system is different. Modern CASA systems can automatically view multiple fields in a shallow specimen chamber to capture strobe-like images of 500 to >2000 sperm, at 50 or 60 frames per second, in clear or complex extenders, and in <2 minutes, store information for ≥30 frames and provide summary data for each spermatozoon and the population. A few systems evaluate sperm morphology concurrent with motion. CASA cannot accurately predict ‘fertility’ that will be obtained with a semen sample or subject. However, when carefully validated, current CASA systems provide information important for quality assurance of semen planned for marketing, and for the understanding of the diversity of sperm responses to changes in the microenvironment in research. The four take-home messages from this review are: (1) animal species, extender or medium, specimen chamber, intensity of illumination, imaging hardware and software, instrument settings, technician, etc., all affect accuracy and precision of output values; (2) semen production facilities probably do not need a substantially different CASA system whereas biology laboratories would benefit from systems capable of imaging and tracking sperm in deep chambers for a flexible period of time; (3) software should enable grouping of individual sperm based on one or more attributes so outputs reflect subpopulations or clusters of similar sperm with unique properties; means or medians for the total population are insufficient; and (4) a field-use, portable CASA system for measuring one motion and two or three morphology attributes of individual sperm is needed for field theriogenologists or andrologists working with human sperm outside urban centers; appropriate hardware to capture images and process data apparently are available.     

Using System Emulation to Model Next-Generation Shared Virtual Memory Clusters

Recently much effort has been spent on providing a shared address space abstraction on clusters of small-scale symmetric multiprocessors. However, advances in technology will soon make it possible to construct these clusters with larger-scale cc-NUMA nodes, connected with non-coherent networks that offer latencies and bandwidth comparable to interconnection networks used in hardware cache-coherent systems. The shared memory abstraction can be provided on these systems in software across nodes and hardware within nodes.Recent simulation results have demonstrated that certain features of modern system area networks can be used to greatly reduce shared virtual memory (SVM) overheads [5,19]. In this work we leverage these results and we use detailed system emulation to investigate building future software shared memory clusters. We use an existing, large-scale hardware cache-coherent system with 64 processors to emulate a complete future cluster. We port our existing infrastructure (communication layer and shared memory protocol) on this system and study the behavior of a set of real applications. We present results for both 32- and 64-processor system configurations.We find that: (i) System emulation is invaluable in quantifying potential benefits from changes in the technology of commodity components. More importantly, it reveals potential problems in future systems that are easily overlooked in simulation studies. Thus, system emulation should be used along with other modeling techniques (e.g., simulation, implementation) to investigate future trends. (ii) Our work shows that current SVM protocols can only partially take advantage of faster interconnects and wider nodes due to operating system and architectural implications. We quantify the related issues and identify the areas where more research is required for future SVM clusters.     

3D TOF-PET image reconstruction using total variation regularization

In this paper we introduce a semi-analytic algorithm for 3-dimensional image reconstruction for positron emission tomography (PET). The method consists of the back-projection of the acquired data into the most likely image voxel according to time-of-flight (TOF) information, followed by the filtering step in the image space using an iterative optimization algorithm with a total variation (TV) regularization. TV regularization in image space is more computationally efficient than usual iterative optimization methods for PET reconstruction with full system matrix that use TV regularization. The efficiency comes from the one-time TOF back-projection step that might also be described as a reformatting of the acquired data. An important aspect of our work concerns the evaluation of the filter operator of the linear transform mapping an original radioactive tracer distribution into the TOF back-projected image. We obtain concise, closed-form analytical formula for the filter operator. The proposed method is validated with the Monte Carlo simulations of the NEMA IEC phantom using a one-layer, 50 cm-long cylindrical device called Jagiellonian PET scanner. The results show a better image quality compared with the reference TOF maximum likelihood expectation maximization algorithm.     

Brain imaging tools in neurosciences

In this chapter brain imaging tools in neurosciences are presented. These include a brief overview on single-photon emission tomography (SPET) and a detailed focus on positron emission tomography (PET) and functional magnetic resonance imaging (fMRI). In addition, a critical discussion on the advantages and disadvantages of the three diagnostic systems is added.Furthermore, this article describes the image analysis tools from visual analysis over region-of-interest technique up to statistical parametric mapping, co-registration methods, and network analysis. It also compares the newly developed combined PET/CT scanner approach with established image fusion software approaches.There is rapid change: Better scanner qualities, new software packages and scanner concepts are on the road paved for an amply bright future in neurosciences.     

Real-time multichannel imaging framework for endoscopy, catheters, and fixed geometry intraoperative systems

To address the need for a clinically applicable intravital optical imaging system, we developed a new hardware and software framework. We demonstrate its utility by applying it to an endoscope-based white light and fluorescent imaging system. The capabilities include acquisition and visualization algorithms that perform registration, segmentation, and histogram-based autoexposure of two imaging channels (full-spectrum white light and near-infrared fluorescence), all in real time. Data are processed and saved as 12-bit files, matching the standards of clinical imaging. Dynamic range is further improved by the evaluation of flux as a quantitative parameter. The above features are demonstrated in a series of in vitro experiments, and the in vivo application is shown with the visualization of fluorescent-labeled vasculature of a mouse peritoneum. The approach may be applied to diverse systems, including handheld devices, fixed geometry intraoperative devices, catheter-based imaging, and multimodal systems.     

TOPASE-MED : comment repenser l’imagerie TEP grâce aux détecteurs semiconducteurs

This paper presents the main outcomes of the TOPASE-MED project, a feasibility study of a semiconductor-based PET imaging system, using CdTe as detection material. This project has followed three main goals: dimensioning a CdTe-based imager by simulation, developing technological bricks needed to build such a system and demonstrating experimentally the potential of the technology with a small scale mock-up.     

Maximizing content across scales: Moving multimodal microscopy and mesoscopy toward molecular imaging

Molecular imaging aims to depict the molecules in living patients. However, because this aim is still far beyond reach, patchworks of different solutions need to be used to tackle this overarching goal. From the vast toolbox of imaging techniques, we focus on those recent advances in optical microscopy that image molecules and cells at the submicron to centimeter scale. Mesoscopic imaging covers the “imaging gap” between techniques such as confocal microscopy and magnetic resonance imagingthat image entire live samples but with limited resolution. Microscopy focuses on the cellular level; mesoscopy visualizes the organization of molecules and cells into tissues and organs. The correlation between these techniques allows us to combine disciplines ranging from whole body imaging to basic research of model systems. We review current developments focused on improving microscopic and mesoscopic imaging technologies and on hardware and software that push the current sensitivity and resolution boundaries.     

TEMP/TDM et TEP/TDM en cardiologie : quel avenir ?

Over the recent years, clinical cardiology has witnessed a rapid evolution of multi-slice computed tomography (CT), starting with 4-slice CT developing into the current state of the heart 64-slice CT technology. This technology permits non-invasive visualization of the coronaries with high precision. CT coronary angiography will likely play an important role in the diagnosis of coronary artery disease. Because not all coronary stenoses detected by CT angiography are flow limiting, the stress myocardial perfusion imaging data complement the CT information. The integration of nuclear imaging (SPECT or PET) and CT data provides a potential opportunity to delineate the anatomic extent and the physiologic severity of coronary artery disease. The objective of this article is to provide a critical view of the relative strengths and weaknesses of myocardial perfusion imaging and CT coronary angiography, which we hope will help elucidate the potential role of these modalities in the diagnosis and management algorithms of patients with known or suspected coronary artery disease.     

TEP/IRM hybride en neuro-imagerie

The hybrid Positron Emission Tomography/Magnetic Resonance Imaging (PET/MRI) is a newly available imaging modality combining the molecular and metabolic PET information with the morphological and functional data provided by MRI. Integrated PET/MRI tomographs were conceived in analogy to the current PET/Computed Tomography (PET/CT) technology, with specific properties linked to the intrinsic differences of MRI and CT imaging. In the field of neuro-imaging, in particular, MRI provides a larger panel of information, as compared with CT, and is already systematically fused and used as a support for PET images for diagnostic and research purposes. We summarize here our current experience with the first integrated PET/MRI tomograph installed in Switzerland, concerning specifically three clinical applications: brain tumors characterization, the diagnosis of neurodegenerative dementias and the presurgical evaluation of pharmaco-resistant epilepsy. With this sequential tomograph, we could combine the full range of diagnostic MR sequences (including diffusion tensor imaging, tractography, spectroscopy, functional MR) with PET imaging of brain glucose metabolism (by ¹⁸F-Fluorodeoxyglucose–FDG) and of amino acid transport (by ¹⁸F-Fluoroethyltyrosine–FET). We also summarize the main results obtained in neuro-imaging by the different groups working with these new hybrid tomographs. These data show that PET/MRI, acquired in a single imaging session, may represent the modality of choice for neuro-imaging.     

Small animal PET imaging

Positron emission tomography (PET) is well established as an important research and clinical molecular imaging modality. Although the size differences between humans and rodents create formidable challenges for the application of PET imaging in small animals, advances in technology over the past several years have enabled the translation of this imaging modality to preclinical applications. In this article we discuss the basic principles of PET instrumentation and radiopharmaceuticals, and examine the key factors responsible for the qualitative and quantitative imaging capabilities of small animal PET systems. We describe the criteria that PET imaging agents must meet, and provide examples of small animal PET imaging to give the reader a broad perspective on the capabilities and limitations of this evolving technology. A crucial driver for future advances in PET imaging is the availability of molecular imaging probes labeled with positron-emitting radionuclides. The strong translational science potential of small animal and human PET holds great promise to dramatically advance our understanding of human disease. The assessment of molecular and functional processes using imaging agents as either direct or surrogate biomarkers will ultimately enable the characterization of disease expression in individual patients and thus facilitate tailored treatment plans that can be monitored for their effectiveness in each subject.     

Machine learning in quantitative PET: A review of attenuation correction and low-count image reconstruction methods

The rapid expansion of machine learning is offering a new wave of opportunities for nuclear medicine. This paper reviews applications of machine learning for the study of attenuation correction (AC) and low-count image reconstruction in quantitative positron emission tomography (PET). Specifically, we present the developments of machine learning methodology, ranging from random forest and dictionary learning to the latest convolutional neural network-based architectures. For application in PET attenuation correction, two general strategies are reviewed: 1) generating synthetic CT from MR or non-AC PET for the purposes of PET AC, and 2) direct conversion from non-AC PET to AC PET. For low-count PET reconstruction, recent deep learning-based studies and the potential advantages over conventional machine learning-based methods are presented and discussed. In each application, the proposed methods, study designs and performance of published studies are listed and compared with a brief discussion. Finally, the overall contributions and remaining challenges are summarized.     

Brain PET imaging optimization with time of flight and point spread function modelling

PurposeTo assess the influence of reconstruction algorithms and parameters on the PET image quality of brain phantoms in order to optimize reconstruction for clinical PET brain studies in a new generation PET/CT.MethodsThe 3D Hoffman phantom that simulates ¹⁸F-fluorodeoxyglucose (FDG) distribution was imaged in a Siemens Biograph mCT TrueV PET/CT with Time of Flight (TOF) and Point Spread Function (PSF) modelling. Contrast-to-Noise Ratio (CNR), contrast and noise were studied for different reconstruction models: OSEM, OSEM + TOF, OSEM + PSF and OSEM + PSF + TOF.The 2D multi-compartment Hoffman phantom was filled to simulate 4 different tracers' spatial distribution: FDG, ¹¹C-flumazenil (FMZ), ¹¹C-Methionine (MET) and 6-¹⁸F-fluoro-l-dopa (FDOPA). The best algorithm for each tracer was selected by visual inspection. The maximization of CNR determined the optimal parameters for each reconstruction.ResultsIn the 3D Hoffman phantom, both noise and contrast increased with increasing number of iterations and decreased with increasing FWHM. OSEM + PSF + TOF reconstruction was generally superior to other reconstruction models. Visual analysis of the 2D Hoffman brain phantom suggested that OSEM + PSF + TOF is the optimum algorithm for tracers with focal uptake, such as MET or FDOPA, and OSEM + TOF for tracers with diffuse cortical uptake (i.e. FDG and FMZ). Optimization of CNR demonstrated that OSEM + TOF reconstruction must be performed with 2 iterations and a filter FWHM of 3 mm, and OSEM + PSF + TOF reconstruction with 4 iterations and 1 mm FWHM filter.ConclusionsOptimization of reconstruction algorithm and parameters has been performed to take particular advantage of the last generation PET scanner, recommending specific settings for different brain PET radiotracers.     

Accelerating Image Reconstruction in Dual-Head PET System by GPU and Symmetry Properties

Positron emission tomography (PET) is an important imaging modality in both clinical usage and research studies. We have developed a compact high-sensitivity PET system that consisted of two large-area panel PET detector heads, which produce more than 224 million lines of response and thus request dramatic computational demands. In this work, we employed a state-of-the-art graphics processing unit (GPU), NVIDIA Tesla C2070, to yield an efficient reconstruction process. Our approaches ingeniously integrate the distinguished features of the symmetry properties of the imaging system and GPU architectures, including block/warp/thread assignments and effective memory usage, to accelerate the computations for ordered subset expectation maximization (OSEM) image reconstruction. The OSEM reconstruction algorithms were implemented employing both CPU-based and GPU-based codes, and their computational performance was quantitatively analyzed and compared. The results showed that the GPU-accelerated scheme can drastically reduce the reconstruction time and thus can largely expand the applicability of the dual-head PET system.     

An Integrated Pipeline for de Novo Assembly of Microbial Genomes

Remarkable advances in DNA sequencing technology have created a need for de novo genome assembly methods tailored to work with the new sequencing data types. Many such methods have been published in recent years, but assembling raw sequence data to obtain a draft genome has remained a complex, multi-step process, involving several stages of sequence data cleaning, error correction, assembly, and quality control. Successful application of these steps usually requires intimate knowledge of a diverse set of algorithms and software. We present an assembly pipeline called A5 (Andrew And Aaron''s Awesome Assembly pipeline) that simplifies the entire genome assembly process by automating these stages, by integrating several previously published algorithms with new algorithms for quality control and automated assembly parameter selection. We demonstrate that A5 can produce assemblies of quality comparable to a leading assembly algorithm, SOAPdenovo, without any prior knowledge of the particular genome being assembled and without the extensive parameter tuning required by the other assembly algorithm. In particular, the assemblies produced by A5 exhibit 50% or more reduction in broken protein coding sequences relative to SOAPdenovo assemblies. The A5 pipeline can also assemble Illumina sequence data from libraries constructed by the Nextera (transposon-catalyzed) protocol, which have markedly different characteristics to mechanically sheared libraries. Finally, A5 has modest compute requirements, and can assemble a typical bacterial genome on current desktop or laptop computer hardware in under two hours, depending on depth of coverage.