Tracing the path from health to disease:forwards and backwards

Positron Emission Tomography (PET) is currently underutilised and can provide even more valuable information. PET is not merely an imaging device, but a measurement device. It measures molecules and their concentration inside a living subject. And as by definition life is not a static process, PET measures how molecules travel inside our bodies and provides a direct way to measure the kinetics of biochemical reactions.There are more technological developments needed to enable dynamic imaging and kinetics in clinical practice for a range of radioactive molecules. Furthermore, quantification of biological processes using PET has several challenges related to imaging a living subject including the effects of ionising radiation. Can we minimise the radiation dose per scan which will then make it easier to justify scanning a person with multiple radioactive molecules?For example, imaging multiple molecules simultaneously will allow to evaluate pixel-by-pixel the potential performance of drugs and swiftly decide how to proceed with treatments. In addition, it can help measuring the potential crosstalk of diseases such as cancer and cardiovascular diseases, or of different organs such as brain and heart, or gut and brain axes.But more research is necessary to allow imaging two or more radioactive molecules simultaneously. Advancing PET technology can empower medicine by tracing several molecular pathways and interactions from human health to disease – forwards and backwards – and has a lot to offer for detecting and understanding disease processes and optimising precision medicine

Generalized 3D and 4D motion compensated whole-body PET image reconstruction employing nested em deconvolution

Whole-body dynamic and parametric PET imaging has recently gained increased interest as a clinically feasible truly quantitative imaging solution for enhanced tumor detectability and treatment response monitoring in oncology. However, in comparison to static scans, dynamic PET acquisitions are longer, especially when extended to large axial field-of-view whole-body imaging, increasing the probability of voluntary (bulk) body motion. In this study we propose a generalized and novel motion-compensated PET image reconstruction (MCIR) framework to recover resolution from realistic motion-contaminated static (3D), dynamic (4D) and parametric PET images even without the need for gated acquisitions. The proposed algorithm has been designed for both single-bed and whole-body static and dynamic PET scans. It has been implemented in fully 3D space on STIR open-source platform by utilizing the concept of optimization transfer to efficiently compensate for motion at each tomographic expectation-maximization (EM) update through a nested Richardson-Lucy EM iterative deconvolution algorithm. The performance of the method, referred as nested RL-MCIR reconstruction, was evaluated on realistic 4D simulated anthropomorphic digital XCAT phantom data acquired with a clinically feasible whole-body dynamic PET protocol and contaminated with measured non-rigid motion from MRI scans of real human volunteers at multiple dynamic frames. Furthermore, in order to assess the impact of our method in whole-body PET parametric imaging, the reconstructed motion-corrected dynamic PET images were fitted with a multi-bed Patlak graphical analysis method to produce metabolic uptake rate (Ki parameter in Patlak model) images of highly quantitative value. Our quantitative Contrast-to-Noise (CNR) and noise vs. bias trade-off analysis results suggest considerable resolution enhancement in both dynamic and parametric motion-degraded whole-body PET images after applying nested RL-MCIR method, without amplification of noise

FDG PET/CT versus Bone Marrow Biopsy for Diagnosis of Bone Marrow Involvement in Non-Hodgkin Lymphoma:A Systematic Review

The management of non-Hodgkin lymphoma (NHL) patients requires the identification of bone marrow involvement (BMI) using a bone marrow biopsy (BMB), as recommended by international guidelines. Multiple studies have shown that [F-18]FDG positron emission tomography, combined with computed tomography (PET/CT), may provide important information and may detect BMI, but there is still an ongoing debate as to whether it is sensitive enough for NHL patients in order to replace or be used as a complimentary method to BMB. The objective of this article is to systematically review published studies on the performance of [F-18]FDG PET/CT in detecting BMI compared to the BMB for NHL patients. A population, intervention, comparison, and outcome (PICO) search in PubMed and Scopus databases (until 1 November 2021) was performed. A total of 41 studies, comprising 6147 NHL patients, were found to be eligible and were included in the analysis conducted in this systematic review. The sensitivity and specificity for identifying BMI in NHL patients were 73% and 90% for [F-18]FDG PET/CT and 56% and 100% for BMB. For aggressive NHL, the sensitivity and specificity to assess the BMI for the [F-18]FDG PET/CT was 77% and 94%, while for the BMB it was 58% and 100%. However, sensitivity and specificity to assess the BMI for indolent NHL for the [F-18]FDG PET/CT was 59% and 85%, while for the BMB it was superior, and equal to 94% and 100%. With regard to NHL, a [F-18]FDG PET/CT scan can only replace BMB if it is found to be positive and if patients can be categorized as having advanced staged NHL with high certainty. [F-18]FDG PET/CT might recover tumors missed by BMB, and is recommended for use as a complimentary method, even in indolent histologic subtypes of NHL

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 (&lt; 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 (∼ 500 MBq) with a high sensitivity and an excellent count-rate performance.</p

Evaluation of STIR Library Adapted for PET Scanners with Non-Cylindrical Geometry

Software for Tomographic Image Reconstruction (STIR) is an open source C++ library used to reconstruct single photon emission tomography and positron emission tomography (PET) data. STIR has an experimental scanner geometry modelling feature to accurately model detector placement. In this study, we test and improve this new feature using several types of data: Monte Carlo simulations and measured phantom data acquired from a dedicated brain PET prototype scanner. The results show that the new geometry class applied to non-cylindrical PET scanners improved spatial resolution, uniformity, and image contrast. These are directly observed in the reconstructions of small features in the test quality phantom. Overall, we conclude that the revised "BlocksOnCylindrical" class will be a valuable addition to the next STIR software release with adjustments of existing features (Single Scatter Simulation, forward projection, attenuation corrections) to "BlocksOnCylindrical"

Image Reconstruction Analysis for Positron Emission Tomography with Heterostructured Scintillators

The concept of structure engineering has been proposed for exploring the next generation of radiation detectors with improved performance. A TOF-PET geometry with heterostructured scintillators with a pixel size of 3.0x3.1x15 mm3 was simulated using Monte Carlo. The heterostructures consisted of alternating layers of BGO as a dense material with high stopping power and plastic (EJ232) as a fast light emitter. The detector time resolution was calculated as a function of the deposited and shared energy in both materials on an event-by-event basis. While sensitivity was reduced to 32% for 100 &#x03BC;m thick plastic layers and 52% for 50 &#x03BC;m, the CTR distribution improved to 204&#x00B1;49 ps and 220&#x00B1;41 ps respectively, compared to 276 ps that we considered for bulk BGO. The complex distribution of timing resolutions was accounted for in the reconstruction. We divided the events into three groups based on their CTR and modeled them with different Gaussian TOF kernels. On a NEMA IQ phantom, the heterostructures had better contrast recovery in early iterations. On the other hand, BGO achieved a better contrast to noise ratio (CNR) after the 15th iteration due to the higher sensitivity. The developed simulation and reconstruction methods constitute new tools for evaluating different detector designs with complex time responses

Integration of advanced 3D SPECT modeling into the open-source STIR framework

Purpose: The Software for Tomographic Image Reconstruction (STIR,http://stir.sourceforge.net) package is an open source object-oriented library implemented in C++. Although its modular design is suitable for reconstructing data from several modalities, it currently only supports Positron Emission Tomography (PET) data. In this work, the authors present results for Single Photon Emission Computed Tomography (SPECT) imaging. / Methods: This was achieved by the complete integration of a 3D SPECT system matrix modeling library into STIR. / Results: The authors demonstrate the flexibility of the combined software by reconstructing simulated and acquired projections from three different scanners with different iterative algorithms of STIR. / Conclusions: The extension of the open source STIR project with advanced SPECT modeling will enable the research community to study the performance of several algorithms on SPECT data, and potentially implement new algorithms by expanding the existing framework

A 3D MR-acquisition scheme for nonrigid bulk motion correction in simultaneous PET-MR.

PURPOSE: Positron emission tomography (PET) is a highly sensitive medical imaging technique commonly used to detect and assess tumor lesions. Magnetic resonance imaging (MRI) provides high resolution anatomical images with different contrasts and a range of additional information important for cancer diagnosis. Recently, simultaneous PET-MR systems have been released with the promise to provide complementary information from both modalities in a single examination. Due to long scan times, subject nonrigid bulk motion, i.e., changes of the patient's position on the scanner table leading to nonrigid changes of the patient's anatomy, during data acquisition can negatively impair image quality and tracer uptake quantification. A 3D MR-acquisition scheme is proposed to detect and correct for nonrigid bulk motion in simultaneously acquired PET-MR data. METHODS: A respiratory navigated three dimensional (3D) MR-acquisition with Radial Phase Encoding (RPE) is used to obtain T1- and T2-weighted data with an isotropic resolution of 1.5 mm. Healthy volunteers are asked to move the abdomen two to three times during data acquisition resulting in overall 19 movements at arbitrary time points. The acquisition scheme is used to retrospectively reconstruct dynamic 3D MR images with different temporal resolutions. Nonrigid bulk motion is detected and corrected in this image data. A simultaneous PET acquisition is simulated and the effect of motion correction is assessed on image quality and standardized uptake values (SUV) for lesions with different diameters. RESULTS: Six respiratory gated 3D data sets with T1- and T2-weighted contrast have been obtained in healthy volunteers. All bulk motion shifts have successfully been detected and motion fields describing the transformation between the different motion states could be obtained with an accuracy of 1.71 ± 0.29 mm. The PET simulation showed errors of up to 67% in measured SUV due to bulk motion which could be reduced to less than 10% with the proposed motion compensation approach. CONCLUSIONS: A MR acquisition scheme which yields both high resolution 3D anatomical data and highly accurate nonrigid motion information without an increase in scan time is presented. The proposed method leads to a strong improvement in both MR and PET image quality and ensures an accurate assessment of tracer uptake

A multifractal approach to space-filling recovery for PET quantification.

Purpose: A new image-based methodology is developed for estimating the apparent space-filling properties of an object of interest in PET imaging without need for a robust segmentation step and used to recover accurate estimates of total lesion activity (TLA). Methods: A multifractal approach and the fractal dimension are proposed to recover the apparent space-filling index of a lesion (tumor volume, TV) embedded in nonzero background. A practical implementation is proposed, and the index is subsequently used with mean standardized uptake value (SUVmean) to correct TLA estimates obtained from approximate lesion contours. The methodology is illustrated on fractal and synthetic objects contaminated by partial volume effects (PVEs), validated on realistic 18F-fluorodeoxyglucose PET simulations and tested for its robustness using a clinical 18F-fluorothymidine PET test-retest dataset. Results: TLA estimates were stable for a range of resolutions typical in PET oncology (4-6 mm). By contrast, the space-filling index and intensity estimates were resolution dependent. TLA was generally recovered within 15% of ground truth on postfiltered PET images affected by PVEs. Volumes were recovered within 15% variability in the repeatability study. Results indicated that TLA is a more robust index than other traditional metrics such as SUVmean or TV measurements across imaging protocols. Conclusions: The fractal procedure reported here is proposed as a simple and effective computational alternative to existing methodologies which require the incorporation of image preprocessing steps (i.e., partial volume correction and automatic segmentation) prior to quantification