Axial Field Of View Research Articles

Feasibility of using abbreviated scan protocols with population-based input functions for accurate kinetic modeling of [18F]-FDG datasets from a long axial FOV PET scanner

BackgroundAccurate kinetic modeling of 18F-fluorodeoxyglucose ([18F]-FDG) positron emission tomography (PET) data requires accurate knowledge of the available tracer concentration in the plasma during the scan time, known as the arterial input function (AIF). The gold standard method to derive the AIF requires collection of serial arterial blood samples, but the introduction of long axial field of view (LAFOV) PET systems enables the use of non-invasive image-derived input functions (IDIFs) from large blood pools such as the aorta without any need for bed movement. However, such protocols require a prolonged dynamic PET acquisition, which is impractical in a busy clinical setting. Population-based input functions (PBIFs) have previously shown potential in accurate Patlak analysis of [18F]-FDG datasets and can enable the use of shortened dynamic imaging protocols. Here, we exploit the high sensitivity and temporal resolution of a LAFOV PET system and explore the use of PBIF with abbreviated protocols in [18F]-FDG total body kinetic modeling.MethodsDynamic PET data were acquired in 24 oncological subjects for 65 min following the administration of [18F]-FDG. IDIFs were extracted from the descending thoracic aorta, and a PBIF was generated from 16 datasets. Five different scaled PBIFs (sPBIFs) were generated by scaling the PBIF with the AUC of IDIF curve tails using various portions of image data (35–65, 40–65, 45–65, 50–65, and 55–65 min post-injection). The sPBIFs were compared with the IDIFs using the AUCs and Patlak Ki estimates in tumor lesions and cerebral gray matter. Patlak plot start time (t*) was also varied to evaluate the performance of shorter acquisitions on the accuracy of Patlak Ki estimates. Patlak Ki estimates with IDIF and t* = 35 min were used as reference, and mean bias and precision (standard deviation of bias) were calculated to assess the relative performance of different sPBIFs. A comparison of parametric images generated using IDIF and sPBIFs was also performed.ResultsThere was no statistically significant difference between AUCs of the IDIF and sPBIFs (Wilcoxon test: P > 0.05). Excellent agreement was shown between Patlak Ki estimates obtained using sPBIF and IDIF. Using the sPBIF55–65 with the Patlak model, 20 min of PET data (i.e., 45 to 65 min post-injection) achieved < 15% precision error in Ki estimates in tumor lesions compared to the estimates with the IDIF. Parametric images reconstructed using the IDIF and sPBIFs with and without an abbreviated protocol were visually comparable. Using Patlak Ki generated with an IDIF and 30 min of PET data as reference, Patlak Ki images generated using sPBIF55–65 with 20 min of PET data (t* = 45 min) provided excellent image quality with structural similarity index measure > 0.99 and peak signal-to-noise ratio > 55 dB.ConclusionWe demonstrate the feasibility of performing accurate [18F]-FDG Patlak analysis using sPBIFs with only 20 min of PET data from a LAFOV PET scanner.

Positronium Lifetime Image Reconstruction for TOF PET.

Positron emission tomography is widely used in clinical and preclinical applications. Positronium lifetime carries information about the tissue microenvironment where positrons are emitted, but such information has not been captured because of two technical challenges. One challenge is the low sensitivity in detecting triple coincidence events. This problem has been mitigated by the recent developments of PET scanners with long (1-2 m) axial field of view. The other challenge is the low spatial resolution of the positronium lifetime images formed by existing methods that is determined by the time-of-flight (TOF) resolution (200-500 ps) of existing PET scanners. This paper solves the second challenge by developing a new image reconstruction method to generate high-resolution positronium lifetime images using existing TOF PET. Simulation studies demonstrate that the proposed method can reconstruct positronium lifetime images at much better spatial resolution than the limit set by the TOF resolution of the PET scanner. The proposed method opens up the possibility of performing positronium lifetime imaging using existing TOF PET scanners. The lifetime information can be used to understand the tissue microenvironment in vivo which could facilitate the study of disease mechanism and selection of proper treatments.

The potential of a medium-cost long axial FOV PET system for nuclear medicine departments.

Total body positron emission tomography (TB-PET) has recently been introduced in nuclear medicine departments. There is a large interest in these systems, but for many centers, the high acquisition cost makes it very difficult to justify their current operational budget. Here, we propose medium-cost long axial FOV scanners as an alternative. Several medium-cost long axial FOV designs are described with their advantages and drawbacks. We describe their potential for higher throughput, more cost-effective scanning, a larger group of indications, and novel research opportunities. The wider spread of TB-PET can also lead to the fast introduction of new tracers (at a low dose), new methodologies, and optimized workflows. A medium-cost TB-PET would be positioned between the current standard PET-CT and the full TB-PET systems in investment but recapitulate most advantages of full TB-PET. These systems could be more easily justified financially in a standard academic or large private nuclear medicine department and still have ample research options.

Design and optimization of a quad-directional stereo vision sensor with wide field of view based on single camera

Miniaturized multi-directional stereo vision sensor with a wide field of view (FOV) and high measurement precision is highly desirable for internal inspection in confined spaces. However, the current analysis of the design and optimization strategies for the sensor layout are not quite comprehensive. To make optimal use of the sensor and achieve high measurement accuracy, a thorough understanding of this strategy is required. In this work, we present a quad-directional stereo vision sensor based on a single camera and a dual mirror pyramid with no constraint on the placement of the devices. Geometrical analysis of the sensor is conducted by ray-tracing to examine effects of the parameters on the measurement precision, such as model accuracy, depth of field, and optical path difference. On this basis, we have investigated the method to optimize the structural parameters to maximize the overall axial and radial FOV and the utilization efficiency of the sensor. The design and optimization strategies are summarized to optimally set up the structural parameters and a miniaturized prototype of the sensor is developed and verified by both simulations and experiments.

Simulated Reduced-Count Whole-Body FDG PET: Evaluation in Children and Young Adults Imaged on a Digital PET Scanner.

BACKGROUND. Digital PET scanners with increased sensitivity may allow shorter scan acquisition times or reductions in administered radiopharmaceutical activities. OBJECTIVE. The purpose of this study was to evaluate in children and young adults the impact of shorter simulated acquisition times on the quality of whole-body FDG PET images obtained using a digital PET/CT system. METHODS. This retrospective study included 27 children and young adults (nine male and 18 female patients) who underwent clinically indicated whole-body FDG PET/CT examinations performed using a 25-cm axial FOV PET/CT system at 90 s per bed position (expressed hereafter as seconds per bed). Raw list-mode data were reprocessed to simulate acquisition times of 60, 55, 50, 45, 40, and 30 s/bed. Three radiologists independently reviewed reconstructed images and assigned Likert scores for lesion conspicuity, normal structure conspicuity, image quality, and image noise. A separate observer recorded the SUVmax, SUVmean, and SD of the SUV (SUVSD) for liver, thigh, and the most FDG-avid lesion. The SUVSD/SUVmean (the SUVSD divided by the SUVmean) was calculated as a surrogate of image noise. ANOVA, the Friedman test, and the Dunn test were used to compare qualitative measures (combining reader scores) and SUV measurements. RESULTS. The mean patient age was 10.8 ± 8.3 (SD) years, mean BMI was 18.7 ± 2.9, and mean administered FDG activity was 4.44 ± 0.37 MBq/kg (0.12 ± 0.01 mCi/kg). No qualitative measure showed a significant difference versus 90 s/bed for the simulated acquisition at 60 s/bed (all p > .05). Significant differences (all p < .05) versus 90 s/bed were observed for lesion conspicuity at at most 40 s/bed, conspicuity of normal structures and overall image quality at at most 45 s/bed, and image noise at at most 55 s/bed. SUVmean was not significantly different from 90 s/bed for any site for any reduced-count simulation (all p > .05). SUVSD/SUVmean and SUVmax showed gradual increases with decreasing acquisition times and were significantly different from 90 s/bed only for liver at 60 s/bed (for SUVmax: 1.00 ± 0.00 vs 1.05 ± 0.03, p = .02; for SUVSD/SUVmean: 0.09 ± 0.02 vs 0.11 ± 0.02, p = .04). CONCLUSION. Favorable findings for the simulated acquisition at 60 s/bed suggest that, in children and young adults who undergo imaging performed using a 25-cm FOV digital PET scanner, acquisition time or administered FDG activity may be decreased by approximately 33% from the clinical standard without significantly impacting image quality. CLINICAL IMPACT. A 25-cm axial FOV digital scanner may allow FDG PET/CT examinations to be performed with reduced radiation exposure or faster scan acquisition times.

Total-body PET: a new paradigm for molecular imaging.

Total body (TB) positron emission tomography (PET) instruments have dramatically changed the paradigm of PET clinical and research studies due to their very high sensitivity and capability to image dynamic radiopharmaceutical distributions in the major organs of the body simultaneously. In this manuscript, we review the design of these systems and discuss general challenges and trade-offs to maximize the performance gains of current TB-PET systems. We then describe new concepts and technology that may impact future TB-PET systems. The manuscript summarizes what has been learned from the initial sites with TB-PET and explores potential research and clinical applications of TB-PET. The current generation of TB-PET systems range in axial field-of-view (AFOV) from 1 to 2 m and serve to illustrate the benefits and opportunities of a longer AFOV for various applications in PET. In only a few years of use these new TB-PET systems have shown that they will play an important role in expanding the field of molecular imaging and benefiting clinical practice.

Motion correction and its impact on quantification in dynamic total-body 18F-fluorodeoxyglucose PET

BackgroundThe total-body positron emission tomography (PET) scanner provides an unprecedented opportunity to scan the whole body simultaneously, thanks to its long axial field of view and ultrahigh temporal resolution. To fully utilize this potential in clinical settings, a dynamic scan would be necessary to obtain the desired kinetic information from scan data. However, in a long dynamic acquisition, patient movement can degrade image quality and quantification accuracy.MethodsIn this work, we demonstrated a motion correction framework and its importance in dynamic total-body FDG PET imaging. Dynamic FDG scans from 12 subjects acquired on a uEXPLORER PET/CT were included. In these subjects, 7 are healthy subjects and 5 are those with tumors in the thorax and abdomen. All scans were contaminated by motion to some degree, and for each the list-mode data were reconstructed into 1-min frames. The dynamic frames were aligned to a reference position by sequentially registering each frame to its previous neighboring frame. We parametrized the motion fields in-between frames as diffeomorphism, which can map the shape change of the object smoothly and continuously in time and space. Diffeomorphic representations of motion fields were derived by registering neighboring frames using large deformation diffeomorphic metric matching. When all pairwise registrations were completed, the motion field at each frame was obtained by concatenating the successive motion fields and transforming that frame into the reference position. The proposed correction method was labeled SyN-seq. The method that was performed similarly, but aligned each frame to a designated middle frame, was labeled as SyN-mid. Instead of SyN, the method that performed the sequential affine registration was labeled as Aff-seq. The original uncorrected images were labeled as NMC. Qualitative and quantitative analyses were performed to compare the performance of the proposed method with that of other correction methods and uncorrected images.ResultsThe results indicated that visual improvement was achieved after correction of the SUV images for the motion present period, especially in the brain and abdomen. For subjects with tumors, the average improvement in tumor SUVmean was 5.35 ± 4.92% (P = 0.047), with a maximum improvement of 12.89%. An overall quality improvement in quantitative Ki images was also observed after correction; however, such improvement was less obvious in K1 images. Sampled time–activity curves in the cerebral and kidney cortex were less affected by the motion after applying the proposed correction. Mutual information and dice coefficient relative to the reference also demonstrated that SyN-seq improved the alignment between frames over non-corrected images (P = 0.003 and P = 0.011). Moreover, the proposed correction successfully reduced the inter-subject variability in Ki quantifications (11.8% lower in sampled organs). Subjective assessment by experienced radiologists demonstrated consistent results for both SUV images and Ki images.ConclusionTo conclude, motion correction is important for image quality in dynamic total-body PET imaging. We demonstrated a correction framework that can effectively reduce the effect of random body movements on dynamic images and their associated quantification. The proposed correction framework can potentially benefit applications that require total-body assessment, such as imaging the brain-gut axis and systemic diseases.

Fast and memory-efficient reconstruction of sparse Poisson data in listmode with non-smooth priors with application to time-of-flight PET

Objective. Complete time of flight (TOF) sinograms of state-of-the-art TOF PET scanners have a large memory footprint. Currently, they contain ∼4 · 109 data bins which amount to ∼17 GB in 32 bit floating point precision. Moreover, their size will continue to increase with advances in the achievable detector TOF resolution and increases in the axial field of view. Using iterative algorithms to reconstruct such enormous TOF sinograms becomes increasingly challenging due to the memory requirements and the computation time needed to evaluate the forward model for every data bin. This is especially true for more advanced optimization algorithms such as the stochastic primal-dual hybrid gradient (SPDHG) algorithm which allows for the use of non-smooth priors for regularization using subsets with guaranteed convergence. SPDHG requires the storage of additional sinograms in memory, which severely limits its application to data sets from state-of-the-art TOF PET systems using conventional computing hardware. Approach. Motivated by the generally sparse nature of the TOF sinograms, we propose and analyze a new listmode (LM) extension of the SPDHG algorithm for image reconstruction of sparse data following a Poisson distribution. The new algorithm is evaluated based on realistic 2D and 3D simulationsn, and a real data set acquired on a state-of-the-art TOF PET/CT system. The performance of the newly proposed LM SPDHG algorithm is compared against the conventional sinogram SPDHG and the listmode EM-TV algorithm. Main results. We show that the speed of convergence of the proposed LM-SPDHG is equivalent the original SPDHG operating on binned data (TOF sinograms). However, we find that for a TOF PET system with 400 ps TOF resolution and 25 cm axial FOV, the proposed LM-SPDHG reduces the required memory from approximately 56 to 0.7 GB for a short dynamic frame with 107 prompt coincidences and to 12.4 GB for a long static acquisition with 5·108 prompt coincidences. Significance. In contrast to SPDHG, the reduced memory requirements of LM-SPDHG enables a pure GPU implementation on state-of-the-art GPUs—avoiding memory transfers between host and GPU—which will substantially accelerate reconstruction times. This in turn will allow the application of LM-SPDHG in routine clinical practice where short reconstruction times are crucial.

Axial scalable add-on PET/MRI prototype based on four-layer DOI detectors integrated with a RF coil

We developed an add-on PET which was a PET insert based on 4-layered depth-of-interaction (DOI) detectors integrated with a birdcage RF-coil. The PET detectors were placed close to subjects to achieve high sensitivity. The DOI capability suppress degradation of spatial resolution at the edge of the field of view (FOV). Previously, we developed an first prototype which had a short axial FOV. In order to extend the axial FOV, we developed new scalable add-on PET prototype. The constructed RF-coil of the new prototype was combined with 24 DOI-PET detector units Each detector unit with two PET detectors was shielded with a carbon fiber shielding box. Each PET detector consisted of a 14 × 14 × 4-layer array of lutetium fine silicate crystals (1.9 mm × 1.9 mm × 4.0 mm), an 8 × 8 multi-pixel photon counter (MPPC, S12641PA-050) array and a readout circuit board with an ASIC. The RF coil was tuned for a 3T clinical MRI (MAGNETOM Verio, Siemens). We evaluated performance the scalable add-on PET prototype in simultaneous PET/MRI measurements. We obtained spatial resolutions of 2.0 mm at the center of the FOV and better than 3.3 mm in the whole FOV. The energy resolution of 12.4 % was obtained at 511 keV. In addition, we observed no degradation of PET performance caused by the MRI measurement. The signal-to-noise ratio (SNR) of the MRI image was 186.2 in simultaneous measurements with the PET. The maximum ΔB0 and maximum difference of the secondary magnetic field due to the eddy current effect were smaller than 0.2 ppm and ±1.0μT, respectively. It meant that the influence of the PET detectors on the static magnetic field and secondary magnetic field did not cause problems.

Quantitative evaluation of a deep learning-based framework to generate whole-body attenuation maps using LSO background radiation in long axial FOV PET scanners

PurposeAttenuation correction is a critically important step in data correction in positron emission tomography (PET) image formation. The current standard method involves conversion of Hounsfield units from a computed tomography (CT) image to construct attenuation maps (µ-maps) at 511 keV. In this work, the increased sensitivity of long axial field-of-view (LAFOV) PET scanners was exploited to develop and evaluate a deep learning (DL) and joint reconstruction-based method to generate µ-maps utilizing background radiation from lutetium-based (LSO) scintillators.MethodsData from 18 subjects were used to train convolutional neural networks to enhance initial µ-maps generated using joint activity and attenuation reconstruction algorithm (MLACF) with transmission data from LSO background radiation acquired before and after the administration of 18F-fluorodeoxyglucose (18F-FDG) (µ-mapMLACF-PRE and µ-mapMLACF-POST respectively). The deep learning-enhanced µ-maps (µ-mapDL-MLACF-PRE and µ-mapDL-MLACF-POST) were compared against MLACF-derived and CT-based maps (µ-mapCT). The performance of the method was also evaluated by assessing PET images reconstructed using each µ-map and computing volume-of-interest based standard uptake value measurements and percentage relative mean error (rME) and relative mean absolute error (rMAE) relative to CT-based method.ResultsNo statistically significant difference was observed in rME values for µ-mapDL-MLACF-PRE and µ-mapDL-MLACF-POST both in fat-based and water-based soft tissue as well as bones, suggesting that presence of the radiopharmaceutical activity in the body had negligible effects on the resulting µ-maps. The rMAE values µ-mapDL-MLACF-POST were reduced by a factor of 3.3 in average compared to the rMAE of µ-mapMLACF-POST. Similarly, the average rMAE values of PET images reconstructed using µ-mapDL-MLACF-POST (PETDL-MLACF-POST) were 2.6 times smaller than the average rMAE values of PET images reconstructed using µ-mapMLACF-POST. The mean absolute errors in SUV values of PETDL-MLACF-POST compared to PETCT were less than 5% in healthy organs, less than 7% in brain grey matter and 4.3% for all tumours combined.ConclusionWe describe a deep learning-based method to accurately generate µ-maps from PET emission data and LSO background radiation, enabling CT-free attenuation and scatter correction in LAFOV PET scanners.

An encoder-decoder network for direct image reconstruction on sinograms of a long axial field of view PET.

Deep learning is an emerging reconstruction method for positron emission tomography (PET), which can tackle complex PET corrections in an integrated procedure. This paper optimizes the direct PET reconstruction from sinogram on a long axial field of view (LAFOV) PET. This paper proposes a novel deep learning architecture to reduce the biases during direct reconstruction from sinograms to images. This architecture is based on an encoder-decoder network, where the perceptual loss is used with pre-trained convolutional layers. It is trained and tested on data of 80 patients acquired from recent Siemens Biograph Vision Quadra long axial FOV (LAFOV) PET/CT. The patients are randomly split into a training dataset of 60 patients, a validation dataset of 10 patients, and a test dataset of 10 patients. The 3D sinograms are converted into 2D sinogram slices and used as input to the network. In addition, the vendor reconstructed images are considered as ground truths. Finally, the proposed method is compared with DeepPET, a benchmark deep learning method for PET reconstruction. Compared with DeepPET, the proposed network significantly reduces the root-mean-squared error (NRMSE) from 0.63 to 0.6 (p &lt; 0.01) and increases the structural similarity index (SSIM) and peak signal-to-noise ratio (PSNR) from 0.93 to 0.95 (p &lt; 0.01) and from 82.02 to 82.36 (p &lt; 0.01), respectively. The reconstruction time is approximately 10s per patient, which is shortened by 23 times compared with the conventional method. The errors of mean standardized uptake values (SUVmean) for lesions between ground truth and the predicted result are reduced from 33.5 to 18.7% (p = 0.03). In addition, the error of max SUV is reduced from 32.7 to 21.8% (p = 0.02). The results demonstrate the feasibility of using deep learning to reconstruct images with acceptable image quality and short reconstruction time. It is shown that the proposed method can improve the quality of deep learning-based reconstructed images without additional CT images for attenuation and scattering corrections. This study demonstrated the feasibility of deep learning to rapidly reconstruct images without additional CT images for complex corrections from actual clinical measurements on LAFOV PET. Despite improving the current development, AI-based reconstruction does not work appropriately for untrained scenarios due to limited extrapolation capability and cannot completely replace conventional reconstruction currently.

Relating 18F-FDG image signal-to-noise ratio to time-of-flight noise-equivalent count rate in total-body PET using the uEXPLORER scanner

Objective. This work assessed the relationship between image signal-to-noise ratio (SNR) and total-body noise-equivalent count rate (NECR)—for both non-time-of-flight (TOF) NECR and TOF-NECR—in a long uniform water cylinder and 14 healthy human subjects using the uEXPLORER total-body PET/CT scanner. Approach. A TOF-NEC expression was modified for list-mode PET data, and both the non-TOF NECR and TOF-NECR were compared using datasets from a long uniform water cylinder and 14 human subjects scanned up to 12 h after radiotracer injection. Main results. The TOF-NECR for the uniform water cylinder was found to be linearly proportional to the TOF-reconstructed image SNR2 in the range of radioactivity concentrations studied, but not for non-TOF NECR as indicated by the reduced R 2 value. The results suggest that the use of TOF-NECR to estimate the count rate performance of TOF-enabled PET systems may be more appropriate for predicting the SNR of TOF-reconstructed images. Significance. Image quality in PET is commonly characterized by image SNR and, correspondingly, the NECR. While the use of NECR for predicting image quality in conventional PET systems is well-studied, the relationship between SNR and NECR has not been examined in detail in long axial field-of-view total-body PET systems, especially for human subjects. Furthermore, the current NEMA NU 2-2018 standard does not account for count rate performance gains due to TOF in the NECR evaluation. The relationship between image SNR and total-body NECR in long axial FOV PET was assessed for the first time using the uEXPLORER total-body PET/CT scanner.

Physical performance of adaptive axial FOV PET scanners with a sparse detector block rings or a checkerboard configuration

Objective. Using Monte-Carlo simulations, we evaluated the physical performance of a hypothetical state-of-the-art clinical PET scanner with adaptive axial field-of-view (AFOV) based on the validated GATE model of the Siemens Biograph VisionTM PET/CT scanner. Approach. Vision consists of 16 compact PET rings, each consisting of 152 mini-blocks of 5 × 5 Lutetium Oxyorthosilicate crystals (3.2 × 3.2 × 20 mm3). The Vision 25.6 cm AFOV was extended by adopting (i) a sparse mini-block ring (SBR) configuration of 49.6 cm AFOV, with all mini-block rings interleaved with 16 mm axial gaps, or (ii) a sparse mini-block checkerboard (SCB) configuration of 51.2 cm AFOV, with all mini-blocks interleaved with gaps of 16 mm (transaxial) × 16 mm (axial) width in checkerboard pattern. For sparse configurations, a ‘limited’ continuous bed motion (limited-CBM) acquisition was employed to extend AFOVs by 2.9 cm. Spatial resolution, sensitivity, image quality (IQ), NECR and scatter fraction were assessed per NEMA NU2-2012. Main Results. All IQ phantom spheres were distinguishable with all configurations. SBR and SCB percent contrast recovery (% CR) and background variability (% BV) were similar (p-value > 0.05). Compared to Vision, SBR and SCB %CRs were similar (p-values > 0.05). However, SBR and SCB %BVs were deteriorated by 30% and 26% respectively (p-values < 0.05). SBR, SCB and Vision exhibited system sensitivities of 16.6, 16.8, and 15.8 kcps MBq−1, NECRs of 311 kcps @35 kBq cc−1, 266 kcps @25.8 kBq cc−1, and 260 kcps @27.8 kBq cc−1, and scatter fractions of 31.2%, 32.4%, and 32.6%, respectively. SBR and SCB exhibited a smoother sensitivity reduction and noise enhancement rate from AFOV center to its edges. SBR and SCB attained comparable spatial resolution in all directions (p-value > 0.05), yet, up to 1.5 mm worse than Vision (p-values < 0.05). Significance. The proposed sparse configurations may offer a clinically adoptable solution for cost-effective adaptive AFOV PET with either highly-sensitive or long-AFOV acquisitions.

Advanced quantitative evaluation of PET systems using the ACR phantom and NiftyPET software.

PurposeA novel phantom‐imaging platform, a set of software tools, for automated and high‐precision imaging of the American College of Radiology (ACR) positron emission tomography (PET) phantom for PET/magnetic resonance (PET/MR) and PET/computed tomography (PET/CT) systems is proposed.MethodsThe key feature of this platform is the vector graphics design that facilitates the automated measurement of the knife‐edge response function and hence image resolution, using composite volume of interest templates in a 0.5 mm resolution grid applied to all inserts of the phantom. Furthermore, the proposed platform enables the generation of an accurate μ‐map for PET/MR systems with a robust alignment based on two‐stage image registration using specifically designed PET templates. The proposed platform is based on the open‐source NiftyPET software package used to generate multiple list‐mode data bootstrap realizations and image reconstructions to determine the precision of the two‐stage registration and any image‐derived statistics. For all the analyses, iterative image reconstruction was employed with and without modeled shift‐invariant point spread function and with varying iterations of the ordered subsets expectation maximization (OSEM) algorithm. The impact of the activity outside the field of view (FOV) was assessed using two acquisitions of 30 min each, with and without the activity outside the FOV.ResultsThe utility of the platform has been demonstrated by providing a standard and an advanced phantom analysis including the estimation of spatial resolution using all cylindrical inserts. In the imaging planes close to the edge of the axial FOV, we observed deterioration in the quantitative accuracy, reduced resolution (FWHM increased by 1–2 mm), reduced contrast, and background uniformity due to the activity outside the FOV. Although it slows convergence, the PSF reconstruction had a positive impact on resolution and contrast recovery, but the degree of improvement depended on the regions. The uncertainty analysis based on bootstrap resampling of raw PET data indicated high precision of the two‐stage registration.ConclusionsWe demonstrated that phantom imaging using the proposed methodology with the metric of spatial resolution and multiple bootstrap realizations may be helpful in more accurate evaluation of PET systems as well as in facilitating fine tuning for optimal imaging parameters in PET/MR and PET/CT clinical research studies.

Micron-resolution high-performance line field optical coherence tomography and its application

A line-field scanning Fourier-domain optical coherence tomography (OCT) system (LF-FDOCT) that makes high-resolution and large-dynamic-range imaging possible was demonstrated. Unlike the conventional flying-spot OCT system, the x-axis parallel imaging (one B-scan) has a coherent imaging mode. A theoretical simulation of parallel interference imaging was derived, and the anisotropic resolution along two orthogonal directions was achieved. Validated by experimental results, the spatial resolutions along the x and y axis directions were 2.46 and 2.19 μm, and the theoretical resolutions were 1.8 and 1.34 μm, respectively. The field of view (FOV) in the lateral direction was 900 μm ( x ) × 850 μm ( y ) , and the axial resolution and FOV in the experiment were 2.5 and 700 μm, respectively. The maximal axial sensitivity was measured to be 90.5 dB when the sample was a specula. The en face of tomato and the cross-section of multilayer glass were demonstrated based on the LF-FDOCT system. The three-dimensional image of adherend sample including gels and microelectrodes was realized, proving the LF-FDOCT system had the capability of high resolution and high-dynamic-range imaging.

Study on the radiofrequency transparency of electrically floating and ground PET inserts in a 3T clinical MRI system.

The positron emission tomography (PET) insert for a magnetic resonance imaging (MRI) system that implements the radiofrequency (RF) built-in body coil of the MRI system as a transmitter is designed to be RF-transparent, as the coil resides outside the RF-shielded PET ring. This approach reduces the design complexities (e.g., large PET ring diameter) related to implementing a transmit coil inside the PET ring. However, achieving the required field transmission into the imaging region of interest (ROI) becomes challenging because of the RF shield of the PET insert. In this study, a modularly RF-shielded PET insert is used to investigate the RF transparency considering two electrical configurations of the RF shield, namely the electrical floating and ground configurations. The purpose is to find the differences, advantages and disadvantages of these two configurations. Eight copper-shielded PET detector modules (intermodular gap: 3mm) were oriented cylindrically with an inner diameter of 234mm. Each PET module included four-layer Lutetium-yttrium oxyorthosilicate scintillation crystal blocks and front-end readout electronics. RF-shielded twisted-pair cables were used to connect the front-end electronics with the power sources and PET data acquisition systems located outside the MRI room. In the ground configuration, both the detector and cable shields were connected to the RF ground of the MRI system. In the floating configuration, only the RF shields of the PET modules were isolated from the RF ground. Experiments were conducted using two cylindrical homogeneous phantoms in a 3T clinical MRI system, in which the built-in body RF coil (a cylindrical volume coil of diameter 700mm and length 540mm) was implemented as a transceiver. For both PET configurations, the RF and MR imaging performances were lower than those for the MRI-only case, and the MRI system provided specific absorption ratio (SAR) values that were almost double. The RF homogeneity and field strength, and the signal-to-noise ratio (SNR) of the MR images were mostly higher for the floating PET configuration than they were for the ground PET configuration. However, for a shorter axial field-of-view (FOV) of 125mm, both configurations offered almost the same performance with high RF homogeneities (e.g., 76±10%). Moreover, for both PET configurations, 56±6% larger RF pulse amplitudes were required for MR imaging purposes. The increased power is mostly absorbed in the conductive shields in the form of shielding RF eddy currents; as a result, the SAR values only in the phantoms were estimated to be close to the MRI-only values. The floating PET configuration showed higher RF transparency under all experimental setups. For a relatively short axial FOV of 125mm, the ground configuration also performed well which indicated that an RF-penetrable PET insert with the conventional design (e.g., the ground configuration) might also become possible. However, some design modifications (e.g., a wider intermodular gap and using the RF receiver coil inside the PET insert) should improve the RF performance to the level of the MRI-only case.

NEMA NU 2–2018 performance evaluation of a new generation 30-cm axial field-of-view Discovery MI PET/CT

PurposeThe DMI PET/CT is a modular silicon photomultiplier–based scanner with an axial field-of-view (FOV) between 15 and 25 cm depending on ring configuration (3, 4, or 5 rings). A new generation of the system includes a reengineered detector module, featuring improved electronics and an additional 6th ring, extending the axial FOV to 30 cm. We report on the performance evaluation of the 6-ring upgraded Generation 2 (Gen2) system while values are also reported for the 5-ring configuration of the very same system prior to the upgrade.MethodsPET performance was evaluated using the NEMA NU 2–2018 standard for spatial resolution, sensitivity, image quality, count rate performance, timing resolution, and image co-registration accuracy. Patient images were used to assess image quality.ResultsThe average system sensitivity was measured at 32.76 cps/kBq (~ 47% increase to 5 rings at 22.29 cps/kBq) while noise equivalent count rate peaked at 434.3 kcps corresponding to 23.6 kBq/mL (~ 60% increase to Generation 1 (Gen1) and 39% to Gen2 5 rings). Contrast recovery ranged between 54.5 and 85.8% similar to 5 rings, while the 6 rings provided lower background variability (2.3–8.5% for 5 rings vs 1.9–6.8% for 6 rings) and lower lung error (4.0% for the 5 rings and 3.16% for the 6 rings). Transverse/axial full width at half-maximum (FWHM) at 1 cm (3.79/4.26 mm) and 10 cm (4.29/4.55 mm), scatter fraction (40.2%), energy resolution (9.63%), and time-of-flight (TOF) resolution (389.6 ps at 0 kBq/mL) were in line to previously reported values measured across different system configurations. Improved patient image quality is obtained with the 6 rings compared to the 5 rings, while image quality is retained even at reduced scan times, enabling WB dynamic acquisitions.ConclusionsThe higher sensitivity of the 6-ring DMI compared to the 5-ring configuration may lead to improved image quality of clinical images at reduced scan time. Additionally, it could equally be used to allow improved temporal sampling and/or reduced overall scan time in dynamic acquisitions. Conversely, temporal sampling and scan time could be traded per application to further drive injected dose at lower levels.

Abbreviated scan protocols to capture 18F-FDG kinetics for long axial FOV PET scanners.

Kinetic parameters from dynamic 18F-fluorodeoxyglucose (FDG) imaging offer complementary insights to the study of disease compared to static clinical imaging. However, dynamic imaging protocols are cumbersome due to the long acquisition time. Long axial field-of-view (LAFOV) PET scanners (> 70cm) have two advantages for dynamic imaging over clinical PET scanners with a standard axial field-of-view (SAFOV; 16-30cm). The large axial coverage enables multi-organ dynamic imaging in a single bed position, and the high sensitivity may enable clinically routine abbreviated dynamic imaging protocols. In this work, we studied two abbreviated protocols using data from a 65-min dynamic 18F-FDG scan: (A) dynamic imaging immediately post-injection (p.i.) for variable durations, and (B) dynamic imaging immediately p.i. for variable durations plus a 1-h p.i. (5-min-long) datapoint. Nine cancer patients were imaged on the Biograph Vision Quadra (Siemens Healthineers). Time-activity curves over the lesions (N = 39) were fitted using the Patlak graphical analysis and a 2-tissue-compartment (2C, k4 = 0) model for variable scan durations (5-60min). Kinetic parameters from the complete dataset served as the reference. Lesions from all cancers were grouped into low, medium, and high flux groups, and bias and precision of Ki (Patlak) and Ki, K1, k2, and k3 (2C) were calculated for each group. Using only early dynamic data with the 2C (or Patlak) model, accurate quantification of Ki required at least 50 (or 55) min of dynamic data for low flux lesions, at least 30 (or 40) min for medium flux lesions, and at least 15 (or 20) min for high flux lesions to achieve both 10% bias and precision. The addition of the final (5-min) datapoint allowed for accurate quantification of Ki with a bias and precision of 10% using only 10-15min of early dynamic data for either model. Dynamic imaging for 10-15min immediately p.i. followed by a 5-min scan at 1-h p.i can accurately and precisely quantify 18F-FDG on a long axial FOV scanner, potentially allowing for more widespread use of dynamic 18F-FDG imaging.

Total-Body PET: Will It Change Science and Practice?

Total-body (TB) PET scanners with an axial field of view (AFOV) of at least 60 cm can image dynamic radiopharmaceutical distributions in the whole body. Although the benefits of the fine temporal sampling and dramatic increase in system sensitivity afforded by TB PET imaging have been postulated for

Validation of a dedicated positron emission tomography scanner for imaging of the distal limb of standing horses.

A positron emission tomography (PET) scanner, with an openable ring of detectors, was specifically designed to image the distal limb of standing horses. The goals of this prospective, preclinical, experimental, methods comparison study were to validate the safety of the scanner, assess image quality, and optimize scanning protocols. Six research horses were imaged three times (twice standing, once anesthetized) and six horses in active race training were imaged once under standing sedation. Multiple scans of both front fetlocks were obtained with different scan durations and axial fields of view. A total of 94 fetlock scans were attempted and 90 provided images of diagnostic value. Radiotracer uptake was the main factor affecting image quality, while motion did not represent a major issue. Scan duration and field of view also affected image quality. Eight specific lesions were identified on PET images from anesthetized horses and were all also independently recognized on the PET images obtained on standing horses. Maximal standardized uptake values (SUVmax) had good repeatability for the assessment of specific lesions among different scans. Three feet and six carpi were also successfully imaged. This study validated the safety and practicality of a PET scanner specifically designed to image the distal limb in standing horses. Proper preparation of horses, similar to bone scintigraphy, is important for image quality. A 4-min scan with 12cm field of view was considered optimal for clinical fetlock imaging. Evaluation of a larger clinical population is the next step for further assessment of the clinical utility of PET imaging in horses.