EJNMMI Physics最新文献

Background: Combined PET and MRI scanners allow for simultaneous image acquisition, simplifying the interpretation of both PET and MRI images. We prototyped an insert-type PET that can convert a standalone MRI to a PET-MRI system, named Add-on PET. In Add-on PET, we fully integrated the PET modules into a head radiofrequency (RF) coil so that PET detectors can be close to the brain and avoid placing the RF coil in the field of view of PET. This study aimed at confirming the feasibility of human brain simultaneous PET and MRI imaging using a prototype of add-on PET.

Results: The PET images obtained with and without simultaneous MRI sequences were identical (Pearson's correlation coefficient, r = 0.953). Background noise was observed in the MRI images acquired during the PET scan; however, the noise decreased when the count rates of PET declined. The MRI obtained simultaneously was used for attenuation correction, providing well-correlated voxel values with those using the CT-based attenuation correction method (r = 0.989).

Conclusions: The simultaneous PET and MRI images were performed without noticeable artifacts. There was no significant interference in PET images caused by the simultaneous MRI sequence; however, some background noise was observed in the MRI, likely due to the electric current from PET modules used for counting a clinically used radioactivity concentration.

Purpose: To explore the feasibility of reducing scan duration of ¹³N-NH₃ myocardial perfusion imaging (MPI) using a total-body PET/CT scanner.

Methods: Forty-five patients with known or suspected coronary artery disease (CAD) performing rest ¹³N-NH₃ MPI with total-body PET/CT were retrospectively included. PET data were acquired in list mode for 10 min, and reconstructed into sequence images of different scan duration: 10-min, 7-min, 5-min, 3-min, and 2-min (G10 to G2). Subjective visual evaluation including overall impression, image noise and lesion visibility was evaluated using 5-point Likert scale. Quantitative parameters including perfusion defect extent (Extent), total perfusion defect (TPD), summed rest score (SRS), end-diastolic volume (EDV), end-systolic volume (ESV), ejection fraction (EF), and myocardial blood flow (MBF) were analyzed. The full-time images (G10) were served as the reference.

Results: There were no significant differences in subjective visual scores between G7-G5 and G10 groups (p > 0.05). A significant decrease in overall impression and image noise of G3-G2 was observed when compared to G10 (p < 0.05). However, no significant difference in lesion visibility was noted between G3 and G10 (p > 0.05). All G3 image quality was clinically acceptable (≥ 3 points). Except for EDV and ESV, other quantitative parameters showed no significant difference between G7-G3 and G10 (p > 0.05) and agreements were good (ICC = 0.974-0.998). For G2, only TPD exhibited no significant difference when compared to G10 (p > 0.05).

Conclusion: Regarding imaging quality and parametric quantification accuracy of ¹³N-NH₃ MPI, a 3-min scan is clinically acceptable, while a 5-min scan is sufficiently reliable.

Background: Scatter correction is essential for quantitative and accurate time-of-flight (TOF) PET imaging. It is implemented by an accurate scatter estimation algorithm, to calculate the statistical distribution of scattered photons among the measured coincidences. However, to our knowledge, scatter estimation algorithms that account for TOF and that are compatible with custom geometries are not available in open-source reconstruction libraries, such as CASToR and STIR. To this end, we have developed an open-source implementation of the TOF-aware single-scatter-simulation (SSS) algorithm: openSSS.

Results: openSSS is validated on NEMA phantoms and patient data, for three PET geometries, compared to Monte-Carlo simulations and two proprietary vendor-specific reconstruction platforms. The reconstructed images have similar contrast recovery and background variability, deviating by up to 3.7%-point on contrast recovery and 1.8 on background variability and looking visually similar.

Conclusion: We have developed and validated an open-source scatter estimation library to complement reconstruction frameworks. By enabling vendor-independent clinical-grade reconstructions on custom scanner geometries, openSSS represents a crucial step in transparent research on quantitative PET and novel PET scanner designs.

Background: Designing positron emission tomography (PET) scanners involves several significant challenges. These include the precise measurement of the time of arrival of signals, accurate integration of the pulse shape, maintaining low power consumption, and supporting the readout of thousands of channels. To address these challenges, researchers and engineers frequently develop application-specific integrated circuits (ASICs), which are custom-designed readout electronics optimized for specific tasks. As a result, a wide range of ASIC solutions has emerged in PET applications. However, there is currently no comprehensive or standardized comparison of these ASIC designs across the field.

Methods: In this paper, we evaluate the requirements posed to readout electronics in the field of PET, give an overview of the most important ASICs available for PET applications and discuss how to characterize their essential features and performance parameters. We thoroughly review the hardware characteristics of the different circuits, such as the number of readout channels provided, their power consumption, input and output design. Furthermore, we summarize their performance as characterized in literature.

Results: While the ASICs described show common trends towards lower power consumption or a higher number of readout channels over the past two decades, their characteristics and also their performance assessment by the developers, producers and vendors differ in many aspects. To cope with the challenge of selecting a suitable ASIC for a given purpose and PET application from the varying information available, this article suggests a protocol to assess an ASIC's performance parameters and characteristics.

Conclusion: ASICs developed for PET applications are versatile. With novel benchmarks set for the impact of scintillator and photosensor on the time-of-flight performance, the pressure on ASICs to deliver higher timing resolution and cope with an even higher data rate is enormous. Latest developments promise new circuits and improvements in time-of-flight performance. This article provides an overview on existing and emerging readout solutions in PET over the past 20 years, which is currently lacking in literature.

Purpose: Whole-brain segmentation via positron emission tomography (PET) imaging is crucial for advancing neuroscience research and clinical medicine, providing essential insights into biological metabolism and activity within different brain regions. However, the low resolution of PET images may have limited the segmentation accuracy of multiple brain structures. Therefore, we propose a generative multi-object segmentation model for brain PET images to achieve automatic and accurate segmentation.

Methods: In this study, we propose a generative multi-object segmentation model for brain PET images with two learning protocols. First, we pretrained a latent mapping model to learn the mapping relationship between PET and MR images so that we could extract anatomical information of the brain. A 3D multi-object segmentation model was subsequently proposed to apply whole-brain segmentation to MR images generated from integrated latent mapping models. Moreover, a custom cross-attention module based on a cross-attention mechanism was constructed to effectively fuse the functional information and structural information. The proposed method was compared with various deep learning-based approaches in terms of the Dice similarity coefficient, Jaccard index, precision, and recall serving as evaluation metrics.

Results: Experiments were conducted on real brain PET/MR images from 120 patients. Both visual and quantitative results indicate that our method outperforms the other comparison approaches, achieving 75.53% ± 4.26% Dice, 66.02% ± 4.55% Jaccard, 74.64% ± 4.15% recall and 81.40% ± 2.30% precision. Furthermore, the evaluation of the SUV distribution and correlation assessment in the regions of interest demonstrated consistency with the ground truth. Additionally, clinical tolerance rates, which are determined by the tumor background ratio, have confirmed the ability of the method to distinguish highly metabolic regions accurately from normal regions, reinforcing its clinical applicability.

Conclusion: For automatic and accurate whole-brain segmentation, we propose a novel 3D generative multi-object segmentation model for brain PET images, which achieves superior model performance compared with other deep learning methods. In the future, we will apply our whole-brain segmentation method to clinical practice and extend it to other multimodal tasks.

Background: The aim was to develop a theoretical framework for how errors in estimated activities propagate to a dispersion in time-integrated activity in radionuclide-therapy dosimetry and how this affects the comparison of radionuclide-therapy dosimetry schemes.

Methods: Formulae for the variance of relative errors of estimated time-integrated activities and relative differences in time-integrated activities between measurement schemes when one or more time-points are removed were derived using the law of propagation of uncertainty for a population of time-activity-curve parameters. The formulae were derived under the assumptions of fixed coefficients of variation for estimated activities, and underlying mono-exponential curves. Analytical predictions were compared with results from numerical simulations and data for kidneys, liver, and spleen from a data-set of 18 patients treated with ¹⁷⁷Lu-DOTA-TATE.

Results: The dispersion in time-integrated activity is minimized if the time-points used for curve fitting have a large dispersion and are centered over the mean of $\tau ={\lambda }_{\text{eff}}^{-1}$ over the population, where ${\lambda }_{\text{eff}}$ is the effective decay constant (i.e., the sum of the biological and physical decay constants). For large dispersions of decay constants in the population, the centering of time-points becomes gradually less important. The analytical expressions replicated the main trends from the numerical simulations. Furthermore, the analytical expressions predicted correctly the optimal reduced imaging schedule in 9 of 12 pairwise comparisons between schedules for patients.

Conclusions: The dispersion of errors and deviations in estimated time-activity curves can be predicted using simple formulae. These formulae have the potential to be used for optimization of dosimetry measurement schemes for established and new radiopharmaceuticals as long as the mean and dispersion of biological half-lives are known in the patient population.

Purpose: ¹⁸F-labelled somatostatin receptor tracers have recently gained popularity due to their better spatial resolution, longer half-life and lower costs compared to ⁶⁸Ga-labeled tracers. The aim of this study was to evaluate the impact and limitations of reduced administered activities of [¹⁸F]SiTATE on image quality, lesion detectability and quantitative PET parameters in a long axial field-of-view (LAFOV) PET/CT scanner.

Methods: Twenty-four patients with histologically confirmed neuroendocrine tumor, who underwent clinically indicated [¹⁸F]SiTATE PET/CT examination (3.0 MBq/kg, 5 min PET scan time) on a Siemens Biograph Vision Quadra LAFOV PET/CT, were included retrospectively in this study. PET list-mode data were rebinned for shorter frame durations to simulate 5 min scans with lower activities of injected radiotracer. A comparison of image reconstruction in high sensitivity (HS) and ultra-high sensitivity mode (UHS) mode was performed. Subjective image quality, noise and lesion detectability of n = 122 lesions were rated using a 5-point Likert scale. The molecular tumor volume (MTV), signal-to-noise ratio (SNR), tumor-to-liver activity concentration ratio (TLR) and standardized uptake values (SUV) were analyzed.

Results: Subjective image quality decreased with simulated reduction of injected activity with generally superior ratings in the UHS mode compared to the HS mode. Despite a reduction to 1 MBq/kg of [¹⁸F]SiTATE all lesions were still detected while at 0.25 MBq/kg lesion detectability decreased to 70% (HS) and 93% (UHS). Only minor changes in SUV_mean and TLR were detected with reduced activity. However, reduced activities led to an increase in SUV_SD, which in turn caused a decrease in SNR (at 1 MBq/kg: 7.3 in HS and 9.0 in UHS mode and an increase in deviation of the MTV.

Conclusion: Reducing the administered activity of injected [¹⁸F]SiTATE by 66% to 1 MBq/kg (HS & UHS) is feasible in a LAFOV PET/CT scanner, maintaining clinically diagnostic image quality without statistically significant deviations in PET uptake parameters and MTV. Furthermore, in low activity [¹⁸F]SiTATE PET/CT, the UHS mode improves image quality and noise as well as lesion detectability compared to HS mode, further reinforcing the clinical benefits of this recently introduced reconstruction mode.

Purpose: Therapeutic administration of ⁹⁰Y-loaded microspheres is routinely used for primary and secondary liver tumours. For activity-based therapeutic prescription the activity must be within 10% of the intended activity. Previous studies reported significant discrepancies between manufacturer-declared vial activities and both experimental and Monte-Carlo assessments, greater than 10%, for resin/glass ⁹⁰Y-microspheres. The objective of this work was to investigate whether these discrepancies were also seen in patients.

Methods: We analysed patient ⁹⁰Y-PET reconstructions (99 glass and 15 resin microspheres) from 4 different institutions and 4 different systems. We considered tail-fitting background scaling (TFBS) and absolute scaling (ABS), for scatter correction. Residuals after therapeutic injection were measured. Eighty-one patients were imaged with PET/CT and 33 with PET/MR. The PET measured activity (A_PET) was assessed in the whole liver. The ratio A_PET/A_calibrator was calculated for each patient, where A_calibrator was the injected activity measured by the dose calibrator corrected for residual and lung shunt.

Results: Quantification ratio between calibrators and PET was significantly different from 1, regardless of the scatter correction used. In glass microspheres, the mean A_PET/CT/A_calibrator was 0.84 ± 0.06 for TFBS and 0.90 ± 0.06 for ABS (0.66 ± 0.09 and 0.76 ± 0.07 for (A_PET/MR/A_calibrator)). The mean A_PET/CT/A_calibrator ratio for resin microspheres was 1.16 ± 0.09 for TFBS and 1.30 ± 0.12 for ABS.

Conclusions: We observed in patients similar activity discrepancies as reported for vials, with a relative difference of 44 ± 16% between glass and resin ⁹⁰Y-loaded microspheres. In ⁹⁰Y hepatic radioembolization, the 10% accuracy prerequisite on knowing the administered therapeutic activity is then unlikely to be met.

Purpose: Patients with dementia symptoms often struggle to limit movements during PET examinations, necessitating motion compensation in brain PET imaging to ensure the high image quality needed for diagnostic accuracy. This study validates a data-driven motion-compensated (MoCo) PET brain image reconstruction algorithm that corrects head motion by integrating the detected motion frames and their associated rigid body transformations into the iterative image reconstruction. Validation was conducted using phantom scans, healthy volunteers, and clinical patients using four radiotracers with distinct tracer activity distributions.

Methods: We conducted technical validation experiments of the algorithm using Hoffman brain phantom scans during a series of controlled movements, followed by two blinded reader studies assessing image quality between standard images and MoCo images in 38 clinical patients receiving dementia scans with [¹⁸F]Fluorodeoxyglucose, [¹⁸F]N-(3-iodopro-2E-enyl)-2beta-carbomethoxy-3beta-(4'-methylphenyl)-nortropane, [¹⁸F]flutemetamol, and a research group comprising 25 elderly subjects scanned with [¹⁸F]fluoroethoxybenzovesamicol.

Results: The Hoffman brain phantom study demonstrated the algorithm's capability to detect and correct for even minimal movements, 1-mm translations and 1⁰ rotations, applied to the phantom. Within the clinical cohort, where standard images were deemed suboptimal or non-diagnostic, all MoCo images were classified as having acceptable diagnostic quality. In the research cohort, MoCo images consistently matched or surpassed the standard image quality even in cases with minimal head movement, and the MoCo algorithm never led to degraded image quality.

Conclusion: The PET brain MoCo reconstruction algorithm was robust and worked well for four different tracers with markedly different uptake patterns. Moco images markedly improved the image quality for patients who were unable to lie still during a PET examination and obviated the need for any repeat scans. Thus, the method was clinically feasible and has the potential for improving diagnostic accuracy.

Background: Zirconium-89 (Zr-89) PET tracers have become increasingly significant in the field of nuclear medicine due to their 3-day physical half-life, allowing for the study of dynamic biological processes over relatively long timeframes. To date there has been limited publication of studies focused on optimisation of acquisition parameters for Zr-89 PET. This paper outlines a short phantom study investigating the optimal beta regularization parameter for quantitation and noise in block sequential regularised expectation maximisation (BSREM) also known as Bayesian penalized likelihood (BPL) reconstruction, for varying image noise characteristics (acquisition duration).

Results: The choice of the beta regularisation parameter substantially impacts image quality and quantitation. For larger volumes, BSREM reconstruction enhanced image quality (lower noise) and maintained quantitation, whereas for smaller volumes quantitation worsened as compared to OSEM for high regularisation parameters.

Conclusion: Where BSREM reconstruction is used for Zr-89 images, careful attention must be paid to the choice of weighting factor, especially for quantitative clinical studies. The effect of varying beta on several measures of image quality was characterised for the case of a phantom, with the results indicating that the value of beta for optimal Zr-89 quantitation is lower than what is generally used for optimal visualisation. This work demonstrates the need for careful attention to the reconstruction methods used for quantitative imaging studies, such as those required for theragnostic imaging.