EJNMMI Physics最新文献

Background: ²⁰³Pb and ²¹²Pb show promise as theragnostic agents for targeted alpha therapy (TAT) because two chemically identical isotopes can be used for diagnostic imaging and treatment. In the ²¹²Pb decay chain, in addition to alpha and beta particles, a large number of photons are emitted, those with an energy of 239 keV and the characteristic X-rays of ²¹²Pb could be used for imaging. ²⁰³Pb decays by photon emission with an energy of 279 keV, which appears suitable for gamma camera imaging. The aim of this study was to investigate suitable imaging protocols and to characterize the scintigraphic imaging properties and their implications for the clinical feasibility as theragnostic isotopes.

Methods: Planar and SPECT/CT images were obtained with medium- and high-energy collimators on a Siemens Symbia Intevo 6 using a NEMA image quality phantom in various phantom setups and another body-shaped phantom with several inserts. Different energy windows were investigated and measurements were evaluated in terms of sensitivity, count rate performance, spatial resolution, contrast recovery, lesion detectability, and image quantification.

Results: Evaluation of image quality showed superior imaging characteristics for ²⁰³Pb compared to ²¹²Pb regarding spatial resolution, contrast recovery, image noise, and quantification accuracy. Both medium- and high- energy collimators were suitable for ²⁰³Pb imaging, with the medium energy collimators showed slightly better imaging properties. Images obtained with the HE collimators in the 79 keV energy window showed the best visual image quality for ²¹²Pb. Due to high-energy photon emissions from ²¹²Pb daughter nuclides (e.g., 2.6 MeV from ²⁰⁸Tl), dead time related count losses occurred even at low activities (20% count loss at 20 MBq for MELP collimators).

Conclusions: According to our results and first-in-human imaging studies, SPECT/CT imaging with the ^203/212Pb theragnostic pair is clinically feasible. ²⁰³Pb is an appropriate imaging surrogate to investigate pharmacokinetics and perform predictive dosimetry. The less favorable imaging characteristics of ²¹²Pb make image quantification and post-treatment dosimetry challenging and require further research.

Purpose: EasyPET.3D is a preclinical positron emission tomography (PET) scanner with a unique scanning method based on two face-to-face detector modules with two axes of motion. Its performance evaluation is presented using the NEMA NU-4 standards and an animal model.

Methods: Each detector module consists of a 32 × 2 pixelated cerium-doped lutetium-yttrium oxyorthosilicate (LYSO:Ce) scintillator array with individual crystals of 2.0 × 2.0 × 30 mm³. The crystal arrays are coupled to 1.3 × 1.3 mm² silicon photomultipliers (SiPMs). The transaxial field-of-view (FoV) is adjustable up to 48 mm in diameter, and the axial length is 73 mm. The performance characterization includes spatial resolution, sensitivity, count rate, scatter fraction (SF), and image quality (IQ) measurements. Furthermore, mice experiments were conducted to evaluate the in vivo imaging capability.

Results: Spatial resolution at the FoV centre (CFoV) in radial, tangential, and axial directions was 0.98±0.08, 0.97±0.06 and 0.94±0.08 mm, respectively. An absolute sensitivity of 0.23% was measured at CFoV. The mouse-like phantom SF was 16% (913 cps at 18 MBq). Recovery coefficients in the IQ phantom varied from 21±34% to 85±50% (1 to 5 mm diameter rods, accordingly). The uniformity was 17.6%, and spill-over ratios for water-filled and air-filled chambers were 0.49 and 0.40, respectively.

Conclusion: EasyPET.3D geometry favours the reduction of parallax error, despite its low sensitivity. The system linearity is suitable for the low range of activities (7-8 MBq) used for mice imaging. The overall performance showed that easyPET.3D has potential for entry-level preclinical applications.

Background: The combination of longer axial field-of-view (AFOV) and time-of-flight positron emission tomography (PET) has significantly improved system sensitivity and, as a result, image quality. This study investigates a cost-effective extended AFOV PET system design using monolithic LYSO detectors with depth-of-interaction capabilities. These detectors, arranged in a vertical flat-panel geometry and positioned closer to the patient, enable superior spatial resolution while maintaining a compact and affordable system design. We simulate the performance of two flat-panel PET configurations: one with a fully populated 106 cm AFOV and another cost-efficient design featuring a reduced AFOV with axial gaps and vertical panel motion optimized for head and torso imaging.

Methods: Both configurations consist of two monolithic LYSO-based flat panels placed 50 cm apart. The panels are 71 cm wide, with the Long Flat Panel (L-FP) design extending to a length of 106 cm while the Sparse Medium Flat Panel (SpM-FP) design measures 60 cm in length. Monte Carlo simulations evaluated the two designs using the NEMA protocol and additional tests for a more thorough assessment. Sensitivity, spatial resolution, axial noise variability, and image quality were analyzed, and an XCAT phantom at standard dose was used to demonstrate the achievable clinical image quality.

Results: The SpM-FP showed 4-5 times lower sensitivity than the L-FP, requiring an acquisition time of 2-3 min to match the image quality achieved by the L-FP in 30 s. This finding is supported by the contrast-to-noise ratio of the image quality phantom and the standard deviation values obtained from the liver and lung regions of the XCAT phantom. Both configurations achieved uniform spatial resolution below 2 mm in the two directions parallel to the panels and an average of 3-3.5 mm in the direction towards the panels, with slight degradation observed away from the center of the AFOV. Additionally, the axial noise profile of the SpM-FP revealed minimal variability.

Conclusions: The SpM-FP design shows potential as a cost-effective system, combining the benefits of extended AFOV, superior spatial resolution and high patient throughput.

Background: This study evaluates the feasibility of using a simplified Patlak parametric imaging technique with a scaled population-based input function (sPBIF) in pancreatic cancer.

Methods: Twenty-six patients underwent multi-bed, multi-pass [¹⁸F]FDG PET/CT scans, from which both dynamic and static PET images were reconstructed. Patlak parametric images were generated from the dynamic PET series using both the image-derived input function (IDIF) and the sPBIF. The consistency between IDIF and sPBIF was evaluated by comparing the area under the curve (AUC) and Patlak parameters derived from both input functions. The detectability of pancreatic lesions, assessed by tumor-to-background ratio (TBR) and contrast-to-noise ratio (CNR), was compared between SUV and Patlak parametric images. Additionally, the correlation between clinicopathological features and PET parameters, including SUV and Patlak values, was analyzed.

Results: We found good agreement between the AUC for IDIF and sPBIF with correlation coefficients of 0.87 and 0.93 for the 0-30 min and 0-50 min intervals, respectively. The Patlak parameters from IDIF and sPBIF presented correlation coefficients higher than 0.94. The SUV and Patlak K_i exhibited correlation coefficients greater than 0.92 and 0.73 in malignant and benign pancreatic lesions, respectively. The SUV and Patlak V₀ correlated with correlation coefficients higher than 0.75 in benign lesions, but exhibited only a weak correlation in malignant lesions. The TBR of Patlak K_i was significantly higher in malignant lesions compared to SUV. However, the CNR of Patlak K_i was lower due to increased noise in the parametric images. Most clinicopathological features showed weak correlation with PET parameters, except for a marginal classification of lesion differentiation by the maximum K_i value.

Conclusions: The sPBIF approach enables the acquisition of additional Patlak parametric images alongside static SUV imaging in pancreatic cancer patients. K_i parametric imaging provided higher contrast than static imaging for detecting pancreatic lesions.

Background: This study aimed to analyse the quantitative capabilities of cadmium-zinc-telluride (CZT)-based SPECT-CT cameras using ^99mTc, comparable to the analysis performed a decade ago for the sodium iodide (NaI) SPECT-CT systems available on the market at that time. This survey assessed one dual-head (GE Discovery NM870 CZT) and two ring (GE Starguide, Spectrum Dynamics Veriton 200) CZT cameras, as well as a state-of-the-art NaI dual-head system (Siemens Intevo Bold) that served as reference. Attenuation and scatter correction accuracy was explored, contrast recovery for small cold and hot rods measured, as well as the quantification in a large uniform area using user-determined conversion factors. Tomography reconstruction was performed with the manufacturers' iterative algorithms that allowed for attenuation correction, scatter correction and resolution recovery.

Results: Using the NEMA NU-2 1994 dedicated phantom, attenuation and scatter corrections seemed to perform very well. Equally, the contrast recovery of cold rods seemed to be superior for the CZT systems. However, the contrast recovery for the hot rods was inferior to the NaI camera, whereas it was comparable without the scatter correction. Finally, a quantification error of less than 5% was shown to be reachable when using adequate user-determined conversion factors. For the NaI camera, all results were similar to those of the past study.

Conclusions: Without scatter correction, the CZT SPECT systems showed contrast performance similar to the NaI camera. With scatter correction, this held true for cold objects but the contrast of hot objects was not significantly improved or was degraded depending on the system considered and the object size. Quantification errors of less than 5% were achievable. It is hoped that on-going developments at both manufacturers will improve the scatter correction accuracy.

Purpose: Dopamine transporter (DAT) SPECT is an effective tool for early Parkinson's disease (PD) detection and heavily hampered by attenuation. Attenuation correction (AC) is the most important correction among other corrections. Transfer learning (TL) with fine-tuning (FT) a pre-trained model has shown potential in enhancing deep learning (DL)-based AC methods. In this study, we investigate leveraging realistic Monte Carlo (MC) simulation data to create a pre-trained model for TL-based AC (TLAC) to improve AC performance for DAT SPECT.

Methods: A total number of 200 digital brain phantoms with realistic ^99mTc-TRODAT-1 distribution was used to generate realistic noisy SPECT projections using MC SIMIND program and an analytical projector. One hundred real clinical ^99mTc-TRODAT-1 brain SPECT data were also retrospectively analyzed. All projections were reconstructed with and without CT-based attenuation correction (CTAC/NAC). A 3D conditional generative adversarial network (cGAN) was pre-trained using 200 pairs of simulated NAC and CTAC SPECT data. Subsequently, 8, 24, and 80 pairs of clinical NAC and CTAC DAT SPECT data were employed to fine-tune the pre-trained U-Net generator of cGAN (TLAC-MC). Comparisons were made against without FT (DLAC-MC), training on purely limited clinical data (DLAC-CLI), clinical data with data augmentation (DLAC-AUG), mixed MC and clinical data (DLAC-MIX), TL using analytical simulation data (TLAC-ANA), and Chang's AC (ChangAC). All datasets used for DL-based methods were split to 7/8 for training and 1/8 for validation, and a 1-/2-/5-fold cross-validation were applied to test all 100 clinical datasets, depending on the numbers of clinical data used in the training model.

Results: With 8 available clinical datasets, TLAC-MC achieved the best result in Normalized Mean Squared Error (NMSE) and Structural Similarity Index Measure (SSIM) (TLAC-MC; NMSE = 0.0143 ± 0.0082/SSIM = 0.9355 ± 0.0203), followed by DLAC-AUG, DLAC-MIX, TLAC-ANA, DLAC-CLI, DLAC-MC, ChangAC and NAC. Similar trends exist when increasing the number of clinical datasets. For TL-based AC methods, the fewer clinical datasets available for FT, the greater the improvement as compared to DLAC-CLI using the same number of clinical datasets for training. Joint histograms analysis and Bland-Altman plots of SBR results also demonstrate consistent findings.

Conclusion: TLAC is feasible for DAT SPECT with a pre-trained model generated purely based on simulation data. TLAC-MC demonstrates superior performance over other DL-based AC methods, particularly when limited clinical datasets are available. The closer the pre-training data is to the target domain, the better the performance of the TLAC model.

Background: Cell culture can be categorized into two major types: adherent and suspension. Both are used in a range of diverse research applications, exhibiting Pros and Cons, depending on what is being studied. In the field of Internal Emitters (IE), different morphological features such as nuclei size, cytoplasm ratio, and shape could influence its non-uniformity deposition and thus impact on the biological outcome. In this work we tested the hypothesis that cellular morphology differences, offered by adherent and suspension cultures, influence the radiosensitizing effect of gold nanoparticles (AuNPs).

Methods: Using two PC3 cellular models, taken using confocal microscopy, we conducted Monte Carlo simulations to investigate the effects of different irradiation conditions on cellular Survival Fractions (SF). Our simulations focused on cells exposed to two distinct irradiation sources: ⁶⁰Co and 14 MeV protons, along both the longer and shorter axes of the cells to assess directional influences on cell survival. Additionally, we compared the SF of cells adherent to the culture flask with those in suspension, reflecting different experimental and potentially clinical scenarios.

Results: In the absence of AuNPs, neither cell type nor irradiation direction significantly affected SF for the radiation types tested. However, with AuNPs present, SF demonstrated a strong dependence on irradiation direction and cell morphology.

Conclusions: Our results indicate that the direction of irradiation plays a crucial role in determining the effectiveness of AuNPs in reducing SF. Furthermore, the results suggest that using cells in suspension will reduce the dependence of cell survival on the beam direction during irradiation, regardless of the radiation quality used.