EJNMMI Physics最新文献

{"title":"Image optimization for low-dose ¹⁸F-FDG breast PET/MRI using deep learning: a pilot study.","authors":"Quinton J Keigley, Leah C Henze Bancroft, Kelley Salem, Kuan-Hao Su, Abolfazl Mehranian, Matthew G Spangler-Bickell, Alan B McMillan, Scott B Perlman, Roberta M Strigel, Tyler J Bradshaw, Samuel A Hurley, Lu Mao, Amy M Fowler","doi":"10.1186/s40658-026-00918-9","DOIUrl":"10.1186/s40658-026-00918-9","url":null,"abstract":"<p><strong>Background: </strong>Positron emission tomography with magnetic resonance imaging (PET/MRI) provides noninvasive molecular characterization of breast cancer and has the potential to improve diagnostic accuracy, staging, treatment response assessment, and guide personalized care. Reducing the radiation dose from 2-deoxy-2-[¹⁸F]fluoro-D-glucose (¹⁸F-FDG) to a level similar to digital mammography while maintaining image quality may facilitate clinical utilization. This study was performed to evaluate diagnostic image quality and lesion conspicuity of low-dose ¹⁸F-FDG breast PET/MRI using denoising and to evaluate the effect of denoising on radiotracer uptake semi-quantification.</p><p><strong>Methods: </strong>This pilot study was a secondary analysis of a single-institution prospective study of ¹⁸F-FDG breast PET/MRI for 23 women with primary invasive breast cancer. Random undersampling of the PET data from a 30-min simultaneous prone ¹⁸F-FDG breast PET/MRI was used to produce simulated low-dose (SLD) images approximating 90% reduced injected activity (37 MBq). A deep learning-based, denoising (DN) algorithm was then applied. SLD and DN datasets were evaluated by three readers for image quality and lesion conspicuity and were compared to full-dose images to assess clinical acceptability. Image noise was quantified by liver SUV_{standard deviation}. ¹⁸F-FDG uptake (SUV_max and SUV_mean) was measured in tumor and normal breast tissue and compared between datasets. Wilcoxon signed rank test, repeated measures analysis of variance, and Bland-Altman analyses were performed.</p><p><strong>Results: </strong>Compared to SLD, DN datasets scored better for artifacts, perceived signal-to-noise ratio, image sharpness/resolution, and overall image quality (p < 0.001). Compared to full-dose images, DN scored better than SLD for diagnostic image quality (p < 0.001) and lesion conspicuity (p = 0.002). For diagnostic image quality, DN was equivalent or slightly inferior to full-dose images in 89.9% (62/69) of reads. Readers preferred DN (76.8%; 53/69) to SLD (4.3%; 3/69), and both were preferred equally in 10.1% (7/69) of reads. Compared to SLD, quantitative image noise was less in DN images (p < 0.0001). Agreement was excellent between all datasets for tumor SUV_max and SUV_mean.</p><p><strong>Conclusions: </strong>Acceptable image quality may be achieved with low-dose ¹⁸F-FDG breast PET/MRI using denoising, which warrants further prospective validation.</p>","PeriodicalId":11559,"journal":{"name":"EJNMMI Physics","volume":" ","pages":""},"PeriodicalIF":3.5,"publicationDate":"2026-07-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13654906/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148445101","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Evaluation of deep learning-based reconstruction models on non-TOF BGO PET/CT: impact of acquisition times and BSREM penalization factors on lesion detectability and SNR.","authors":"Anna Stenvall, David Minarik, Elin Trägårdh, Sofia Kvernby","doi":"10.1186/s40658-026-00919-8","DOIUrl":"10.1186/s40658-026-00919-8","url":null,"abstract":"<p><strong>Background: </strong>New long field-of-view (FOV) PET scanners using bismuth germanate (BGO) detectors without time-of-flight (TOF) capability are now available. These systems incorporate deep learning-based TOF (DLb-TOF) models to compensate for the absence of TOF. There is a lack of studies systematically investigating the optimal balance between signal to noise ratio and lesion detectability across a broader range of acquisition times and β-values for these DLb-TOF models. This study aims to evaluate the trade-off between acquisition time, signal-to-noise ratio (SNR) and lesion detectability to guide optimization of clinical protocol.</p><p><strong>Materials and methods: </strong>Twenty patients referred for a clinical [¹⁸F]fluorodeoxyglucose (FDG) PET scan were included. Each patient received 3.5 MBq/kg of [¹⁸F]FDG and underwent a whole-body PET acquisition (120 s/bed) on a digital BGO PET/CT (32 cm FOV) 60 min post-injection. Data were reconstructed into images (384 × 384 matrix) representing different acquisition times (120 s, 90 s, 60 s, 45 s, 30 s and 15 s) using BSREM with β-values ranging from 50 to 1100. Three DLb-TOF models (Low, Medium, High) were applied. Volumes of interest were placed in the liver and two avid lesions per patient. SNR were calculated as SUVmean_liver/SD_liver and detectability were calculated as SUVpeak_tumor/SUVpeak_liver.</p><p><strong>Results: </strong>SNR increased with longer acquisition times and higher β-values. DLb-TOF models improved SNR across all settings, with the Low DLb-TOF model producing the largest increase. Lesion detectability depended on the acquisition time and β-value. At longer acquisition times (120 s, 90 s), β100 provided the highest detectability, while shorter times (60-15 s) required higher β-value (β300) for optimal detectability. Among DLb-TOF models, the High model gave the best detectability overall, though the Low model performed better at lower β-values.</p><p><strong>Conclusion: </strong>SNR increased with higher β-values, longer acquisition times, and DLb-TOF application. Lesion detectability, defined as the ratio of SUV_peak in the lesion to SUV_peak in the liver, depended on the β-value, acquisition time, and the DLb-TOF model used. The Low DLb-TOF model had the best SNR but at the expense of detectability. The optimal parameters for the evaluated BGO PET/CT system, balancing SNR and lesion detectability within a clinical reasonable acquisition time, were 60-90 s with β-values of 500-300, in combination with the Medium DLb-TOF model, when 3.5 MBq/kg [¹⁸F]FDG was administered.</p>","PeriodicalId":11559,"journal":{"name":"EJNMMI Physics","volume":" ","pages":""},"PeriodicalIF":3.5,"publicationDate":"2026-07-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13369060/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148430109","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Estimation of effective half-life and lesion-specific kinetics in I-131 therapy for differentiated thyroid cancer using dual-timepoint imaging.","authors":"Yusuke Iizuka, Ryota Nakashima, Rihito Aizawa, Masaaki Kajisako, Maki Shioji, Katsuhiko Mitsumoto, Koji Itagaki, Shigeto Kawase, Takashi Mizowaki","doi":"10.1186/s40658-026-00916-x","DOIUrl":"10.1186/s40658-026-00916-x","url":null,"abstract":"<p><strong>Background: </strong>Accurate estimation of lesion-specific effective half-life (T_eff) is essential for patient-specific dosimetry in radioiodine (I-131) therapy for differentiated thyroid cancer (DTC). Although conventional multi-timepoint imaging provides detailed kinetic information, it is often impractical for routine clinical implementation. This study prospectively evaluated a simplified dual-timepoint planar imaging protocol aimed at balancing quantitative reliability with clinical feasibility.</p><p><strong>Methods: </strong>Fifty patients with DTC undergoing I-131 therapy were prospectively analyzed. Whole-body planar images were acquired twice after administration: an early scan at 1.98-3.25 days (mean, 2.71 days) and a delayed scan at 8.97-17.16 days (interval between the two scans ranged from 6.18 to 14.28 days [mean, 12.35 days]). Lesion-specific T_eff values were calculated assuming mono-exponential clearance between the two scans using a log-linear approximation of measured activity counts. Quantitative reproducibility was assessed by comparing activity-count calibration slopes derived from an internal reference I-131 capsule between independent imaging sessions.</p><p><strong>Results: </strong>The mean T_eff was 2.16 ± 0.56 days and 3.11 ± 0.74 days for thyroid bed (n = 35) and metastatic (n = 19; p < 0.001) lesions, respectively. Among metastatic sites, bone and lung metastases showed numerically similar T_eff values (3.22 ± 0.76 and 3.36 ± 0.80 days, respectively); however, this subgroup comparison was limited by the small sample size. Calibration slopes derived from the internal reference capsule demonstrated only 5.0% inter-session variability, indicating high quantitative reproducibility.</p><p><strong>Conclusions: </strong>Dual-timepoint planar imaging incorporating internal capsule calibration enables reproducible estimation of lesion-specific T_eff in patients undergoing I-131 therapy for DTC. This approach achieves a practical balance between quantitative accuracy and clinical feasibility, enabling reliable characterization of iodine kinetics with minimal imaging burden and supporting individualized dosimetry in routine clinical practice.</p>","PeriodicalId":11559,"journal":{"name":"EJNMMI Physics","volume":" ","pages":""},"PeriodicalIF":3.5,"publicationDate":"2026-07-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13574748/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148396292","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Impact of reduced ¹⁸F-MK6240 PET/MR acquisition duration on image quality and tau pathology assessment in patients with cognitive impairment.","authors":"Kai Liao, Jia Li, Fangyang Jiao, Zhu Zhang, Lu Xu, Zhengjie Wang, Wenbo Li, Hua Pang","doi":"10.1186/s40658-026-00914-z","DOIUrl":"10.1186/s40658-026-00914-z","url":null,"abstract":"<p><strong>Background: </strong>¹⁸F-MK6240 tau positron emission tomography (PET) is critical in Alzheimer's disease diagnosis and therapeutic monitoring. However, the standard 20-minute static acquisition poses challenges for cognitively impaired patients with limited tolerance for prolonged scans. This study evaluates the feasibility of reducing scan time while maintaining diagnostic accuracy through image quality and quantitative comparisons.</p><p><strong>Methods: </strong>69 memory clinic patients (27 males and 42 females) who underwent ¹⁸F-MK6240 PET examinations were retrospectively analyzed. All 20-minutes scans were acquired 90 min post-injection of ~ 3.7 MBq/kg ¹⁸F-MK6240 and reconstructed mainly into 5-, 10-, 15-, and 20-minute datasets. Images were rated on a 5-point scale for overall quality, noise, and diagnostic confidence. Tau status (positive/negative) was the visually defined, and standardized uptake value ratios (SUVr) of Braak regions were calculated using cerebellar gray matter as reference. Agreement across durations was assessed via Bland-Altman analysis.</p><p><strong>Results: </strong>Among the 69 patients, 50 were classified as tau-positive and 19 as tau-negative. Diagnostic efficacy remained consistent across acquisition times compared to the 20-minute reference. The slight reduction in image quality for the 5-minute images relative to the other groups, but none of the images across any of the four durations were rated as poor (score < 3). For 16 predefined regions used for visual assessment of regional tau involvement, both readers showed near-perfect agreement in scoring the extent of involvement (0%, 1-25%, 26-75%, or > 75%) across the four scan durations, as evidenced by Kendall's W coefficients ranging from 0.984 to 1.000 (all p < 0.001). Negative scans showed lower SUVr spread over Braak stages of four different time duration. Bland-Altman analysis demonstrated high agreement in Braak-stage SUVr values between the 20-minute images and the shortened acquisitions with mean differences close to zero across all comparisons.</p><p><strong>Conclusion: </strong>Shortening ¹⁸F-MK6240 PET acquisition to 5 min on a modern high-sensitivity PET/MR system results in a small, clinically acceptable decline in image quality. It does not compromise the reliability of visual reads or the stability of semi-quantitative measures compared to the standard 20-minute scan. These findings support the feasibility of 5-minute protocols, which offer practical benefits like reduced motion artifacts and improved patient throughput, as an operationally efficient alternative in clinical tau imaging.</p>","PeriodicalId":11559,"journal":{"name":"EJNMMI Physics","volume":" ","pages":""},"PeriodicalIF":3.5,"publicationDate":"2026-06-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13582771/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148344365","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Data-efficient unsupervised deep learning deformable SPECT/CT registration framework for voxel-level radionuclide therapy dosimetry: validation using clinical ¹³¹I DTC therapy data.","authors":"Junyi Liu, Xuanhe Wang, Hui Zhang, Ziqiu Xu, Xuemei Wang, Xie George Xu","doi":"10.1186/s40658-026-00911-2","DOIUrl":"10.1186/s40658-026-00911-2","url":null,"abstract":"<p><strong>Purpose: </strong>To develop a data-efficient, unsupervised deep learning framework for deformable SPECT/CT registration that supports voxel-based dosimetry in radionuclide therapy, particularly in clinical settings with limited imaging datasets.</p><p><strong>Methods: </strong>We propose Nufit-Reg, an unsupervised deep learning network for deformable SPECT/CT registration. The network employs dual Swin-Transformer-based encoders to process CT and SPECT images separately, with cross-stitch units enabling structured feature sharing and multimodal integration across hierarchical stages. To overcome data scarcity, a two-stage training strategy was adopted. In the first stage, inter-patient pre-training was performed using randomly paired iodine-131 SPECT/CT scans (a total of 58 scans) to learn general anatomical correspondences. In the second stage, few-shot fine-tuning was performed using intra-patient sequential SPECT/CT pairs derived from quantitative scans (12 patients, each with three time points), enabling the model to adapt to patient-specific temporal consistency while being optimized across multiple patients. Registration performance was evaluated against Elastix and UTSRMorph using image similarity metrics, including structural similarity (SSIM), weighted SSIM (wSSIM), local normalized cross-correlation (LNCC), and mutual information (MI), as well as deformation regularity assessed via Jacobian determinant analysis. The downstream impact of registration on voxel-level time-activity-curve (TAC) fitting and tumor dose distributions (D_2%, D_98%) was also quantitatively analyzed.</p><p><strong>Results: </strong>Nufit-Reg achieved a superior weighted SSIM (0.8968 ± 0.0241). It significantly outperforming Elastix and CT UTSRMorph. In dosimetry analysis, the enhanced registration accuracy led to an 11.7% reduction in tumor fitting RMSE compared to Elastix. These improvements aligned with more stable dose distributions. This was evidenced by reduced D_2% extremes (110.81 to 95.1 Gy), and higher median D_98% 3.30 Gy.</p><p><strong>Conclusion: </strong>This study introduces Nufit-Reg, a two-stage unsupervised framework that achieves accurate and efficient deformable SPECT/CT registration under data-limited conditions. By combining inter-patient pre-training with intra-patient fine-tuning, Nufit-Reg provides a practical solution for supporting individualized voxel-based dosimetry in I-131 radionuclide therapy and potentially for other radionuclide treatments in data-scarce clinical environments.</p>","PeriodicalId":11559,"journal":{"name":"EJNMMI Physics","volume":" ","pages":""},"PeriodicalIF":3.5,"publicationDate":"2026-06-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13590463/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148344396","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"It's PET but not as we know it: radiation protection considerations when using a novel specimen PET-CT scanner during tumour resections for urology and head & neck patients.","authors":"L M Rowley, C Pickles, K Hodgson, S E Kallioinen, D MacDonald, G Walton, O Adesanya","doi":"10.1186/s40658-026-00904-1","DOIUrl":"10.1186/s40658-026-00904-1","url":null,"abstract":"<p><strong>Purpose: </strong>To evaluate the radiation protection requirements for a UK first specimen PET-CT scanner, the AURA10 (Xeos, Ghent), as assessed through a clinical trial investigating its use for intra-operative surgical margin assessment in urology and head and neck (H&N) tumour removal.</p><p><strong>Methods: </strong>A radiation risk assessment was performed to inform radiation protection requirements and training. 0.8 MBq/kg of ¹⁸Fluorine fluorodeoxyglucose and 50 MBq of ⁶⁸Gallium prostate-specific membrane antigen were administered for H&N and urology cases respectively. Whole body optically stimulated luminescence dosimeters, finger and eye ThermoLuminescent dosimeters and electronic personal dosimeters were issued to staff in theatres, recovery, and histopathology. Dose rate measurements were recorded at the position of staff members in theatres. Measured counts and dose rate from the resected specimen and swabs were obtained and contamination monitoring of the room were performed following removal of the patient.</p><p><strong>Results: </strong>Training sessions and dry runs with surgical staff helped identify radiation risks and optimise workflow. Occupational doses from surgeons and scrub nurses were the highest for both modalities. Doses to other theatre staff were below dose limits for members of the public in the UK. Doses to staff outside theatres, including recovery and histopathology, were found to be below threshold values. Low level contamination was present in swabs (< 6 kBq and < 250 kBq for H&N and urology cases respectively).</p><p><strong>Conclusion: </strong>Thorough staff training, systems of work and shielding are required to ensure radiation doses to staff are minimised and contamination and radioactive waste are contained. There were difficult occasions during shift changes and untrained staff rota-ed in, but nuclear medicine supervision and then the introduction of theatre-based cascade trainers helped solidify learning and provide assurance to theatre staff and staff showed good compliance with the systems of work in place. Annual doses to theatre staff are heavily dependent on workload, with surgeons and scrub nurses closest to the patient receiving whole body doses of 39 µSv and 12 µSv, and finger doses of 88 µSv and 48 µSv respectively per case for H&N. Corresponding urology doses per case were measured as 7.2 µSv and 2.5 µSv for whole body and 16 µSv and below threshold values for the assisting surgeon and scrub nurse respectively.</p><p><strong>Trial registry: </strong>www.</p><p><strong>Clinicaltrials: </strong>gov . URL trail registry record: Study Details | NCT06676943 | Investigating the Diagnostic Performance of High-resolution Specimen PET-CT in Determining Margin Status in Cancer Resection | ClinicalTrials.gov.</p>","PeriodicalId":11559,"journal":{"name":"EJNMMI Physics","volume":" ","pages":""},"PeriodicalIF":3.5,"publicationDate":"2026-06-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13590457/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148344340","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Optimising [Formula: see text] PET imaging for dosimetry in SIRT: insights from phantom and simulation studies on the Discovery MI scanner.","authors":"Farzam Sayah, Benoît Presles, Hussein Harb, Tien-Phong Pham, Jean-Louis Alberini, Romain Popoff, Jean-Marc Vrigneaud","doi":"10.1186/s40658-026-00912-1","DOIUrl":"10.1186/s40658-026-00912-1","url":null,"abstract":"<p><strong>Background: </strong>The aim of this study was to optimise the acquisition and reconstruction parameters for [Formula: see text] imaging on a digital PET scanner (Discovery MI 4-ring) under high (3 GBq), intermediate (1 GBq), and low (200 MBq) activity conditions. First, quantitative linearity was evaluated. Then, NEMA IEC body phantom acquisitions were reconstructed using various scan durations and Q.Clear reconstruction parameters. Next, optimal protocols were identified by minimising the discrepancies between absorbed dose maps derived from images (using the Local Deposition Model (LDM)) and those obtained from Monte Carlo (MC) simulations. The images reconstructed with these optimal protocols were then used to evaluate effective spatial resolution and to compare the accuracy of LDM with that of the Dose Voxel Kernel (DVK) approach.</p><p><strong>Results: </strong>Quantitative linearity analysis revealed an underestimation of phantom activity at high activity (up to - 15.7% at 3.6 GBq) and an overestimation at lower levels (up to 52.1% at 208 MBq). At high activity, the most accurate results were produced by 15- and 20-minute acquisitions with intermediate beta values (2000-5000). In contrast, intermediate and low activity levels required longer acquisition times and higher beta values (> 6000). Effective spatial resolution ranged from 7 mm at high activity to 24.9 mm at low activity. In terms of absorbed dose accuracy, the mean absorbed dose was underestimated in all spheres of the phantom. However, the error in the mean absorbed dose could be kept within 10% in the background by applying non-linearity corrections. Using MC as reference, LDM achieved greater accuracy in terms of mean absorbed dose and Dose Volume Histogram (DVH) agreement in the spheres, while DVK performed better in the background.</p><p><strong>Conclusions: </strong>This study enabled the optimisation of scan duration and beta parameter values for Q.Clear reconstructions for dosimetric purposes. Although accurate dosimetry remains challenging in [Formula: see text] PET imaging due to quantitative nonlinearity and limited spatial resolution, an error of less than 10% on the mean absorbed dose can be achieved in large structures if model-specific nonlinearities are corrected for.</p>","PeriodicalId":11559,"journal":{"name":"EJNMMI Physics","volume":" ","pages":""},"PeriodicalIF":3.5,"publicationDate":"2026-06-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13594012/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148316451","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Denoising of 4D dynamic PET images using spatiotemporal regularization with integrated temporal restoration (SPRINTER).","authors":"Hamed Yousefi, Mahdjoub Hamdi, Yujie Wang, Biwen Wang, Richard Laforest, Matthew Brier, Yasheng Chen, Hongyu An","doi":"10.1186/s40658-026-00898-w","DOIUrl":"10.1186/s40658-026-00898-w","url":null,"abstract":"&lt;p&gt;&lt;strong&gt;Purpose: &lt;/strong&gt;High-quality 4D dynamic PET imaging is often compromised by noise, especially in low-count frames, which limits clinical utility and quantitative accuracy. This study proposes a novel spatiotemporal denoising method (SPRINTER) that integrates anatomical priors, self-supervised adaptive principal component analysis (aPCA), and deep learning to enhance image quality and preserve time activity fidelity without relying on ground-truth data.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Methods: &lt;/strong&gt;The method combines anatomically guided aPCA-based temporal smoothing with a supervised 3D ResUNet for spatial denoising. The resulting high signal-to-noise ratio, spatially denoised images are iteratively refined using a temporal regularization strategy to enhance contrast. The model was trained using brain scan datasets from 220 participants who were administered one of the following PET/MRI radiotracers: &lt;sup&gt;18&lt;/sup&gt;F-AV45, &lt;sup&gt;18&lt;/sup&gt;F-FDG, &lt;sup&gt;15&lt;/sup&gt;O-HO, &lt;sup&gt;15&lt;/sup&gt;O-OO, and &lt;sup&gt;11&lt;/sup&gt;C-PiB for generalizability testing. Evaluations were performed on synthetic simulations with known ground-truth data and real acquired brain scan data. We compared the proposed method against multiple baseline approaches, including conventional reconstruction (OSEM), spatial-only and temporal-only denoising strategies, and two unsupervised reference methods: Non-Local Means (NLM) filtering, a classical denoising approach, and Noise2Void (N2V). These baselines were selected to reflect both conventional and recent unsupervised deep learning denoising paradigms applicable to PET imaging. Performance was assessed using both synthetic simulations with known ground truth and real acquired PET data. In addition to voxel-level image quality metrics, the impact of denoising on downstream quantitative analysis was evaluated using Ki parametric imaging derived from simulation data. This enabled direct assessment of tracer kinetic estimation accuracy across different denoising strategies.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Results: &lt;/strong&gt;We compared SPRINTER with OSEM, spatial-only, temporal-only, and two existing unsupervised denoising approaches, including NLM and Noise2Void. Across both simulation and acquired datasets, SPRINTER significantly outperformed all comparison methods (p &lt; 0.05, ANOVA with Bonferroni multiple comparison corrections). The largest gains were observed for the noisiest data using &lt;sup&gt;15&lt;/sup&gt;O-HO and &lt;sup&gt;15&lt;/sup&gt;O-OO tracers, where SPRINTER achieved marked SNR improvements in acquired data (e.g., &lt;sup&gt;15&lt;/sup&gt;O-HO: 3.92 ± 1.28 vs. 2.68 ± 1.24; p = 0.096; &lt;sup&gt;15&lt;/sup&gt;O-OO: 3.71 ± 1.79 vs. 2.53 ± 1.15 for NLM; p = 0.082). These improvements were consistently superior to those obtained with NLM and Noise2Void, which showed either spatial blurring or limited performance in low-count frames. In simulation studies, SPRINTER significantly reduced voxel-wise reconstruction error compared to all baselines (NRMSE: 0.07 ± 0.04 and 0.09 ± 0.05 vs. 0.33 ± 0.08 to 0.07 an","PeriodicalId":11559,"journal":{"name":"EJNMMI Physics","volume":" ","pages":""},"PeriodicalIF":3.5,"publicationDate":"2026-06-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13575004/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148276296","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Limitations in diagnostics and quantification of small lesions with low uptake in the clinical context of prostate ¹⁸F/⁶⁸Ga-PSMA PET/MRI.","authors":"Maike E Lindemann, Walter Jentzen, Alina Küper, Pedro Fragoso Costa, Marcel Gratz, Lale Umutlu, James Nagarajah, Stephan G Nekolla, Ivo Rausch, Ken Herrmann, Harald H Quick, David Kersting","doi":"10.1186/s40658-026-00902-3","DOIUrl":"10.1186/s40658-026-00902-3","url":null,"abstract":"<p><strong>Purpose: </strong>The aim of this study was to investigate the limits of diagnostics and therapy planning for patients with prostate cancer using non-time-of-flight ¹⁸F/⁶⁸Ga-PSMA PET/MRI under clinically challenging imaging conditions with small lesion sizes and low uptake. Lesion detectability and quantification accuracy were evaluated for different acquisition and reconstruction parameters in a systematic phantom study and subsequent on patient data.</p><p><strong>Methods: </strong>PET/MRI measurements were performed using a small lesion NEMA phantom. PET data were acquired for nine different activity concentrations (AC). Data of a longer single-bed protocol in the pelvis or a shorter whole-body protocol were reconstructed using relative or absolute scatter correction (SC). PET images were analysed considering a ± 25% deviation range between imaged and true AC as acceptable. Thirteen PSMA-PET/MRI patients with primary lesions or lymph node metastasis < 12 mm in the pelvis were included in this study. The presence of the halo artefact was evaluated in six ¹⁸F-PSMA and seven ⁶⁸Ga-PSMA PET/MRI patients. For 21 lesions (diameter 6.4-12.3 mm) in total, the AC was quantified.</p><p><strong>Results: </strong>For both radiotracers, the 9.7 mm sphere was still visible at 0.16 kBq/mL with emission times > 40 min. The 3.7 mm sphere was only detectable at 22 kBq/mL with emission times > 4 min. All spheres ≥ 6.5 mm provide acceptable quantification at an AC of 1.32 kBq/mL for ¹⁸F PET/MRI protocols of ≥ 12 min and 2.75 kBq/mL for ⁶⁸Ga PET/MRI protocols. In phantom data, no halo artefact was observable and different SC methods had no impact on quantification. 4/6 ¹⁸F-PSMA patients and 7/7 ⁶⁸Ga-PSMA patients showed a halo around the bladder using relative SC, which could be reduced in all patients using absolute SC. Comparing the minimum quantifiable AC (MQAC) from in the phantom study as a threshold to the patient data, all lesions provided acceptable quantification with values > MQAC (AC 3.3-108.5 kBq/mL) for equal reconstruction and acquisition parameters.</p><p><strong>Conclusions: </strong>The results demonstrated that the detection of lesions in the sub-centimetre range and a reliable quantification of ¹⁸F/⁶⁸Ga-PSMA uptake using standard acquisition and reconstruction parameters within clinical PET/MRI protocols is possible. This allows for an individual assessment of potential therapy options for each patient.</p>","PeriodicalId":11559,"journal":{"name":"EJNMMI Physics","volume":" ","pages":""},"PeriodicalIF":3.5,"publicationDate":"2026-06-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13287300/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148257826","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"High-resolution PET detectors with dual-ended readout using cost-effective highly multiplexed readout circuit and MPT2321 ASIC.","authors":"Zhiqiang Zhu, Denghong Ren, Weiming Chen, Wei Shen, Xianchao Huang, Ning Ren, Zhonghua Kuang, Zhanli Hu, Yongfeng Yang, Zheng Liu","doi":"10.1186/s40658-026-00908-x","DOIUrl":"10.1186/s40658-026-00908-x","url":null,"abstract":"<p><strong>Background: </strong>Small-animal positron emission tomography (PET) imaging is commonly employed in biomedical research to accelerate the translation of the discovery in the fields of molecular and cellular biology into the clinical practice. Its performance and cost are largely dependent on the employed detectors and electronics. In this work, a new electronics scheme aiming to simplify PET electronics is evaluated using two dual-ended readout PET detectors with high spatial resolution.</p><p><strong>Methods: </strong>The first detector is composed of a 16 × 16 lutetium-yttrium oxyorthosilicate (LYSO) array with crystal dimensions of 1.45 × 1.45 × 20 mm³. The second detector is composed of a 26 × 26 LYSO array with crystal dimensions of 0.75 × 0.75 × 20 mm³. Both LYSO arrays are dual-ended read out by 8 × 8 Hamamatsu S14161-3050HS-08 silicon photomultiplier (SiPM) arrays with a sensitive pixel area of 3 × 3 mm² and a pitch of 3.2 mm. The 64 outputs of the SiPM array are read out by a highly multiplexed row-column summation network to convert them to four position-encoded energy signals. The four signals are processed by a commercial 32-channel MPT2321 ASIC. The flood map, energy resolution, depth of interaction (DOI) resolution, and timing resolution of the detectors are measured.</p><p><strong>Results: </strong>The first detector provided a flood map with all crystals resolved and an average peak-to-valley ratio (PVR) of 3.59 was obtained for the flood map quality, an energy resolution of 14.2 ± 0.4%, a DOI resolution of 3.04 ± 0.37 mm and a detector timing resolution (DTR) of 2.24 ± 0.10 ns. The second detector provided a flood map with all crystals resolved and an average PVR of 2.61 was obtained, an energy resolution of 15.3 ± 0.7%, a DOI resolution of 2.56 ± 0.46 mm and a DTR of 2.38 ± 0.20 ns.</p><p><strong>Conclusion: </strong>The electronics scheme evaluated in this study provides competitive energy and DOI performance for high-resolution small-animal PET detectors while significantly reducing electronics channel count and system complexity.</p>","PeriodicalId":11559,"journal":{"name":"EJNMMI Physics","volume":" ","pages":""},"PeriodicalIF":3.5,"publicationDate":"2026-06-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13534385/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148249683","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}