IEEE Transactions on Radiation and Plasma Medical Sciences最新文献

{"title":"Adaptation of a Brain-Dedicated Multipinhole SPECT System for Imaging Higher-Energy Photons of Theranostic Agents—A Simulation Study","authors":"Sophia Pells;Kesava S. Kalluri;Micaehla May;Benjamin Auer;Lars R. Furenlid;Matthew A. Kupinski;Phillip H. Kuo;Robert Licho;Michael A. King","doi":"10.1109/TRPMS.2026.3651065","DOIUrl":"https://doi.org/10.1109/TRPMS.2026.3651065","url":null,"abstract":"Multipinhole single-photon emission computed tomography (SPECT) of the brain is capable of producing high-resolution images. However, pinhole imaging of high-energy photons remains challenging due to the tradeoff of greatly sacrificing sensitivity to limit penetration through the edges of the pinholes and system shielding. The impact of photon penetration on spatial resolution, image contrast, and lesion signal-to-noise was assessed through simulation for the brain-dedicated multipinhole system AdaptiSPECT-C. In addition, minor changes to the system design to reduce penetration were considered; these were updating the materials of the pinhole aperture edges and shutters to a higher-density tungsten alloy and including platinum in the shielding around the pinhole apertures. A significant degradation in spatial resolution, image contrast, and signal-to-noise above approximately 200 keV was found with the current system design. It was shown that adapting the pinhole and shutter material to a higher-density tungsten alloy would greatly reduce this degradation and permit multipinhole imaging with 177Lu and 111In in the human brain. Incorporating a small amount of platinum around each aperture further improved the system point-spread function. However, results indicate high-resolution imaging of 131I would require a larger modification to the system design.","PeriodicalId":46807,"journal":{"name":"IEEE Transactions on Radiation and Plasma Medical Sciences","volume":"10 6","pages":"959-968"},"PeriodicalIF":3.8,"publicationDate":"2026-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148442883","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Exploring Anti-Coincidence Technique for Scattering Contamination Rejection in a Simultaneous PET/SPECT Imaging System","authors":"Yifei Jin;Junwei Du;Simon R. Cherry;Ling-Jian Meng","doi":"10.1109/TRPMS.2025.3649623","DOIUrl":"https://doi.org/10.1109/TRPMS.2025.3649623","url":null,"abstract":"Simultaneous PET/SPECT imaging instruments could enable comprehensive molecular characterization by combining the very high sensitivity and spatial resolution of PET with the ability to image a broad range of radionuclides, including therapeutic isotopes with SPECT. While PET and SPECT hardware can be integrated into a single hardware system, one of the major challenges in simultaneous PET/SPECT imaging is the down-scatter contamination from PET tracers, which can significantly degrade SPECT image quality and quantitative accuracy. In this study, we evaluated the efficacy of using anti-coincidence and active shielding techniques to reject the down-scatter contamination in SPECT data. Using GEANT4 simulations, we analyzed the performance tradeoffs resulting from different choices of active shielding component design, coincidence time windows, and SPECT detector materials (CZT versus GAGG). The anti-coincidence technique effectively rejected contamination events, achieving a signal-to-noise <inline-formula> <tex-math>$(mathbf {mathrm {SNR}})$ </tex-math></inline-formula> enhancement from 0.29 to 1.48 and noise equivalent count rate <inline-formula> <tex-math>$(mathbf {mathrm {NECR}})$ </tex-math></inline-formula> improvement from 41.3 to 89.1 cps with moderate active shielding. Even without active shielding, anti-coincidence alone significantly improved SPECT image quality (<inline-formula> <tex-math>$mathbf {mathrm {SNR}}$ </tex-math></inline-formula>: 1.38; <inline-formula> <tex-math>$mathbf {mathrm {NECR}}$ </tex-math></inline-formula>: 87.0 cps), making it practical for systems where shielding is constrained. In reconstructed images, anti-coincidence improved contrast from 0.78 (raw) to 0.96 and reduced noise from 1508 to 257 counts, outperforming traditional triple-energy-window (TEW) correction (contrast: 0.84; noise: 855). The anti-coincidence technique is also compatible with post-processing scatter corrections, offering a promising strategy for future hybrid PET/SPECT systems in both preclinical and clinical settings.","PeriodicalId":46807,"journal":{"name":"IEEE Transactions on Radiation and Plasma Medical Sciences","volume":"10 6","pages":"908-919"},"PeriodicalIF":3.8,"publicationDate":"2026-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11318973","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148443041","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"IEEE Transactions on Radiation and Plasma Medical Sciences Information for Authors","authors":"","doi":"10.1109/TRPMS.2026.3705473","DOIUrl":"https://doi.org/10.1109/TRPMS.2026.3705473","url":null,"abstract":"","PeriodicalId":46807,"journal":{"name":"IEEE Transactions on Radiation and Plasma Medical Sciences","volume":"10 6","pages":"C3-C3"},"PeriodicalIF":3.8,"publicationDate":"2026-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11595782","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148442539","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"On the Benefits of Quantum Entanglement and Compton Kinematics for Scatter Discrimination in PET Imaging","authors":"M. Moulin;G. Montémont;S. Stanchina;J. M. Létang","doi":"10.1109/TRPMS.2025.3649798","DOIUrl":"https://doi.org/10.1109/TRPMS.2025.3649798","url":null,"abstract":"This article compares methods for rejecting in-patient scattered photons in positron emission tomography instruments, which can degrade image quality by introducing bias and noise. The focus is on events where both annihilation photons interact several times in the detection medium. Compton scattering physics and annihilation photon polarization entanglement are utilized. Events are classified by the number of hits in the detector to assess information quality, and the spatial response from lines of response or Compton cones (CCs) is analyzed. A comparison between methods is made through a simulation of an ideal cylindrical detector with a radius of 15 cm and a thickness of 1 cm, using Geant4. Results from the simulations are used to create histograms for the different observables. Metrics, such as receiver-operating-characteristic (ROC) curves and noise equivalent count (NEC), are used to quantify the efficiency of each method and the influence of hit multiplicity. Alongside this simulation-based investigation, an experiment using a pair of CdZnTe Compton cameras has been set up to validate the entanglement model and its integration simulation. We demonstrate that entanglement information may be considered less valuable, achieving an area under the ROC curve of 52% compared to energy deposition and Compton kinematics, which have an area of 97%. Finally, the obtained detective quantum efficiency (DQE) demonstrates the superiority of CCs for low resolution, up to around 0.05 cm−1, followed by the line of response, which achieves a spatial bandwidth of 1.6 cm−1, thus showing the complementarity between the two types of information. This study highlights the importance of Compton kinematics and the limited value of entanglement for rejecting scattered events.","PeriodicalId":46807,"journal":{"name":"IEEE Transactions on Radiation and Plasma Medical Sciences","volume":"10 6","pages":"930-941"},"PeriodicalIF":3.8,"publicationDate":"2026-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148442461","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Spatiotemporal Deformable Transformer for Lung Cancer Risk Prediction Using Low-Dose CT Images","authors":"Ya-Han Chang;Yi-Hui Lin;Hsing-Chen Meng;Shawn Wu;Yen-Yu Lin;Chun-Rong Huang","doi":"10.1109/TRPMS.2026.3652592","DOIUrl":"https://doi.org/10.1109/TRPMS.2026.3652592","url":null,"abstract":"Low-dose lung computed tomography (LDCT) has been set as the golden standard for lung cancer screening. Current state-of-the-art computer-aided diagnosis (CAD) methods aim to detect visible lung cancer from LDCT images based on well-labeled training data. To provide early alarms, we aim to predict lung cancer risk and locate the potential lung cancer region by utilizing LDCT images in two consecutive years, i.e., LDCT images of the patient captured in the first year and the second year without pixel-level labels. To achieve this goal, a novel weakly supervised spatiotemporal deformable transformer is proposed. Because LDCT images are captured at different time points without prealignment, our method proposes combining spatial attention maps with temporal deformable attention maps to learn spatiotemporal correlations which represent the tumor progression from LDCT images in consecutive years. To achieve weakly supervised learning of the model, we introduce three losses, including classification loss, patch token loss, and side loss. During inference, spatial attention maps with class information cooperate with spatiotemporal correlations of the test image to locate the potential lung cancer region. In the experiments, the proposed method outperforms the state-of-the-art methods and can localize the lung cancer region with only image-level labels.","PeriodicalId":46807,"journal":{"name":"IEEE Transactions on Radiation and Plasma Medical Sciences","volume":"10 6","pages":"861-871"},"PeriodicalIF":3.8,"publicationDate":"2026-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11345485","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148442577","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"LADA-NeRF: Laminography-Aware Dual-Attention Neural Radiodensity Fields","authors":"Ao Wang;Chuandong Tan;Yujie Liu;Haijun Yu;Fenglin Liu","doi":"10.1109/TRPMS.2025.3640389","DOIUrl":"https://doi.org/10.1109/TRPMS.2025.3640389","url":null,"abstract":"Cone beam computed laminography (CL) is widely used for nondestructive testing of plate-like specimen (PLS). However, its asymmetric, limited-angle scanning trajectory causes severe interlayer aliasing artifacts and structural discontinuities in reconstruction images. Existing neural radiodensity fields (NeRF)-based methods sample points along each ray and mainly focus on the penetration path, while ignoring the inherent hierarchical planar structure of PLS, which leads to suboptimal reconstruction quality. To address this problem, we propose laminography-aware dual-attention NeRFs (LADA-NeRF), which is the first NeRF architecture specifically optimized for CL. Specifically, we derive a CL specific pose matrix to model the asymmetric scanning trajectory and replace conventional CT-based ray sampling with dynamic near-far plane adjustment tailored to laminographic geometry. The dual-attention mechanism integrates intraplane attention block (IPAB) to capture geometric correlations within layered planes and line segment-based attention block (LSAB) to model density dependencies along penetration paths, with complementary feature fusion via element-wise summation. Simulations and physical experiments show that LADA-NeRF significantly outperforms competing methods in suppressing artifacts and recovering structural details, while also highlighting its potential utility in medical imaging applications involving flat structure. Compared with the best-performing algorithm in each group, it achieves an average improvement of 0.58–1.91 dB in 3-D PSNR and 0.019-0.034 in 3-D SSIM, as evidenced by quantitative metrics and visual quality.","PeriodicalId":46807,"journal":{"name":"IEEE Transactions on Radiation and Plasma Medical Sciences","volume":"10 6","pages":"849-860"},"PeriodicalIF":3.8,"publicationDate":"2026-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148442721","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"IEEE Transactions on Radiation and Plasma Medical Sciences Publication Information","authors":"","doi":"10.1109/TRPMS.2026.3705475","DOIUrl":"https://doi.org/10.1109/TRPMS.2026.3705475","url":null,"abstract":"","PeriodicalId":46807,"journal":{"name":"IEEE Transactions on Radiation and Plasma Medical Sciences","volume":"10 6","pages":"C2-C2"},"PeriodicalIF":3.8,"publicationDate":"2026-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11595913","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148442448","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Dual-Input Dynamic Convolution for Positron Range Correction in PET Image Reconstruction","authors":"Youness Mellak;Alexandre Bousse;Thibaut Merlin;Élise Émond;Mikko Hakulinen;Dimitris Visvikis","doi":"10.1109/TRPMS.2025.3647264","DOIUrl":"https://doi.org/10.1109/TRPMS.2025.3647264","url":null,"abstract":"PR blurring degrades positron emission tomography (PET) image resolution, particularly for high-energy emitters like gallium-68 (68Ga). We introduce dual-input dynamic convolution (DDConv), a novel computationally efficient approach trained with voxel-specific positron range (PR) point spread functions (PSFs) from Monte Carlo (MC) simulations and designed to be utilized within an iterative reconstruction algorithm to perform PR correction (PRC). By dynamically inferring local blurring kernels through a trained convolutional neural network (CNN), DDConv captures complex tissue interfaces more accurately than prior methods. Additionally, it also computes the transpose operator, ensuring consistency within iterative PET reconstruction. Comparisons with a state-of-the-art, tissue-dependent correction confirm the advantages of DDConv in recovering higher-resolution details in heterogeneous regions, including bone–soft tissue and lung–soft tissue boundaries. Experiments across digital phantoms and MC-simulated data show that DDConv offers near-MC accuracy and outperforms the state-of-the-art technique, namely spatially-variant and tissue-dependent (SVTD), especially in areas with complex material interfaces. Results from real phantom experiments further confirm DDConv’s robustness and practical applicability: while both DDConv and SVTD performed similarly in homogeneous soft-tissue regions, DDConv provided more accurate activity recovery and sharper delineation at heterogeneous lung–soft tissue interfaces. Our code available at <uri>https://github.com/mellak/ddconv-prc</uri>.","PeriodicalId":46807,"journal":{"name":"IEEE Transactions on Radiation and Plasma Medical Sciences","volume":"10 6","pages":"888-898"},"PeriodicalIF":3.8,"publicationDate":"2026-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148442814","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Quantitative Evaluation of Spatially-Variant Deformations Recovered by Deep Learning on Clinical-Like Breast Lesions","authors":"Min Gao;Juhi Raj;Hassan Rizwan;Bruno Barufaldi;Srilalan Krishnamoorthy;Mael Millardet;Andrew D. A. Maidment;Suleman Surti;Samuel Matej","doi":"10.1109/TRPMS.2025.3649164","DOIUrl":"10.1109/TRPMS.2025.3649164","url":null,"abstract":"The dedicated dual-panel breast-PET (B-PET) scanner can potentially provide improved imaging of breast lesions with higher spatial resolution and sensitivity and lower scanner costs. On the other hand, the dual-panel systems suffer from spatially-variant deformations, due to the limited angular sampling and parallax errors, that need to be mitigated in order to improve visualization and quantification of the breast lesions. Our previous studies demonstrated that the deep-learning approach can significantly reduce spatially-variant deformations in the context of B-PET. However, these studies used only simplified geometric objects with a uniform background for training and testing, which does not fully represent the clinical complexity in B-PET imaging. In this work, we developed a methodology for generation of synthetic clinical-like breast images with complex lesion shapes, including spiculated lesions and following tracer-dependent activity characteristics for [18F]FES and [18F]FDG. Subsequently, the neural network was trained and tested on clinical-like synthetic B-PET data reconstructed using statistical iterative reconstruction (DIRECT-RAMLA) used as the network input. Our results show that the deep learning approach can substantially suppress deformations for both small lesions and the larger phantom itself in dual-panel PET reconstructions. The deep learning approach can also improve quantitative measurements in terms of the lesion contrast metrics and image roughness over the phantom background. A research [18F]FES patient study further confirms the improved visual image quality and a good visual correlation for a heterogeneous lesion with the total body PET imaging result.","PeriodicalId":46807,"journal":{"name":"IEEE Transactions on Radiation and Plasma Medical Sciences","volume":"10 6","pages":"899-907"},"PeriodicalIF":3.8,"publicationDate":"2026-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147610155","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Performance Evaluation of the Time-of-Flight Biograph Vision.X: A Fast Coincidence Time Resolution PET/CT Scanner","authors":"Habib Zaidi;Yazdan Salimi;Mehdi Amini;Gregory Mathoux;Ismini Mainta;Valentina Garibotto","doi":"10.1109/TRPMS.2025.3640401","DOIUrl":"https://doi.org/10.1109/TRPMS.2025.3640401","url":null,"abstract":"This work evaluated the performance characteristics of the Biograph Vision.X PET/CT system according to the National Electrical Manufacturers Association (NEMA) NU 2-2018 standards. This novel system is based on the Biograph Vision 600 with an axial field-of-view (FOV) of 26.1 cm, consisting of 8 rings of 38 detector blocks using the same detector modules combining <inline-formula> <tex-math>$5 times 5$ </tex-math></inline-formula> array of <inline-formula> <tex-math>$3.2 times 3.2 times $ </tex-math></inline-formula> 20 mm lutetium-oxyorthosilicate crystals with <inline-formula> <tex-math>$16 times $ </tex-math></inline-formula> 16 mm array of silicon photomultiplier-based photodetectors. The Biograph Vision.X scanner is a newly released time-of-flight (TOF) whole-body hybrid PET/CT imaging system featuring exclusive proprietary high-performance detector electronic assembly (DEA) technology with optimized digital electronics and digital processing along the entire imaging chain to achieve fast coincidence time resolution PET. In addition, examples of 3-D Hoffman phantom and clinical 18F-FDG brain and whole-body studies were compared with scans performed sequentially after the Biograph Vision 600 PET/CT scanner. The Biograph Vision.X had a radial, tangential and axial spatial resolution in terms of full-width at half-maximum of 3.4, 3.5, and 3.5 mm, respectively, at a 1 cm offset from the center of the FOV. The sensitivity was 19.2 cps/kBq at the center and 10 cm off-center, while the peak noise-equivalent count-rate (NECR) was 291 kcps at 27.2 kBq/mL. The TOF resolution varied from 178.7 to 182.0 ps as the count rate increased up to the peak NECR. Generally, the image contrast observed on the NEMA image quality phantom ranged from 74.1% to 91.8%. The Biograph Vision.X is a competitive newly introduced device outperforming its predecessor, the Biograph Vision 600, by reaching the fastest TOF performance in the industry, thus achieving ~7.5 TOF gain improvement compared to 6.2 on the Vision 600.","PeriodicalId":46807,"journal":{"name":"IEEE Transactions on Radiation and Plasma Medical Sciences","volume":"10 6","pages":"951-958"},"PeriodicalIF":3.8,"publicationDate":"2026-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11284795","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148442959","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}