IEEE Transactions on Radiation and Plasma Medical Sciences最新文献

{"title":"Attenuation Pre-Correction in Iterative PET Image Reconstruction: What is the Statistical Cost?","authors":"Yifan Hu, Kathryn Fontaine, Yassir Najmaoui, Thibault Marin, Richard E Carson","doi":"10.1109/trpms.2026.3738670","DOIUrl":"10.1109/trpms.2026.3738670","url":null,"abstract":"<p><p>Attenuation pre-correction (APC) is an effective strategy to reduce the computational cost of iterative PET image reconstruction by decoupling object-dependent attenuation effects from the system sensitivity image. However, APC alters the statistical properties of the projection data, leading to a mismatch between the assumed Poisson likelihood and the true data distribution. In this work, we investigate the statistical cost of APC in terms of image variance increase. By modeling APC reconstruction as a misspecified likelihood problem, we derive the variance lower bound using the Godambe information matrix (GIM), which provides a principled alternative to the conventional Fisher information matrix. To enable efficient computation for large-scale three-dimensional PET systems, we introduce a zero-picosecond time-of-flight (ZPT) assumption and derive a closed-form expression for the variance ratio of APC relative to MLEM. Theoretical predictions are validated against simulations using iterative reconstruction. Simulations demonstrate that attenuation heterogeneity along the contributing lines of response is the dominant factor driving APC-induced variance increase, while the impact of TOF resolution becomes secondary for modern TOF PET systems with timing resolution on the order of 200 ps. Three-dimensional evaluations with ZPT across different scanner geometries show large increases (>100%) in lesion variance on whole-body and total-body scanners, while a more moderate increase is observed on a brain-dedicated scanner. Experimental validation using human PET data further confirms the theoretical findings. This work provides a quantitative framework for evaluating the statistical cost of APC PET reconstruction.</p>","PeriodicalId":46807,"journal":{"name":"IEEE Transactions on Radiation and Plasma Medical Sciences","volume":" ","pages":""},"PeriodicalIF":3.8,"publicationDate":"2026-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13665234/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149197000","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.2026.3726151","DOIUrl":"https://doi.org/10.1109/TRPMS.2026.3726151","url":null,"abstract":"","PeriodicalId":46807,"journal":{"name":"IEEE Transactions on Radiation and Plasma Medical Sciences","volume":"10 7","pages":"C3-C3"},"PeriodicalIF":3.8,"publicationDate":"2026-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11677015","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148877904","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 Publication Information","authors":"","doi":"10.1109/TRPMS.2026.3726149","DOIUrl":"https://doi.org/10.1109/TRPMS.2026.3726149","url":null,"abstract":"","PeriodicalId":46807,"journal":{"name":"IEEE Transactions on Radiation and Plasma Medical Sciences","volume":"10 7","pages":"C2-C2"},"PeriodicalIF":3.8,"publicationDate":"2026-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11677016","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148877919","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":"Sensitivity and Count Rate Performance Studies of the BrainPET-7T Insert With 18F, 124I, and 22Na","authors":"Debora Niekämper;Lutz Tellmann;Jürgen J. Scheins;Chris Hoffmann;Stefan Spellerberg;Elisabeth Pfaehler;Natia Beriashvili;Keith George Ciantar;N. Jon Shah;Christoph Lerche","doi":"10.1109/TRPMS.2025.3650091","DOIUrl":"https://doi.org/10.1109/TRPMS.2025.3650091","url":null,"abstract":"The BrainPET-7T insert is designed for simultaneous human-brain positron emission tomography imaging with ultrahigh-field MRI. It offers a high sensitivity and signal-to-noise ratio by detector blocks of pixelated LSO scintillators with a height of 2.4cm, digital silicon photomultiplier readout, and enhanced data processing methods. This makes it particulary interesting for &lt;inline-formula&gt; &lt;tex-math&gt;$pmb {beta ^{+}}text {-}pmb {gamma }$ &lt;/tex-math&gt;&lt;/inline-formula&gt;-emitter applications, such as dual-isotope imaging, which rely on the detection of triple coincidences. We investigated the scanner sensitivity using the isotopes &lt;inline-formula&gt; &lt;tex-math&gt;${}^{124}rm {I}$ &lt;/tex-math&gt;&lt;/inline-formula&gt; and &lt;inline-formula&gt; &lt;tex-math&gt;${}^{22}rm {Na}$ &lt;/tex-math&gt;&lt;/inline-formula&gt;, in comparison to &lt;inline-formula&gt; &lt;tex-math&gt;${}^{18}rm {F}$ &lt;/tex-math&gt;&lt;/inline-formula&gt;. Count rate performance was assessed using &lt;inline-formula&gt; &lt;tex-math&gt;${}^{124}rm {I}$ &lt;/tex-math&gt;&lt;/inline-formula&gt; and &lt;inline-formula&gt; &lt;tex-math&gt;${}^{18}rm {F}$ &lt;/tex-math&gt;&lt;/inline-formula&gt; for different energy window settings with an analysis following the NEMA NU 2-2018 protocol. For the count rate determination, an adapted strategy for estimating the scatter fraction (SF) for &lt;inline-formula&gt; &lt;tex-math&gt;$pmb {beta ^{+}}text {-}pmb {gamma }$ &lt;/tex-math&gt;&lt;/inline-formula&gt;-emitters was applied. The peak double coincidence sensitivity for &lt;inline-formula&gt; &lt;tex-math&gt;${}^{18}rm {F}$ &lt;/tex-math&gt;&lt;/inline-formula&gt; measured at the center and off-center was between &lt;inline-formula&gt; &lt;tex-math&gt;$pmb {mathrm {(10.16pm 0.08)~%}}$ &lt;/tex-math&gt;&lt;/inline-formula&gt; and &lt;inline-formula&gt; &lt;tex-math&gt;$pmb {mathrm {(12.37pm 0.10)~%}}$ &lt;/tex-math&gt;&lt;/inline-formula&gt; for energy windows of 440keV to 594keV and 420keV to 650keV. The true triple sensitivities obtained at the isocenter were &lt;inline-formula&gt; &lt;tex-math&gt;$pmb {mathrm {(3.13pm 0.09)~%}}$ &lt;/tex-math&gt;&lt;/inline-formula&gt; and &lt;inline-formula&gt; &lt;tex-math&gt;$pmb {mathrm {(4.88pm 0.12)~%}}$ &lt;/tex-math&gt;&lt;/inline-formula&gt; for &lt;inline-formula&gt; &lt;tex-math&gt;${}^{124}rm {I}$ &lt;/tex-math&gt;&lt;/inline-formula&gt; and between &lt;inline-formula&gt; &lt;tex-math&gt;$pmb {mathrm {(0.8662pm 0.23)~%}}$ &lt;/tex-math&gt;&lt;/inline-formula&gt; and &lt;inline-formula&gt; &lt;tex-math&gt;$pmb {mathrm {(3.112pm 0.05)~%}}$ &lt;/tex-math&gt;&lt;/inline-formula&gt; for &lt;inline-formula&gt; &lt;tex-math&gt;${}^{22}rm {Na}$ &lt;/tex-math&gt;&lt;/inline-formula&gt; depending on the selected energy window and rejection rule. The maximum &lt;inline-formula&gt; &lt;tex-math&gt;$pmb {R_{mathrm {NEC}}}$ &lt;/tex-math&gt;&lt;/inline-formula&gt; of the &lt;inline-formula&gt; &lt;tex-math&gt;${}^{18}rm {F}$ &lt;/tex-math&gt;&lt;/inline-formula&gt;-measurement was 276kcps at 16.3kBqmL&lt;inline-formula&gt; &lt;tex-math&gt;${}^{{{-}1}}$ &lt;/tex-math&gt;&lt;/inline-formula&gt;, while the maximum &lt;inline-formula&gt; &lt;tex-math&gt;$pmb {R_{mathrm {true}}}$ &lt;/tex-math&gt;&lt;/inline-formula&gt; was 780kcps at 22.7kBqmL&lt;inline-formula&gt; &lt;tex-math&gt;${}^{{{-}1}}$ &lt;/tex-math&gt;&lt;/inline-formula&gt; for an energy window of 440keV to 594keV. The SF ranged from 28% to 33% and the random f","PeriodicalId":46807,"journal":{"name":"IEEE Transactions on Radiation and Plasma Medical Sciences","volume":"10 7","pages":"1152-1160"},"PeriodicalIF":3.8,"publicationDate":"2026-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11357519","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148877880","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":"Simulation Study of a Scintillation Photon Counting TOF-PET Detector Using a Monolithic Crystal and SiPM Array","authors":"Seungeun Lee;Woon-Seng Choong;Joshua W. Cates","doi":"10.1109/TRPMS.2026.3651965","DOIUrl":"https://doi.org/10.1109/TRPMS.2026.3651965","url":null,"abstract":"Time-of-flight positron emission tomography (TOF-PET) detectors capable of advancing coincidence time resolution (CTR) beyond what is currently achieved in state-of-the-art commercial systems can enable higher reconstructed signal-to-noise-ratio (SNR) and image quality due to a number of benefits that stem from more accurate localization of annihilation events along system lines-of-response. The focus of current efforts in this research area is to push system CTR <inline-formula> <tex-math>$leq 100$ </tex-math></inline-formula> ps, where significant gains in reconstructed image SNR and quality would be realized. Accomplishing this goal with a detector that does not sacrifice 511-keV photon detection efficiency is aided by optimal use of scintillation photon statistics for advanced time-of-interaction estimators. TOF-PET detectors which can also position 511-keV photon interactions in 3-D benefit from the ability to account for 3-D position of interaction-dependent scintillation photon transit time variance in the time of interaction estimate. We are designing an advanced TOF-PET module to achieve <inline-formula> <tex-math>$leq 100$ </tex-math></inline-formula>-ps CTR and accurate 3-D event positioning based on a scintillation photon counting detector concept. A parametric design study was performed with an experimentally validated Monte Carlo simulation framework to investigate optimal detector geometry and configuration, guided by achievable CTR and 3-D positioning resolution. These studies outline the design of a prototype module to experimentally demonstrate this concept.","PeriodicalId":46807,"journal":{"name":"IEEE Transactions on Radiation and Plasma Medical Sciences","volume":"10 7","pages":"1113-1123"},"PeriodicalIF":3.8,"publicationDate":"2026-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148877940","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":"Development of a Preclinical PET Scanner With DOI Capabilities Using Semi-Monolithic Detectors","authors":"Neus Cucarella;Marta Freire;Antonio J. González;David Sánchez;Andrea Gonzalez-Montoro;Santiago Jiménez-Serrano;Francis Loignon-Houle;Laura Moliner;Celia Valladares;Peter Bruyndonckx;Carlos Correcher;José M. Benlloch","doi":"10.1109/TRPMS.2025.3648052","DOIUrl":"https://doi.org/10.1109/TRPMS.2025.3648052","url":null,"abstract":"Most preclinical positron emission tomography (PET) scanners are based on pixelated detectors without depth-of-interaction (DOI) capabilities, which is crucial to correct for parallax errors. Semi-monolithic crystals have the potential to combine the timing capabilities of pixelated crystals and the 3-D positioning accuracy of monolithic scintillators. In this work, we present a preclinical PET prototype consisting of 2 rings defining an inner diameter of 106 mm and an axial length of 52 mm. Each ring contains 14 arrays of <inline-formula> <tex-math>$1~mathrm {times }~22$ </tex-math></inline-formula> LYSO slabs of 0.97 mm <inline-formula> <tex-math>$mathrm {times }~25$ </tex-math></inline-formula>.6 mm <inline-formula> <tex-math>$mathrm {times }$ </tex-math></inline-formula> 12 mm, coupled to <inline-formula> <tex-math>$8~mathrm {times }~8$ </tex-math></inline-formula> silicon photomultiplier arrays. The sensitivity, spatial resolution, count rate performance, and image quality (IQ) were studied using the NEMA NU 4-2008 protocol. All images were reconstructed using the maximum-likelihood expectation–maximization algorithm with 0.5 mm3 voxel size, including DOI information and normalization correction. A mean spatial resolution for all measured positions and across the three directions (axial, transaxial, and radial) of <inline-formula> <tex-math>$1.61~mathrm {pm }~0$ </tex-math></inline-formula>.19 mm was obtained at the center of the field of view. A peak sensitivity of 3.5% was obtained at the center of the scanner, for an energy window (EW) between 358 and 664 keV. The noise equivalent count rate peak reached 106.9 kcps for an activity of 11.7 MBq using the mouse-sized phantom, the same EW window, and a time coincidence window of 10 ns. For the IQ phantom, contrast recovery coefficients of 0.20, 0.62, 0.75, 0.81, and 0.85 were found for the 1, 2, 3, 4, and 5 mm rods, respectively. Spill-over-ratio values of 0.10 for air-filled and 0.23 for water-filled cylinders were measured. Also, according to the Rayleigh criterion, 1.5, 1.2, and 1 mm hot spots of a micro-Derenzo phantom were well distinguished.","PeriodicalId":46807,"journal":{"name":"IEEE Transactions on Radiation and Plasma Medical Sciences","volume":"10 7","pages":"1143-1151"},"PeriodicalIF":3.8,"publicationDate":"2026-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11313865","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148877894","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":"SGS-Mamba: Semantic Gap-Sensitive Mamba Network for Medical Small Lesion Segmentation","authors":"Xiaoshan Xie;Zhiheng Zhou;Wenlve Zhou;Xu Jing;Ming Deng","doi":"10.1109/TRPMS.2026.3653810","DOIUrl":"https://doi.org/10.1109/TRPMS.2026.3653810","url":null,"abstract":"Accurate segmentation of small lesions is critical for the early diagnosis and intervention of severe diseases. U-shaped networks (U-Nets) are widely used models for lesion segmentation, renowned for their strong feature extraction capabilities and encoder–decoder architecture, which incorporates direct skip connection (DSC) to preserve spatial details. However, their decoders often exhibit information-specific biases toward the content provided by DSC due to the semantic gap between the encoder–decoder feature sets, rather than maintaining a strict one-to-one correspondence. This semantic mismatch reduces their effectiveness in segmenting small lesions with weak or indistinct features, thereby failing to meet high-precision clinical requirements. To address this limitation, we propose the semantic gap-sensitive mamba U-shaped network (SGS-Mamba), enhancing sensitivity to small lesions across three dimensions: 1) long-range interaction; 2) guided filtering; and 3) semantic alignment. Specifically, an adaptive visual state space block is designed to focus on small lesions by leveraging long-range contextual modeling. A self-guided filtering attention (SGFA) at the bottleneck is employed to enhance small lesions through noise suppression and attention focus. The semantic gap-sensitive skip connection (SGSC), incorporating cross-guided filtering module and Rényi divergence regularization, are designed to bridge the semantic gap through long-range interaction and semantic alignment. Experiments conducted on three small lesion datasets and one multilabel dataset demonstrate state-of-the-art performance, while maintaining competitive computational efficiency. Furthermore, when the SGFA and SGSC modules are integrated as plug-and-play components within other architectures, they consistently yield substantial improvements, underscoring that their benefits generalize effectively across diverse architectures and tasks.","PeriodicalId":46807,"journal":{"name":"IEEE Transactions on Radiation and Plasma Medical Sciences","volume":"10 7","pages":"1049-1060"},"PeriodicalIF":3.8,"publicationDate":"2026-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148877881","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":"HANS-Net: Hyperbolic Convolution and Adaptive Temporal Attention for Accurate and Generalizable Liver and Tumor Segmentation in CT Imaging","authors":"Arefin Ittesafun Abian;Ripon Kumar Debnath;Md. Abdur Rahman;Mohaimenul Azam Khan Raiaan;Md Rafiqul Islam;Asif Karim;Reem E. Mohamed;Sami Azam","doi":"10.1109/TRPMS.2026.3654628","DOIUrl":"https://doi.org/10.1109/TRPMS.2026.3654628","url":null,"abstract":"Accurate liver and tumor segmentation on abdominal CT images is critical for reliable diagnosis and treatment planning, but remains challenging due to complex anatomical structures, variability in tumor appearance, and limited annotated data. To address these issues, we introduce hyperbolic-convolutions adaptive-temporal-attention with neural-representation and synaptic-plasticity network (HANS-Net), a novel segmentation framework that synergistically combines hyperbolic convolutions (HCs) for hierarchical geometric representation, a wavelet-inspired decomposition module for multiscale texture learning, a biologically motivated synaptic plasticity mechanism for adaptive feature enhancement, and an implicit neural representation (INR) branch to model fine-grained and continuous anatomical boundaries. In addition, we incorporate uncertainty-aware Monte Carlo dropout to quantify prediction confidence and lightweight temporal attention to improve interslice consistency without sacrificing efficiency. Extensive evaluations of the liver tumor segmentation challenge (LiTS) dataset demonstrate that HANS-Net achieves a mean Dice score of 93.26%, an IoU of 88.09%, an average symmetric surface distance (ASSD) of 0.72 mm, and a volume overlap error (VOE) of 11.91%. Furthermore, cross-dataset validation on the AMOS 2022 dataset obtains an average Dice of 85.09%, IoU of 76.66%, ASSD of 19.49 mm, and VOE of 23.34%, indicating strong generalization across different datasets. These results confirm the effectiveness and robustness of HANS-Net in providing anatomically consistent, accurate, and confident liver and tumor segmentation.","PeriodicalId":46807,"journal":{"name":"IEEE Transactions on Radiation and Plasma Medical Sciences","volume":"10 7","pages":"1061-1074"},"PeriodicalIF":3.8,"publicationDate":"2026-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148877962","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":"LAC3DUnet: Local Attention Capsule 3D-Unet for Pixel-Level 3-D Brachytherapy Dose Prediction in Brain Therapy","authors":"Jingjing Zhang;Huazhi Cui;Xiaokun Hu;Teng Li","doi":"10.1109/TRPMS.2026.3656596","DOIUrl":"https://doi.org/10.1109/TRPMS.2026.3656596","url":null,"abstract":"Background: Gliomas are one of the most common malignant tumors in the brain’s nervous system. Brachytherapy allows precise treatment of gliomas while reducing damage to other normal tissues. In practice, clinicians need to adjust the radiotherapy plan several times to determine the particle positions for optimal dose distribution. Much progress has been made in deep learning-based external radiation therapy, but reliable prediction methods are still lacking for brachytherapy. Purpose: To fill the gap in brachytherapy, this study developed the local attention capsule 3D-Unet (LAC3DUnet) for predicting 3-D dose distributions for glioblastoma brachytherapy. Methods: A local attention module has been integrated before each downsampling stage to improve the model by capturing intricate local features. In addition, a capsule module has been included before the final downsampling layer, amalgamating multiple features into a comprehensive vector. This enhancement substantially boosts the model’s capability to recognize crucial features within intricate 3-D brain structures. Results: The mean absolute error (MAE) for all voxels of body is 3.04% for all tested plans. It is improved by 5.21%, 1.95%, and 1.55% over the comparative 3D-Unet, HDUnet, and ResNet, respectively. Our model performs very well on the clinical indicators D100, D90, D80, V200, V100, and V90, and the errors between most of the indicators and the values of the indicators given by the doctors are achieved to be the lowest among the compared models. Only D90 and V200 have slightly larger errors than the comparison model. Conclusions: The LAC3DUnet demonstrates higher accuracy in dose prediction and excels those existing dose prediction models. It provides an effective model in assisting current automation of treatment planning in Brachytherapy for glioblastoma.","PeriodicalId":46807,"journal":{"name":"IEEE Transactions on Radiation and Plasma Medical Sciences","volume":"10 7","pages":"1161-1168"},"PeriodicalIF":3.8,"publicationDate":"2026-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148877909","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":"Design and Evaluation of a 2.5D-Assembled High-Density Detection Module for the Ultrahigh Resolution Brain PET Scanner","authors":"Jonathan Bouchard;Arnaud Samson;Romain Espagnet;Caroline Paulin;Nicolas Viscogliosi;Jean-François Beaudoin;Louis Arpin;Charles Bourcier-Guérette;Roger Lecomte;Réjean Fontaine","doi":"10.1109/TRPMS.2025.3643324","DOIUrl":"https://doi.org/10.1109/TRPMS.2025.3643324","url":null,"abstract":"The LabPET II modular technology was identified as a promising platform for a new generation of ultrahigh resolution (UHR) brain Positron emission tomography (PET) scanners. Scaling up from preclinical systems to achieve a human brain field-of-view introduces significant challenges that require high-density, low-noise detection modules (DMs) capable of dissipating over 1.1 kW of heat within a confined volume. To address these constraints, a new UHR DM, referred to as the UHR-DM, was developed based on a 2.5-D stacked printed circuit board architecture. This design embeds two readout application-specific integrated circuits (ASICs) between two circuit boards to enhance thermal management, mechanical alignment, and electrical performance, while preserving full backward compatibility with the existing LabPET II platform. This article presents a detailed comparison between the UHR-DM and the original LabPET II DM (LP2-DM). Key improvements include improved heat extraction through direct conduction, reduced parasitic capacitance via shorter and more uniform trace routing, and enhanced noise immunity enabled by embedded shielding. A dedicated testbench was used to evaluate thermal performance, baseline stability, noise characteristics, intrinsic and full-system coincidence time resolution (CTR), and time-over-threshold (ToT) energy resolution. Results show that the UHR-DM design reduces ASIC operating temperature by up to 43%, lowers noise by 60% when using high electronic gains, and improves channel-to-channel noise uniformity. It also achieves more consistent CTR and energy resolution without compromising any performance aspect of the original design. These enhancements will facilitate the upcoming integration all 129 024 individual channels required by the UHR brain PET scanner to achieve a spatial resolution of 1.25 mm at the center of the field of view.","PeriodicalId":46807,"journal":{"name":"IEEE Transactions on Radiation and Plasma Medical Sciences","volume":"10 7","pages":"1099-1112"},"PeriodicalIF":3.8,"publicationDate":"2026-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148877934","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}