EJNMMI Physics最新文献

{"title":"A fully automated AI-based method for tumour detection and quantification on [¹⁸F]PSMA-1007 PET-CT images in prostate cancer.","authors":"Elin Trägårdh, Johannes Ulén, Olof Enqvist, Måns Larsson, Kristian Valind, David Minarik, Lars Edenbrandt","doi":"10.1186/s40658-025-00786-9","DOIUrl":"10.1186/s40658-025-00786-9","url":null,"abstract":"<p><strong>Background: </strong>In this study, we further developed an artificial intelligence (AI)-based method for the detection and quantification of tumours in the prostate, lymph nodes and bone in prostate-specific membrane antigen (PSMA)-targeting positron emission tomography with computed tomography (PET-CT) images.</p><p><strong>Methods: </strong>A total of 1064 [¹⁸F]PSMA-1007 PET-CT scans were used (approximately twice as many compared to our previous AI model), of which 120 were used as test set. Suspected lesions were manually annotated and used as ground truth. A convolutional neural network was developed and trained. The sensitivity and positive predictive value (PPV) were calculated using two sets of manual segmentations as reference. Results were also compared to our previously developed AI method. The correlation between manually and AI-based calculations of total lesion volume (TLV) and total lesion uptake (TLU) were calculated.</p><p><strong>Results: </strong>The sensitivities of the AI method were 85% for prostate tumour/recurrence, 91% for lymph node metastases and 61% for bone metastases (82%, 86% and 70% for manual readings and 66%, 88% and 71% for the old AI method). The PPVs of the AI method were 85%, 83% and 58%, respectively (63%, 86% and 39% for manual readings, and 69%, 70% and 39% for the old AI method). The correlations between manual and AI-based calculations of TLV and TLU ranged from r = 0.62 to r = 0.96.</p><p><strong>Conclusion: </strong>The performance of the newly developed and fully automated AI-based method for detecting and quantifying prostate tumour and suspected lymph node and bone metastases increased significantly, especially the PPV. The AI method is freely available to other researchers ( www.recomia.org ).</p>","PeriodicalId":11559,"journal":{"name":"EJNMMI Physics","volume":"12 1","pages":"78"},"PeriodicalIF":3.2,"publicationDate":"2025-08-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12367631/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144947114","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":"Development and validation of 3D super-resolution convolutional neural network for ¹⁸F-FDG-PET images.","authors":"Hiroki Endo, Kenji Hirata, Keiichi Magota, Takaaki Yoshimura, Chietsugu Katoh, Kohsuke Kudo","doi":"10.1186/s40658-025-00791-y","DOIUrl":"10.1186/s40658-025-00791-y","url":null,"abstract":"","PeriodicalId":11559,"journal":{"name":"EJNMMI Physics","volume":"12 1","pages":"77"},"PeriodicalIF":3.2,"publicationDate":"2025-08-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12364773/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144872011","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":"Toward the standardization of radiopharmaceutical therapies: a technical note evaluating a clinical dosimetry workflow for single-time-point ¹⁷⁷Lu SPECT/CT-based therapies.","authors":"Taehyung Peter Kim, Wendy Siman, Vivek Mishra, Santiago Aguirre, Siju C George","doi":"10.1186/s40658-025-00764-1","DOIUrl":"10.1186/s40658-025-00764-1","url":null,"abstract":"<p><strong>Purpose: </strong>The lack of standardized dosimetry workflows in lutetium-177 ( <math><mmultiscripts><mrow></mrow> <mrow></mrow> <mn>177</mn></mmultiscripts> </math> Lu) radiopharmaceutical therapies results in inconsistent absorbed doses and limits treatment planning. This study aims to evaluate the accuracy and variability of a single-time-point ¹⁷⁷Lu SPECT/CT commercial workflow to help harmonize its protocol.</p><p><strong>Methods: </strong>The dosimetry workflow evaluated in this study predominatly followed that of MIM SurePlan^TM MRT. ¹⁷⁷Lu SPECT/CT images of a Jaszczak and a NEMA phantoms were acquired in GE 670 DR scanner. Absorbed dose (Gy/MBq/s) was calculated in the background and sphere inserts with varied reconstruction iterations, calibrations, voxel-based dosimetry methods, and target volume segmentations. Ground truth absorbed doses were created using CT images and voxel S-value (VSV) water kernels. The validity of the density-corrected (DC) kernel for use in ground-truth dosimetry evaluations was further investigated. The accuracy and variability of the dosimetry workflow were evaluated using percent error and the coefficient of variation (CV) of mean absorbed doses.</p><p><strong>Results: </strong>Mean absorbed dose accuracy improved for both the voxel-based VSV and local deposition (LD) methods until 480 equivalent iterations for all target volumes. DC kernel was found viable for creating reference absorbed doses. The calibration CV was 5.18% when phantom and calibration regions were varied. The VSV method demonstrated absorbed doses that were 10 to 150% higher than those calculated with the LD method. The overall variability in absorbed dose reached up to 84% when reconstruction, calibration, dosimetry, and segmentation methods were varied.</p><p><strong>Conclusions: </strong>A single dosimetry workflow has demonstrated markedly large variability in absorbed dose accuracy. By evaluating the accuracy of absorbed dose, our study helped to propose a harmonized MIM SurePlan^TM MRT workflow for single-time-point <math><mmultiscripts><mrow></mrow> <mrow></mrow> <mn>177</mn></mmultiscripts> </math> Lu SPECT/CT-based therapies.</p>","PeriodicalId":11559,"journal":{"name":"EJNMMI Physics","volume":"12 1","pages":"76"},"PeriodicalIF":3.2,"publicationDate":"2025-08-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12354439/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144854917","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":"Motion correction of simultaneous brain PET/MR images based on tracer uptake characteristics.","authors":"Sheng-Chieh Chiu, Jose Angelo U Perucho, Yu-Hua Dean Fang","doi":"10.1186/s40658-025-00789-6","DOIUrl":"10.1186/s40658-025-00789-6","url":null,"abstract":"<p><strong>Background: </strong>Simultaneous PET/MR imaging enables precise anatomical localization and PET quantification by reducing PET-to-MR misalignments. However, involuntary motion during scans may still cause misalignment and quantification imprecision. Current mutual information (MI)-based co-registration methods do not account for the tissue-specific uptake patterns of PET and therefore could result in suboptimal alignment. To address this, we proposed a novel image co-registration method, namely the tracer characteristic-based co-registration (TCBC) method, which takes advantage of specific PET uptake patterns within a selected anatomical region to improve the image alignment and PET quantification.</p><p><strong>Results: </strong>TCBC was evaluated using simulation and in vivo ¹⁸F-Florbetapir PET/MR data from the OASIS-3 dataset. In simulations, TCBC demonstrated superior alignment accuracy with lower root mean square error and higher R-squared values compared to the conventional MI-based co-registration from FreeSurfer in recovering the simulated patient motion. In the retrospective human study, we evaluated the detectability of age-related amyloid burden in healthy controls under different co-registration methods as a demonstrative use case. TCBC significantly enhanced the detectability of age-related amyloid burden with stronger correlations across all five regions of evaluation, such as the medial orbitofrontal cortex (p < 0.001), precuneus (p = 0.004), and early amyloid-β composite (p = 0.002), compared to FSMC (p = 0.004, 0.007, and 0.006, respectively) and uncorrected (p = 0.378, 0.023, and 0.039, respectively) methods. Bootstrap analyses also confirmed TCBC's robustness in smaller samples, yielding tighter confidence intervals and lower means of p-values, such as 0.032 (95% CI: 0.029-0.035) in the precuneus and 0.008 (CI: 0.007-0.010) in the medial orbitofrontal cortex, outperforming FSMC (p = 0.046 with CI: 0.042-0.049, and p = 0.040 with CI: 0.036-0.044, respectively).</p><p><strong>Conclusions: </strong>The TCBC method reduces image misalignment, improves PET quantification, and may have a good potential for being applied to both research and clinical studies with simultaneous brain PET/MR.</p><p><strong>Clinical trial number: </strong>Not applicable.</p>","PeriodicalId":11559,"journal":{"name":"EJNMMI Physics","volume":"12 1","pages":"75"},"PeriodicalIF":3.2,"publicationDate":"2025-07-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12311070/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144741664","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":"Development of a population of digital brain phantoms for radionuclide imaging research in Parkinson's disease.","authors":"Wenbo Huang, Han Jiang, Guang-Uei Hung, Yonghua Zhao, Ruibing Wang, Greta S P Mok","doi":"10.1186/s40658-025-00787-8","DOIUrl":"10.1186/s40658-025-00787-8","url":null,"abstract":"<p><strong>Purpose: </strong>Dopamine transporter (DAT) SPECT is a powerful tool for early diagnosis of Parkinson's disease (PD), while digital phantoms and Monte Carlo (MC) simulations can serve as important research tools. This study aims to develop a novel digital brain phantom population for ^99mTc-TRODAT-1 (^99mTc) and ¹²³I-ioflupane (¹²³I) brain SPECT, and to assess attenuation correction (AC) and scatter correction (SC) in DAT SPECT.</p><p><strong>Methods: </strong>Striatum, brain background (gray and white matter), and cold regions (skull and cerebrospinal fluid) were segmented from 200 T1 MRI brain images from the PPMI dataset. Striatal binding ratio (SBR) values were retrospectively collected from 200 ¹²³I and 100 ^99mTc DAT SPECT patients with suspected PD symptoms from PPMI and a local hospital, respectively. Various activity values were assigned to the randomly paired segmented regions according to a range of SBR values based on the SPECT Visual Interpretation (VI) assessment scheme. The new phantom population was combined with MC simulation tool SIMIND to generate realistic noisy projections. Quantitative accuracy of reconstructed images with attenuation correction (AC) and scatter correction (SC) was assessed.</p><p><strong>Results: </strong>A population of 1000 normal and abnormal PD phantoms was generated for both tracers. Visual comparisons and quantitative analyses demonstrated that simulated data exhibited high similarity to clinical data. Reconstructed images with AC + SC achieved the best quantitative results, followed by AC only, without AC and SC, and SC only.</p><p><strong>Conclusion: </strong>The developed digital DAT SPECT phantom population can be served for a wide range of PD applications. Attenuation impacts image quality the most in DAT SPECT, while AC + SC is effective to enhance image quality and quantitative accuracy of DAT SPECT.</p>","PeriodicalId":11559,"journal":{"name":"EJNMMI Physics","volume":"12 1","pages":"74"},"PeriodicalIF":3.2,"publicationDate":"2025-07-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12307856/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144728786","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":"Hyperparameter-controlled regularized reconstruction method based on object structure and acquisition conditions in SPECT.","authors":"Tomoya Minagawa, Kensuke Hori, Takeyuki Hashimoto","doi":"10.1186/s40658-025-00788-7","DOIUrl":"10.1186/s40658-025-00788-7","url":null,"abstract":"<p><strong>Background: </strong>In clinical nuclear medicine, reconstruction methods incorporating regularization terms have been widely investigated. However, searching for optimal hyperparameters for the entire examination is time-consuming and arduous because the optimal hyperparameters need to be determined experimentally and vary depending on factors, including the acquisition condition, reconstruction condition, and so on. In this study, we propose a row-action type automatic regularized expectation maximization method (RAREM). This method considers the acquisition conditions and object structure for determining the hyperparameters and does not require the user to set the hyperparameters experimentally. This study was conducted using numerical simulations and a real SPECT system METHODS: Total variation-expectation maximization (TV-EM) and modified-block sequential regularized EM (BSREM) were compared with RAREM, with the optimal hyperparameters of the two conventional reconstruction methods determined in advance from normalized root mean square error (NRMSE) results. This simulation examination utilized three types of phantoms with the number of counts and projections being examined in six ways each, resulting in a total of 108 conditions. The NRMSE and structural similarity index measure (SSIM) were used to evaluate of the simulation examination, and the Mann-Whitney U test was used for statistical analysis. In the real examination, two types of phantoms were used, and the number of projections was examined in three ways, for a total of six conditions. Contrast recovery coefficient (CRC) and specific binding ratio (SBR) were used to evaluate the real examination RESULTS: The NRMSE, CRC, and SBR of RAREM were equivalent to those of the conventional methods, and the SSIM of RAREM was equivalent to or better than that of the conventional methods, with significant differences in some cases. The results indicated that RAREM worked well with the evaluated object structure and considered the acquisition conditions CONCLUSION: In this study, an automatically controlled regularization reconstruction method was proposed. The proposed method does not require the user to set hyperparameters experimentally and can avoid the investigation of optimal hyperparameters; it is an alternative to conventional regularized methods in clinical.</p>","PeriodicalId":11559,"journal":{"name":"EJNMMI Physics","volume":"12 1","pages":"73"},"PeriodicalIF":3.2,"publicationDate":"2025-07-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12307274/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144728787","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":"MSA-Net: a multi-scale and adversarial learning network for segmenting bone metastases in low-resolution SPECT imaging.","authors":"Yusheng Wu, Qiang Lin, Yang He, XianWu Zeng, Yongchun Cao, ZhengXing Man, Caihong Liu, Yusheng Hao, Zhengqi Cai, Jinshui Ji, Xiaodi Huang","doi":"10.1186/s40658-025-00785-w","DOIUrl":"10.1186/s40658-025-00785-w","url":null,"abstract":"<p><strong>Background: </strong>Single-photon emission computed tomography (SPECT) plays a crucial role in detecting bone metastases from lung cancer. However, its low spatial resolution and lesion similarity to benign structures present significant challenges for accurate segmentation, especially for lesions of varying sizes.</p><p><strong>Methods: </strong>We propose a deep learning-based segmentation framework that integrates conditional adversarial learning with a multi-scale feature extraction generator. The generator employs cascade dilated convolutions, multi-scale modules, and deep supervision, while the discriminator utilizes multi-scale L1 loss computed on image-mask pairs to guide segmentation learning.</p><p><strong>Results: </strong>The proposed model was evaluated on a dataset of 286 clinically annotated SPECT scintigrams. It achieved a Dice Similarity Coefficient (DSC) of 0.6671, precision of 0.7228, and recall of 0.6196 - outperforming both classical and recent adversarial segmentation models in multi-scale lesion detection, especially for small and clustered lesions.</p><p><strong>Conclusion: </strong>Our results demonstrate that the integration of multi-scale feature learning with adversarial supervision significantly improves the segmentation of bone metastasis in SPECT imaging. This approach shows potential for clinical decision support in the management of lung cancer.</p>","PeriodicalId":11559,"journal":{"name":"EJNMMI Physics","volume":"12 1","pages":"72"},"PeriodicalIF":3.2,"publicationDate":"2025-07-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12290148/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144697909","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":"Feasibility of in vivo small animal imaging using a clinical total-body PET/CT system.","authors":"Julia G Mannheim, Wenhong Lan, Maurizio Conti, Franziska Siedler, Marcel A Krueger, Kristina Herfert, Christian la Fougère, Fabian P Schmidt","doi":"10.1186/s40658-025-00782-z","DOIUrl":"10.1186/s40658-025-00782-z","url":null,"abstract":"<p><strong>Background: </strong>Clinical PET scanners have long been explored for preclinical imaging, but limited spatial resolution and sensitivity have restricted their use for preclinical studies. The recent availability of total-body (TB) PET/CT scanners with extended axial fields of view (FOVs) has largely overcome sensitivity limitations, enabling potential new opportunities for small-animal imaging. This study evaluated the feasibility and performance of the Biograph Vision Quadra TB-PET/CT for rodent imaging compared to the dedicated small-animal PET scanner Inveon DPET.</p><p><strong>Material and methods: </strong>Recovery coefficients (RC), image noise, and optimum image reconstruction parameters were assessed using the preclinical NEMA NU 4-2008 image quality phantom and a sub-cohort of three anesthetized mice as a proof-of-concept demonstrating the feasibility of the setup. In vivo quantification accuracy was evaluated by scanning nine frozen mice simultaneously in three different arrangements with the Quadra compared with individual scans at the Inveon. To ensure comparability, all mice were snap-frozen after 1 h uptake of [¹⁸F]FDG, scanned sequentially and individually at the Inveon (90 min p.i.), and subsequently scanned at the Quadra with decay-corrected acquisition times. SUV_mean and SUV_max values were determined for liver, muscle and brain regions on both systems. To evaluate potential position-dependent effects within the extended axial FOV, a single frozen mouse was scanned at multiple positions.</p><p><strong>Results: </strong>Phantom rods ≥ 2 mm could be resolved with the Quadra, showing a comparable RC for larger structures, e.g. for the 5 mm rod of 1.17 compared to 1.09 (Inveon) when using point-spread-function modeling, whilst having lower noise of 5.1%SD vs 9.0%SD. No substantial position-dependent effects were detected in the phantom or single-mouse scan across the axial FOV. SUV_mean values were consistent between both scanner across all investigated organs, with liver and muscle uptake remaining comparable for frame durations down to 5 s. SUV_max values exhibited greater variability, with significant differences observed in muscle and brain regions.</p><p><strong>Conclusion: </strong>Despite the lower spatial resolution of the clinical TB-PET/CT scanner (~ 3-4 mm) compared to the dedicated preclinical scanner (~ 1.5 mm), robust SUV_mean quantification was achievable. Together with successful in vivo imaging of anesthetized mice, these findings support the feasibility of using clinical TB-PET/CT for preclinical research, acknowledging spatial resolution as a limiting factor.</p>","PeriodicalId":11559,"journal":{"name":"EJNMMI Physics","volume":"12 1","pages":"71"},"PeriodicalIF":3.0,"publicationDate":"2025-07-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12286903/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144689586","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":"Modeling of a population-based input function (PBIF) using the Feng model in dynamic ⁶⁸Ga-DOTATOC whole body PET/CT scans: feasibility of shortened imaging protocols on PET/CT Vision 600 system ^®.","authors":"Thomas Godefroy, Mathieu Pavoine, David Bourhis, Romain Le Pennec, Kevin Kerleguer, Romain Floch, Pierre-Yves Salaün, Nicolas Karakatsanis, Philippe Thuillier, Ronan Abgral","doi":"10.1186/s40658-025-00773-0","DOIUrl":"10.1186/s40658-025-00773-0","url":null,"abstract":"<p><strong>Background: </strong>This study focuses on modeling a population-based input function (PBIF) in dynamic ⁶⁸Ga-DOTATOC PET/CT exams, with the aim of developing clinically adoptable protocols. The PBIF is derived from an image-derived input function (IDIF), ensuring a non-invasive and standardized approach to tracer kinetic modeling.</p><p><strong>Methods: </strong>Patients with well-differentiated neuroendocrine tumors were included from the GAPETNET clinical trial (n = 37), divided into a PBIF modeling group (n = 20) and an independent validation group (n = 17). Dynamic whole-body (dWB) PET/CT imaging was performed using a Vision 600 PET/CT system. A population-based input function (PBIF) was modeled using the Feng approach and scaled to individual patient-specific IDIFs over two different time windows (sPBIF_3 - 7: 25-55 min, sPBIF_5 - 7: 40-55 min). The scaled PBIF was normalized to IDIF data from 6 to 55 min post-injection. A full individual patient-specific IDIF using data from 0 to 70 min post-injectionwas used as the reference for AUC and Ki comparisons. IDIFs and scaled PBIFs were compared by assessing the area under the curve (AUC) and radiotracer influx rate (Ki). Linear correlation and Bland-Altman analyses were conducted for AUC and Ki comparisons. Additionally, Mann-Whitney tests were performed to compare Ki values obtained with IDIF and sPBIF in both tumoral lesions and physiological organs.</p><p><strong>Results: </strong>The lowest mean relative AUC bias was observed with sPBIF_3 - 7, calculated to be 2.7 ± 7.9%, and was slightly higher with sPBIF_5 - 7 (7.35 ± 8.58%). The correlation coefficient (R²) with the sPBIFs was high, with a minimum of 0.95 for the sPBIF_5 - 7. When analyzing K_i metrics, biases tended to be lower with the 40-55 min time window (Mean ± SD bias = 1.61 ± 3.33 for K_{i max} and 1.64 ± 2.96 for K_{i mean}). No significant differences in K_i values was observed with the sPBIFs compared to the IDIF (p > 0.05), for either tumoral lesion or physiological organs.</p><p><strong>Conclusion: </strong>Our study has demonstrated the feasibility the PBIF approach to estimate tumor or physiological Ki values from a shortened dWB ⁶⁸Ga-DOTATOC PET acquisition, using the Feng model.</p>","PeriodicalId":11559,"journal":{"name":"EJNMMI Physics","volume":"12 1","pages":"70"},"PeriodicalIF":3.0,"publicationDate":"2025-07-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12271040/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144648851","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":"Assessment and clinical relevance of pulmonary shunt on ¹⁶⁶Ho-Scout Imaging in hepatocellular carcinoma.","authors":"Evelyn Vranken, An De Crop, Victor Nuttens, Ruben Vandenbulcke, Tom Dewaele, Thomas Ryckaert, Jochen Decaestecker, Sofie De Meulder, Pieter De Bondt","doi":"10.1186/s40658-025-00783-y","DOIUrl":"10.1186/s40658-025-00783-y","url":null,"abstract":"&lt;p&gt;&lt;strong&gt;Aim: &lt;/strong&gt;Prediction of posttreatment lung mean dose (LMD) during liver radioembolization (RE) work-up is essential for risk evaluation of radiation pneumonitis, especially when treating large hepatocellular carcinoma (HCC) where the chance of arteriovenous shunting is not negligible. In case of holmium-166-([&lt;sup&gt;166&lt;/sup&gt;Ho])-RE, either [&lt;sup&gt;99m&lt;/sup&gt;Tc]TcMAA or &lt;sup&gt;166&lt;/sup&gt;Ho-microspheres can be used as scout tracers. Safety of use of &lt;sup&gt;166&lt;/sup&gt;Ho-scout has been demonstrated previously, but, to our notice, evaluation of lung radiation dose due to &lt;sup&gt;166&lt;/sup&gt;Ho-scout activity in case of significant lung shunting has not been described so far. Therefore, a retrospective study was conducted to evaluate the presence of pulmonary shunting in HCC patients influencing therapeutical approach and to assess lung &lt;sup&gt;166&lt;/sup&gt;Ho-scout dose in these patients.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Materials and methods: &lt;/strong&gt;Twenty-nine HCC patients referred for RE were retrospectively evaluated. All work-ups were performed with &lt;sup&gt;166&lt;/sup&gt;Ho-microspheres. Scout imaging consisted of a hybrid SPECT/CT acquisition covering the thoraco-abdominal region. As mentioned in the manufacturer's instruction for use of &lt;sup&gt;166&lt;/sup&gt;Ho-microspheres, the possibility of &gt; 30 Gy lung radiation exposure in a single treatment is withheld as contra-indication for RE. In patients with lung shunt resulting in predicted posttreatment LMD &gt; 30 Gy, lung &lt;sup&gt;166&lt;/sup&gt;Ho-scout dose due to patient-specific injected activity was calculated, alongside two hypothetical scenarios: lung &lt;sup&gt;166&lt;/sup&gt;Ho-scout dose related to patient's lung shunt fraction (LSF) assuming administration of leaflet prescribed maximum &lt;sup&gt;166&lt;/sup&gt;Ho-scout activity and in case of 100% LSF according to patient-specific injected scout activity. Afterwards, these patients were followed for 3 months or till death.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Results: &lt;/strong&gt;In the 29 patients, average predicted posttreatment LMD was 10.0 Gy (range 0.1-138.9 Gy), four of them revealing predicted LMD &gt; 30 Gy. Based on patient-specific injected &lt;sup&gt;166&lt;/sup&gt;Ho-scout activity (range 100-200 MBq), average lung &lt;sup&gt;166&lt;/sup&gt;Ho-scout dose of 0.5 Gy (range 0.1-0.8 Gy) was calculated in these 4 patients. Assuming administration of leaflet prescribed maximum activity of 250 MBq, average lung &lt;sup&gt;166&lt;/sup&gt;Ho-scout dose would be 0.9 Gy (range 0.4-1.7 Gy). In case of a 100% LSF, average lung &lt;sup&gt;166&lt;/sup&gt;Ho-scout dose would be 2.2 Gy (range 1.5-2.7 Gy) due to patient-specific scout activity. In these 4 patients, RE was denied and alternative treatment was started. No pulmonary adverse events related to &lt;sup&gt;166&lt;/sup&gt;Ho-scout were recorded.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Conclusion: &lt;/strong&gt;This study supports previous reports that &lt;sup&gt;166&lt;/sup&gt;Ho-scout is a safe alternative to [&lt;sup&gt;99m&lt;/sup&gt;Tc]TcMAA -scout and underlines the importance of predicting posttreatment LMD when treating large HCC since 13.8% of our patient group presented arteriovenous shunt","PeriodicalId":11559,"journal":{"name":"EJNMMI Physics","volume":"12 1","pages":"69"},"PeriodicalIF":3.0,"publicationDate":"2025-07-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12259507/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144625528","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}