EJNMMI Physics最新文献

{"title":"Generating synthetic brain PET images of synaptic density based on MR T1 images using deep learning.","authors":"Xinyuan Zheng, Patrick Worhunsky, Qiong Liu, Xueqi Guo, Xiongchao Chen, Heng Sun, Jiazhen Zhang, Takuya Toyonaga, Adam P Mecca, Ryan S O'Dell, Christopher H van Dyck, Gustavo A Angarita, Kelly Cosgrove, Deepak D'Souza, David Matuskey, Irina Esterlis, Richard E Carson, Rajiv Radhakrishnan, Chi Liu","doi":"10.1186/s40658-025-00744-5","DOIUrl":"10.1186/s40658-025-00744-5","url":null,"abstract":"<p><strong>Purpose: </strong>Synaptic vesicle glycoprotein 2 A (SV2A) in human brains is an important biomarker of synaptic loss associated with several neurological disorders. However, SV2A tracers, such as [¹¹C]UCB-J, are less available in practice due to constrains such as cost, radiation exposure and onsite cyclotron. We therefore aim to generate synthetic [¹¹C]UCB-J PET images based on MRI in this study.</p><p><strong>Methods: </strong>We implemented a convolution-based 3D encoder-decoder to predict [¹¹C]UCB-J SV2A PET images. A total of 160 participants who underwent both MRI and [¹¹C]UCB-J PET imaging, including individuals with schizophrenia, cannabis use disorder, Alzheimer's disease, were used in this study. The model was trained on pairs of T1-weighted MRI and [¹¹C]UCB-J distribution volume ratio images, and tested through a 10-fold cross-validation process. The image translation accuracy was evaluated based on the mean squared error, structural similarity index, percentage bias and Pearson's correlation coefficient between the ground truth and the predicted images. Additionally, we assessed the prediction accuracy of selected regions of interest (ROIs) crucial for brain disorders to evaluate our results.</p><p><strong>Results: </strong>The generated SV2A PET images are visually similar to the ground truth in terms of contrast and tracer distribution, quantitatively with low bias (< 2%) and high similarity (> 0.9). Across all diagnostic categories and ROIs, including the hippocampus, frontal, occipital, parietal, and temporal regions, the synthetic SV2A PET images exhibit an average bias of less than 5% compared to the ground truth. The model also demonstrates a capacity for noise reduction, producing images of higher quality compared to the low-dose scans.</p><p><strong>Conclusion: </strong>We conclude that it is feasible to generate robust SV2A PET images with promising accuracy from MRI via a data-driven approach.</p>","PeriodicalId":11559,"journal":{"name":"EJNMMI Physics","volume":"12 1","pages":"30"},"PeriodicalIF":3.0,"publicationDate":"2025-03-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11958861/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143751601","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":"A digital twin of the Biograph Vision Quadra long axial field of view PET/CT: Monte Carlo simulation and image reconstruction framework.","authors":"Christian M Pommranz, Ezzat A Elmoujarkach, Wenhong Lan, Jorge Cabello, Pia M Linder, Hong Phuc Vo, Julia G Mannheim, Andrea Santangelo, Maurizio Conti, Christian la Fougère, Magdalena Rafecas, Fabian P Schmidt","doi":"10.1186/s40658-025-00738-3","DOIUrl":"10.1186/s40658-025-00738-3","url":null,"abstract":"<p><strong>Background: </strong>The high sensitivity and axial coverage of large axial field of view (LAFOV) PET scanners have an unmet potential for total-body PET research. Despite these technological advances, inherent challenges to PET scans such as patient motion persist. To provide simulation-derived ground truth information, we developed a digital replica of the Biograph Vision Quadra LAFOV PET/CT scanner closely mimicking real event processing and image reconstruction.</p><p><strong>Material and methods: </strong>The framework uses a GATE model in combination with vendor-specific software prototypes for event processing and image reconstruction (e7 tools, Siemens Healthineers). The framework was validated against experimental measurements following the NEMA NU-2 2018 standard. In addition, patient-like simulations were performed with the XCAT phantom, including respiratory motion and modeled lesions of 5, 10, 20 mm size, to assess the impact of motion artefacts on PET images using a motion-free reference.</p><p><strong>Results: </strong>The simulation framework demonstrated high accuracy in replicating scanner performance in terms of image quality, contrast recovery (37 mm sphere: 86.5% and 85.5%; 28 mm: 82.6% and 82.4%; 22 mm: 78.8% and 77.7%; 17 mm: 74.9% and 74.6%; 13 mm: 67.0% and 67.9%; 10 mm: 55.5% and 64.3%), image noise (CV of 7.5% and 7.7%) and sensitivity (174.6 cps/kBq and 175.3 cps/kBq) for the simulation and experimental data, respectively. High agreement was found for the spatial resolution with a difference of 0.4 ± 0.3 mm and the NECR aligned well with a maximum deviation of 9%, particularly in the clinical activity range below 10 kBq/mL. Motion induced artefacts resulted in a quantification error at lesion level between - 12.3% and - 45.1%.</p><p><strong>Conclusion: </strong>The experimentally validated digital twin of the Biograph Vision Quadra facilitates detailed studies of realistic patient scenarios while offering unprecedented opportunities for motion correction, dosimetry, AI training, and imaging protocol optimization.</p>","PeriodicalId":11559,"journal":{"name":"EJNMMI Physics","volume":"12 1","pages":"31"},"PeriodicalIF":3.0,"publicationDate":"2025-03-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11958866/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143751596","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":"Effects of a deep learning-based image quality enhancement method on a digital-BGO PET/CT system for ¹⁸F-FDG whole-body examination.","authors":"Kenta Miwa, Shin Yamagishi, Shun Kamitaki, Kouichi Anraku, Shun Sato, Tensho Yamao, Noriaki Miyaji, Kaito Wachi, Naochika Akiya, Kei Wagatsuma, Kazuhiro Oguchi","doi":"10.1186/s40658-025-00742-7","DOIUrl":"10.1186/s40658-025-00742-7","url":null,"abstract":"<p><strong>Background: </strong>The digital-BGO PET/CT system, Omni Legend 32, incorporates modified block sequential regularized expectation maximization (BSREM) image reconstruction and a deep learning-based time-of-flight (TOF)-like image quality enhancement process called Precision DL (PDL). The present study aimed to define the fundamental characteristics of PDL using phantom and clinical images.</p><p><strong>Methods: </strong>A NEMA IEC body phantom was scanned using the Omni Legend 32 PET/CT system. All PET/CT images were acquired over 60 and 90 s per bed position, with a 384 × 384 matrix. Phantom images were reconstructed using OSEM + PSF and BSREM at β values of 100-1,000, combined with low (LPDL), medium (MPDL), and high (HPDL) PDL. We evaluated contrast recovery, background variability, and the contrast-to-noise ratio (CNR) of a 10 mm hot sphere. Thirty clinical whole-body ¹⁸F-FDG PET/CT examinations were included. Clinical images were reconstructed using OSEM + PSF and BSREM at β values of 200, 300, 400, 500, and 600, determined based on findings from the phantom study, combined with the three PDL models. Noise levels, mean SUV (SUV_mean), and the signal-to-noise ratio (SNR) of the liver as well as signal-to-background ratios (SBR) and maximum SUV (SUV_max) of lesions were evaluated. Two blinded readers evaluated visual image quality and rated several aspects to complement the analysis.</p><p><strong>Results: </strong>Contrast recovery and background variability decreased as the β value increased. This trend was consistent even when PDL processing was added to BSREM. Increased strength of the PDL models led to higher CNR. Noise levels decreased as a function of increasing β values in BSREM, resulting in a higher SNR, but lower SBR. Combining PDL with BSREM resulted in all β values producing better results in terms of noise, SBR, and SNR than OSEM + PSF. As the PDL increased (LPDL < MPDL < HPDL), noise levels, SBR, and SNR became higher. The β values of 400, 200, 300, and 300 for BSREM, LPDL, MPDL, and HPDL, respectively, resulted in noise equivalent to OSEM + PSF but significantly increased the SUV_max (9%, 15%, 18%, and 27%), SBR (16%, 17%, 20%, and 32%), and SNR (17%, 19%, 31%, and 36%), respectively. The visual evaluation of image quality yielded similar scores across BSREM + PDL reconstructions, although BSREM with β = 600 combined with MPDL delivered the best overall image quality and total mean score.</p><p><strong>Conclusion: </strong>The combination of BSREM and PDL significantly enhanced the SUV_max of lesions and image quality compared with OSEM + PSF. A combination of BSREM at β values of 500-600 and MPDL is recommended for oncological whole-body PET/CT imaging when using PDL on the Omni Legend.</p>","PeriodicalId":11559,"journal":{"name":"EJNMMI Physics","volume":"12 1","pages":"29"},"PeriodicalIF":3.0,"publicationDate":"2025-03-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11950486/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143729252","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":"Improving image reconstruction to quantify dynamic whole-body PET/CT: Q.Clear versus OSEM.","authors":"Sam Springer, Jeremy Basset-Sagarminaga, Tineke van de Weijer, Vera B Schrauwen-Hinderling, Walter H Backes, Roel Wierts","doi":"10.1186/s40658-025-00736-5","DOIUrl":"10.1186/s40658-025-00736-5","url":null,"abstract":"&lt;p&gt;&lt;strong&gt;Background: &lt;/strong&gt;The introduction of PET systems featuring increased count rate sensitivity has resulted in the development of dynamic whole-body PET acquisition protocols to assess &lt;sup&gt;18&lt;/sup&gt;F-FDG uptake rate ( &lt;math&gt;&lt;msub&gt;&lt;mi&gt;K&lt;/mi&gt; &lt;mi&gt;i&lt;/mi&gt;&lt;/msub&gt; &lt;/math&gt; ) using &lt;sup&gt;18&lt;/sup&gt;F-FDG PET/CT. However, in short-axis field-of-view (SAFOV) PET/CT systems, multiple bed positions are required per time frame to achieve whole-body coverage. This results in high noise levels, requiring higher &lt;sup&gt;18&lt;/sup&gt;F-FDG activity administration and, consequently, increased patient radiation dose. Bayesian penalized-likelihood PET reconstruction (e.g. Q.Clear, GE Healthcare) has been shown to effectively suppress image noise compared to standard reconstruction techniques. This study investigated the impact of Bayesian penalized-likelihood reconstruction on dynamic whole-body &lt;sup&gt;18&lt;/sup&gt;F-FDG PET quantification.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Methods: &lt;/strong&gt;Dynamic whole-body &lt;sup&gt;18&lt;/sup&gt;F-FDG PET/CT data (SAFOV PET Discovery MI 5R, GE Healthcare) of healthy volunteers and one lung cancer patient, consisting of a ten-minute dynamic scan of the thoracic region followed by six whole-body passes, were reconstructed with Q.Clear and Ordered Subset Expectation Maximization (OSEM) according to EARL 2 standards. Image noise in the measured time-activity-curves (TAC) was determined for the myocardium, hamstring, liver, subcutaneous adipose tissue and lung lesion for both reconstruction methods. &lt;math&gt;&lt;msub&gt;&lt;mi&gt;K&lt;/mi&gt; &lt;mi&gt;i&lt;/mi&gt;&lt;/msub&gt; &lt;/math&gt; values were calculated using Patlak analysis. Finally, bootstrapping was used to investigate the effect of image noise levels on &lt;math&gt;&lt;msub&gt;&lt;mi&gt;K&lt;/mi&gt; &lt;mi&gt;i&lt;/mi&gt;&lt;/msub&gt; &lt;/math&gt; values (bias and precision) as a function of magnitude of &lt;math&gt;&lt;msub&gt;&lt;mi&gt;K&lt;/mi&gt; &lt;mi&gt;i&lt;/mi&gt;&lt;/msub&gt; &lt;/math&gt; and volume-of-interest (VOI) size for both computationally simulated TACs ( &lt;math&gt;&lt;msub&gt;&lt;mi&gt;K&lt;/mi&gt; &lt;mi&gt;i&lt;/mi&gt;&lt;/msub&gt; &lt;/math&gt;  = 1.0-50.0·10&lt;sup&gt;-3&lt;/sup&gt;·ml·cm&lt;sup&gt;-3&lt;/sup&gt;·min&lt;sup&gt;-1&lt;/sup&gt;) and the measured TACs.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Results: &lt;/strong&gt;Compared to OSEM, Q.Clear showed 40-55% lower noise levels for all tissue types (p &lt; 0.05). For the measured TACs no systematic bias in &lt;math&gt;&lt;msub&gt;&lt;mi&gt;K&lt;/mi&gt; &lt;mi&gt;i&lt;/mi&gt;&lt;/msub&gt; &lt;/math&gt; with either reconstruction method was observed. &lt;math&gt;&lt;msub&gt;&lt;mi&gt;K&lt;/mi&gt; &lt;mi&gt;i&lt;/mi&gt;&lt;/msub&gt; &lt;/math&gt; precision decreased with decreasing VOI size, with that of Q.Clear being superior compared to OSEM for small VOIs of 0.56 cm&lt;sup&gt;3&lt;/sup&gt; in all tissues (p &lt; 0.05), with the largest difference in relative precision for small values of &lt;math&gt;&lt;msub&gt;&lt;mi&gt;K&lt;/mi&gt; &lt;mi&gt;i&lt;/mi&gt;&lt;/msub&gt; &lt;/math&gt; . The simulated TACs corroborated these results, with Q.Clear providing the best precision for small values of &lt;math&gt;&lt;msub&gt;&lt;mi&gt;K&lt;/mi&gt; &lt;mi&gt;i&lt;/mi&gt;&lt;/msub&gt; &lt;/math&gt; and small VOIs in all tissues.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Conclusion: &lt;/strong&gt;Q.Clear reconstruction of dynamic whole-body PET/CT data yields more precise &lt;math&gt;&lt;msub&gt;&lt;mi&gt;K&lt;/mi&gt; &lt;mi&gt;i&lt;/mi&gt;&lt;/msub&gt; &lt;/math&gt; val","PeriodicalId":11559,"journal":{"name":"EJNMMI Physics","volume":"12 1","pages":"27"},"PeriodicalIF":3.0,"publicationDate":"2025-03-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11947397/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143718053","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":"Establishment of a practical methodology for evaluating equieffective dose of individual patients based on RT-PHITS.","authors":"Tatsuhiko Sato, Takuya Furuta, Hidetaka Sasaki, Tadashi Watabe","doi":"10.1186/s40658-025-00743-6","DOIUrl":"10.1186/s40658-025-00743-6","url":null,"abstract":"<p><strong>Background: </strong>The RadioTherapy package based on PHITS (RT-PHITS) is an individual dosimetry system applicable to both targeted radionuclide therapy (TRT) and external radiotherapy. This study aims to establish a practical methodology for evaluating both absorbed doses and equieffective doses (EQDX) by improving RT-PHITS.</p><p><strong>Methods: </strong>We developed an Excel-based program, ExPORT-PHITS, which simplifies the conversion of the dose rates of specific organs and tumors calculated by RT-PHITS into corresponding absorbed doses and EQDX. ExPORT-PHITS offers two options for evaluating EQDX, each adopting a different type of microdosimetric kinetic model, to assess its dependence. The performance of the improved RT-PHITS, including ExPORT-PHITS, was evaluated using SPECT/CT images of two castration-resistant prostate cancer patients with bone metastases after the injection of ²²³RaCl₂ and ^99mTc-MDP.</p><p><strong>Results: </strong>Reasonable agreement was observed between absorbed doses calculated by RT-PHITS, IDAC Dose 2.1, and MIRDcalc, although absorbed doses in normal organs following the injection of ²²³RaCl₂ were comparatively higher than those reported in other studies. Results for ²²³RaCl₂ also showed that EQD2 tended to exceed the corresponding absorbed doses and RBE-weighted doses, while the relation was reversed for the injection of ^99mTc-MDP.</p><p><strong>Conclusions: </strong>These findings underscore RT-PHITS as a valuable tool for accurately modeling and optimizing individual TRT, especially for treatments involving α-ray emitters.</p>","PeriodicalId":11559,"journal":{"name":"EJNMMI Physics","volume":"12 1","pages":"28"},"PeriodicalIF":3.0,"publicationDate":"2025-03-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11947395/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143718415","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":"Accuracy and precision analyses of single-time-point dosimetry utilising physiologically-based pharmacokinetic modelling and non-linear mixed-effects modelling.","authors":"Indra Budiansah, Deni Hardiansyah, Ade Riana, Supriyanto Ardjo Pawiro, Ambros J Beer, Gerhard Glatting","doi":"10.1186/s40658-025-00726-7","DOIUrl":"10.1186/s40658-025-00726-7","url":null,"abstract":"<p><strong>Purpose: </strong>The aim of this study was to investigate the accuracy and precision of single-time-point (STP) dosimetry using a physiologically-based pharmacokinetic (PBPK) model with non-linear mixed-effects modelling (NLMEM).</p><p><strong>Methods: </strong>Biokinetic data of [¹¹¹In]In-DOTA-TATE in tumours, kidneys, liver, spleen, and whole body were collected from eight patients. The imaging was performed using planar scintigraphy at 2, 4, 24, 48, and 72 h after injection. Serum activity concentration was quantified at 5 and 15 min; 0.5, 1, 2, and 4 h; and 1, 2, and 3 d after injection. The PBPK model was fitted to the biokinetic data using NONMEM software version 7.5.1. Goodness-of-fit (GoF) criteria were visual inspection of the biokinetic curves, relative standard errors (RSEs) of the fitted parameters < 50%, and the absolute values of the off-diagonal elements in the correlation matrix < 0.8. All-time-point (ATP) fitting was performed, and the obtained absorbed doses (ADs) were used as reference (rADs). The leave-one-out Jackknife method was applied to calculate STP ADs (sADs). The accuracy of STP dosimetry was evaluated using the relative deviation between sADs and rADs. The time point, which resulted in the smallest root-mean-square error (RMSE), was selected as the optimal time point for STP dosimetry. The precision of the AD was calculated as ratio of AD RSE and AD values.</p><p><strong>Results: </strong>The ATP fitting was adequate based on the GoF test. STP dosimetry at 48 h after injection provided an acceptable estimation of ADs, yielding the lowest RMSE values for the kidney and tumour, calculated as (7 ± 2)% and (14 ± 4)%, respectively. The ADs in STP dosimetry showed lower precision than in ATP dosimetry. For instance, the ADs precision in ATP and STP dosimetry for kidneys in term median[min, max] were 3[3, 3]% and 6[5, 6]%, respectively. Similar results were found for the tumours where the precision of the ADs in ATP and STP dosimetry were 4[4, 5]% and 9[8, 12] %, respectively.</p><p><strong>Conclusion: </strong>STP dosimetry exhibits acceptable accuracy, although it shows a decrease in precision compared to ATP fitting. Precision information is clinically relevant for developing the optimal strategies for simplified dosimetry protocols.</p>","PeriodicalId":11559,"journal":{"name":"EJNMMI Physics","volume":"12 1","pages":"26"},"PeriodicalIF":3.0,"publicationDate":"2025-03-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11947405/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143729250","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":"Towards fully automatized [177Lu]Lu-PSMA personalized dosimetry based on 360° CZT whole-body SPECT/CT: a proof-of-concept.","authors":"Arnaud Dieudonné, Aya Terro, Arthur Dumouchel, Solène Perret, Agathe Edet-Sanson, Pierre Vera, Sébastien Hapdey, Romain Modzelewski, David Tonnelet, Pierre Decazes","doi":"10.1186/s40658-025-00727-6","DOIUrl":"10.1186/s40658-025-00727-6","url":null,"abstract":"<p><strong>Background: </strong>The advent of 360° CZT gamma-cameras allows to conceive personalised dosimetry studies from whole-body SPECT/CT data. We aimed to demonstrate the proof-of-concept of an automated personalized dosimetry pipeline for [¹⁷⁷Lu]Lu-PSMA organ dosimetry, called SimpleDose, and to compare to other dosimetry approaches.</p><p><strong>Methods: </strong>The organ segmentation is based on a nnU-Net framework that was trained to allow for the segmentation of 23 organs and structures over all the body. The method implemented to model the energy deposition is the collapsed-cone-superposition (CCS) taking into account non-uniform activity and density distributions. Ten patients with metastatic castration resistant prostate cancer treated [¹⁷⁷Lu]Lu-PSMA-617 were included. All SPECT/CT acquisitions were performed on a VERITON-CT 200 (Spectrum Dynamics®, Caesarea, Israel) from head to mid-thigh with 5 min per bed. The absorbed-dose-rates were computed with SimpleDose and compared with organ-level MIRD approach and local-deposition-method (LDM) for bone marrow, kidneys, liver, lungs, pancreas, salivary glands and spleen. Finally, an example of multi-time-point and single-time-point dosimetry is given.</p><p><strong>Results: </strong>The median (IQR) calculation time with SimpleDose (SD), for segmentation, computation of dose-rates and descriptive statistics was 161 (23) seconds at a resolution of 2.46 × 2.46 × 2.46 mm³ (Intel Xeon 20 × 3.70 GHz CPU computer). The median (IQR) differences between SD and MIRD and LDM, were respectively 1.8 (61) % and  - 16 (76) % in bone marrow, 2.4 (1.5) % and  - 93.1 (0.4) % in kidneys, 2.9 (3.4) % and  - 9.2 (3.0) % in liver, 21 (13) % and 13 (13) % in lungs, 11 (3.3) % and  - 11 (3.0) % in pancreas, 1.1 (12) % and 3.8 (8.4) % in salivary glands, 4.0 (4.3) % and  - 10.0 (4.5) % in spleen. For the clinical example, the multi-time-point dosimetry with 4 time-points took 14 min, while the single-time-point approach took 3.5 min from day 1 dataset and 3.3 min from day 3.</p><p><strong>Conclusion: </strong>The SimpleDose platform demonstrated its capability to compute organ-absorbed-dose rates in a simple and fast manner with close results to the standard MIRD approach for soft-tissues organs. SimpleDose is freely available for demonstration purpose as a Software as a Service (SaaS) at https://oncometer3d.com .</p>","PeriodicalId":11559,"journal":{"name":"EJNMMI Physics","volume":"12 1","pages":"25"},"PeriodicalIF":3.0,"publicationDate":"2025-03-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11925831/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143669296","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":"Towards harmonized holmium-166 SPECT image quality for dosimetry: a multi-center, multi-vendor study.","authors":"Lovisa E L Westlund Gotby, Martina Stella, Camille D E Van Speybroeck, Daphne Lobeek, Floris H P van Velden, Mette K Stam, Petra Dibbets-Schneider, Daphne M V de Vries-Huizing, Erik-Jan Rijkhorst, Berlinda J de Wit-van de Veen, Roel Wierts, Rob van Rooij","doi":"10.1186/s40658-025-00733-8","DOIUrl":"10.1186/s40658-025-00733-8","url":null,"abstract":"<p><strong>Background: </strong>Reliable dosimetry based on SPECT/CT imaging is essential to achieve personalized ¹⁶⁶Ho-radioembolization treatment planning and evaluation. This study quantitatively evaluates multiple acquisition and reconstruction protocols for ¹⁶⁶Ho-SPECT imaging based on data from five Dutch hospitals. We aim to recommend an imaging protocol which harmonizes ¹⁶⁶Ho-SPECT images for reproducible and accurate dosimetry in a multi-scanner and multi-center setting.</p><p><strong>Methods: </strong>Cylindrical and NEMA IEC phantoms, filled with ¹⁶⁶Ho-chloride, were imaged using seven SPECT/CT scanners from two vendors (GE HealthCare and Siemens Healthineers). Data were acquired with a photopeak window centered at 81 keV. Two adjacent scatter windows, and one upper scatter window at 118 keV were used for triple-energy window (TEW) and dual-energy window (DEW) scatter correction, respectively. The TEW and DEW reconstructions used vendor-specific software. Additionally, a vendor-neutral software package with Monte Carlo (MC) scatter correction (Hermes Medical Solutions) was used to study the influence of scanner hardware on the image quality. System sensitivity was measured in projection data of the cylindrical phantom. The axial uniformity in the cylindrical phantom was used to characterize the impact of the scatter correction method. The image quality was evaluated by the coefficient of variation (COV; noise), the contrast recovery coefficients (CRCs) and contrast-to-noise ratios (CNRs).</p><p><strong>Results: </strong>TEW scatter correction resulted in superior uniformity and higher CRCs compared to the DEW (CRC for the largest sphere over all scanners, mean ± SD (range): TEW 0.54 ± 0.07 (0.36-0.65), DEW 0.44 ± 0.04 (0.34-0.51)). DEW resulted in lower noise levels compared to TEW (16% lower on average). The DEW and TEW images resulted in comparable CNRs. The system sensitivities and the vendor-neutral image reconstructions demonstrated differences in hardware between the two vendors, most likely due to the characteristics of the vendor-specific medium energy collimator.</p><p><strong>Conclusion: </strong>This study demonstrates that TEW scatter correction increases the accuracy of ¹⁶⁶Ho-SPECT images compared to DEW, and we henceforth recommend adopting this method in the clinical ¹⁶⁶Ho-dosimetry workflow. Scanner hardware has a substantial impact on the characteristics of the acquired data, and identical reconstruction settings will therefore not automatically lead to harmonized image quality.</p>","PeriodicalId":11559,"journal":{"name":"EJNMMI Physics","volume":"12 1","pages":"24"},"PeriodicalIF":3.0,"publicationDate":"2025-03-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11920561/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143656566","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":"A novel method for harmonization of PET image spatial resolution without phantoms.","authors":"Felix Carbonell, Alex P Zijdenbos, Evan Hempel, Mihály Hajós, Barry J Bedell","doi":"10.1186/s40658-025-00740-9","DOIUrl":"10.1186/s40658-025-00740-9","url":null,"abstract":"<p><strong>Background: </strong>Estimation of the spatial resolution in real images is extremely important in several fields, including crystallography, optics, microscopy, and tomography. In human PET imaging, estimating spatial resolution typically involves the acquisition of images from a physical phantom, typically a Hoffman phantom, which poses a logistical burden, especially in large multi-center studies. Indeed, phantom images may not always be readily available, and this method requires constant monitoring of scanner updates or replacements, scanning protocol changes, and image reconstruction guidelines to establish a equivalence with scans acquired from human subjects.</p><p><strong>Methods: </strong>We propose a new computational approach that allows estimation of spatial resolution directly from human subject PET images. The proposed technique is based on the generalization of the logarithmic intensity plots in the 2D Fourier domain to the 3D case. The spatial resolution of the image is obtained through the estimated coefficients of a multiple linear regression problem having the logarithm of the squared norm of the Fourier transform as dependent variable and the squared 3D frequencies as multiple predictors.</p><p><strong>Results: </strong>The proposed approach was applied to a cohort of subjects consisting of [18F]florbetapir amyloid PET images and matching phantoms from a Phase II clinical trial, and a second cohort including β-amyloid, FDG, and tau PET images from the Alzheimer's Disease Neuroimaging Initiative (ADNI) study. The resulting in-plane and axial resolution estimators varied between 3.5 mm and 8.5 mm for both PET and matching phantom images. They also yielded less than one voxel size across-subjects variability in groups of images sharing the same PET scanner model and reconstruction parameters. For human PET images, we also proved that the spatial resolution estimators showed: (1) a very high reproducibility, as measured by intraclass correlation coefficients (ICC > 0.985), (2) a strong cross-tracer linear correlations, and (3) a high within-subject longitudinal consistency, as measured by the maximum difference value between pairs of visits from the same subject.</p><p><strong>Conclusions: </strong>Our novel approach does not only eliminate the need for surrogate phantom data, but also provides a general framework that can be applied to a wide range of tracers and other imaging modalities, such as SPECT.</p><p><strong>Clinical trial data: </strong>Cognito Therapeutics' OVERTURE clinical trial (NCT03556280, 2021-08-24), https://clinicaltrials.gov/study/NCT03556280 .</p>","PeriodicalId":11559,"journal":{"name":"EJNMMI Physics","volume":"12 1","pages":"23"},"PeriodicalIF":3.0,"publicationDate":"2025-03-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11906943/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143623994","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":"Machine-learning based quantification of lung shunt fraction from 99mTc-MAA SPECT/CT for selective internal radiation therapy of liver tumors using TriDFusion (3DF).","authors":"Daniel Lafontaine, Finn Augensen, Adam Kesner, Raoul Vincent, Assen Kirov, Simone Krebs, Heiko Schöder, John L Humm","doi":"10.1186/s40658-025-00732-9","DOIUrl":"10.1186/s40658-025-00732-9","url":null,"abstract":"<p><strong>Background: </strong>Prior to selective internal radiotherapy of liver tumors, a determination of the lung shunt fraction (LSF) is performed using 99mTc- macroaggregated albumin (99mTc-MAA) injected into the hepatic artery. Most commonly planar but sometimes SPECT/CT images are acquired upon which regions of interests are drawn manually to define the liver and the lung. The LSF is then calculated by taking the count ratios between these two organs. An accurate estimation of the LSF is necessary to avoid an excessive pulmonary irradiation dose.</p><p><strong>Methods: </strong>In this study, we propose a computational, semi-automatic approach for LSF calculation from SPECT/CT scans, based on machine learning 3D segmentation, implemented within TriDFusion (3DF). We retrospectively compared this approach with the LSF calculated using the standard planar approach on 150 patients. Using CT images (from the SPECT/CT) as a blueprint, the TotalSegmentor machine learning algorithm automatically computes masks for the liver and lungs. Then, the SPECT attenuation-corrected images are fused with the CT and, based on the CT segmentation mask, TriDFusion (3DF) generates volume-of- interest (VOI) regions on the SPECT images. The liver and lung VOIs are further augmented to compensate for breathing motion. Finally, the LSF is calculated using the number of counts in the respective VOIs. Measurements using an anthropomorphic 3D-printed phantom with variable 99mTc activity concentrations for the liver and lungs were performed to validate the accuracy of the algorithm.</p><p><strong>Results: </strong>On average, LSF determined from 2D planar images were between 21 and 70% higher than those determined from SPECT/CT data. Semi-automated determination of the LSF using TriDFusion (3DF) analysis of SPECT-CT acquisitions was within 4-12% of the phantom-determined ratio measurements (ground truth).</p><p><strong>Conclusions: </strong>The utilization of TriDFusion (3DF) AI 3D Lung Shunt is a precise method for quantifying lung shunt fraction (LSF) and is more accurate than planar 2D image-based estimates. By incorporating machine learning segmentation and compensating for breathing motion, the approach underscores the potential of artificial intelligence (AI)-driven techniques to revolutionize pulmonary imaging, providing clinicians with efficient and reliable tools for treatment planning and patient management.</p>","PeriodicalId":11559,"journal":{"name":"EJNMMI Physics","volume":"12 1","pages":"22"},"PeriodicalIF":3.0,"publicationDate":"2025-03-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11893963/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143596592","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}