EJNMMI Physics最新文献

{"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":"<p><strong>Background: </strong>The introduction of PET systems featuring increased count rate sensitivity has resulted in the development of dynamic whole-body PET acquisition protocols to assess <sup>18</sup>F-FDG uptake rate ( <math><msub><mi>K</mi> <mi>i</mi></msub> </math> ) using <sup>18</sup>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 <sup>18</sup>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 <sup>18</sup>F-FDG PET quantification.</p><p><strong>Methods: </strong>Dynamic whole-body <sup>18</sup>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. <math><msub><mi>K</mi> <mi>i</mi></msub> </math> values were calculated using Patlak analysis. Finally, bootstrapping was used to investigate the effect of image noise levels on <math><msub><mi>K</mi> <mi>i</mi></msub> </math> values (bias and precision) as a function of magnitude of <math><msub><mi>K</mi> <mi>i</mi></msub> </math> and volume-of-interest (VOI) size for both computationally simulated TACs ( <math><msub><mi>K</mi> <mi>i</mi></msub> </math>  = 1.0-50.0·10<sup>-3</sup>·ml·cm<sup>-3</sup>·min<sup>-1</sup>) and the measured TACs.</p><p><strong>Results: </strong>Compared to OSEM, Q.Clear showed 40-55% lower noise levels for all tissue types (p < 0.05). For the measured TACs no systematic bias in <math><msub><mi>K</mi> <mi>i</mi></msub> </math> with either reconstruction method was observed. <math><msub><mi>K</mi> <mi>i</mi></msub> </math> precision decreased with decreasing VOI size, with that of Q.Clear being superior compared to OSEM for small VOIs of 0.56 cm<sup>3</sup> in all tissues (p < 0.05), with the largest difference in relative precision for small values of <math><msub><mi>K</mi> <mi>i</mi></msub> </math> . The simulated TACs corroborated these results, with Q.Clear providing the best precision for small values of <math><msub><mi>K</mi> <mi>i</mi></msub> </math> and small VOIs in all tissues.</p><p><strong>Conclusion: </strong>Q.Clear reconstruction of dynamic whole-body PET/CT data yields more precise <math><msub><mi>K</mi> <mi>i</mi></msub> </math> 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}

{"title":"Automated segmentation of the sacro-iliac joints, posterior spinal joints and discovertebral units on low-dose computed tomography for Na[¹⁸F]F PET lesion detection in spondyloarthritis patients.","authors":"Wouter R P van der Heijden, Floris H P van Velden, Robert Hemke, Tom C Doorschodt, Ronald Boellaard, Conny J van der Laken, Gerben J C Zwezerijnen","doi":"10.1186/s40658-025-00734-7","DOIUrl":"10.1186/s40658-025-00734-7","url":null,"abstract":"<p><strong>Purpose: </strong>Spondyloarthritis (SpA) is a chronic inflammatory rheumatic disease which involves the axial skeleton. Quantitative sodium fluoride-18 (Na[¹⁸F]F) PET/CT is a new imaging approach promising for accurate diagnosis and treatment monitoring by assessment of molecular bone pathology in SpA. Detection of Na[¹⁸F]F PET positive lesions is time-consuming and subjective, and can be replaced by automatic methods. This study aims to develop and validate an algorithm for automated segmentation of the posterior spinal joints, sacro-iliac joints (SIJs) and discovertebral units (DVUs) on low-dose computed tomography (LDCT), and to employ these segmentations for threshold-based lesion detection.</p><p><strong>Methods: </strong>Two segmentation methods were developed using Na[¹⁸F]F PET/LDCT images from SpA patients. The first method employed morphological operations to delineate the joints and DVUs, while the second used a multi-atlas-based approach. The performance and reproducibility of these methods were assessed on ten manually segmented LDCTs using average Hausdorff distance (HD) and dice similarity coefficient (DSC) for DVUs and SIJs, and mean error distance for the posterior joints. Various quantitative PET metrics and background corrections were compared to determine optimal lesion detection performance relative to visual assessment.</p><p><strong>Results: </strong>The morphological method achieved significantly better DSC (0.82 (0.73-0.88) vs. 0.74 (0.68-0.79); p < 0.001) for all DVUs combined compared to the atlas-based method. The atlas-based method outperformed the morphological method for the posterior joints with a median error distance of 4.00 mm (4.00-5.66) vs. 5.66 mm (4.00-8.00) (p < 0.001). For lesion detection, the atlas-based segmentations were more successful than the morphological method, with the most accurate metric being the maximum standardized uptake value (SUVmax) of the lesional Na[¹⁸F]F uptake, corrected for the median SUV (SUVmedian) of the spine, with an area under the curve of 0.90.</p><p><strong>Conclusion: </strong>We present the first methods for detailed automatic segmentation of the posterior spinal joints, DVUs and SIJs on LDCT. The atlas-based method is the most appropriate, reaching high segmentation performance and lesion detection accuracy. More research on the PET-based lesion segmentation is required, to develop a pipeline for fully automated lesional Na[¹⁸F]F uptake quantification.</p>","PeriodicalId":11559,"journal":{"name":"EJNMMI Physics","volume":"12 1","pages":"20"},"PeriodicalIF":3.0,"publicationDate":"2025-03-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11891110/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143585194","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":"Myocardial perfusion imaging SPECT left ventricle segmentation with graphs.","authors":"Ádám István Szűcs, Béla Kári, Oszkár Pártos","doi":"10.1186/s40658-025-00728-5","DOIUrl":"10.1186/s40658-025-00728-5","url":null,"abstract":"<p><strong>Purpose: </strong>Various specialized and general collimators are used for myocardial perfusion imaging (MPI) with single-photon emission computed tomography (SPECT) to assess different types of coronary artery disease (CAD). Alongside the wide variability in imaging characteristics, the apriori \"learnt\" information of left ventricular (LV) shape can affect the final diagnosis of the imaging protocol. This study evaluates the effect of prior information incorporation into the segmentation process, compared to deep learning (DL) approaches, as well as the differences of 4 collimation techniques on 5 different datasets.</p><p><strong>Methods: </strong>This study was implemented on 80 patients database. 40 patients were coming from mixed black-box collimators, 10 each, from multi-pinhole (MPH), low energy high resolution (LEHR), CardioC and CardioD collimators. The testing was evaluated on a new continuous graph-based approach, which automatically segments the left ventricular volume with prior information on the cardiac geometry. The technique is based on the continuous max-flow (CMF) min-cut algorithm, which performance was evaluated in precision, recall, IoU and Dice score metrics.</p><p><strong>Results: </strong>In the testing it was shown that, the developed method showed a good improvement over deep learning reaching higher scores in most of the evaluation metrics. Further investigating the different collimation techniques, the evaluation of receiver operating characterstic (ROC) curves showed different stabilities on the various collimators. Running Wilcoxon signed-rank test on the outlines of the LVs showed differentiability between the collimation procedures. To further investigate these phenomena the model parameters of the LVs were reconstructed and evaluated by the uniform manifold approximation and projection (UMAP) method, which further proved that collimators can be differentiated based on the projected LV shapes alone.</p><p><strong>Conclusions: </strong>The results show that prior information incorporation can enhance the performance of segmentation methods and collimation strategies have a high effect on the projected cardiac geometry.</p>","PeriodicalId":11559,"journal":{"name":"EJNMMI Physics","volume":"12 1","pages":"21"},"PeriodicalIF":3.0,"publicationDate":"2025-03-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11893936/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143596596","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":"The first human study of add-on PET: A PET-integrated RF coil for 3 T MRI.","authors":"Miwako Takahashi, Fumihiko Nishikido, Go Akamatsu, Hideaki Tashima, Yuma Iwao, Mikio Suga, Taiga Yamaya","doi":"10.1186/s40658-025-00731-w","DOIUrl":"10.1186/s40658-025-00731-w","url":null,"abstract":"<p><strong>Background: </strong>Combined PET and MRI scanners allow for simultaneous image acquisition, simplifying the interpretation of both PET and MRI images. We prototyped an insert-type PET that can convert a standalone MRI to a PET-MRI system, named Add-on PET. In Add-on PET, we fully integrated the PET modules into a head radiofrequency (RF) coil so that PET detectors can be close to the brain and avoid placing the RF coil in the field of view of PET. This study aimed at confirming the feasibility of human brain simultaneous PET and MRI imaging using a prototype of add-on PET.</p><p><strong>Results: </strong>The PET images obtained with and without simultaneous MRI sequences were identical (Pearson's correlation coefficient, r = 0.953). Background noise was observed in the MRI images acquired during the PET scan; however, the noise decreased when the count rates of PET declined. The MRI obtained simultaneously was used for attenuation correction, providing well-correlated voxel values with those using the CT-based attenuation correction method (r = 0.989).</p><p><strong>Conclusions: </strong>The simultaneous PET and MRI images were performed without noticeable artifacts. There was no significant interference in PET images caused by the simultaneous MRI sequence; however, some background noise was observed in the MRI, likely due to the electric current from PET modules used for counting a clinically used radioactivity concentration.</p>","PeriodicalId":11559,"journal":{"name":"EJNMMI Physics","volume":"12 1","pages":"19"},"PeriodicalIF":3.0,"publicationDate":"2025-03-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11885769/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143566298","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}