EJNMMI Physics最新文献

{"title":"On the Effect of the Patient Table on Attenuation in Myocardial Perfusion Imaging SPECT.","authors":"Tamino Huxohl, Gopesh Patel, Wolfgang Burchert","doi":"10.1186/s40658-024-00713-4","DOIUrl":"10.1186/s40658-024-00713-4","url":null,"abstract":"<p><strong>Background: </strong>The topic of the effect of the patient table on attenuation in myocardial perfusion imaging (MPI) SPECT is gaining new relevance due to deep learning methods. Existing studies on this effect are old, rare and only consider phantom measurements, not patient studies. This study investigates the effect of the patient table on attenuation based on the difference between reconstructions of phantom scans and polar maps of patient studies.</p><p><strong>Methods: </strong>Jaszczak phantom scans are acquired according to quality control and MPI procedures. An algorithm is developed to automatically remove the patient table from the CT for attenuation correction. The scans are then reconstructed with attenuation correction either with or without the patient table in the CT. The reconstructions are compared qualitatively and on the basis of their percentage difference. In addition, a small retrospective cohort of 15 patients is examined by comparing the resulting polar maps. Polar maps are compared qualitatively and based on the segment perfusion scores.</p><p><strong>Results: </strong>The phantom reconstructions look qualitatively similar in both the quality control and MPI procedures. The percentage difference is highest in the lower part of the phantom, but it always remains below 17.5%. Polar maps from patient studies also look qualitatively similar. Furthermore, the segment scores are not significantly different (p=0.83).</p><p><strong>Conclusions: </strong>The effect of the patient table on attenuation in MPI SPECT is negligible.</p>","PeriodicalId":11559,"journal":{"name":"EJNMMI Physics","volume":"12 1","pages":"3"},"PeriodicalIF":3.0,"publicationDate":"2025-01-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11746982/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143002278","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":"AI-based automatic patient positioning in a digital-BGO PET/CT scanner: efficacy and impact.","authors":"John A Kennedy, Tala Palchan-Hazan, Zohar Keidar","doi":"10.1186/s40658-025-00715-w","DOIUrl":"10.1186/s40658-025-00715-w","url":null,"abstract":"<p><strong>Background: </strong>A recently released digital solid-state positron emission tomography/x-ray CT (PET/CT) scanner with bismuth germanate (BGO) scintillators provides an artificial intelligence (AI) based system for automatic patient positioning. The efficacy of this digital-BGO system in patient placement at the isocenter and its impact on image quality and radiation exposure was evaluated.</p><p><strong>Method: </strong>The digital-BGO PET/CT with AI-based auto-positioning was compared (χ², Mann-Whitney tests) to a solid-state lutetium-yttrium oxyorthosilicate (digital-LYSO) PET/CT with manual patient positioning (n = 432 and 343 studies each, respectively), with results split into groups before and after the date of a recalibration of the digital-BGO auto-positioning camera. To measure the transverse displacement of the patient center from the scanner isocenter (off-centering), CT slices were retrospectively selected and automatically analyzed using in-house software. Noise was measured as the coefficient of variation within the liver of absolute Hounsfield units referenced to air. Radiation exposure was recorded as dose-length product (DLP). Off-centering measurements were validated by a phantom study.</p><p><strong>Results: </strong>The phantom validation study gave < 1.6 mm error in 15 off-centering measurements. Patient off-centering was biased 1.92 ± 1.79 cm (mean ± standard deviation) in the posterior direction which was significantly different from the 0.22 ± 1.21 cm bias in the left lateral direction (p < 0.0001, Wilcoxon). After recalibration, 27% (38/140) of the studies had off-centering results > 2.5cm for the digital-BGO, which was significantly better than the 49% (143/292, p < 0.001) before recalibration and better than for the digital-LYSO: 54% (119/222, p < 0.001) before and 55% (66/121, p < 0.001) after. On average, CT image quality was superior for non-obese patients who were most closely aligned with the isocenter: noise increased by 3.2 ± 0.1% for every 1 cm increase in off-centering. DLP increased by 144 ± 22 Gy cm for every 1 cm increase in anterior off-centering.</p><p><strong>Conclusion: </strong>AI-based automatic patient positioning in a digital-BGO PET/CT scanner significantly reduces patient off-centering, thereby improving image quality and ensuring proper radiation exposure.</p>","PeriodicalId":11559,"journal":{"name":"EJNMMI Physics","volume":"12 1","pages":"4"},"PeriodicalIF":3.0,"publicationDate":"2025-01-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11746997/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143002273","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 timing resolution of BGO for TOF-PET: a comparative analysis with and without deep learning.","authors":"Francis Loignon-Houle, Nicolaus Kratochwil, Maxime Toussaint, Carsten Lowis, Gerard Ariño-Estrada, Antonio J Gonzalez, Etiennette Auffray, Roger Lecomte","doi":"10.1186/s40658-024-00711-6","DOIUrl":"10.1186/s40658-024-00711-6","url":null,"abstract":"<p><strong>Background: </strong>The renewed interest in BGO scintillators for TOF-PET is driven by the improved Cherenkov photon detection with new blue-sensitive SiPMs. However, the slower scintillation light from BGO causes significant time walk with leading edge discrimination (LED), which degrades the coincidence time resolution (CTR). To address this, a time walk correction (TWC) can be done by using the rise time measured with a second threshold. Deep learning, particularly convolutional neural networks (CNNs), can also enhance CTR by training with digitized waveforms. It remains to be explored how timing estimation methods utilizing one (LED), two (TWC), or multiple (CNN) waveform data points compare in CTR performance of BGO scintillators.</p><p><strong>Results: </strong>In this work, we compare classical experimental timing estimation methods (LED, TWC) with a CNN-based method using the signals from BGO crystals read out by NUV-HD-MT SiPMs and high-frequency electronics. For <math> <mrow><mrow><mn>2</mn> <mo>×</mo> <mn>2</mn> <mo>×</mo> <mn>3</mn></mrow> <mspace></mspace> <msup><mtext>mm</mtext> <mn>3</mn></msup> </mrow> </math> crystals, implementing TWC results in a CTR of 129 ± 2 ps FWHM, while employing the CNN yields 115 ± 2 ps FWHM, marking improvements of 18 % and 26 %, respectively, relative to the standard LED estimator. For <math> <mrow><mrow><mn>2</mn> <mo>×</mo> <mn>2</mn> <mo>×</mo> <mn>20</mn></mrow> <mspace></mspace> <msup><mtext>mm</mtext> <mn>3</mn></msup> </mrow> </math> crystals, both methods yield similar CTR (around 240 ps FWHM), offering a <math><mo>∼</mo></math> 15 % gain over LED. The CNN, however, exhibits better tail suppression in the coincidence time distribution.</p><p><strong>Conclusions: </strong>The higher complexity of waveform digitization needed for CNNs could potentially be mitigated by adopting a simpler two-threshold approach, which appears to currently capture most of the essential information for improving CTR in longer BGO crystals. Other innovative deep learning models and training strategies may nonetheless contribute further in a near future to harnessing increasingly discernible timing features in TOF-PET detector signals.</p>","PeriodicalId":11559,"journal":{"name":"EJNMMI Physics","volume":"12 1","pages":"2"},"PeriodicalIF":3.0,"publicationDate":"2025-01-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11739447/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143002276","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 SwiftScan step-and-shoot continuous mode improves SPECT scanning efficiency: a preliminary phantom and clinical test.","authors":"Jicheng Li, Kai Zhang, Xingru Pang, Lele Huang, Xiaoxue Tian, Jiangyan Liu","doi":"10.1186/s40658-024-00709-0","DOIUrl":"10.1186/s40658-024-00709-0","url":null,"abstract":"<p><strong>Purpose: </strong>The aim of the study was to investigate the value of SwiftScan Step-and-Shoot Continuous (SSC) scanning mode in enhancing image quality and to explore appropriate scanning parameters for reducing scan time.</p><p><strong>Methods: </strong>This study was composed of a phantom study and two clinical tests. The differences in visual image quality scores, coefficient of variance (COV) of the background, image signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR), and recovery coefficient (RC) of the sphere were compared between SSC mode and traditional Step-and-Shoot (SS) mode in the phantom study. Various \"shoot\" acquisition times (5s, 10s, 15s) and \"step\" angles (3-degree, 6-degree, 9-degree) were evaluated and verified. In the clinical tests, bone tomography and parathyroid tomography were performed on 30 patients each. Differences in visual image quality scores, background COV, image SNR, CNR, and standardized uptake value (SUV) of lesions were compared between the two modes.</p><p><strong>Results: </strong>In the phantom study, SSC mode demonstrated higher visual scores and significantly reduced background COV (P < 0.05), and significantly increased SNR and CNR (P < 0.05) compared to SS mode. No significant alteration in RC was observed (P > 0.05). In the clinical tests, no significant differences were found between the optimal SSC scan combination (10s \"shoot\" and 6-degree \"step\")/ (10s \"shoot\" and 3-degree \"step\") and the traditional SS scan combination (15s \"shoot\" and 6-degree \"step\")/ (15s \"shoot\" and 3-degree \"step\") in visual image quality scores, background COV, image SNR, CNR, and SUV of bone and parathyroid high uptake lesions (P > 0.05).</p><p><strong>Conclusion: </strong>The SwiftScan SSC mode can reduce acquisition time by 33% while maintaining similar image quality and quantification accuracy compared to SS mode. An SSC scanning protocol with a 10s \"shoot\" acquisition and 6-degree \"step\" or with a 10s \"shoot\" acquisition and 3-degree \"step\" over a 360-degree rotation, is recommended for clinical use.</p>","PeriodicalId":11559,"journal":{"name":"EJNMMI Physics","volume":"12 1","pages":"1"},"PeriodicalIF":3.0,"publicationDate":"2025-01-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11695528/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142913994","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":"Ultra-fast [¹⁸F]florbetapir PET imaging using the uMI Panorama PET/CT system.","authors":"Xueqian Yang, Meiqi Wu, Menglin Liang, Haiqiong Zhang, Bo Li, Chenhui Mao, Liling Dong, Yuan Wang, Haiqun Xing, Chao Ren, Zhenghai Huang, Qingxiang Wen, Qi Ge, Zhengqing Yu, Feng Feng, Jing Gao, Li Huo","doi":"10.1186/s40658-024-00712-5","DOIUrl":"10.1186/s40658-024-00712-5","url":null,"abstract":"<p><strong>Background: </strong>There is a need for faster amyloid PET scans to reduce patients' discomfort, minimize movement artifacts, and increase throughput. The recently introduced uMI Panorama PET/CT system featuring enhanced spatial resolution and sub-200ps TOF offers the potential for shorter scan duration without sacrificing image quality or efficacy to detect Aβ deposition. The study aims to establish a faster acquisition protocol for [¹⁸F]florbetapir PET imaging using digital PET/CT scanner uMI Panorama, while ensuring adequate image quality and amyloid-β (Aβ) detectability comparable to the standard 10-minute scan.</p><p><strong>Methods: </strong>Thirty-eight participants (29 Aβ positive and 9 Aβ negative) from a prospective dementia cohort at Peking Union Medical University Hospital underwent routine [¹⁸F]florbetapir PET scans using the uMI Panorama PET/CT scanner and a T1-weighted brain MRI scan. List-mode PET data were reconstructed into durations of 10 min, 2 min, 1 min, 45 s, and 30 s (G10min, G2min, G1min, G45s, G30s). Two trained nuclear medicine physicians independently evaluated the image quality using a 5-point scale and provided binary diagnosis. Standardized uptake value ratios (SUVr) of the composite cortex (frontal, lateral parietal, lateral temporal, and cingulate cortices) were calculated to discriminate Aβ status and coefficient of variation assessed objective image quality. Comparisons of image quality and Aβ detectability between various fast scan groups and G10min group were conducted.</p><p><strong>Results: </strong>The subjective image quality evaluation and Aβ detectability results from the two physicians showed both good intra-reader and inter-reader agreements (Cohen's kappa coefficient: 0.759-1.000). The subjective and objective image qualities of the G2min scans were comparable to the G10min scans, whereas adequate image quality was achieved with the G1min and G45s scans (5-point score ≥ 3). Subjective visual diagnosis by two physicians yielded consistent accuracy for G10min, G2min, and G1min groups, but lower specificity for G45s and G30s groups. The objective detection of Aβ status by cortex SUVr across all scan durations maintained perfect discriminatory efficiency and relatively high effect size (Hedge's G: 2.48-2.54).</p><p><strong>Conclusions: </strong>A 1-min ultra-fast scan is feasible for [¹⁸F]florbetapir PET imaging using uMI Panorama PET/CT, while maintaining adequate image quality and Aβ diagnostic efficiency.</p><p><strong>Clinical trial registration: </strong>NCT05023564. Registered September 2022 https://clinicaltrials.gov/search?term=NCT05023564 .</p>","PeriodicalId":11559,"journal":{"name":"EJNMMI Physics","volume":"11 1","pages":"107"},"PeriodicalIF":3.0,"publicationDate":"2024-12-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11683033/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142909326","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":"Trapezoidal back projection for positron emission tomography reconstruction.","authors":"Dóra Varnyú, Krisztián Paczári, László Szirmay-Kalos","doi":"10.1186/s40658-024-00710-7","DOIUrl":"10.1186/s40658-024-00710-7","url":null,"abstract":"<p><strong>Background: </strong>In the back projection step of the 3D PET reconstruction, all Lines of Responses (LORs) that go through a given voxel need to be identified and included in an integral. The standard Monte Carlo solution to this task samples stochastically the surfaces of the detector crystals and the volume of the voxel to search for valid LORs. To get a low noise Monte Carlo estimate, the number of samples needs to be very high, making the computational cost of the projection significant. In this paper, a novel deterministic projection algorithm called trapezoidal back projection (TBP) is proposed that replaces the extensive Monte Carlo sampling. Its goal is to determine all LORs that contribute to a given voxel together with their exact contribution weights. This is achieved by trapezoidal rasterization and a pre-computed look-up table.</p><p><strong>Results: </strong>The precision and speed of the proposed TBP algorithm were compared to that of the Monte Carlo back projection of 1000, 10,000 and 100,000 samples. Measurements were run on a National Electrical Manufacturers Association (NEMA) NU 4-2008 image quality phantom as well as on a mouse acquisition. Results show that the TBP algorithm achieves the same low noise level (2.5 Uniformity %STD) as the Monte Carlo method with the highest sample number, but 13 times faster-the highest-precision Monte Carlo back projection takes 31.3 s, while TBP takes only 2.3 s on the NEMA NU 4-2008 image quality phantom of <math><mrow><mn>200</mn> <mo>×</mo> <mn>200</mn> <mo>×</mo> <mn>333</mn></mrow> </math> voxels.</p><p><strong>Conclusion: </strong>The proposed deterministic TBP algorithm achieves a low noise level in a short runtime, thus it can be a promising solution for the back projection of the 3D PET reconstruction. Its performance advantage could be used to reduce either the reconstruction time, the data acquisition time, or the noise level of the image.</p>","PeriodicalId":11559,"journal":{"name":"EJNMMI Physics","volume":"11 1","pages":"106"},"PeriodicalIF":3.0,"publicationDate":"2024-12-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11669645/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142892993","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":"EMATA: a toolbox for the automatic extraction and modeling of arterial inputs for tracer kinetic analysis in [¹⁸F]FDG brain studies.","authors":"Mattia De Francisci, Erica Silvestri, Andrea Bettinelli, Tommaso Volpi, Manu S Goyal, Andrei G Vlassenko, Diego Cecchin, Alessandra Bertoldo","doi":"10.1186/s40658-024-00707-2","DOIUrl":"10.1186/s40658-024-00707-2","url":null,"abstract":"<p><strong>Purpose: </strong>PET imaging is a pivotal tool for biomarker research aimed at personalized medicine. Leveraging the quantitative nature of PET requires knowledge of plasma radiotracer concentration. Typically, the arterial input function (AIF) is obtained through arterial cannulation, an invasive and technically demanding procedure. A less invasive alternative, especially for [¹⁸F]FDG, is the image-derived input function (IDIF), which, however, often requires correction for partial volume effect (PVE), usually performed via venous blood samples. The aim of this paper is to present EMATA: Extraction and Modeling of Arterial inputs for Tracer kinetic Analysis, an open-source MATLAB toolbox. EMATA automates IDIF extraction from [¹⁸F]FDG brain PET images and additionally includes a PVE correction procedure that does not require any blood sampling.</p><p><strong>Methods: </strong>To assess the toolbox generalizability and present example outputs, EMATA was applied to brain [¹⁸F]FDG dynamic data of 80 subjects, extracted from two distinct datasets (40 healthy controls, 40 glioma patients). Additionally, to compare with the reference standard, quantification using both IDIF and AIF was carried out on a third open-access dataset of 18 healthy individuals.</p><p><strong>Results: </strong>EMATA consistently performs IDIF extraction across all datasets, despite differences in scanners and acquisition protocols. Remarkably high agreement is observed when comparing Patlak's K_i between IDIF and AIF (R²: 0.98 ± 0.02).</p><p><strong>Conclusion: </strong>EMATA proved adaptability to different datasets characteristics and the ability to provide arterial input functions that can be used for reliable PET quantitative analysis.</p>","PeriodicalId":11559,"journal":{"name":"EJNMMI Physics","volume":"11 1","pages":"105"},"PeriodicalIF":3.0,"publicationDate":"2024-12-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11666860/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142881707","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":"Addressing lung truncation in ^99mTc-MAA SPECT/CT for ⁹⁰Y microsphere radioembolization treatment planning.","authors":"M Allan Thomas, Richard Laforest, John Karageorgiou, Dan Giardina, Tyler J Fraum, Chris D Malone, Justin K Mikell","doi":"10.1186/s40658-024-00705-4","DOIUrl":"10.1186/s40658-024-00705-4","url":null,"abstract":"<p><strong>Background: </strong>Prior studies have established that macroaggregated albumin (MAA)-SPECT/CT offers more robust lung shunt fraction (LSF) and lung mean absorbed dose (LMD) estimates in ⁹⁰Y radioembolization in comparison to planar imaging. However, incomplete SPECT/CT coverage of the lungs is common due to clinical workflows, complicating its potential use for LSF and LMD calculations. In this work, lung truncation in MAA-SPECT/CT was addressed via correction strategies to improve ⁹⁰Y treatment planning.</p><p><strong>Methods: </strong>Lung truncation was simulated in 56 cases with adequate (> 90%, mean: 98%) lung coverage in MAA-SPECT/CT by removing slices in ~ 5 mm increments from the lung apices to the diaphragm. A wide range of lung coverages from 100% to < 1% in ~ 2% increments were created. LSF and LMD were calculated with four methods. (1) 2D planar imaging standard (not truncated), truncated lung SPECT/CT data was: (2) used with no corrections (SPECT_Trunc), (3) uniformly extrapolated to full lung coverage (SPECT_Uniform), (4) fit with an empirical model to predict lung counts at full lung coverage (SPECT_Fit). To determine counts for LSF, full lung volumes, those modified at the lung/liver boundary (Lungs 2-cm), and those isolated to the left lung (Left Lung) were used. The correction methods were then applied to 31 independent cases without full lung coverage (< 90%, mean: 74%). The variations in LSF and LMD estimates from each correction method were analyzed.</p><p><strong>Results: </strong>Averaged across simulated lung coverages from 40 to 80%, percent errors relative to non-truncated data for SPECT_Trunc were (mean ± σ) - 22% ± 15% for LSF and 34% ± 29% for LMD. SPECT_Uniform had similar errors with 29% ± 26% for both LSF and LMD. SPECT_Fit yielded the most accurate and precise estimates for LSF and LMD, with errors of 11% ± 20% for both. The Left Lung approach equalized LMD errors in all three correction methods, with percent errors of 3% ± 17% (SPECT_Trunc), 2% ± 17% (SPECT_Uniform), and 4% ± 13% (SPECT_Fit). In the 31 cases without ground truth LSF or LMD, Left Lung produced highly comparable LMD estimates, with a mean (max) coefficient of variation across the three correction methods of 4% (20%).</p><p><strong>Conclusion: </strong>LSF and LMD can be estimated for ⁹⁰Y radioembolization using truncated lung coverage data in MAA-SPECT/CT. Empirical models to predict lung counts at full lung coverage produced LSF and LMD estimates with minimal bias and uncertainty. With lung/liver boundary adjustments, all SPECT/CT methods assessed in this work yielded LMD estimates comparable to ground truth, even down to 50% lung coverage.</p>","PeriodicalId":11559,"journal":{"name":"EJNMMI Physics","volume":"11 1","pages":"104"},"PeriodicalIF":3.0,"publicationDate":"2024-12-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11655778/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142846201","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":"Realization of high-end PET devices that assist conventional PET devices in improving image quality via diffusion modeling.","authors":"Qiyang Zhang, Chao Zhou, Xu Zhang, Wei Fan, Hairong Zheng, Dong Liang, Zhanli Hu","doi":"10.1186/s40658-024-00706-3","DOIUrl":"10.1186/s40658-024-00706-3","url":null,"abstract":"<p><strong>Purpose: </strong>This study aimed to implement high-end positron emission tomography (PET) equipment to assist conventional PET equipment in improving image quality via a distribution learning-based diffusion model.</p><p><strong>Methods: </strong>A diffusion model was first trained on a dataset of high-quality (HQ) images acquired by a high-end PET device (uEXPLORER scanner), and the quality of the conventional PET images was later improved on the basis of this trained model built on null-space constraints. Data from 180 patients were used in this study. Among them, 137 patients who underwent total-body PET/computed tomography scans via a uEXPLORER scanner at the Sun Yat-sen University Cancer Center were retrospectively enrolled. The datasets of 50 of these patients were used to train the diffusion model. The remaining 87 cases and 43 PET images acquired from The Cancer Imaging Archive were used to quantitatively and qualitatively evaluate the proposed method. The nonlocal means (NLM) method, UNet and a generative adversarial network (GAN) were used as reference methods.</p><p><strong>Results: </strong>The incorporation of HQ imaging priors derived from high-end devices into the diffusion model through network training can enable the sharing of information between scanners, thereby pushing the limits of conventional scanners and improving their imaging quality. The quantitative results showed that the diffusion model based on null-space constraints produced better and more stable results than those of the methods based on NLM, UNet and the GAN and is well suited for cross-center and cross-device imaging.</p><p><strong>Conclusion: </strong>A diffusion model based on null-space constraints is a flexible framework that can effectively utilize the prior information provided by high-end scanners to improve the image quality of conventional scanners in cross-center and cross-device scenarios.</p>","PeriodicalId":11559,"journal":{"name":"EJNMMI Physics","volume":"11 1","pages":"103"},"PeriodicalIF":3.0,"publicationDate":"2024-12-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11656007/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142846202","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":"Validation of dosimetry programs (Olinda & IDAC) for evaluation of absorbed dose in ¹⁷⁷LuPSMA therapy of metastatic castration-resistant prostate cancer (mCRPC) using Monte Carlo simulation.","authors":"Sirwan Maroufpour, Kamran Aryana, Shahrokh Nasseri, Zahra Fazeli, Hossein Arabi, Mehdi Momennezhad","doi":"10.1186/s40658-024-00691-7","DOIUrl":"10.1186/s40658-024-00691-7","url":null,"abstract":"<p><strong>Purpose: </strong>Clinical trials have yielded promising results for ¹⁷⁷Lutetium Prostate Specific Membrane Antigen (¹⁷⁷Lu-PSMA) therapy in metastatic castration resistant prostate cancer (mCRPC) patients. However, the development of precise methods for internal dosimetry and accurate dose estimation has been considered ongoing research. This study aimed to calculate the absorbed dose to the critical organs and metastasis regions using GATE 9.0 Monte Carlo simulation (MCS) as a gold standard to compare the OLINDA 1.1 and IDAC 2.1 software.</p><p><strong>Material and methods: </strong>This study investigated absorbed doses to different organs in 9 mCRPC patients during their first treatment cycle. Whole-body planar images were acquired at 1 ± 0.5, 4 ± 0.5, 24 ± 2, 48 ± 2, 72 ± 2, and 144 ± 2 h post-injection, with SPECT/CT images obtained at 24 ± 2 h. Absorbed doses were calculated for five organs and the entire metastasis regions using GATE, OLINDA, and IDAC platforms. The spherical method was used to determine and compare the absorbed doses in metastatic regions and undefined organs in OLINDA and IDAC Phantom.</p><p><strong>Results: </strong>The organ-absorbed dose calculations produced by GATE were consistent with those obtained from OLINDA and IDAC. The average percentage differences in absorbed dose for all organs between Monte Carlo calculations and the estimated from IDAC and OLINDA were -0.24 ± 2.14% and 5.16 ± 5.66%, respectively. There was a significant difference between GATE and both IDAC (17.55 ± 29.1%) and OLINDA (25.86 ± 18.04%) in determining absorbed doses to metastatic areas using the spherical model.</p><p><strong>Conclusion: </strong>The absorbed dose of organs in the first treatment cycle remained below tolerable limits. However, cumulative absorbed doses should be considered for the administered activities in the next cycles of treatment. While Monte Carlo, IDAC, and OLINDA results were aligned for organ dose calculations, patient-specific dosimetry may be necessary due to anatomical and functional changes. Accurate dose estimation for undefined organs and metastatic regions using the spherical model is significantly influenced by tissue density, highlighting the value of CT imaging.</p>","PeriodicalId":11559,"journal":{"name":"EJNMMI Physics","volume":"11 1","pages":"102"},"PeriodicalIF":3.0,"publicationDate":"2024-12-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11612135/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142767060","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}