Analysis methods for in-beam PET images in proton therapy treatment verification: a comparison based on Monte Carlo simulations
M. Moglioni, A. C. Kraan, A. Berti, P. Carra, P. Cerello, M. Ciocca, V. Ferrero, E. Fiorina, E. Mazzoni, M. Morrocchi, F. Pennazio, A. Retico, V. Rosso, G. Spor… 展开作者
M. Moglioni, A. C. Kraan, A. Berti, P. Carra, P. Cerello, M. Ciocca, V. Ferrero, E. Fiorina, E. Mazzoni, M. Morrocchi, F. Pennazio, A. Retico, V. Rosso, G. Sportelli, V. Vitolo, G. Bisogni
背景和目的：束内正电子发射断层成像（PET）是质子治疗中可用于体内非侵入性治疗监测的模式之一。可以比较在各种治疗会话期间获得的PET分布，以便识别具有解剖学变化的区域。本工作的目的是在质子治疗验证的分次间PET图像比较的背景下测试和比较不同的分析方法。研究方法：在我们的研究中，我们使用FLUKA Monte Carlo代码和人工生成的CT扫描来模拟质子治疗过程中不同阶段的束内PET分布。我们比较了Beam-Eye-View方法、Most-Likely-Shift方法、基于体素的形态学方法和伽马评估方法，以比较治疗开始时和治疗几周后的PET图像。将结果与CT扫描进行比较。结果和结论：如果有很多统计数据可用，则三维方法（如VBM和伽马）优于二维方法（如MLS和BEV），因为这些方法允许识别具有异常活动的区域。VBM方法的缺点是需要大量的MC模拟。伽马分析的缺点是，在公差标准上不存在临床适应症。在计算时间方面，BEV和MLS方法是优选的。我们建议同时使用这四种方法，以便最好地确定活动变化的位置和原因。
英文摘要：
Background and purpose: In-beam Positron Emission Tomography (PET) is one of the modalities that can be used for in-vivo non-invasive treatment monitoring in proton therapy. PET distributions obtained during various treatment sessions can be compared in order to identify regions that have anatomical changes. The purpose of this work is to test and compare different analysis methods in the context of inter-fractional PET image comparison for proton treatment verification.
Methods: For our study we used the FLUKA Monte Carlo code and artificially generated CT scans to simulate in-beam PET distributions at different stages during proton therapy treatment. We compared the Beam-Eye-View method, the Most-Likely-Shift method, the Voxel-Based-Morphology method and the gamma evaluation method to compare PET images at the start of treatment, and after a few weeks of treatment. The results were compared to the CT scan.
Results and conclusions: Three-dimensional methods like VBM and gamma are preferred above two-dimensional methods like MLS and BEV if much statistics is available, since the these methods allow to identify the regions with anomalous activity. The VBM approach has as disadvantage that a larger number of MC simulations is needed. The gamma analysis has the disadvantage that no clinical indication exist on tolerance criteria. In terms of calculation time, the BEV and MLS method are preferred. We recommend to use the four methods together, in order to best identify the location and cause of the activity changes.
Analysis of time-profiles with in-beam PET monitoring in charged particle therapy
背景资料：在带电粒子治疗中利用PET成像的治疗验证通常通过将空间分布的测量结果与蒙特卡罗（MC）预测进行比较来完成。然而，衰减曲线可以提供关于治疗和被照射组织的额外的独立信息。到目前为止，大多数研究都集中在长时间间隔上。在这里，我们调查的可靠性MC预测的空间和时间（衰变率）的轮廓照射后不久，我们展示了如何衰变率可以给出一个指示的元素，其中的幻影组成。方法和材料：在Bronowice质子治疗中心的回旋加速器中心，在临床和接近临床的条件下对各种幻影进行了辐照。使用平面16 x 16 cm $^2$ PET系统采集PET数据。用FLUKA程序模拟了粒子间的相互作用和光子在体模中的传播。分析包括实验数据和MC模拟的空间和时间分布之间的比较，以及拟合程序，以获得各种同位素的贡献在幻影。结果和结论：在一维空间和衰变率分布中，数据和MC预测之间有很好的一致性。通过用多个简单指数拟合衰变速率获得的$^{11}$ C、$^{15}$ O和$^{10}$ C的分数通常与MC预期一致。与MC中的预测值相比，我们发现数据中的$^{10}$ C略微过量，这在PE体模中尤其明显。
The First Nozzle-Mounted Compton Camera Prompt Gamma Imaging System for In Vivo Proton Therapy Dose Verification
University of Maryland School of Medicine（马里兰大学医学院）；University of Cape Town（开普敦大学）；University of Wisconsin School of Medicine and Public Health（威斯康星大学医学院与公共卫生学院）；University of Maryland, Baltimore County（马里兰大学巴尔的摩县分校）；H3D, Inc.（H3D公司）
Sensitivity analysis of biological washout and depth selection for a machine learning based dose verification framework in proton therapy
Wuhan University（武汉大学）；University of Texas MD Anderson Cancer Center（德克萨斯大学MD安德森癌症中心）；University of Texas Southwestern Medical Center（德克萨斯大学西南医学中心）；Shenzhen Bay Laboratory（深圳湾实验室）
Deep Learning-Based Automatic Delineation of Liver Domes in kV Triggered Images for Online Breath-hold Reproducibility Verification of Liver Stereotactic Body Radiation Therapy
Cleveland Clinic Foundation（克利夫兰医学中心）；Case Western Reserve University（凯斯西储大学）
Beam modelling of Hitachi PROBEAT proton therapy system for a GPU-based Fast Monte Carlo dose engine
University of Nebraska Omaha（内布拉斯加大学奥马哈分校）；Rice University（莱斯大学）；The University of Texas MD Anderson Cancer（德克萨斯大学安德森癌症中心）；Mevion Medical System（美维医疗系统）；Emory University（埃默里大学）
Terbium-149 PET/CT: First Quantitative Imaging with a Clinical Long-Axial Field-of-View Scanner
Department of Nuclear Medicine, Inselspital, Bern University Hostpital, University of Bern（伯尔尼大学医院因塞尔斯皮塔尔核医学科）；ARTORG Center for Biomedical Engineering Research, University of Bern（伯尔尼大学ARTORG生物医学工程研究中心）；Albert Einstein Center for Fundamental Physics (AEC), Laboratory for High Energy Physics (LHEP), University of Bern（伯尔尼大学阿尔伯特·爱因斯坦基础物理中心（AEC）高能物理实验室（LHEP））；Center for Radiopharmaceutical Sciences, PSI Center for Life Sciences, Villigen-PSI（维利根-PSI PSI生命科学中心放射药学科学中心）；Institut Laue-Langevin（朗之万研究所）；Laboratory of Radiochemistry, PSI Center for Nuclear Engineering and Sciences（PSI核工程与科学中心放射化学实验室）
Towards real-time ion range verification via hybrid Compton-PET 3D imaging at isochronous cyclotrons
Instituto de Física Corpuscular (CSIC-University of Valencia)（粒子物理研究所（西班牙科学理事会-瓦伦西亚大学））；Universitat Politècnica de Catalunya（加泰罗尼亚理工大学）；GSI Helmholtzzentrum für Schwerionenforschung（德国重离子研究中心）；Institut für Kernphysik, Technische Universität Darmstadt（达姆施塔特工业大学核物理研究所）；West German Proton Therapy Centre（西德质子治疗中心）
Prompt Gamma Timing for range verification with carbon ion irradiation: first experimental measurements and comparison with Geant4 Monte Carlo simulations
Istituto Nazionale di Fisica Nucleare Sezione di Torino（意大利国家核物理研究所都灵分部）；Università degli Studi di Torino（都灵大学）；Universidade Estadual de Santa Cruz（圣克鲁斯州立大学）；Fondazione Centro Nazionale di Adroterapia Oncologica（国家肿瘤重离子治疗中心基金会）
Secondary radiation measurements for particle therapy applications: prompt photons produced by $^{4}$He, $^{12}$C and $^{16}$O ion beams in a PMMA target
Fast proton transport and neutron production in proton therapy using Fourier neural operators
Fraunhofer ENAS（弗劳恩霍夫 ENAS）；Technical University Chemnitz（德累斯顿工业大学）；Western Norway University of Applied Sciences（西挪威应用科学大学）；University of Bergen（卑尔根大学）
Automatic Quantification of Serial PET/CT Images for Pediatric Hodgkin Lymphoma Patients Using a Longitudinally-Aware Segmentation Network
University of Wisconsin（威斯康星大学）；University of Wisconsin Carbone Comprehensive Cancer Center（威斯康星大学卡本综合癌症中心）；Emory University School of Medicine（埃默里大学医学院）；Aflac Cancer and Blood Disorders Center（aflac癌症与血液疾病中心）；Roswell Park Comprehensive Cancer Center（罗斯威尔公园综合癌症中心）；University at Buffalo Jacobs School of Medicine and Biomedical Sciences（布法罗大学雅各布斯医学与生物医学科学学院）；Imaging and Radiation Oncology Core Rhode Island（罗德岛影像与放射肿瘤学核心机构）
