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3. A quantitative assessment of Geant4 for predicting the yield and distribution of positron-emitting fragments in ion beam therapy

Author

Chacon, Andrew, Rutherford, Harley, Hamato, Akram, Nitta, Munetaka, Nishikido, Fumihiko, Iwao, Yuma, Tashima, Hideaki, Yoshida, Eiji, Akamatsu, Go, Takyu, Sodai, Kang, Han Gyu, Franklin, Daniel R., Parodi, Katia, Yamaya, Taiga, Rosenfeld, Anatoly, Guatelli, Susanna, and Safavi-Naeini, Mitra

Subjects
Physics - Computational Physics, Physics - Medical Physics
Abstract

Purpose: To compare the accuracy with which different hadronic inelastic physics models across ten Geant4 Monte Carlo simulation toolkit versions can predict positron-emitting fragments produced along the beam path during carbon and oxygen ion therapy. Materials and Methods: Phantoms of polyethylene, gelatin or poly(methyl methacrylate) were irradiated with monoenergetic carbon and oxygen ion beams. Post-irradiation, 4D PET images were acquired and parent $^{11}$C, $^{10}$C and $^{15}$O radionuclides contributions in each voxel were determined from the extracted time activity curves. Experiments were simulated in Geant4 Monte Carlo versions 10-11.1, with three different fragmentation models: binary ion cascade (BIC), quantum molecular dynamics (QMD) and the Liege intranuclear cascade (INCL++) - 30 combinations. Total/parent isotope positron annihilation yields were compared between simulations and experiments using normalised mean squared error and Pearson cross-correlation coefficient. Depth of maximum/distal 50\% peak position yield were also compared. Results: Performance varied considerably across versions and models, with no one best predicting all positron-emitting fragments. BIC in Geant4 10.2 provided the best overall agreement with experimental results in the largest number of test cases. QMD consistently provided the best estimates of both the depth of peak positron yield (10.4 and 10.6) and the distal 50\%-of-peak point (10.2), while BIC also performed well and INCL generally performed the worst across most Geant4 versions. Conclusions: Best spatial prediction of annihilation yield and positron-emitting fragment production during carbon and oxygen ion therapy was found to be 10.2.p03 with BIC or QMD. These version/model combinations are recommended for future heavy ion therapy research., Comment: This manuscript has been submitted to IOP's Journal of Physics in Medicine and Biology, on the 5th of February 2024

Published
2024

8. Fully 3D Implementation of the End-to-end Deep Image Prior-based PET Image Reconstruction Using Block Iterative Algorithm

Author

Hashimoto, Fumio, Onishi, Yuya, Ote, Kibo, Tashima, Hideaki, and Yamaya, Taiga

Subjects
Physics - Medical Physics, Computer Science - Computer Vision and Pattern Recognition, Computer Science - Machine Learning, Electrical Engineering and Systems Science - Image and Video Processing
Abstract

Deep image prior (DIP) has recently attracted attention owing to its unsupervised positron emission tomography (PET) image reconstruction, which does not require any prior training dataset. In this paper, we present the first attempt to implement an end-to-end DIP-based fully 3D PET image reconstruction method that incorporates a forward-projection model into a loss function. To implement a practical fully 3D PET image reconstruction, which could not be performed due to a graphics processing unit memory limitation, we modify the DIP optimization to block-iteration and sequentially learn an ordered sequence of block sinograms. Furthermore, the relative difference penalty (RDP) term was added to the loss function to enhance the quantitative PET image accuracy. We evaluated our proposed method using Monte Carlo simulation with [$^{18}$F]FDG PET data of a human brain and a preclinical study on monkey brain [$^{18}$F]FDG PET data. The proposed method was compared with the maximum-likelihood expectation maximization (EM), maximum-a-posterior EM with RDP, and hybrid DIP-based PET reconstruction methods. The simulation results showed that the proposed method improved the PET image quality by reducing statistical noise and preserved a contrast of brain structures and inserted tumor compared with other algorithms. In the preclinical experiment, finer structures and better contrast recovery were obtained by the proposed method. This indicated that the proposed method can produce high-quality images without a prior training dataset. Thus, the proposed method is a key enabling technology for the straightforward and practical implementation of end-to-end DIP-based fully 3D PET image reconstruction., Comment: 9 pages, 10 figures

Published
2022
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20. Quantitative PET in the 2020s: a roadmap

Author

Meikle, Steven R, Sossi, Vesna, Roncali, Emilie, Cherry, Simon R, Banati, Richard, Mankoff, David, Jones, Terry, James, Michelle, Sutcliffe, Julie, Ouyang, Jinsong, Petibon, Yoann, Ma, Chao, El Fakhri, Georges, Surti, Suleman, Karp, Joel S, Badawi, Ramsey D, Yamaya, Taiga, Akamatsu, Go, Schramm, Georg, Rezaei, Ahmadreza, Nuyts, Johan, Fulton, Roger, Kyme, André, Lois, Cristina, Sari, Hasan, Price, Julie, Boellaard, Ronald, Jeraj, Robert, Bailey, Dale L, Eslick, Enid, Willowson, Kathy P, and Dutta, Joyita

Subjects
Medical and Biological Physics, Physical Sciences, Biomedical Imaging, Bioengineering, Detection, screening and diagnosis, 4.1 Discovery and preclinical testing of markers and technologies, 4.2 Evaluation of markers and technologies, Generic health relevance, Artificial Intelligence, History, 20th Century, History, 21st Century, Humans, Image Processing, Computer-Assisted, Imaging, Three-Dimensional, Kinetics, Medical Oncology, Neoplasms, Positron Emission Tomography Computed Tomography, Positron-Emission Tomography, Prognosis, Radiopharmaceuticals, Systems Biology, Tomography, X-Ray Computed, Positron emission tomography, magnetic resonance imaging, time-of-flight PET, total-body PET, motion correction, dosimetry, quantification, Other Physical Sciences, Biomedical Engineering, Clinical Sciences, Nuclear Medicine & Medical Imaging, Medical and biological physics
Abstract

Positron emission tomography (PET) plays an increasingly important role in research and clinical applications, catalysed by remarkable technical advances and a growing appreciation of the need for reliable, sensitive biomarkers of human function in health and disease. Over the last 30 years, a large amount of the physics and engineering effort in PET has been motivated by the dominant clinical application during that period, oncology. This has led to important developments such as PET/CT, whole-body PET, 3D PET, accelerated statistical image reconstruction, and time-of-flight PET. Despite impressive improvements in image quality as a result of these advances, the emphasis on static, semi-quantitative 'hot spot' imaging for oncologic applications has meant that the capability of PET to quantify biologically relevant parameters based on tracer kinetics has not been fully exploited. More recent advances, such as PET/MR and total-body PET, have opened up the ability to address a vast range of new research questions, from which a future expansion of applications and radiotracers appears highly likely. Many of these new applications and tracers will, at least initially, require quantitative analyses that more fully exploit the exquisite sensitivity of PET and the tracer principle on which it is based. It is also expected that they will require more sophisticated quantitative analysis methods than those that are currently available. At the same time, artificial intelligence is revolutionizing data analysis and impacting the relationship between the statistical quality of the acquired data and the information we can extract from the data. In this roadmap, leaders of the key sub-disciplines of the field identify the challenges and opportunities to be addressed over the next ten years that will enable PET to realise its full quantitative potential, initially in research laboratories and, ultimately, in clinical practice.

Published
2021

35. A quantitative assessment of Geant4 for predicting the yield and distribution of positron-emitting fragments in ion beam therapy

Author

Chacon, Andrew, primary, Rutherford, Harley, additional, Mohammadi, Akram, additional, Nitta, Munetaka, additional, Nishikido, Fumihiko, additional, Iwao, Yuma, additional, Tashima, Hideaki, additional, Yoshida, Eiji, additional, Akamatsu, Go, additional, Takyu, Sodai, additional, Kang, Han Gyu, additional, Franklin, Daniel Robert, additional, Parodi, Katia, additional, Yamaya, Taiga, additional, Rosenfeld, Anatoly B, additional, Guatelli, Susanna, additional, and Safavi-Naeini, Mitra, additional

Published
2024
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38. Three-Gamma Imaging in Nuclear Medicine: A Review

Author

Tashima, Hideaki and Yamaya, Taiga

Abstract

Three-gamma imaging is attracting attention as a futuristic diagnostic imaging method that surpasses positron emission tomography (PET). Its conceptual key is using $\beta ^{+}$ - $\gamma $ nuclides that simultaneously emit a prompt gamma ray with the positron decay. In this review, we have categorized the utilizations of prompt gamma rays into three categories: 1) multiple positron emitter imaging; 2) reconstruction-less positron emission imaging; and 3) positronium lifetime imaging. Multiple positron emitter imaging utilizes the prompt gamma ray as a trigger to discriminate from signals of pure positron emitters to enable simultaneous injection and imaging of two different radioisotopes. Reconstruction-less positron emission imaging combines PET and Compton imaging technologies to estimate the source position as almost a point for each triple coincidence event. Positronium lifetime imaging utilizes the prompt gamma ray as a starting signal to measure the time difference between positronium formation and annihilation for each triple coincidence event as its lifetime. This is because the positronium lifetime is affected by the surrounding microenvironment of electrons, it is expected to provide new information regarding biological conditions, such as the hypoxia state. In this review we introduce the principles of the three categories of three-gamma imaging methods, prototype development, and demonstration experiments.

Published
2024
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41. Whole Gamma Imaging

Author

Yamaya, Taiga, primary, Tashima, Hideaki, additional, Takyu, Sodai, additional, and Takahashi, Miwako, additional

Published
2024
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44. Development of DynamicMC for PHITS Monte Carlo package

Author

Watabe, Hiroshi, primary, Sato, Tatsuhiko, additional, Yu, Kwan Ngok, additional, Zivkovic, Milena, additional, Krstic, Dragana, additional, Nikezic, Dragoslav, additional, Kim, Kyeong Min, additional, Yamaya, Taiga, additional, Kawachi, Naoki, additional, Tanaka, Hiroki, additional, Haque, A K F, additional, Islam, M Rafiqul, additional, and Shahmohammadi Beni, Mehrdad, additional

Published
2023
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