Dose reconstruction from PET images in carbon ion therapy: a deconvolution approach

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dc.contributor.authorHofmann, Ten_AU
dc.contributor.authorPinto, Men_AU
dc.contributor.authorMohammadi, Aen_AU
dc.contributor.authorNitta, Men_AU
dc.contributor.authorNishikido, Fen_AU
dc.contributor.authorIwao, Yen_AU
dc.contributor.authorTashima, Hen_AU
dc.contributor.authorYoshida, Een_AU
dc.contributor.authorChacon, Aen_AU
dc.contributor.authorSafavi-Naeini, Men_AU
dc.contributor.authorRosenfeld, ABen_AU
dc.contributor.authorYamaya, Ten_AU
dc.contributor.authorParodi, Ken_AU
dc.date.accessioned2025-01-13T04:52:59Zen_AU
dc.date.available2025-01-13T04:52:59Zen_AU
dc.date.issued2019-01-01en_AU
dc.date.statistics2024-11-19en_AU
dc.description.abstractDose and range verification have become important tools to bring carbon ion therapy to a higher level of confidence in clinical applications. Positron emission tomography is among the most commonly used approaches for this purpose and relies on the creation of positron emitting nuclei in nuclear interactions of the primary ions with tissue. Predictions of these positron emitter distributions are usually obtained from time-consuming Monte Carlo simulations or measurements from previous treatment fractions, and their comparison to the current, measured image allows for treatment verification. Still, a direct comparison of planned and delivered dose would be highly desirable, since the dose is the quantity of interest in radiation therapy and its confirmation improves quality assurance in carbon ion therapy. In this work, we present a deconvolution approach to predict dose distributions from PET images in carbon ion therapy. Under the assumption that the one-dimensional PET distribution is described by a convolution of the depth dose distribution and a filter kernel, an evolutionary algorithm is introduced to perform the reverse step and predict the depth dose distribution from a measured PET distribution. Filter kernels are obtained from either a library or are created for any given situation on-the-fly, using predictions of the β + -decay and depth dose distributions, and the very same evolutionary algorithm. The applicability of this approach is demonstrated for monoenergetic and polyenergetic carbon ion irradiation of homogeneous and heterogeneous solid phantoms as well as a patient computed tomography image, using Monte Carlo simulated distributions and measured in-beam PET data. Carbon ion ranges are predicted within less than 0.5 mm and 1 mm deviation for simulated and measured distributions, respectively. © 2019 Institute of Physics and Engineering in Medicine.en_AU
dc.description.sponsorshipThis work has been financially supported by the the DFG Cluster of Excellence MAP, PROSALMU, the NIRS International Open Laboratory and the QST International Research Initiative. The authors would like to thank Adrian Fochi for his contribution to this work and the team of Prof Dr Belka from Klinikum Großhadern for providing the patient CT.en_AU
dc.format.mediumElectronicen_AU
dc.identifier.citationHofmann, T., Pinto, M., Mohammadi, A., Nitta, M., Nishikido, F., Iwao, Y., Tashima, H., Yoshida, E., Chacon, A., Safavi-Naeini, M., Rosenfeld, A., Yamaya, T., & Parodi, K. (2019). Dose reconstruction from PET images in carbon ion therapy: a deconvolution approach. Physics in Medicine & Biology, 64(2), 025011. doi:10.1088/1361-6560/aaf676en_AU
dc.identifier.issn0031-9155en_AU
dc.identifier.issn1361-6560en_AU
dc.identifier.issue2en_AU
dc.identifier.journaltitlePhysics in Medicine and Biologyen_AU
dc.identifier.urihttps://doi.org/10.1088/1361-6560/aaf676en_AU
dc.identifier.urihttps://apo.ansto.gov.au/handle/10238/15933en_AU
dc.identifier.volume64en_AU
dc.languageengen_AU
dc.language.isoenen_AU
dc.publisherIOP Publishingen_AU
dc.relation.uri025011en_AU
dc.subjectCarbonen_AU
dc.subjectIonsen_AU
dc.subjectImagesen_AU
dc.subjectDosesen_AU
dc.subjectPositronsen_AU
dc.subjectTomographyen_AU
dc.subjectNucleien_AU
dc.subjectInteractionsen_AU
dc.subjectMonte Carlo Methoden_AU
dc.subjectSimulationen_AU
dc.subjectPositron computed tomographyen_AU
dc.subjectNeoplasmsen_AU
dc.subjectIrradiationen_AU
dc.titleDose reconstruction from PET images in carbon ion therapy: a deconvolution approachen_AU
dc.typeJournal Articleen_AU
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