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Micro/nanometric Scale Study of Energy Deposition and its Impact on the Biological Response for Ionizing Radiation: Brachytherapy radionuclides, proton and carbon ion beams
Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology, Medical Radiation Science. (Medical Radiation Science)
2016 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

Research in radiotherapy for cancer treatment focuses on finding methods that can improve the compromise between tumour cell inactivation versus damage to the surrounding healthy tissue. As new radiation modalities such as proton therapy become accessible for everyday clinical practice, a better understanding of the variation in biological response of the tumour and healthy tissues would improve treatment planning to achieve optimal outcome. The development of radiobiological models capable of accurate predictions of biological effectiveness is needed.

Existing radiation quality descriptors such as absorbed dose and LET are insufficient to explain variation in biological effectiveness for different treatment modalities. The stochastic nature of ionizing radiation creates discrete patterns of energy deposition (ED) sites which can now be analysed through sophisticated computer simulations (e.g. Monte Carlo track structure codes). This opens the possibility to develop a nanometre characterization of radiation quality based on the spatial cluster patterns of ED.

The aim of this thesis is to investigate the track structure (ED spatial pattern) properties of several radiation qualities at a micro- and nanometric scale while exploring their influence in biological response through correlations with published experimental data. This work uses track structure data simulated for a set of 15 different radiation qualities: 4 commonly used brachytherapy sources, 6 different proton energies, 4 different carbon ion energies, and 60Co photons used as reference radiation for quantification of biological effectiveness.

At a micrometre level, the behaviour of the microdosimetric spread in energy deposition for target sizes of the order of cell nuclei was analysed. The degree of the influence it had in the biological response was found to be negligible for photon sources but for protons and carbon ions the impact increased with decreasing particle energy suggesting it may be a confounding factor in biological response.

Finally, this thesis outlines a framework for modelling the relative biological effectiveness based on the frequency distribution of cluster order as a surrogate for the nanometre classification for the physical properties of radiation quality. The results indicate that this frequency is a valuable descriptor of ionizing radiation. The positive correlation across the different types of ionizing radiation encourages further development of the framework by incorporating the behavior of the microdosimetric spread and expanding tests to other experimental datasets.

Place, publisher, year, edition, pages
Uppsala: Acta Universitatis Upsaliensis, 2016. , 53 p.
Series
Digital Comprehensive Summaries of Uppsala Dissertations from the Faculty of Medicine, ISSN 1651-6206 ; 1188
Keyword [en]
Ionizing radiation, Monte Carlo track structure code, Microdosimetric spread, Energy deposition clustering, RBE
National Category
Cancer and Oncology
Research subject
Medical Radiophysics
Identifiers
URN: urn:nbn:se:uu:diva-279385ISBN: 978-91-554-9495-7 (print)OAI: oai:DiVA.org:uu-279385DiVA: diva2:908007
Public defence
2016-04-22, Skoogssalen, Akademiska Sjukhuset, Ing. 78-79, Uppsala, 09:30 (English)
Opponent
Supervisors
Available from: 2016-04-01 Created: 2016-03-01 Last updated: 2016-04-05
List of papers
1. Monte Carlo calculated microdosimetric spread for cell nucleus-sized targets exposed to brachytherapy 125I and 192Ir sources and 60Co cell irradiation
Open this publication in new window or tab >>Monte Carlo calculated microdosimetric spread for cell nucleus-sized targets exposed to brachytherapy 125I and 192Ir sources and 60Co cell irradiation
2013 (English)In: Physics in Medicine and Biology, ISSN 0031-9155, E-ISSN 1361-6560, Vol. 58, no 17, 6149-6162 p.Article in journal (Refereed) Published
Abstract [en]

The stochastic nature of ionizing radiation interactions causes a microdosimetric spread in energy depositions for cell or cell nucleus-sized volumes. The magnitude of the spread may be a confounding factor in dose response analysis. The aim of this work is to give values for the microdosimetric spread for a range of doses imparted by 125I and 192Ir brachytherapy radionuclides, and for a 60Co source. An upgraded version of the Monte Carlo code PENELOPE was used to obtain frequency distributions of specific energy for each of these radiation qualities and for four different cell nucleus-sized volumes. The results demonstrate that the magnitude of the microdosimetric spread increases when the target size decreases or when the energy of the radiation quality is reduced. Frequency distributions calculated according to the formalism of Kellerer and Chmelevsky using full convolution of the Monte Carlo calculated single track frequency distributions confirm that at doses exceeding 0.08 Gy for 125I, 0.1 Gy for 192Ir, and 0.2 Gy for 60Co, the resulting distribution can be accurately approximated with a normal distribution. A parameterization of the width of the distribution as a function of dose and target volume of interest is presented as a convenient form for the use in response modelling or similar contexts.

National Category
Radiology, Nuclear Medicine and Medical Imaging
Identifiers
urn:nbn:se:uu:diva-208046 (URN)10.1088/0031-9155/58/17/6149 (DOI)000323517700024 ()
Funder
Swedish National Infrastructure for Computing (SNIC), p2011144
Available from: 2013-09-24 Created: 2013-09-23 Last updated: 2017-12-06
2. Reply to the comment on ‘Monte Carlo calculated microdosimetric spread for cell nucleus-sized targets exposed to brachytherapy 125I and 192Ir sources and 60Co cell irradiation’
Open this publication in new window or tab >>Reply to the comment on ‘Monte Carlo calculated microdosimetric spread for cell nucleus-sized targets exposed to brachytherapy 125I and 192Ir sources and 60Co cell irradiation’
2016 (English)In: Physics in Medicine and Biology, ISSN 0031-9155, E-ISSN 1361-6560, Vol. 61, no 13, 5103-5106 p.Article in journal, Editorial material (Refereed) Published
Abstract [en]

A discrepancy between the Monte Carlo derived relative standard deviation sigma(rel)(z) (microdosimetric spread) and experimental data was reported by Villegas et al (2013 Phys. Med. Biol. 58 6149-62) suggesting wall effects as a plausible explanation. The comment by Lindborg et al (2015 Phys. Med. Biol. 60 8621-4) concludes that this is not a likely explanation. A thorough investigation of the Monte Carlo (MC) transport code used for track simulation revealed a critical bug. The corrected MC version yielded sigma(rel)(z) values that are now within experimental uncertainty. Other microdosimetric findings are hereby communicated.

National Category
Radiology, Nuclear Medicine and Medical Imaging
Research subject
Medical Radiophysics
Identifiers
urn:nbn:se:uu:diva-279243 (URN)10.1088/0031-9155/61/13/5103 (DOI)000378094000023 ()
Funder
Swedish National Infrastructure for Computing (SNIC), p2011144
Available from: 2016-02-29 Created: 2016-02-29 Last updated: 2017-11-30Bibliographically approved
3. Microdosimetric spread for cell-sized targets exposed to 60Co, 192Ir and 125I sources
Open this publication in new window or tab >>Microdosimetric spread for cell-sized targets exposed to 60Co, 192Ir and 125I sources
2015 (English)In: Radiation Protection Dosimetry, ISSN 0144-8420, E-ISSN 1742-3406, Vol. 166, no 1-4, 365-368 p.Article in journal (Refereed) Published
Abstract [en]

The magnitude of the spread in specific energy deposition per cell may be a confounding factor in dose–response analysis motivating derivation of explicit data for the most common brachytherapy isotopes 125I and 192Ir, and for 60Co radiation frequently used as reference in RBE studies. The aim of this study is to analyse the microdosimetric spread as given by the frequency distribution of specific energy for a range of doses imparted by 125I, 192Ir and 60Co sources. An upgraded version of the Monte Carlo code PENELOPE was used for scoring energy deposition distributions in liquid water for each of the radiation qualities. Frequency distributions of specific energy were calculated according to the formalism of Kellerer and Chmelevsky. Results indicate that the magnitude of the microdosimetric spread increases with decreasing target size and decreasing energy of the radiation quality. Within the clinical relevant dose range (1 to 100 Gy), the spread does not exceed 4 % for 60Co, 5 % for 192Ir and 6 % for 125I. The frequency distributions can be accurately approximated with symmetrical normal distributions at doses down to 0.2 Gy for 60Co, 0.1 Gy for 192Ir and 0.08 Gy for 125I.

National Category
Cancer and Oncology Radiology, Nuclear Medicine and Medical Imaging
Identifiers
urn:nbn:se:uu:diva-259745 (URN)10.1093/rpd/ncv200 (DOI)000361806600075 ()
Funder
Swedish National Infrastructure for Computing (SNIC), p2011144
Available from: 2015-08-11 Created: 2015-08-11 Last updated: 2017-12-04
4. Cluster pattern analysis of energy deposition sites for the brachytherapy sources 103Pd, 125I, 192Ir, 137Cs, and 60Co
Open this publication in new window or tab >>Cluster pattern analysis of energy deposition sites for the brachytherapy sources 103Pd, 125I, 192Ir, 137Cs, and 60Co
2014 (English)In: Physics in Medicine and Biology, ISSN 0031-9155, E-ISSN 1361-6560, Vol. 59, no 18, 5531-5543 p.Article in journal (Refereed) Published
Abstract [en]

Analysing the pattern of energy depositions may help elucidate differences in the severity of radiation-induced DNA strand breakage for different radiation qualities. It is often claimed that energy deposition (ED) sites from photon radiation form a uniform random pattern, but there is indication of differences in RBE values among different photon sources used in brachytherapy. The aim of this work is to analyse the spatial patterns of EDs from 103Pd, 125I, 192Ir, 137Cs sources commonly used in brachytherapy and a 60Co source as a reference radiation. The results suggest that there is both a non-uniform and a uniform random component to the frequency distribution of distances to the nearest neighbour ED. The closest neighbouring EDs show high spatial correlation for all investigated radiation qualities, whilst the uniform random component dominates for neighbours with longer distances for the three higher mean photon energy sources (192Ir, 137Cs, and 60Co). The two lower energy photon emitters (103Pd and 125I) present a very small uniform random component. The ratio of frequencies of clusters with respect to 60Co differs up to 15% for the lower energy sources and less than 2% for the higher energy sources when the maximum distance between each pair of EDs is 2 nm. At distances relevant to DNA damage, cluster patterns can be differentiated between the lower and higher energy sources. This may be part of the explanation to the reported difference in RBE values with initial DSB yields as an endpoint for these brachytherapy sources.

Keyword
clusters, energy deposition sites, brachytherapy
National Category
Radiology, Nuclear Medicine and Medical Imaging Cancer and Oncology
Identifiers
urn:nbn:se:uu:diva-235065 (URN)10.1088/0031-9155/59/18/5531 (DOI)000341381900022 ()25170775 (PubMedID)
Funder
Swedish National Infrastructure for Computing (SNIC), p2011144
Available from: 2014-10-29 Created: 2014-10-28 Last updated: 2017-12-05
5. Corrigendum to ’Cluster pattern analysis of energy deposition sites for the brachytherapy sources 103Pd,125I,192Ir,137Cs and 60Co’, PMB 59 (2014) 5531-43
Open this publication in new window or tab >>Corrigendum to ’Cluster pattern analysis of energy deposition sites for the brachytherapy sources 103Pd,125I,192Ir,137Cs and 60Co’, PMB 59 (2014) 5531-43
2016 (English)In: Physics in Medicine and Biology, ISSN 0031-9155, E-ISSN 1361-6560, Vol. 61, no 15, 5883-5886 p.Article in journal (Refereed) Published
National Category
Other Medical Sciences
Research subject
Medical Radiophysics
Identifiers
urn:nbn:se:uu:diva-279246 (URN)10.1088/0031-9155/61/15/5883 (DOI)000384207500025 ()
Funder
Swedish National Infrastructure for Computing (SNIC), p2011144
Available from: 2016-02-29 Created: 2016-02-29 Last updated: 2017-11-30Bibliographically approved
6. The impact on linear-quadratic parameterization of cell survival data from the microdosimetric spread of specific energy for different cell nuclei size distributions.
Open this publication in new window or tab >>The impact on linear-quadratic parameterization of cell survival data from the microdosimetric spread of specific energy for different cell nuclei size distributions.
Show others...
(English)Manuscript (preprint) (Other academic)
National Category
Other Medical Sciences
Research subject
Medical Radiophysics
Identifiers
urn:nbn:se:uu:diva-279210 (URN)
Funder
Swedish National Infrastructure for Computing (SNIC), p2011144
Available from: 2016-02-29 Created: 2016-02-29 Last updated: 2016-04-28
7. Energy deposition clustering as a functional radiation quality descriptor for modelling relative biological effectiveness
Open this publication in new window or tab >>Energy deposition clustering as a functional radiation quality descriptor for modelling relative biological effectiveness
2016 (English)In: Medical physics (Lancaster), ISSN 0094-2405, Vol. 43, no 12, 6322-6335 p.Article in journal (Refereed) Published
Abstract [en]

Purpose: To explore the use of the frequency of the energy deposition (ED) clusters of different sizes (cluster order, CO) as a surrogate (instead of, e.g., LET) classification of the physical characteristics of ionizing radiation at a nanometer scale, to construct a framework for the calculation of relative biological effectiveness (RBE) with cell survival as endpoint.

Methods: The frequency of cluster order f(CO) is calculated by sorting the ED sites generated with the Monte Carlo track structure code LIonTrack into clusters based on a single parameter called the cluster distance d(C) being the maximum allowed distance between two neighboring EDs belonging to a cluster. Published cell survival data parameterized with the linear-quadratic (LQ) model for V79 cells exposed to 15 different radiation qualities (including brachytherapy sources, proton, and carbon ions) were used as input to a fitting procedure, designed to determine a weighting function w(CO) that describes the capacity of a cluster of a certain CO to damage the cell's sensitive volume. The proposed framework uses both f(CO) and w(CO) to construct surrogate based functions for the LQ parameters a and beta from which RBE values can be derived.

Results: The results demonstrate that radiation quality independent weights w(CO) exist for both the a and beta parameters. This enables the calculation of a values that correlate to their experimental counterparts within experimental uncertainties (relative residual of 15% for d(C) = 2.5 nm). The combination of both a and beta surrogate based functions, despite the higher relative residuals for beta values, yielded an RBE function that correlated to experimentally derived RBE values (relative residual of 16.5% for d(C) = 2.5 nm) for all radiation qualities included in this work.

Conclusions: The f(CO) cluster characterization of ionizing radiation at a nanometer scale can effectively be used to calculate particle and energy dependent a and beta values to predict RBE values with potential applications to, e.g., treatment planning systems in radiotherapy. (C) 2016 American Association of Physicists in Medicine.

Keyword
RBE, Monte Carlo track structure, linear-quadratic model, energy deposition clusters
National Category
Cancer and Oncology
Research subject
Medical Radiophysics
Identifiers
urn:nbn:se:uu:diva-279240 (URN)10.1118/1.4966033 (DOI)000390237200012 ()
Funder
Swedish National Infrastructure for Computing (SNIC), p2011144Swedish Radiation Safety Authority
Available from: 2016-02-29 Created: 2016-02-29 Last updated: 2017-11-30Bibliographically approved

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