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Proposing a Clinical Model for RBE Based on Proton Track-End Counts.

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Title: Proposing a Clinical Model for RBE Based on Proton Track-End Counts.
Authors: Henthorn, Nicholas T.1,2 (AUTHOR) nicholas.henthorn@manchester.ac.uk, Gardner, Lydia L.3 (AUTHOR), Aitkenhead, Adam H.1,4 (AUTHOR), Rowland, Benjamin C.1,2 (AUTHOR), Shin, Jungwook5 (AUTHOR), Smith, Edward A.K.1,2 (AUTHOR), Merchant, Michael J.1,2 (AUTHOR), Mackay, Ranald I.1,4 (AUTHOR), Kirkby, Karen J.1,2 (AUTHOR), Chaudhary, Pankaj3 (AUTHOR), Prise, Kevin M.3 (AUTHOR), McMahon, Stephen J.1,3 (AUTHOR), Underwood, Tracy S.A.1,2,6 (AUTHOR)
Source: International Journal of Radiation Oncology, Biology, Physics. Jul2023, Vol. 116 Issue 4, p916-926. 11p.
Subjects: Linear energy transfer, Monte Carlo method, Protons, Atomic number, Proton therapy
Abstract: In proton therapy, the clinical application of linear energy transfer (LET) optimization remains contentious, in part because of challenges associated with the definition and calculation of LET and its exact relationship with relative biological effectiveness (RBE) because of large variation in experimental in vitro data. This has raised interest in other metrics with favorable properties for biological optimization, such as the number of proton track ends in a voxel. In this work, we propose a novel model for clinical calculations of RBE, based on proton track end counts. We developed an effective dose concept to translate between the total proton track-end count per unit mass in a voxel and a proton RBE value. Dose, track end, and dose-averaged LET (LET d) distributions were simulated using Monte Carlo models for a series of water phantoms, in vitro radiobiological studies, and patient treatment plans. We evaluated the correlation between track ends and regions of elevated biological effectiveness in comparison to LET d -based models of RBE. Track ends were found to correlate with biological effects in in vitro experiments with an accuracy comparable to LET d. In patient simulations, our track end model identified the same biological hotspots as predicted by LET d -based radiobiological models of proton RBE. These results suggest that, for clinical optimization and evaluation, an RBE model based on proton track end counts may match LET d -based models in terms of information provided while also offering superior statistical properties. [ABSTRACT FROM AUTHOR]
Copyright of International Journal of Radiation Oncology, Biology, Physics is the property of Pergamon Press - An Imprint of Elsevier Science and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Engineering Source
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PubType: Academic Journal
PubTypeId: academicJournal
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  Data: Proposing a Clinical Model for RBE Based on Proton Track-End Counts.
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  Data: <searchLink fieldCode="AR" term="%22Henthorn%2C+Nicholas+T%2E%22">Henthorn, Nicholas T.</searchLink><relatesTo>1,2</relatesTo> (AUTHOR)<i> nicholas.henthorn@manchester.ac.uk</i><br /><searchLink fieldCode="AR" term="%22Gardner%2C+Lydia+L%2E%22">Gardner, Lydia L.</searchLink><relatesTo>3</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Aitkenhead%2C+Adam+H%2E%22">Aitkenhead, Adam H.</searchLink><relatesTo>1,4</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Rowland%2C+Benjamin+C%2E%22">Rowland, Benjamin C.</searchLink><relatesTo>1,2</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Shin%2C+Jungwook%22">Shin, Jungwook</searchLink><relatesTo>5</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Smith%2C+Edward+A%2EK%2E%22">Smith, Edward A.K.</searchLink><relatesTo>1,2</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Merchant%2C+Michael+J%2E%22">Merchant, Michael J.</searchLink><relatesTo>1,2</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Mackay%2C+Ranald+I%2E%22">Mackay, Ranald I.</searchLink><relatesTo>1,4</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Kirkby%2C+Karen+J%2E%22">Kirkby, Karen J.</searchLink><relatesTo>1,2</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Chaudhary%2C+Pankaj%22">Chaudhary, Pankaj</searchLink><relatesTo>3</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Prise%2C+Kevin+M%2E%22">Prise, Kevin M.</searchLink><relatesTo>3</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22McMahon%2C+Stephen+J%2E%22">McMahon, Stephen J.</searchLink><relatesTo>1,3</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Underwood%2C+Tracy+S%2EA%2E%22">Underwood, Tracy S.A.</searchLink><relatesTo>1,2,6</relatesTo> (AUTHOR)
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  Data: <searchLink fieldCode="JN" term="%22International+Journal+of+Radiation+Oncology%2C+Biology%2C+Physics%22">International Journal of Radiation Oncology, Biology, Physics</searchLink>. Jul2023, Vol. 116 Issue 4, p916-926. 11p.
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  Data: <searchLink fieldCode="DE" term="%22Linear+energy+transfer%22">Linear energy transfer</searchLink><br /><searchLink fieldCode="DE" term="%22Monte+Carlo+method%22">Monte Carlo method</searchLink><br /><searchLink fieldCode="DE" term="%22Protons%22">Protons</searchLink><br /><searchLink fieldCode="DE" term="%22Atomic+number%22">Atomic number</searchLink><br /><searchLink fieldCode="DE" term="%22Proton+therapy%22">Proton therapy</searchLink>
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: In proton therapy, the clinical application of linear energy transfer (LET) optimization remains contentious, in part because of challenges associated with the definition and calculation of LET and its exact relationship with relative biological effectiveness (RBE) because of large variation in experimental in vitro data. This has raised interest in other metrics with favorable properties for biological optimization, such as the number of proton track ends in a voxel. In this work, we propose a novel model for clinical calculations of RBE, based on proton track end counts. We developed an effective dose concept to translate between the total proton track-end count per unit mass in a voxel and a proton RBE value. Dose, track end, and dose-averaged LET (LET d) distributions were simulated using Monte Carlo models for a series of water phantoms, in vitro radiobiological studies, and patient treatment plans. We evaluated the correlation between track ends and regions of elevated biological effectiveness in comparison to LET d -based models of RBE. Track ends were found to correlate with biological effects in in vitro experiments with an accuracy comparable to LET d. In patient simulations, our track end model identified the same biological hotspots as predicted by LET d -based radiobiological models of proton RBE. These results suggest that, for clinical optimization and evaluation, an RBE model based on proton track end counts may match LET d -based models in terms of information provided while also offering superior statistical properties. [ABSTRACT FROM AUTHOR]
– Name: AbstractSuppliedCopyright
  Label:
  Group: Ab
  Data: <i>Copyright of International Journal of Radiation Oncology, Biology, Physics is the property of Pergamon Press - An Imprint of Elsevier Science and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=egs&AN=164301730
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        Value: 10.1016/j.ijrobp.2022.12.056
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        Text: English
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      – SubjectFull: Linear energy transfer
        Type: general
      – SubjectFull: Monte Carlo method
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      – SubjectFull: Protons
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              Text: Jul2023
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