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Towards optimal heterogeneous prostate radiotherapy dose prescriptions based on patient‐specific or population‐based biological features.

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Title: Towards optimal heterogeneous prostate radiotherapy dose prescriptions based on patient‐specific or population‐based biological features.
Authors: Zhao, Yutong1 (AUTHOR) yutong.zhao960314@gmail.com, Haworth, Annette2 (AUTHOR), Reynolds, Hayley M.3 (AUTHOR), Williams, Scott G.4,5 (AUTHOR), Finnegan, Robert2,6,7 (AUTHOR), Rowshanfarzad, Pejman1 (AUTHOR), Ebert, Martin A.1,8,9 (AUTHOR)
Source: Medical Physics. May2024, Vol. 51 Issue 5, p3766-3781. 16p.
Subjects: Medical prescriptions, Prostate, Drug dosage, Dose-response relationship (Radiation), Radiotherapy, Tumor grading, Urodynamics
Abstract: Background: Escalation of prescribed dose in prostate cancer (PCa) radiotherapy enables improvement in tumor control at the expense of increased toxicity. Opportunities for reduction of treatment toxicity may emerge if more efficient dose escalation can be achieved by redistributing the prescribed dose distribution according to the known heterogeneous, spatially‐varying characteristics of the disease. Purpose: To examine the potential benefits, limitations and characteristics of heterogeneous boost dose redistribution in PCa radiotherapy based on patient‐specific and population‐based spatial maps of tumor biological features. Method: High‐resolution prostate histology images, from a cohort of 63 patients, annotated with tumor location and grade, provided patient‐specific "maps" and a population‐based "atlas" of cell density and tumor probability. Dose prescriptions were derived for each patient based on a heterogeneous redistribution of the boost dose to the intraprostatic lesions, with the prescription maximizing patient tumor control probability (TCP). The impact on TCP was assessed under scenarios where the distribution of population‐based biological data was ignored, partially included, or fully included in prescription generation. Heterogeneous dose prescriptions were generated for three combinations of maps and atlas, and for conventional fractionation (CF), extreme hypo‐fractionation (EH), moderate hypo‐fractionation (MH), and whole Pelvic RT + SBRT Boost (WPRT + SBRT). The predicted efficacy of the heterogeneous prescriptions was compared with equivalent homogeneous dose prescriptions. Results: TCPs for heterogeneous dose prescriptions were generally higher than those for homogeneous dose prescriptions. TCP escalation by heterogeneous dose prescription was the largest for CF. When only using population‐based atlas data, the generated heterogeneous dose prescriptions of 55 to 58 patients (out of 63) had a higher TCP than for the corresponding homogeneous dose prescriptions. The TCPs of the heterogeneous dose prescriptions generated with the population‐based atlas and tumor probability maps did not differ significantly from those using patient‐specific biological information. The generated heterogeneous dose prescriptions achieved significantly higher TCP than homogeneous dose prescriptions in the posterior section of the prostate. Conclusion: Heterogeneous dose prescriptions generated via biologically‐optimized dose redistribution can produce higher TCP than the homogeneous dose prescriptions for the majority of the patients in the studied cohort. For scenarios where patient‐specific biological information was unavailable or partially available, the generated heterogeneous dose prescriptions can still achieve TCP improvement relative to homogeneous dose prescriptions. [ABSTRACT FROM AUTHOR]
Copyright of Medical Physics is the property of Wiley-Blackwell 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.)
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  Data: Towards optimal heterogeneous prostate radiotherapy dose prescriptions based on patient‐specific or population‐based biological features.
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  Data: <searchLink fieldCode="AR" term="%22Zhao%2C+Yutong%22">Zhao, Yutong</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> yutong.zhao960314@gmail.com</i><br /><searchLink fieldCode="AR" term="%22Haworth%2C+Annette%22">Haworth, Annette</searchLink><relatesTo>2</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Reynolds%2C+Hayley+M%2E%22">Reynolds, Hayley M.</searchLink><relatesTo>3</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Williams%2C+Scott+G%2E%22">Williams, Scott G.</searchLink><relatesTo>4,5</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Finnegan%2C+Robert%22">Finnegan, Robert</searchLink><relatesTo>2,6,7</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Rowshanfarzad%2C+Pejman%22">Rowshanfarzad, Pejman</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Ebert%2C+Martin+A%2E%22">Ebert, Martin A.</searchLink><relatesTo>1,8,9</relatesTo> (AUTHOR)
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  Data: <searchLink fieldCode="JN" term="%22Medical+Physics%22">Medical Physics</searchLink>. May2024, Vol. 51 Issue 5, p3766-3781. 16p.
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  Data: <searchLink fieldCode="DE" term="%22Medical+prescriptions%22">Medical prescriptions</searchLink><br /><searchLink fieldCode="DE" term="%22Prostate%22">Prostate</searchLink><br /><searchLink fieldCode="DE" term="%22Drug+dosage%22">Drug dosage</searchLink><br /><searchLink fieldCode="DE" term="%22Dose-response+relationship+%28Radiation%29%22">Dose-response relationship (Radiation)</searchLink><br /><searchLink fieldCode="DE" term="%22Radiotherapy%22">Radiotherapy</searchLink><br /><searchLink fieldCode="DE" term="%22Tumor+grading%22">Tumor grading</searchLink><br /><searchLink fieldCode="DE" term="%22Urodynamics%22">Urodynamics</searchLink>
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: Background: Escalation of prescribed dose in prostate cancer (PCa) radiotherapy enables improvement in tumor control at the expense of increased toxicity. Opportunities for reduction of treatment toxicity may emerge if more efficient dose escalation can be achieved by redistributing the prescribed dose distribution according to the known heterogeneous, spatially‐varying characteristics of the disease. Purpose: To examine the potential benefits, limitations and characteristics of heterogeneous boost dose redistribution in PCa radiotherapy based on patient‐specific and population‐based spatial maps of tumor biological features. Method: High‐resolution prostate histology images, from a cohort of 63 patients, annotated with tumor location and grade, provided patient‐specific "maps" and a population‐based "atlas" of cell density and tumor probability. Dose prescriptions were derived for each patient based on a heterogeneous redistribution of the boost dose to the intraprostatic lesions, with the prescription maximizing patient tumor control probability (TCP). The impact on TCP was assessed under scenarios where the distribution of population‐based biological data was ignored, partially included, or fully included in prescription generation. Heterogeneous dose prescriptions were generated for three combinations of maps and atlas, and for conventional fractionation (CF), extreme hypo‐fractionation (EH), moderate hypo‐fractionation (MH), and whole Pelvic RT + SBRT Boost (WPRT + SBRT). The predicted efficacy of the heterogeneous prescriptions was compared with equivalent homogeneous dose prescriptions. Results: TCPs for heterogeneous dose prescriptions were generally higher than those for homogeneous dose prescriptions. TCP escalation by heterogeneous dose prescription was the largest for CF. When only using population‐based atlas data, the generated heterogeneous dose prescriptions of 55 to 58 patients (out of 63) had a higher TCP than for the corresponding homogeneous dose prescriptions. The TCPs of the heterogeneous dose prescriptions generated with the population‐based atlas and tumor probability maps did not differ significantly from those using patient‐specific biological information. The generated heterogeneous dose prescriptions achieved significantly higher TCP than homogeneous dose prescriptions in the posterior section of the prostate. Conclusion: Heterogeneous dose prescriptions generated via biologically‐optimized dose redistribution can produce higher TCP than the homogeneous dose prescriptions for the majority of the patients in the studied cohort. For scenarios where patient‐specific biological information was unavailable or partially available, the generated heterogeneous dose prescriptions can still achieve TCP improvement relative to homogeneous dose prescriptions. [ABSTRACT FROM AUTHOR]
– Name: AbstractSuppliedCopyright
  Label:
  Group: Ab
  Data: <i>Copyright of Medical Physics is the property of Wiley-Blackwell 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.)
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        Value: 10.1002/mp.16936
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        Text: English
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    Subjects:
      – SubjectFull: Medical prescriptions
        Type: general
      – SubjectFull: Prostate
        Type: general
      – SubjectFull: Drug dosage
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      – SubjectFull: Dose-response relationship (Radiation)
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      – SubjectFull: Tumor grading
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      – SubjectFull: Urodynamics
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      – TitleFull: Towards optimal heterogeneous prostate radiotherapy dose prescriptions based on patient‐specific or population‐based biological features.
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              M: 05
              Text: May2024
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