Prioritized Optimization of Total Toxicity Burden for Head and Neck Cancer Patients.

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Title: Prioritized Optimization of Total Toxicity Burden for Head and Neck Cancer Patients.
Authors: Polan, D.1 (AUTHOR), Mierzwa, M.L.1 (AUTHOR), Epelman, M.2 (AUTHOR), Sun, Y.1,3 (AUTHOR), Schonewolf, C.1 (AUTHOR), Shah, J.L.1 (AUTHOR), Schipper, M.1,3 (AUTHOR), Matuszak, M.M.1 (AUTHOR)
Source: International Journal of Radiation Oncology, Biology, Physics. 2021 Supplement, Vol. 111 Issue 3, pS53-S54. 2p.
Subjects: Head & neck cancer, Cancer patients, Parotid glands, Deglutition disorders
Abstract: Purpose/objective(s): Head and neck cancer (HNC) RT typically results in high doses to organs-at-risk (OARs), contributing to decreased quality-of-life (QOL) seen in patient reported outcomes (PRO). Current RT planning methods are driven by singular dosimetric trade-offs that may be inconsistent with improving a patient's overall predicted total toxicity burden (TTB). We developed an aggregate toxicity assessment over time including PROs that represents a paradigm shift over informal summary of individual toxicity. Here we introduce a treatment planning approach to directly optimize and reduce the predicted TTB-PRO of a patient's RT plan.Materials/methods: We implemented a prioritized approach to TTB optimization using an in-house optimization plugin linked to a commercial treatment planning system. Prioritized TTB (P-TTB) plans were optimized using a two-stage hierarchal method for inverse IMRT planning. In the first stage, TTB, defined as the weighted-sum of NTCPs, is minimized subject to high-priority OAR dose limits, target prescription, and target coverage requirements. Weights for the toxicities directly represent the relative undesirability of toxicities. In the second stage, a weighted-sum dose-metric objective is minimized, similar to current clinical practice. This stage is subject to the same constraints as the first stage, but an additional constraint for TTB is incorporated based on the optimal solution of the first stage. Using this approach, we retrospectively generated plans for 5 HNC patients and compared the resulting plans to IMRT plans generated without the added TTB constraint. Both plans consisted of 9 equally spaced beams with the same OAR dose limits and dose-metric objective. Target dose requirements were based on simultaneous integrated boost prescriptions of 70 and 56 Gy delivered in 35 fractions. TTB was calculated using previously published NTCP models for dysphagia and xerostomia. Dysphagia was based on increase in aspiration or HNQOL score > 81 as a function of pharyngeal constrictor (PC) mean dose. Xerostomia was based on parotid flow ratio < 25% of pretreatment (grade 4) or xerostomia questionnaire > 73 as a function of parotid gland (PG) mean dose.Results: Our optimization engine successfully generated P-TTB plans for all five patients while maintaining similar target coverage to the standard dosimetrically optimized plans. P-TTB plans resulted in average absolute NTCP reductions of 15.5% (range: 0.2 - 53.4) for dysphagia and 20.5% (1.9 - 68.5) for xerostomia. These changes correlate to average mean dose decreases of 6.9 Gy (0.2 - 22.7) for PC and 10.2 Gy (1.2 - 33.5) for PGs. P-TTB planning resulted in greater fluence modulation and higher doses to OARs not included in the calculation of TTB.Conclusion: The P-TTB planning method offers an intuitive optimization approach to balancing trade-offs between various treatment outcomes and has the ability to directly reduce and redistribute predicted toxicity which may aid in improving QOL for HNC patients receiving RT. [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.)
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  Data: Prioritized Optimization of Total Toxicity Burden for Head and Neck Cancer Patients.
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  Data: &lt;searchLink fieldCode=&quot;AR&quot; term=&quot;%22Polan%2C+D%2E%22&quot;&gt;Polan, D.&lt;/searchLink&gt;&lt;relatesTo&gt;1&lt;/relatesTo&gt; (AUTHOR)&lt;br /&gt;&lt;searchLink fieldCode=&quot;AR&quot; term=&quot;%22Mierzwa%2C+M%2EL%2E%22&quot;&gt;Mierzwa, M.L.&lt;/searchLink&gt;&lt;relatesTo&gt;1&lt;/relatesTo&gt; (AUTHOR)&lt;br /&gt;&lt;searchLink fieldCode=&quot;AR&quot; term=&quot;%22Epelman%2C+M%2E%22&quot;&gt;Epelman, M.&lt;/searchLink&gt;&lt;relatesTo&gt;2&lt;/relatesTo&gt; (AUTHOR)&lt;br /&gt;&lt;searchLink fieldCode=&quot;AR&quot; term=&quot;%22Sun%2C+Y%2E%22&quot;&gt;Sun, Y.&lt;/searchLink&gt;&lt;relatesTo&gt;1,3&lt;/relatesTo&gt; (AUTHOR)&lt;br /&gt;&lt;searchLink fieldCode=&quot;AR&quot; term=&quot;%22Schonewolf%2C+C%2E%22&quot;&gt;Schonewolf, C.&lt;/searchLink&gt;&lt;relatesTo&gt;1&lt;/relatesTo&gt; (AUTHOR)&lt;br /&gt;&lt;searchLink fieldCode=&quot;AR&quot; term=&quot;%22Shah%2C+J%2EL%2E%22&quot;&gt;Shah, J.L.&lt;/searchLink&gt;&lt;relatesTo&gt;1&lt;/relatesTo&gt; (AUTHOR)&lt;br /&gt;&lt;searchLink fieldCode=&quot;AR&quot; term=&quot;%22Schipper%2C+M%2E%22&quot;&gt;Schipper, M.&lt;/searchLink&gt;&lt;relatesTo&gt;1,3&lt;/relatesTo&gt; (AUTHOR)&lt;br /&gt;&lt;searchLink fieldCode=&quot;AR&quot; term=&quot;%22Matuszak%2C+M%2EM%2E%22&quot;&gt;Matuszak, M.M.&lt;/searchLink&gt;&lt;relatesTo&gt;1&lt;/relatesTo&gt; (AUTHOR)
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  Data: &lt;searchLink fieldCode=&quot;JN&quot; term=&quot;%22International+Journal+of+Radiation+Oncology%2C+Biology%2C+Physics%22&quot;&gt;International Journal of Radiation Oncology, Biology, Physics&lt;/searchLink&gt;. 2021 Supplement, Vol. 111 Issue 3, pS53-S54. 2p.
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  Data: &lt;searchLink fieldCode=&quot;DE&quot; term=&quot;%22Head+%26+neck+cancer%22&quot;&gt;Head &amp; neck cancer&lt;/searchLink&gt;&lt;br /&gt;&lt;searchLink fieldCode=&quot;DE&quot; term=&quot;%22Cancer+patients%22&quot;&gt;Cancer patients&lt;/searchLink&gt;&lt;br /&gt;&lt;searchLink fieldCode=&quot;DE&quot; term=&quot;%22Parotid+glands%22&quot;&gt;Parotid glands&lt;/searchLink&gt;&lt;br /&gt;&lt;searchLink fieldCode=&quot;DE&quot; term=&quot;%22Deglutition+disorders%22&quot;&gt;Deglutition disorders&lt;/searchLink&gt;
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: &lt;bold&gt;Purpose/objective(s): &lt;/bold&gt;Head and neck cancer (HNC) RT typically results in high doses to organs-at-risk (OARs), contributing to decreased quality-of-life (QOL) seen in patient reported outcomes (PRO). Current RT planning methods are driven by singular dosimetric trade-offs that may be inconsistent with improving a patient&#39;s overall predicted total toxicity burden (TTB). We developed an aggregate toxicity assessment over time including PROs that represents a paradigm shift over informal summary of individual toxicity. Here we introduce a treatment planning approach to directly optimize and reduce the predicted TTB-PRO of a patient&#39;s RT plan.&lt;bold&gt;Materials/methods: &lt;/bold&gt;We implemented a prioritized approach to TTB optimization using an in-house optimization plugin linked to a commercial treatment planning system. Prioritized TTB (P-TTB) plans were optimized using a two-stage hierarchal method for inverse IMRT planning. In the first stage, TTB, defined as the weighted-sum of NTCPs, is minimized subject to high-priority OAR dose limits, target prescription, and target coverage requirements. Weights for the toxicities directly represent the relative undesirability of toxicities. In the second stage, a weighted-sum dose-metric objective is minimized, similar to current clinical practice. This stage is subject to the same constraints as the first stage, but an additional constraint for TTB is incorporated based on the optimal solution of the first stage. Using this approach, we retrospectively generated plans for 5 HNC patients and compared the resulting plans to IMRT plans generated without the added TTB constraint. Both plans consisted of 9 equally spaced beams with the same OAR dose limits and dose-metric objective. Target dose requirements were based on simultaneous integrated boost prescriptions of 70 and 56 Gy delivered in 35 fractions. TTB was calculated using previously published NTCP models for dysphagia and xerostomia. Dysphagia was based on increase in aspiration or HNQOL score &gt; 81 as a function of pharyngeal constrictor (PC) mean dose. Xerostomia was based on parotid flow ratio &lt; 25% of pretreatment (grade 4) or xerostomia questionnaire &gt; 73 as a function of parotid gland (PG) mean dose.&lt;bold&gt;Results: &lt;/bold&gt;Our optimization engine successfully generated P-TTB plans for all five patients while maintaining similar target coverage to the standard dosimetrically optimized plans. P-TTB plans resulted in average absolute NTCP reductions of 15.5% (range: 0.2 - 53.4) for dysphagia and 20.5% (1.9 - 68.5) for xerostomia. These changes correlate to average mean dose decreases of 6.9 Gy (0.2 - 22.7) for PC and 10.2 Gy (1.2 - 33.5) for PGs. P-TTB planning resulted in greater fluence modulation and higher doses to OARs not included in the calculation of TTB.&lt;bold&gt;Conclusion: &lt;/bold&gt;The P-TTB planning method offers an intuitive optimization approach to balancing trade-offs between various treatment outcomes and has the ability to directly reduce and redistribute predicted toxicity which may aid in improving QOL for HNC patients receiving RT. [ABSTRACT FROM AUTHOR]
– Name: AbstractSuppliedCopyright
  Label:
  Group: Ab
  Data: &lt;i&gt;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&#39;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.&lt;/i&gt; (Copyright applies to all Abstracts.)
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      – Type: doi
        Value: 10.1016/j.ijrobp.2021.07.139
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        Text: English
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        StartPage: S53
    Subjects:
      – SubjectFull: Head & neck cancer
        Type: general
      – SubjectFull: Cancer patients
        Type: general
      – SubjectFull: Parotid glands
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      – SubjectFull: Deglutition disorders
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      – TitleFull: Prioritized Optimization of Total Toxicity Burden for Head and Neck Cancer Patients.
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