Amplification of Higher-Order Salivary Gland Volume Effects from External Beam Radiotherapy in Normal Tissue Complication Probability Modeling of Radiopharmaceutical Therapy

Salivary glands are common organs at risk in both head and neck external beam radiotherapy (EBRT) and radiopharmaceutical therapy (RPT), but incidences of xerostomia in RPT are inconsistent with the EBRT Quantitative Analysis of Normal Tissue Effects in the Clinic (QUANTEC) limits. In EBRT, salivary...

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Main Authors: Chunming Gu, Robert F. Hobbs, Ana P. Kiess, Junghoon Lee, Todd McNutt, Harry Quon, Zhuoyao Xin, Tahir I. Yusufaly
Format: Article
Language:English
Published: MDPI AG 2025-02-01
Series:Radiation
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Online Access:https://www.mdpi.com/2673-592X/5/1/8
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author Chunming Gu
Robert F. Hobbs
Ana P. Kiess
Junghoon Lee
Todd McNutt
Harry Quon
Zhuoyao Xin
Tahir I. Yusufaly
author_facet Chunming Gu
Robert F. Hobbs
Ana P. Kiess
Junghoon Lee
Todd McNutt
Harry Quon
Zhuoyao Xin
Tahir I. Yusufaly
author_sort Chunming Gu
collection DOAJ
description Salivary glands are common organs at risk in both head and neck external beam radiotherapy (EBRT) and radiopharmaceutical therapy (RPT), but incidences of xerostomia in RPT are inconsistent with the EBRT Quantitative Analysis of Normal Tissue Effects in the Clinic (QUANTEC) limits. In EBRT, salivary glands are usually assumed to be parallel organs, with QUANTEC guidelines based on <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><msub><mi>D</mi><mrow><mi>m</mi><mi>e</mi><mi>a</mi><mi>n</mi></mrow></msub></semantics></math></inline-formula>, but this is known to be a gross over-simplification of the full complexity of the underlying functional organization. The goal of this work is to combine machine learning of EBRT dose–outcome data with stylized small-scale RPT dosimetry to discover more reliable normal tissue complication probability (NTCP) models of xerostomia across both modalities. A retrospective cohort of 211 EBRT patients was analyzed using a custom-designed in-house machine learning workflow. From this, a hierarchy of three models of increasing complexity was trained, evaluated for performance and generalization, and coupled with stylized small-scale salivary gland dosimetry to assess the influence of model complexity on the predicted NTCP for plausible patterns of RPT dose nonuniformity. The three models in the hierarchy (A, B, C), in increasing order of complexity, associate xerostomia with the following: the mean dose to the whole contralateral parotid (model A), the mean dose to a ductally localized region (model B) and a serial interaction dose term between two ductal sub-compartments (model C). While the difference between the three models for EBRT <i>p</i>-values and AUCs is rather marginal, for physiologically driven ductal dose distributions in RPT, the predicted reduction in TD50 can be as large as a factor of 10. These results provide hints towards a plausible reconciliation of the observed inconsistency of xerostomia in RPT with EBRT dose limits.
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spelling doaj-art-e883656c499d45d3bf3e23ef925cb20e2025-08-20T03:44:04ZengMDPI AGRadiation2673-592X2025-02-0151810.3390/radiation5010008Amplification of Higher-Order Salivary Gland Volume Effects from External Beam Radiotherapy in Normal Tissue Complication Probability Modeling of Radiopharmaceutical TherapyChunming Gu0Robert F. Hobbs1Ana P. Kiess2Junghoon Lee3Todd McNutt4Harry Quon5Zhuoyao Xin6Tahir I. Yusufaly7Department of Radiology and Radiological Sciences, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USADepartment of Radiation Oncology and Molecular Radiation Sciences, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USADepartment of Radiation Oncology and Molecular Radiation Sciences, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USADepartment of Radiation Oncology and Molecular Radiation Sciences, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USADepartment of Radiation Oncology and Molecular Radiation Sciences, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USADepartment of Radiation Oncology and Molecular Radiation Sciences, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USADepartment of Radiology and Radiological Sciences, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USADepartment of Radiology and Radiological Sciences, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USASalivary glands are common organs at risk in both head and neck external beam radiotherapy (EBRT) and radiopharmaceutical therapy (RPT), but incidences of xerostomia in RPT are inconsistent with the EBRT Quantitative Analysis of Normal Tissue Effects in the Clinic (QUANTEC) limits. In EBRT, salivary glands are usually assumed to be parallel organs, with QUANTEC guidelines based on <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><msub><mi>D</mi><mrow><mi>m</mi><mi>e</mi><mi>a</mi><mi>n</mi></mrow></msub></semantics></math></inline-formula>, but this is known to be a gross over-simplification of the full complexity of the underlying functional organization. The goal of this work is to combine machine learning of EBRT dose–outcome data with stylized small-scale RPT dosimetry to discover more reliable normal tissue complication probability (NTCP) models of xerostomia across both modalities. A retrospective cohort of 211 EBRT patients was analyzed using a custom-designed in-house machine learning workflow. From this, a hierarchy of three models of increasing complexity was trained, evaluated for performance and generalization, and coupled with stylized small-scale salivary gland dosimetry to assess the influence of model complexity on the predicted NTCP for plausible patterns of RPT dose nonuniformity. The three models in the hierarchy (A, B, C), in increasing order of complexity, associate xerostomia with the following: the mean dose to the whole contralateral parotid (model A), the mean dose to a ductally localized region (model B) and a serial interaction dose term between two ductal sub-compartments (model C). While the difference between the three models for EBRT <i>p</i>-values and AUCs is rather marginal, for physiologically driven ductal dose distributions in RPT, the predicted reduction in TD50 can be as large as a factor of 10. These results provide hints towards a plausible reconciliation of the observed inconsistency of xerostomia in RPT with EBRT dose limits.https://www.mdpi.com/2673-592X/5/1/8normal tissue complication probability modelingradiopharmaceutical therapyexternal beam radiotherapy
spellingShingle Chunming Gu
Robert F. Hobbs
Ana P. Kiess
Junghoon Lee
Todd McNutt
Harry Quon
Zhuoyao Xin
Tahir I. Yusufaly
Amplification of Higher-Order Salivary Gland Volume Effects from External Beam Radiotherapy in Normal Tissue Complication Probability Modeling of Radiopharmaceutical Therapy
Radiation
normal tissue complication probability modeling
radiopharmaceutical therapy
external beam radiotherapy
title Amplification of Higher-Order Salivary Gland Volume Effects from External Beam Radiotherapy in Normal Tissue Complication Probability Modeling of Radiopharmaceutical Therapy
title_full Amplification of Higher-Order Salivary Gland Volume Effects from External Beam Radiotherapy in Normal Tissue Complication Probability Modeling of Radiopharmaceutical Therapy
title_fullStr Amplification of Higher-Order Salivary Gland Volume Effects from External Beam Radiotherapy in Normal Tissue Complication Probability Modeling of Radiopharmaceutical Therapy
title_full_unstemmed Amplification of Higher-Order Salivary Gland Volume Effects from External Beam Radiotherapy in Normal Tissue Complication Probability Modeling of Radiopharmaceutical Therapy
title_short Amplification of Higher-Order Salivary Gland Volume Effects from External Beam Radiotherapy in Normal Tissue Complication Probability Modeling of Radiopharmaceutical Therapy
title_sort amplification of higher order salivary gland volume effects from external beam radiotherapy in normal tissue complication probability modeling of radiopharmaceutical therapy
topic normal tissue complication probability modeling
radiopharmaceutical therapy
external beam radiotherapy
url https://www.mdpi.com/2673-592X/5/1/8
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