Spatial Radiation Dose Influence on Xerostomia Recovery and Its Comparison to Acute Incidence in Patients With Head and Neck Cancer.


Journal

Advances in radiation oncology
ISSN: 2452-1094
Titre abrégé: Adv Radiat Oncol
Pays: United States
ID NLM: 101677247

Informations de publication

Date de publication:
Historique:
received: 11 02 2019
revised: 10 08 2019
accepted: 26 08 2019
entrez: 14 4 2020
pubmed: 14 4 2020
medline: 14 4 2020
Statut: epublish

Résumé

Radiation-induced xerostomia is one of the most prevalent symptoms during and after head and neck cancer radiation therapy (RT). We aimed to discover the spatial radiation dose-based (voxel dose) importance pattern in the major salivary glands in relation to the recovery of xerostomia 18 months after RT, and to compare the recovery voxel dose importance pattern to the acute incidence (injury) pattern. This study included all patients within our database with xerostomia outcomes after completion of curative intensity modulated RT. Common Terminology Criteria for Adverse Events xerostomia grade was used to define recovered versus nonrecovered group at baseline, between end of treatment and 18 months post-RT, and beyond 18 months, respectively. Ridge logistic regression was performed to predict the probability of xerostomia recovery. Voxel doses within geometrically defined parotid glands (PG) and submandibular glands (SMG), demographic characteristics, and clinical factors were included in the algorithm. We plotted the normalized learned weights on the 3-dimensional PG and SMG structures to visualize the voxel dose importance for predicting xerostomia recovery. A total of 146 head and neck cancer patients from 2008 to 2016 were identified. The superior region of the ipsilateral and contralateral PG was the most influencial for xerostomia recovery. The area under the receiver operating characteristic curve evaluated using 10-fold cross-validation for ridge logistic regression was 0.68 ± 0.07. Compared with injury, the recovery voxel dose importance pattern was more symmetrical and was influenced by lower dose voxels. The superior portion of the 2 PGs (low dose region) are the most influential on xerostomia recovery and seem to be equal in their contribution. The dissimilarity of the influence pattern between injury and recovery suggests different underlying mechanisms. The importance pattern identified by spatial radiation dose and machine learning methods can improve our understanding of normal tissue toxicities in RT. Further external validation is warranted.

Identifiants

pubmed: 32280822
doi: 10.1016/j.adro.2019.08.009
pii: S2452-1094(19)30122-8
pmc: PMC7136646
doi:

Types de publication

Journal Article

Langues

eng

Pagination

221-230

Informations de copyright

© 2019 The Author(s).

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Auteurs

Yue Guo (Y)

Department of Radiation Oncology and Molecular Radiation Sciences, Johns Hopkins University, Baltimore, Maryland.

Wei Jiang (W)

Department of Civil Engineering, Johns Hopkins System Institute, Johns Hopkins University, Baltimore, Maryland.

Pranav Lakshminarayanan (P)

Department of Radiation Oncology and Molecular Radiation Sciences, Johns Hopkins University, Baltimore, Maryland.

Peijin Han (P)

Department of Radiation Oncology and Molecular Radiation Sciences, Johns Hopkins University, Baltimore, Maryland.

Zhi Cheng (Z)

Department of Radiation Oncology and Molecular Radiation Sciences, Johns Hopkins University, Baltimore, Maryland.

Michael Bowers (M)

Department of Radiation Oncology and Molecular Radiation Sciences, Johns Hopkins University, Baltimore, Maryland.

Xuan Hui (X)

Department of Public Health Sciences, University of Chicago, Chicago, Illinois; and.

Ilya Shpitser (I)

Department of Computer Science, Johns Hopkins University, Baltimore, Maryland.

Sauleh Siddiqui (S)

Department of Civil Engineering, Johns Hopkins System Institute, Johns Hopkins University, Baltimore, Maryland.

Russell H Taylor (RH)

Department of Computer Science, Johns Hopkins University, Baltimore, Maryland.

Harry Quon (H)

Department of Radiation Oncology and Molecular Radiation Sciences, Johns Hopkins University, Baltimore, Maryland.

Todd McNutt (T)

Department of Radiation Oncology and Molecular Radiation Sciences, Johns Hopkins University, Baltimore, Maryland.

Classifications MeSH