Abstract

Xerostomia is a common consequence of radiotherapy in head and neck cancer. The objective was to compare the regional radiation dose distribution in patients that developed xerostomia within 6 months of radiotherapy and those recovered from xerostomia within 18 months post-radiotherapy. We developed a feature generation pipeline to extract dose volume histogram features from geometrically defined ipsilateral/contralateral parotid glands, submandibular glands, and oral cavity surrogates for each patient. Permutation tests with multiple comparisons were performed to assess the dose difference between injury vs. non-injury and recovery vs. non-recovery. Ridge logistic regression models were applied to predict injury and recovery using clinical features along with dose features (D10-D90) of the subvolumes extracted from oral cavity and salivary gland contours + 3 mm peripheral shell. Model performances were assessed by the area under the receiver operating characteristic curve (AUC) using nested cross-validation. We found that different regional dose/volume metrics patterns exist for injury vs. recovery. Compared to injury, recovery has increased importance to the subvolumes receiving lower dose. Within the subvolumes, injury tends to have increased importance towards D10 from D90. This suggests that different threshold for xerostomia injury and recovery. Injury is induced by the subvolumes receiving higher dose, and the ability to recover can be preserved by further reducing the dose to subvolumes receiving lower dose.

Details

Title
Dose/Volume histogram patterns in Salivary Gland subvolumes influence xerostomia injury and recovery
Author
Han Peijin 1 ; Lakshminarayanan Pranav 1   VIAFID ORCID Logo  ; Jiang, Wei 2 ; Shpitser Ilya 3 ; Hui, Xuan 4   VIAFID ORCID Logo  ; Lee Sang Ho 1   VIAFID ORCID Logo  ; Cheng, Zhi 1 ; Guo, Yue 5 ; Taylor, Russell H 3 ; Siddiqui, Sauleh A 2 ; Bowers, Michael 1 ; Sheikh Khadija 1 ; Kiess, Ana 1 ; Page, Brandi R 1 ; Lee, Junghoon 1 ; Quon, Harry 1 ; McNutt, Todd R 1 

 Johns Hopkins University, Department of Radiation Oncology and Molecular Radiation Sciences, Baltimore, USA (GRID:grid.21107.35) (ISNI:0000 0001 2171 9311) 
 Johns Hopkins University, Department of Civil Engineering, Baltimore, USA (GRID:grid.21107.35) (ISNI:0000 0001 2171 9311) 
 Johns Hopkins University, Department of Computer Science, Baltimore, USA (GRID:grid.21107.35) (ISNI:0000 0001 2171 9311) 
 University of Chicago, Department of Public Health Sciences, Chicago, USA (GRID:grid.170205.1) (ISNI:0000 0004 1936 7822) 
 Johns Hopkins Bloomberg School of Public Health, Department of Epidemiology, Baltimore, USA (GRID:grid.21107.35) (ISNI:0000 0001 2171 9311) 
Publication year
2019
Publication date
Dec 2019
Publisher
Nature Publishing Group
e-ISSN
20452322
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
2188211076
Copyright
This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.