To the top

Page Manager: Webmaster
Last update: 9/11/2012 3:13 PM

Tell a friend about this page
Print version

Image-based Data Mining t… - University of Gothenburg, Sweden Till startsida
Sitemap
To content Read more about how we use cookies on gu.se

Image-based Data Mining to Probe Dosimetric Correlates of Radiation-induced Trismus

Journal article
Authors W. Beasley
M. Thor
A. McWilliam
A. Green
R. Mackay
N. Slevin
Caroline Olsson
Niclas Pettersson
Caterina Finizia
C. Estilo
N. Riaz
N. Y. Lee
J. O. Deasy
M. van Herk
Published in International Journal of Radiation Oncology Biology Physics
Volume 102
Issue 4
Pages 1330-1338
ISSN 0360-3016
Publication year 2018
Published at Institute of Clinical Sciences, Department of Radiation Physics
Institute of Clinical Sciences, Department of Otorhinolaryngology
Pages 1330-1338
Language en
Links dx.doi.org/10.1016/j.ijrobp.2018.05...
Keywords dose-surface maps, prostate-cancer radiotherapy, neck-cancer, head, toxicity, therapy, trial, imrt, risk
Subject categories Cancer and Oncology, Radiology

Abstract

Purpose: To identify imaged regions in which dose is associated with radiation-induced trismus after head and neck cancer radiation therapy (HNRT) using a novel image-based data mining (IBDM) framework. Methods and Materials: A cohort of 86 HNRT patients were analyzed for region identification. Trismus was characterized as a continuous variable by the maximum incisor-to-incisor opening distance (MID) at 6 months after radiation therapy. Patient anatomies and dose distributions were spatially normalized to a common frame of reference using deformable image registration. IBDM was used to identify clusters of voxels associated with MID (P <= .05 based on permutation testing). The result was externally tested on a cohort of 35 patients with head and neck cancer. Internally, we also performed a dose-volume histogram-based analysis by comparing the magnitude of the correlation between MID and the mean dose for the IBDM-identified cluster in comparison with 5 delineated masticatory structures. Results: A single cluster was identified with the IBDM approach (P < .01), partially overlapping with the ipsilateral masseter. The dose-volume histogram-based analysis confirmed that the IBDM cluster had the strongest association with MID, followed by the ipsilateral masseter and the ipsilateral medial pterygoid (Spearman's rank correlation coefficients: R-s = -0.36, -0.35, -0.32; P = .001, .001, .002, respectively). External validation confirmed an association between mean dose to the IBDM cluster and MID (R-s = -0.45; P = .007). Conclusions: IBDM bypasses the common assumption that dose patterns within structures are unimportant. Our novel IBDM approach for continuous outcome variables successfully identified a cluster of voxels that are highly associated with trismus, overlapping partially with the ipsilateral masseter. Tests on an external validation cohort showed an even stronger correlation with trismus. These results support use of the region in HNRT treatment planning to potentially reduce trismus. (C) 2018 Elsevier Inc. All rights reserved.

Page Manager: Webmaster|Last update: 9/11/2012
Share:

The University of Gothenburg uses cookies to provide you with the best possible user experience. By continuing on this website, you approve of our use of cookies.  What are cookies?