DCE-MRI for Pre-Treatment Prediction and Post-Treatment Assessment of Treatment Response in Sites of Squamous Cell Carcinoma in the Head and Neck
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AbstractBackground and Purpose
It is important to identify patients with head and neck squamous cell carcinoma (SCC) who fail to respond to chemoradiotherapy so that they can undergo post-treatment salvage surgery while the disease is still operable. This study aimed to determine the diagnostic performance of dynamic contrast enhanced (DCE)-MRI using a pharmacokinetic model for pre-treatment predictive imaging, as well as post-treatment diagnosis, of residual SCC at primary and nodal sites in the head and neck.
Material and Methods
Forty-nine patients with 83 SCC sites (primary and/or nodal) underwent pre-treatment DCE-MRI, and 43 patients underwent post-treatment DCE-MRI, of which 33 SCC sites had a residual mass amenable to analysis. Pre-treatment, post-treatment and % change in the mean Ktrans, kep, ve and AUGC were obtained from SCC sites. Logistic regression was used to correlate DCE parameters at each SCC site with treatment response at the same site, based on clinical outcome at that site at a minimum of two years.
Results
None of the pre-treatment DCE-MRI parameters showed significant correlations with SCC site failure (SF) (29/83 sites) or site control (SC) (54/83 sites). Post-treatment residual masses with SF (14/33) had significantly higher kep (p = 0.05), higher AUGC (p = 0.02), and lower % reduction in AUGC (p = 0.02), than residual masses with SC (19/33), with the % change in AUGC remaining significant on multivariate analysis.
Conclusion
Pre-treatment DCE-MRI did not predict which SCC sites would fail treatment, but post-treatment DCE-MRI showed potential for identifying residual masses that had failed treatment.
All Author(s) ListAnn D. King, Steven Kwok Keung Chow, Kwok-Hung Yu, Frankie Kwok Fai Mo, David K. W. Yeung, Jing Yuan, Benjamin King Hong Law, Kunwar S. Bhatia, Alexander C. Vlantis, Anil T. Ahuja
Journal namePLoS ONE
Year2015
Month12
Day10
Volume Number10
Issue Number12
PublisherPUBLIC LIBRARY SCIENCE
Pagese0144770
ISSN1932-6203
LanguagesEnglish-United Kingdom
Web of Science Subject CategoriesMultidisciplinary Sciences; Science & Technology - Other Topics

Last updated on 2020-08-08 at 00:44