| ORIGINAL ARTICLE |
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| Year : 2018 | Volume
: 43
| Issue : 1 | Page : 9-15 |
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A treatment planning method for better management of radiation-induced oral mucositis in locally advanced head and neck cancer
Hao Howard Zhang, Warren D D'Souza
Department of Radiation Oncology, University of Maryland School of Medicine, Baltimore, MD, USA
Correspondence Address:
Dr. Hao Howard Zhang
22 S Greene St., Baltimore, MD 21201
USA
 Source of Support: None, Conflict of Interest: None  | Check |
DOI: 10.4103/jmp.JMP_78_17
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Purpose/Aim: To describe a two-phase intensity-modulated radiation therapy (IMRT) treatment planning approach, that is, promising for reduction of oral mucositis risk in locally advanced head-and-neck cancer. Materials and Methods: Ten locally advanced head-and-neck cancer patients who underwent RT were retrospectively collected. Conventional IMRT and volumetric-modulated arc therapy (VMAT) plans were generated for these patients following clinical protocol. Following the first phase of generating conventional IMRT plans, our approach utilized data from Monte Carlo-based kernel superposition dose calculations corresponding to beam apertures (generated from the conventional IMRT plans) and used an exact mathematical programming-based optimization approach applying linear programming (LP) to dose optimization in the second phase. Results: Compared with conventional IMRT and VMAT treatment plans, our novel method achieved better preservation of oral cavity (16%–29% lower mean dose, P < 0.01), parotid glands (6%–17% lower mean dose, P < 0.04), and spinal cord (3-11 Gy lower maximum dose, P < 0.03) and lower doses to nonorgan-at-risk/nontarget normal tissues, with the same or better target coverage. Conclusions: Our LP-based method can be practically implemented in routine clinical use with a goal of limiting radiation-induced oral mucositis for head-and-neck cancer patients. |
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