Literature DB >> 32030481

Correlation of intensity-modulated radiation therapy at a specific radiation dose with the prognosis of nasal mucous damage after radiotherapy.

Gendi Yin1, Bo Tu2, Ling Ye3.   

Abstract

Objective of the present study was to investigate the tolerant radiation dose of nasal mucosa by observing and analyzing patients who received intensity-modulated radiation therapy (IMRT). Patients with nasopharyngeal carcinoma (N = 66) were selected for this study. The modified saccharin assay, endoscopy test, magnetic resonance imaging, and sino-nasal outcome test-20 (SNOT-20) survey were performed for the patients before and at 0 (T0), 3 (T1), 6 (T2), and 12 (T3) months after radiotherapy. The threshold doses of IMRT before radiotherapy and at T0, T1, T2, and T3 were determined as, respectively, 37 Gy, 37 Gy, 39 Gy, and 37 Gy for the saccharin test; 38 Gy, 37 Gy, 40 Gy, and 38 Gy for the endoscopy test; and 39 Gy, 37 Gy, 39 Gy, and 39 Gy for the nasal-related symptom scoring test. The modified saccharin assay, endoscopy test, and SNOT-20 survey revealed that a low dose (< threshold dose) of IMRT was associated with higher mucocilia transport rate (MRT), better endoscopy test score, and improved SNOT-20 score. The patients who received IMRT at a dose less than the threshold had the least damaged nasal mucosa morphology, and functional impairment scores were highest at T1 of IMRT. We conclude that nasal mucosa showed the most serious damage within 3 months after IMRT. If the radiation dose can be controlled within the threshold, the nasal mucosa can recover in the following few months, but recovery will be difficult otherwise.

Entities:  

Keywords:  Intensity-modulated radiation therapy; Nasal mucosa; Radiation dose; Radiation therapy

Year:  2020        PMID: 32030481     DOI: 10.1007/s00411-020-00830-5

Source DB:  PubMed          Journal:  Radiat Environ Biophys        ISSN: 0301-634X            Impact factor:   1.925


  38 in total

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  2 in total

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2.  Magnetic Resonance Imaging Features on Deep Learning Algorithm for the Diagnosis of Nasopharyngeal Carcinoma.

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  2 in total

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