Applicability of Narrow Band Image to Diagnose Laryngopharyngeal Reflux Disease
Objective: 1) To develop the applicability of nasopharyngeal epithelial cell with Narrow Band Image (NBI) to diagnose laryngopharyngeal reflux disease (LPRD). 2) Estimate a correlation between a new questionnaire (Frequency Scale for the Symptom of the GERD; FSSG) and LPRD. Method: We have 88 patien...
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Veröffentlicht in: | Otolaryngology-head and neck surgery 2012-08, Vol.147 (2_suppl), p.P132-P132 |
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Sprache: | eng |
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Zusammenfassung: | Objective: 1) To develop the applicability of nasopharyngeal epithelial cell with Narrow Band Image (NBI) to diagnose laryngopharyngeal reflux disease (LPRD). 2) Estimate a correlation between a new questionnaire (Frequency Scale for the Symptom of the GERD; FSSG) and LPRD.
Method: We have 88 patients who underwent NBI using FSSG. Because of the pattern of nasopharyngeal epithelial cell NBI image, we distinguished grade 1: nothing, grade 2: moderate, and grade 3: severe. All patients answered the FSSG questionnaire and were administered a PPI (rabeprazole10 mg). Student t test was used to compare each category out of 12 questions of FSSG for LPRD patients.
Results: Average age of patients was 59.3 years old. Sixty-nine (78%) patients were detected with grade 2 (46 pts) and grade 3 (23 pts). Nasopharyngeal epithelial cell with NBI showed a specific feature, which nasopharyngeal epithelial round cells were modulated capillary cells raised among LPRD patients. We presumptively call the pattern mackerel cloud pattern. Patients who indicated grade 3 showed higher score in FSSG. “Do you have an unusual (eg, burning) sensation in your throat?” category of 12 questions of FSSG showed a significant difference.
Conclusion: We could show that nasopharyngeal epithelial cell pattern with NBI would be a useful and specific feature to diagnose the LPRD. FSSG is not only used for GERD; it also may be used for LPRD clinically.We are currently confirming nasopharyngeal epithelial cell images using digital image analyzer (Wavelet analyzer). |
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ISSN: | 0194-5998 1097-6817 |
DOI: | 10.1177/0194599812451426a23 |