Detection of Chronic Laryngitis Due

8/11/2019 Detection of Chronic Laryngitis Due

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Detection of Chronic Laryngitisdueto Laryngopharyngeal Reflux

Using Colorand Texture Analysis of

Laryngoscopic Images


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- Approximately 15% of all patients presenting to theotolaryngology office have chronic laryngopharyngeal reflux.

- LPR is the regurgitation of gastric contents onto the mucosal

linings of the pharynx, larynx, and upper aerodigestive tract.

- The presence of acid and pepsin in this sensitive region causes avariety of physiological responses, such as laryngeal edema anderythema, mucosal hypertrophy,4 granuloma, carcinoma, andsubglottic stenosis.

-There is an array of nonspecific signs and symptoms that point toLPR as an underlying etiology,making diagnosis controversial.

BACKGROUND


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BACKGROUND

LPR24 HOURS PHAMBULATORY

COMPUTER

RFS

ANAMNESIS PHYSICAL SIGN


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MATERIAL - METHODS

Laryngoscopic images from 20 subjects with LPR and 42 control subjectswithout LPR were obtained.

status was determined using the reflux finding score. Color and texturefeatures were quantified using hue calculation

and two-dimensional Gabor filtering.

Five regions were analyzed: true vocal folds, false vocal folds, epiglottis,interarytenoid space, and arytenoid mucosae.

This study was conducted under the approval of the ethics committeeof the Shanghai EENT Hospital


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MATERIAL - METHODS

The hue index and textural features formed the input for classification usingthe ANN. A multilayer perceptron (MLP) ANN was used to

provide nonlinear, discriminant analysis of the image features

The MLP consisted of an input layer for data entry, a layer ofhidden nodes (nodes 5, 10, 15, or 20), and an output layer

which provided the classification outcome (ie, non-LPR orLPR)

Receiver operating characteristic (ROC)analysis was used to evaluate diagnostic utility, and intraclass correlation

coefficient analysis was performed to determineinterrater reliability.


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RESULTS


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RESULTS


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RESULTS


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RESULTS


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DISCUSSION

We hypothesized that an ANN-based pattern recognition of hue and texturefeatures would be able to distinguish between non-LPR and LPR laryngoscopy

images .

To assess for LPR, our method first quantified prominent physical signs of thelaryngeal mucosa.

Pertinent limitations of this study include


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CONCLUSION

This preliminary study suggests that a combination of laryngealhue and texture features could potentially be used to identify

LPR.

More investigation would be valuable to further assessthe classification accuracy

Additional research should also focus on the LPR classificationaccuracy observed by our method when it classifies

images based on diagnosis from other objective standards

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Detection of Chronic Laryngitis Due