Study of Chronic Suppurative Otitis Media Using Computed Tomography

Abstract

Chronic Suppurative Otitis Media (CSOM) is one of the leading causes of hearing impairment in developing countries. The study aim are to highlight the high resolution computerized tomography (HRCT) temporal bone findings in chronic middle ear infections with reference to its extent and complications, as well, the presented common signs, symptoms and the duration impact on the anatomical structures and pathological changes in each part and for both sides. Preliminary clinical assessment was obtained for 114 patients diagnosed with CSOM, and then they were referred for a HRCT of temporal bone which was done using multi-detector CT scanner. The results showed Of the 114 patients; 63(55.3%) were males and 51(44.7%) were females: Otorrhoea is the most common symptom, and was found in 113 patients constituting (99.1%) followed by Otolegia 69(60.5%) and headache affected 53(46.5%) of the cases. CSOM is more common in low socio-economic status . In ears affected with CSOM, the maximum CT number (Hounsfield) was found to be changed and was significantly affected with increasing patients’ age. Sclerotic changes and soft tissue density increased as the duration of CSOM increased in right and left middle ears significantly (F=5.802, Sig at 0.000), and (F=23.182, Sig at .015) respectively. Partial and complete erosion were detected in both right and left ossicle in the advanced phase of disease, where the ossicle still intact in the early stage , and the correlation is found to be significant with increasing of CSOM duration (F=16.959, Sig 0.000) and (F= 3.673, Sig =0.036)for right and left ossicles respectively. Changes including total and partial opacification, sclerotic changes, soft tissue density, mucosal thickening V were the findings detected in both right and left mastoid in HRCT for temporal bone scanning. HRCT of temporal bone is useful in identifying various findings related to the location and extent of disease. Also This study concern to characterize the Temporal bone were defining to Fluid, Mucosal, Sclerotic and Soft tissues density using texture feature extraction and extract classification features from CT images. The texture analysis technique used to find the gray level variation in CT images. analyzing the image with Interactive Data Language IDL software to measure the grey level variation of images. The results show that texture analysis give classification accuracy of temporal bone to fluid 86.3%, mucosal 98.2%, sclerotic 99%, While the soft tissue density showed a classification accuracy 92.2%. the overall classification accuracy of temporal bone area 93.6%. These relationships are stored in a Texture Dictionary that can be later used to automatically annotate new CT images with the appropriate temporal bone area names