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The microscopic diagnostic differentiation of odontogenic cysts from other cysts is intricate and may cause perplexity for both clinicians and pathologists. Of particular interest is the odontogenic keratocyst (OKC), a developmental cyst with unique histopathological and clinical characteristics. Nevertheless, what distinguishes this cyst is its aggressive nature and high tendency for recurrence. Clinicians encounter challenges in dealing with this frequently encountered jaw lesion, as there is no consensus on surgical treatment. Therefore, the accurate and early diagnosis of such cysts will benefit clinicians in terms of treatment management and spare subjects from the mental agony of suffering from aggressive OKCs, which impact their quality of life. The objective of this research is to develop an automated OKC diagnostic system that can function as a decision support tool for pathologists, whether they are working locally or remotely. This system will provide them with additional data and insights to enhance their decision-making abilities. This research aims to provide an automation pipeline to classify whole-slide images of OKCs and non-keratocysts (non-KCs: dentigerous and radicular cysts). OKC diagnosis and prognosis using the histopathological analysis of tissues using whole-slide images (WSIs) with a deep-learning approach is an emerging research area. WSIs have the unique advantage of magnifying tissues with high resolution without losing information. The contribution of this research is a novel, deep-learning-based, and efficient algorithm that reduces the trainable parameters and, in turn, the memory footprint. This is achieved using principal component analysis (PCA) and the ReliefF feature selection algorithm (ReliefF) in a convolutional neural network (CNN) named P-C-ReliefF. The proposed model reduces the trainable parameters compared to standard CNN, achieving 97% classification accuracy. [ABSTRACT FROM AUTHOR]

Introduction: Odontogenic cysts are characterized by an expansile non-infiltrative growth through several mechanisms which include presence of mast cells in the capsule. The mast cells can be demonstrated histochemically as well as immunohistochemically. Aim and Objectives: The primary objective of the study was to analyze the presence and distribution of mast cells in radicular cyst, dentigerous cyst and keratocystic odontogenic tumor histochemically and immunohistochemically, to intercompare their expression and to correlate it with the degree of inflammation. Material and Methods: Tissue sections of 30 cases each of radicular cyst, dentigerous cyst and keratocystic odontogenic tumor were stained with toluidine blue and CD117. Quantitation and localization of mast cells was determined by dividing the section into subepithelial and deep zone. The mean number of mast cells was compared between toluidine blue and CD117 for each cyst, and also between two zones for each cyst, using ANOVA test. Correlation of mast cells with degree of inflammation was done using Pearson's correlation coefficient. Results: The mean number of mast cells were maximum in keratocystic odontogenic tumor, both histochemically and immunohistochemically, with high localization in the subepithelial zone. Immunohistochemical staining detected higher number of mast cells than histochemistry (4.54 and 3.23 respectively). Statistically significant correlation of mast cells with degree of inflammation was observed. Conclusion: Mast cells may play a role in the pathogenesis of odontogenic cysts as an elevated number of mast cells were found in the connective tissue capsule of all three odontogenic cysts. [ABSTRACT FROM AUTHOR]

Peripheral facial nerve palsy is the commonest cranial nerve motor neuropathy. The causes range from cerebrovascular accident to iatrogenic damage, but there are few reports of facial nerve paralysis attributable to odontogenic infections. In majority of the cases, recovery of facial muscle function begins within first three weeks after onset. This article reports a unique case of 32-year-old male patient who developed facial pain followed by unilateral facial nerve paralysis due to odontogenic infection. The treatment included extraction of the associated tooth followed by endodontic treatment of the neighboring tooth which resulted in recovery of facial nerve plasy. A thorough medical history and physical examination are the first steps in making any diagnosis. It is essential to rule out other causes of facial paralysis before making the definitive diagnosis, which implies the intervention. The authors hereby, report a case of 32-year-old male patient who developed unilateral facial nerve paralysis due to odontogenic infection with a good prognosis after appropriate treatment. [ABSTRACT FROM AUTHOR]