Journal of ENT and Allied Sciences

Recent advancements in artificial intelligence (AI) have significantly enhanced diagnostic capabilities across medical specialties. This paper explores the integration of AI in otoscopy, a fundamental procedure in otolaryngology for evaluating the ear canal and tympanic membrane. By leveraging machine learning algorithms and deep neural networks, AI systems can analyze otoscopic images with high accuracy, supporting clinicians in detecting conditions such as otitis media, tympanic membrane perforations, and cerumen impaction. This study compares AI-assisted otoscopy diagnosis in 100 patients and diagnosis on otoscopy alone in other 100 patients with the diagnosis established on examination under microscope (EUM) in all 200 patients. The findings suggest that AI-assisted otoscopy improves the diagnostic accuracy by 6%. AI assisted otoscopy holds substantial promise for improving diagnostic consistency, reducing disparities in care, and enabling early intervention in underserved populations.

Histopathology, the microscopic examination of tissues and cells, is fundamental to illness diagnosis as it facilitates intricate visualisation of cellular and tissue structure. The evaluation of cellular morphology and structural patterns is essential for differentiating benign from malignant tumours, identifying infectious agents, and characterising inflammatory and autoimmune disorders. Improvements in histopathological methods, especially immunohistochemistry and molecular pathology, have markedly increased diagnosis accuracy by enabling the identification of specific protein markers and genetic changes linked to certain diseases. An in-depth assessment of critical cellular processes, including differentiation, proliferation rates, apoptosis, and metastatic capability, yields significant insights into disease progression, prognosis, and therapy efficacy. These characteristics are crucial for directing clinical decision-making and formulating focused treatment regimens. Moreover, emerging technologies such as digital pathology and artificial intelligence are revolutionising the sector by enhancing diagnostic speed, standardisation, and accuracy, while facilitating extensive data analysis and pattern identification. The amalgamation of conventional microscopy with sophisticated diagnostic instruments has broadened the scope and significance of histopathology, rendering it an essential element of contemporary medicine. Histopathology enables correct interpretation of intricate cellular patterns, hence aiding precise illness diagnosis and enhancing personalised patient care and clinical outcomes across various conditions.

Blandin–Nuhn cysts are uncommon mucous retention or extravasation lesions originating from the minor salivary glands located on the ventral surface of the tongue. Owing to their infrequent occurrence and variable clinical appearance, these lesions are often misdiagnosed as Ranulas, vascular anomalies, or benign soft-tissue tumors. Clinically, they present as painless, soft, fluctuant swellings that may fluctuate in size and occasionally cause functional discomfort. We report a case of 8 year old child who came to ENT opd with gradually progressing swelling on the ventral surface of tongue. Diagnosis was established through histopathological examination following complete surgical excision.

Background: Epidermal inclusion cysts and lipomas are among the most common benign soft-tissue lesions encountered in the cervical region. However, their simultaneous occurrence at the same anatomical site is uncommon and may pose diagnostic challenges, particularly when preoperative investigations suggest a single pathology. Case Presentation: We report the case of a 48-year-old male who presented with a painless, gradually enlarging swelling in the lateral aspect of the neck. Clinical examination revealed a soft, mobile mass without overlying skin changes. Fine needle aspiration cytology (FNAC) suggested a single benign lesion. However, contrast-enhanced computed tomography (CT) of the neck demonstrated two distinct adjacent lesions, raising suspicion of dual pathology. The patient underwent complete surgical excision of the mass. Histopathological examination confirmed an epidermal inclusion cyst overlying a lipoma. The postoperative course was uneventful, and no recurrence was observed during follow-up. Conclusion: This case underscores the diagnostic limitations of FNAC in complex neck masses and highlights the importance of radiological imaging in preoperative assessment. Histopathological evaluation remains the gold standard for definitive diagnosis and exclusion of malignancy. Complete surgical excision is curative, with an excellent prognosis.