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Articles by Avicenna Medical College and Hospital

Diagnostic accuracy of Magnetic Resonance Imaging to differentiate benign and Malignant Parotid Gland Tumors

Published on: 7th November, 2018

OCLC Number/Unique Identifier: 7929251620

Objective: To determine the diagnostic accuracy of Magnetic Resonance Imaging (MRI) to differentiate Benign and Malignant Parotid Gland Tumors taking histopathology as gold standard. Design: Cross sectional study. Place and duration of study: Department of Diagnostic Radiology, Lahore General Hospital, Lahore from January till July 2014. Methodology: 200 patients of age between 5 to 80 years of either gender with parotid gland swelling, having radiological evidence and clinical suspicion of parotid tumour like fixation to underlying skin, pain, facial palsy and cervical lymphadenopathy were taken. T1 and T2 plain and contrast enhanced 1.5 Tesla MRI unit using standard imaging coil was then carried out. Imaging was further evaluated for the presence or absence of benign or malignant parotid gland tumours using histopathology as a Gold standard. Sensitivity, specificity, positive predictive value, negative predictive value and diagnostic accuracy of MRI were taken against the gold standard. Results: There were 170 males and 30 females having mean age of 40.27±15.04 and 40.12±12.15 years respectively. Sensitivity, specificity, positive predictive value and negative predictive value of MRI were 90.4%, 89.33%, 93.39% and 84.41% respectively. The diagnostic accuracy of MRI to differentiate benign and malignant parotid gland tumours was 90%. These results were taken against surgery histopathology as a gold standard. Conclusion: MRI is highly accurate in differentiating malignant & benign tumours of parotid glands and can be used as an adjunct to histopathology for pre-operative evaluation of the parotid gland tumours.
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Efficiency of Artificial Intelligence for Interpretation of Chest Radiograms in the Republic of Tajikistan

Published on: 25th November, 2024

The article presents data from recent publications and own data on screening studies with interpretation of chest radiographs using artificial intelligence CAD (Computer-Assisted Diagnosis), which, according to WHO recommendations, provides more accurate clinical thresholds for deciding who needs to take a sputum test. Another aspect of the WHO recommendations is the cost-effectiveness of CAD as a tool for triaging patients with tuberculosis symptoms in low-income countries with a high incidence of tuberculosis. Compared with smear microscopy and GeneXpert, without preliminary sorting, the use of mobile digital X-ray machines equipped with a CAD tool reduces costs, allowing sorting of individuals suspected of having tuberculosis for testing on GeneXpert, while reducing the time to start tuberculosis treatment.Thus, conducting a study using portable X-ray machines using a CAD program is a low-cost and easy-to-implement method, does not require large funds, does not require separate rooms, is highly effective, has good image quality, allows you to quickly clarify individuals suspected of having tuberculosis, differentiating it from other pathological changes in the lungs.Our experience shows that machine analysis of chest computed tomography data, due to the higher resolution capabilities of the method and the absence of fundamental disadvantages of radiography, including the effect of shadow summation, the presence of “blind” zones, etc., is finding increasing application in both diagnostics and screening of respiratory diseases. Our use of this tool allowed us to identify additional new cases of phthisio-onco-pulmonary diseases in field conditions.
Cite this ArticleCrossMarkPublonsHarvard Library HOLLISGrowKudosResearchGateBase SearchOAI PMHAcademic MicrosoftScilitSemantic ScholarUniversite de ParisUW LibrariesSJSU King LibrarySJSU King LibraryNUS LibraryMcGillDET KGL BIBLiOTEKJCU DiscoveryUniversidad De LimaWorldCatVU on WorldCat
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