No abstract

Aim:The aim was to develop a high-performance computer-aided diagnosis (CAD) system with image processing and pattern recognition in diagnosing pancreatic cancer by using endosonography images.Materials and Methods:On the images, regions of interest (ROI) of three groups of patients (<40, 40-60 and >60) were extracted by experts; features were obtained from images using three different techniques and were trained separately for each age group with an Artificial Neural Network (ANN) to diagnose cancer. The study was conducted on endosonography images of 202 patients with pancreatic cancer and 130 noncancer patients.Results:122 features were identified from the 332 endosonography images obtained in the study, and the 20 most appropriate features were selected by using the relief method. Images classified under three age groups (in years; <40, 40-60 and >60) were tested via 200 random tests and the following ratios were obtained in the classification: accuracy: 92%, 88.5%, and 91.7%, respectively; sensitivity: 87.5%, 85.7%, and 93.3%, respectively; and specificity: 94.1%, 91.7%, and 88.9%, respectively. When all the age groups were assessed together, the following values were obtained: accuracy: 87.5%, sensitivity: 83.3%, and specificity: 93.3%.Conclusions:It was observed that the CAD system developed in the study performed better in diagnosing pancreatic cancer images based on classification by patient age compared to diagnosis without classification. Therefore, it is imperative to take patient age into consideration to ensure higher performance.

(Cardiol J 2016; 23, 2: 195-201)

Improved diagnostic and therapeutic methods, widespread use of photocoagulation in vascular disorders and vitreoretinal surgery in traumas, effective antimicrobial treatment, increasing use of corticosteroids and immunosuppressants, have contributed to the decreasing frequency of enucleation. Tumor patients generally presented late with advanced tumors totally filling the eye, not salvageable by other non-invasive treatment methods. Prompt diagnosis of intraocular malignant tumors (retinoblastoma and malignant melanoma) may reduce the need for enucleation.

We report a case of a 45-year old woman who was found to have a giant mediastinal tumour with radiological degenerative changes. She underwent thoracotomy to remove the mass, which was eventually diagnosed histologically as an ancient schwannoma, whereas cytological interpretation of the accompanying pleural fluid was malignant. Ancient schwannoma is a rare variant of schwannoma, histologically showing atypical features that may result in erroneous diagnosis of a malignant tumour. Clinical and radiological findings are important aids for further consideration of surgical removal of these potentially resectable tumours.