Jasiūnas, Eugenijus

BACKGROUND: Ultrasound guided fine needle aspiration biopsy with cytologic analysis is an initial step in diagnostic of thyroid nodules. Unfortunately, up to 30% of biopsies are indeterminate and diagnostic surgery is required. The aim of this study was to estimate the diagnostic value of BRAF V600E mutation status combined with cytomorphological features for diagnosis of papillary thyroid cancer (PTC) in cytologically indeterminate thyroid nodules. METHODS: A prospective study analyzed patients who had ultrasound suspicious thyroid nodules, underwent fine needle aspiration and cytological examination, and were classified according to the Bethesda system. Patients from indeterminate diagnostic categories were examined for BRAF V600E mutation and 22 cytomorphological features, and underwent thyroid surgery. A binary logistic regression model was used to evaluate the diagnostic utility. RESULTS: A total of 219 patients met study criteria. After histological examination, 77 (35.2%) patients were diagnosed with PTC and 142 (64.8%) with benign nodular thyroid disease. According to logistic regression model, significant features for PTC diagnosis were: liquid colloid consistency, papillary structures, eosinophilic colloid bodies, and BRAF V600E mutation. Risk groups classified by this model have sensitivity of 80.5% (95% CI: 69.9 to 88.7), specificity of 99.3% (95% CI: 96.1 to 100), positive predictive value of 98.4% (95% CI: 89.8 to 99.8), negative predictive value of 90.4% (95% CI: 85.7 to 93.7), and accuracy of 92.7% (95% CI: 88.4 to 95.8) for PTC diagnosis. CONCLUSIONS: Evaluation of BRAF V600E mutation status combined with cytomorphological features for diagnosis of PTC in cytologically indeterminate thyroid nodules can significantly improve diagnostic accuracy and reduce the number of diagnostic operations (calculator available at www.ptc-calc.we2host.lt).

Purpose This study aims to determine the utility of the Bethesda category and its association with BRAF mutation in prediction of the papillary thyroid cancer (PTC) stage. Methods A prospective study analyzed patients who had ultrasound-suspicious thyroid nodules, underwent FNA and cytological examination, and were classified according to the Bethesda system. Patients from Undetermined Significance Or Follicular Lesion Of Undetermined Significance (AUS/ FLUS), Follicular Neoplasm or Suspicious for a Follicular Neoplasm (FN/SFN), Suspicious for Malignant Cells (SMC), and Positive for Malignant Cells (PMC) groups were examined for the BRAF mutation and had a thyroid surgery. Demographical and histological features and stage of the disease were evaluated for PTC patients in accordance with the Bethesda category and its association with BRAF mutation. Results Three hundred eight of all patients underwent operation. One hundred forty-three (46.4%) of them were diagnosed with PTC. In 14 (9.8%) PTC cases, FNA biopsies were classified as AUS/FLUS, 23 (16.1%) as FN/SFN, 41 (28.7%) as SMC, and 65 (45.5%) as PMC. I–II stages of PTC were diagnosed for 88 (61.5%) patients and III–IVA for 55 (38.5%). Patients from the SMC and PMC groups had larger tumors, higher incidence of lymph node metastases, classical PTC type, B-type Raf (BRAF) positive, and III–IVA stage cancer, than patients from the AUS/FLUS and FN/SFN groups. When comparing 27 (18.9%) BRAF-negative patients from the AUS/FLUS and FN/SFN groups with 116 (81.1%) BRAFnegative patients from the SMC and PMC groups and all BRAF-positive patients, the prediction of more aggressive histological features and stage was slightly improved. Conclusions Higher Bethesda categories are associated with higher stages of PTC. Association of the Bethesda category with BRAF mutation can slightly improve the value of stage prediction.

This research work is devoted to creating the service oriented electronic (distance) environment adaptable to the use's needs. The examples o f designing such adaptive e-service providing system are applied for e-learning environment. The paper analyses the possibilities of integrating ontology into the e-service system for learning needs. One of the possible ways to improve distance learning infrastructure and increase its effectiveness is to extend the present e-learning system by integrating domain ontology and forming intelligent agents' framevvork possible, which enables better adaptation of learning resources to user. The quality ofthe e-learning course is largely influenced by competently prepared educational resources and an effective study support system. The issues of decomposing ontology into different levels of understanding are discussed in order to adapt to learner's tasks and goals. A conceptual approach is proposed for extending the existing distance learning system architecture by intelligent and deeper knowledge layers.

In the medical world today, it is necessary to use some form of information system to keep track of the mass amounts of records and Information that are continuously received by medical companies. The medical field is extremely competitive and although the economy is not strong, medicine will always be necessary and thus will be advancing in one way or another. To keep up with the changing technologies, inventions, and legal regulations, hospitals, private practices, and surgery centers must keep a tight hold on their records, and in this day and age it is impossible to do so by hand. There are 2 types of Information Systems that physicians and their offices can use to keep track of the constant inflow and outflow of information. Medical Practice Management (MPM) software combines data backup and restoration, easy data entry forms, the capability to run on a number of different operating systems, and many more functions. Electronic healthcare Record (EHR) is the second type of information system commonly found in the medical field. EMR allows doctors to quickly process bills, enter patient data, and organize schedules with ease [...]