Pancreatic cancer incidence trends in the United States from 2000-2017: Analysis of Surveillance, Epidemiology and End Results (SEER) database.

Background: Recent incidence trends of pancreatic cancers were reviewed by demographics and histologic type to observe any new findings. Methods: Data was used from the Surveillance, Epidemiology, and End Results (SEER) registry 18 (2000-2017) and it underwent temporal trend analysis. Pancreatic cancer incidence rates were reported based on histological subtype and demographics. Results: The incidence rate of white males increased significantly during 2000-2017 (annual percent change (APC) = 3.5%) compared to previously reported APCs. The incidence of white females grew from an APC of 1.29% to 2.9%. Rates among black ethnicity increased with an APC of 4.2%. Rates among Hispanics and other ethnicities also showed increment. The rates for ductal adenocarcinoma showed a positive trend in all races, with the APC ≥ 6 % for females and APC ≥ 6.5 % for males. The rates of non-secretory endocrine tumors showed a decline in both genders of all five races in recent years after showing an initial positive trend till 2010. Rates for pancreatic adenocarcinoma continued to rise in all ethnicities from 2000-2017. Interestingly, there was a rise in carcinoid type pancreatic neuroendocrine tumors (PNETs) in all ethnicities. Cumulatively, males had a higher incidence than females; male to female Incidence Risk Ratio (IRRs) was 1.32. The IRR was > 1 for age groups ≥ 35 years. The male to female IRRs was less than 1 for cystic adenocarcinoma, secretory endocrine, and solid pseudopapillary carcinomas (IRR = 0.5, 0.9, and 0.2 respectively, confidence intervals 0.4-0.6 and 0.9-1.3, 0.2-0.3, respectively). Conclusion: Pancreatic cancer incidence continued to rise in the years 2000-2017. However, incidence differed by demographics and histologic type. Interestingly, recent years discerned a rise in PNETs (carcinoid type) which has not been reported previously.

Coronavirus (COVID-19) detection from chest radiology images using convolutional neural networks.

Coronavirus disease (Covid-19) has been spreading all over the world and its diagnosis is attracting more research every moment. It is need of the hour to develop automated methods, which could detect this disease at its early stage, in a non-invasive way and within lesser time. Currently, medical specialists are analyzing Computed Tomography (CT), X-Ray, and Ultrasound (US) images or conducting Polymerase Chain Reaction (PCR) for its confirmation on manual basis. In Pakistan, CT scanners are available in most hospitals at district level, while X-Ray machines are available in all tehsil (large urban towns) level hospitals. Being widely used imaging modalities to analyze chest related diseases, produce large volume of medical data each moment clinical environments. Since automatic, time efficient and reliable methods for Covid-19 detection are required as alternate methods, therefore an automatic method of Covid-19 detection using Convolutional Neural Networks (CNN) has been proposed. Three publically available and a locally developed dataset, obtained from Department of Radiology (Diagnostics), Bahawal Victoria Hospital, Bahawalpur (BVHB), Pakistan have been used. The proposed method achieved on average accuracy (96.68 %), specificity (95.65 %), and sensitivity (96.24 %). Proposed model is trained on a large dataset and is being used at the Radiology Department, (BVHB), Pakistan.

Case Report: Kikuchi-Fujimoto Disease: A case of supraclavicular lymphadenopathy.

Kikuchi-Fujimoto Disease (KFD), also known as histiocytic necrotizing lymphadenitis, is a rare cause of cervical lymphadenopathy. Patients usually present with localized lymphadenopathy, fever and fatigue. Because of the poorly understood etiology, it can be mistaken for an infectious disease or even malignance. Here we discuss a case of KFD that initially presented with left sided cervical lymphadenopathy that later progressed to left supraclavicular lymph nodes. Due to its characteristic overlap with other disorders like tuberculous lymphadenitis and lymphoma, KFD remains an arduous diagnosis for physicians. Therefore, one should be made aware of symptoms that can lead to misdiagnosis in patients.