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Architecture, size, and shape of glands are most important patterns used by pathologists for assessment of cancer malignancy in prostate histopathological tissue slides. Varying structures of glands along with cumbersome manual observations may result in subjective and inconsistent assessment. Cribriform gland with irregular border is an important feature in Gleason pattern 4. We propose using deep neural networks for cribriform pattern classification in prostate histopathological images. $163708$ Hematoxylin and Eosin (H\&E) stained images were extracted from histopathologic tissue slides of $19$ patients with prostate cancer and annotated for cribriform patterns. Our automated image classification system analyses the H\&E images to classify them as either `Cribriform' or `Non-cribriform'. Our system uses various deep learning approaches and hand-crafted image pixel intensity-based features. We present our results for cribriform pattern detection across various parameters and configuration allowed by our system. The combination of fine-tuned deep learning models outperformed the state-of-art nuclei feature based methods. Our image classification system achieved the testing accuracy of $85.93~\pm~7.54$ (cross-validated) and $88.04~\pm~5.63$ ( additional unseen test set) across three folds. In this paper, we present an annotated cribriform dataset along with analysis of deep learning models and hand-crafted features for cribriform pattern detection in prostate histopathological images., 21 pages, 4 figures, 6 tables

We present a case of a previously healthy 50-year-old gentleman who had recurrent vomiting and abdominal pain of two-month duration. The patient was subsequently diagnosed with abdominal cocoon on computed tomography. Idiopathic sclerosing encapsulating peritonitis, also known as abdominal cocoon, is a rare cause of small bowel obstruction. Visualization of variable encasement of the small bowel loops by a characteristic membranous sac, either preoperatively with cross-sectional imaging or intraoperatively, is the key to diagnosis. This is a highly treatable condition; surgical excision of the sac with adhesiolysis facilitates a full recovery in affected patients.