Low-Grade Appendiceal Mucinous Neoplasm Involving the Endometrium and Presenting with Mucinous Vaginal Discharge.

Primary appendiceal mucinous lesions are uncommon and represent a spectrum from nonneoplastic mucous retention cysts to invasive adenocarcinoma. Low-grade appendiceal mucinous neoplasms (LAMNs) represent an intermediate category on this spectrum and can be classified according to whether or not they are confined to the appendix. Although LAMNs are frequently confined to the appendix, they can also spread to the peritoneum and clinically progress as pseudomyxoma peritonei (i.e., mucinous ascites). Thus, the appropriate classification of appendiceal primary neoplasia is essential for prognosis and influences clinical management. In addition, the precise classification, management, and clinical outcome of patients with disseminated peritoneal disease remain controversial. Here, we report an unusual case of LAMN with pseudomyxoma peritonei that initially presented with mucinous and bloody vaginal discharge. Pathological evaluation revealed low-grade appendiceal mucinous neoplasm with secondary involvement of the peritoneum, ovaries, and endometrial surface. Therefore, LAMN should be considered in the differential diagnosis of mucinous vaginal discharge

An International Consensus to Standardize Integration of Histopathology in Ulcerative Colitis Clinical Trials

Background & Aims: Histopathology is an emerging treatment target in ulcerative colitis (UC) clinical trials. Our aim was to provide guidance on standardizing biopsy collection protocols, identifying optimal evaluative indices, and defining thresholds for histologic response and remission after treatment. Methods: An international, interdisciplinary expert panel of 19 gastroenterologists and gastrointestinal pathologists was assembled. A modified RAND/University of California, Los Angeles appropriateness methodology was used to address relevant issues. A total of 138 statements were derived from a systematic review of the literature and expert opinion. Each statement was anonymously rated as appropriate, uncertain, or inappropriate using a 9-point scale. Survey results were reviewed and discussed before a second round of voting. Results: Histologic measurements collected using a uniform biopsy strategy are important for assessing disease activity and determining therapeutic efficacy in UC clinical trials. Multiple biopsy strategies were deemed acceptable, including segmental biopsies collected according to the endoscopic appearance. Biopsies should be scored for architectural change, lamina propria chronic inflammation, basal plasmacytosis, lamina propria and epithelial neutrophils, epithelial damage, and erosions/ulcerations. The Geboes score, Robarts Histopathology Index, and Nancy Index were considered appropriate for assessing histologic activity; use of the modified Riley score and Harpaz Index were uncertain. Histologic activity at baseline should be required for enrollment, recognizing this carries operational implications. Achievement of histologic improvement or remission was considered an appropriate and realistic therapeutic target. Current histologic indices require validation for pediatric populations. Conclusions: These recommendations provide a framework for standardized implementation of histopathology in UC trials. Additional work is required to address operational considerations and areas of uncertainty

Update on the Liver Imaging Reporting and Data System: What the Pathologist Needs to Know.

Hepatocellular carcinoma (HCC) is frequently diagnosed noninvasively with imaging techniques. Computed tomography and magnetic resonance imaging play critical roles in the detection, diagnosis, and staging of HCC. Standardization in the interpretation and reporting of imaging modalities has not existed until recently. In 2008, the American College of Radiology supported the development of the Liver Imaging Reporting and Data System (LI-RADS) for standardized terminology, interpretation, and reporting of imaging examinations for the diagnosis of HCC inpatients at risk for HCC. This article reviews the basic concepts of LI-RADS, emphasizing aspects that are most relevant to pathologists, including the categories, diagnostic algorithm, major features, and ancillary features for the diagnosis of HCC. The similarities and differences between LI-RADS and other major radiology-based diagnostic systems in terms of target population, intended users, categorization of observations, and imaging methods are addressed. Importantly, LI-RADS and other systems are designed to diagnose progressed HCC with high specificity and modest sensitivity. LI-RADS and other systems are not designed to detect early HCC and so have limited sensitivity for such lesions. Moreover, despite continuous advances in imaging technology, imaging detection and characterization of small (<1 cm) nodules remains limited; in addition, colocalization of small nodules and pathology is difficult. For these reasons LI-RADS and most other systems require lesions to be 1 cm or greater for the noninvasive diagnosis of HCC. As LI-RADS evolves, it is critical that stakeholders, including pathologists, provide expert input to help standardize and enhance reporting of radiologic findings

Update on the Liver Imaging Reporting and Data System: What the Pathologist Needs to Know.

Hepatocellular carcinoma (HCC) is frequently diagnosed noninvasively with imaging techniques. Computed tomography and magnetic resonance imaging play critical roles in the detection, diagnosis, and staging of HCC. Standardization in the interpretation and reporting of imaging modalities has not existed until recently. In 2008, the American College of Radiology supported the development of the Liver Imaging Reporting and Data System (LI-RADS) for standardized terminology, interpretation, and reporting of imaging examinations for the diagnosis of HCC inpatients at risk for HCC. This article reviews the basic concepts of LI-RADS, emphasizing aspects that are most relevant to pathologists, including the categories, diagnostic algorithm, major features, and ancillary features for the diagnosis of HCC. The similarities and differences between LI-RADS and other major radiology-based diagnostic systems in terms of target population, intended users, categorization of observations, and imaging methods are addressed. Importantly, LI-RADS and other systems are designed to diagnose progressed HCC with high specificity and modest sensitivity. LI-RADS and other systems are not designed to detect early HCC and so have limited sensitivity for such lesions. Moreover, despite continuous advances in imaging technology, imaging detection and characterization of small (<1 cm) nodules remains limited; in addition, colocalization of small nodules and pathology is difficult. For these reasons LI-RADS and most other systems require lesions to be 1 cm or greater for the noninvasive diagnosis of HCC. As LI-RADS evolves, it is critical that stakeholders, including pathologists, provide expert input to help standardize and enhance reporting of radiologic findings

Integrating Community Context Information Into a Reliably Weighted Collaborative Filtering System Using Soft Ratings

In this paper, we aim at developing a new collaborative filtering recommender system using soft ratings, which is capable of dealing with both imperfect information about user preferences and the sparsity problem. On the one hand, Dempster-Shafer theory is employed for handling the imperfect information due to its advantage in providing not only a flexible framework for modeling uncertain, imprecise, and incomplete information, but also powerful operations for fusion of information from multiple sources. On the other hand, in dealing with the sparsity problem, community context information that is extracted from the social network containing all users is used for predicting unprovided ratings. As predicted ratings are not a hundred percent accurate, while the provided ratings are actually evaluated by users, we also develop a new method for calculating user-user similarities, in which provided ratings are considered to be more significant than predicted ones. In the experiments, the developed recommender system is tested on two different data sets; and the experiment results indicate that this system is more effective than CoFiDS, a typical recommender system offering soft ratings