Volume 6 in the Series: The Johns Hopkins Atlases of Pathology AUTHORS: Christopher J. VandenBussche, Syed Z. Ali, Amy G. Zhou, Matthew T. Olson, and Justin A. Bishop SERIES EDITORS: Toby C. Cornish, Norman J. Barker, and Ralph H. Hruban The Johns Hopkins Atlas of Thyroid Pathology is the sixth teaching app in our series from the Johns Hopkins University Department of Pathology. This app is designed to teach residents, fellows, and practicing pathologists the assessment of thyroid fine needle aspiration specimens with histologic correlation. While the material includes numerous examples of common entities, such that viewers can experience the variety of morphologies associated with each entity, rare entities are also included. The app is composed of four modules: an interactive teaching algorithm, a searchable image atlas, an image-based quiz, and a flash card module. Viewing multiple examples of the same entity or feature from this large, rich image atlas will strengthen your diagnostic skills and updated you on key concepts in the area of thyroid cytopathology and pathology. Teaching Algorithm: The teaching algorithm is based on the assessment of cytomorphologic features to arrive at a diagnosis. The algorithm consists of a series of dichotomous decision points focusing on current diagnostic concepts involved in the diagnosis of thyroid fine needle aspiration specimens. It is designed with the Bethesda System for Reporting Thyroid Cytopathology in mind, which will help viewers better understand this widely accepted reporting system. Image Atlas: The image atlas contains over 500 high-resolution color images. The atlas can be viewed by diagnosis, features (these features reinforce the diagnostic features used in the algorithm), and Bethesda System category. In addition to the albums we have provided, you can create your own albums and add images you select from the atlas to these albums. Quiz: The Quiz contains 50 multiple choice questions for self-study. Keep track of your progress or quiz your friends and family! Flash Cards: The Flash cards module allows you to view a randomly generated assortment of images from the image bank and subsequently view the diagnosis and caption by simply ìflippingî the card over. We welcome your feedback. Please e-mail Dr. Hruban at rhruban@jhmi.edu. If you find an error, please let us know so we can correct it.
