Closely mirroring the daily sign-out process, Atlas of Lymph Node Pathology: A Pattern Based Approach is a highly illustrated, efficient guide to accurate diagnosis. This practical reference uses a proven, pattern-based approach to clearly explain how to interpret challenging cases by highlighting red flags in the clinical chart and locating hidden clues in the slides. Useful as a daily “scope-side guide,” it features numerous clinical and educational features that help you find pertinent information, reach a correct diagnosis, and assemble a thorough and streamlined pathology report.
- More than 1,500 high-quality photomicrographs depict reactive and neoplastic processes involving lymph nodes, capturing the full spectrum of morphologic changes associated with common abnormalities, including relatively rare conditions. Captions include a morphologic description, highlighting subtle features and key diagnostic considerations.
- Practical tools throughout the text include:
- Tables that emphasize salient clinicopathologic features, management implications, and therapeutic options
- Discussions of how and when to incorporate immunohistochemical and special stains, as well as the utilization of flow cytometry and molecular tools
- Checklists for key elements of the diagnostic approach and sample notes for inclusion in pathology reports
- Relevant endoscopic images, photographs of select gross specimens, and medical figures
- Brief reviews of normal histology that provide contrast to succeeding patterns
- “Pearls and Pitfalls” and “Near Misses” sections with lessons from real-life sign-out experience
- “Frequently Asked Questions” sections that discuss common diagnostic dilemmas
- “Sample Note” sections that offer a template of how to synthesize complicated or especially challenging topics
- Quizzes in every chapter that provide experience with high-yield, board-style teaching topics
- Read directly on your preferred device(s),such as computer, tablet, or smartphone.
- Easily convert to audiobook,powering your content with natural language text-to-speech.
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