Book Description

While a pattern approach to diagnosis is taught and practiced with almost every other tissue or organ in the body, the lymph node remains a mystery to most residents starting out in pathology and those pathologists with limited experience in the area. A Pattern Approach to Lymph Node Diagnosis demonstrates that a systematic approach to lymph node examination can be achieved through recognition of morphological patterns produced by different disease processes. It presents a combination of knowledge-based assessment and pattern recognition for diagnosis covering the major primary neoplastic and non neoplastic diseases and metastatic tumors in lymph nodes. This volume demonstrates that lymph node compartments can be recognized histologically especially with the aid of immunohistological markers and how this knowledge can be employed effectively to localize and identify pathological changes in the different compartments in order to facilitate histological diagnosis. It also defines histological features that, because of their pathological occurrence in lymph nodes, are useful pointers to specific diagnoses or disease processes. The volume is organized in accordance with the primary pattern of presentation of each diagnostic entity. Differential diagnosis is discussed and each diagnostic entity is accompanied by color illustrations that highlight the diagnostic features. Immunohistochemistry, clinical aspects, relevant cytogenetics and molecular information of each entity is provided by authors who are experts in lymphoproliferative diseases. An algorithmic approach to diagnosis is adopted at the end of each section by listing a set of questions that help to consider diagnostic entities that can present with the morphological features observed. A Pattern Approach to Lymph Node Diagnosis will be of great utility to residents and fellows in pathology and general pathologists making first hand lymph node diagnoses as well as to hematologists and physicians who treat patients with lymphoprolifeative diseases.