Use of indocyanine green near-infrared lymphography to detect sentinel lymph nodes in a dog with a malignant insulinoma: a case report

التفاصيل البيبلوغرافية
العنوان: Use of indocyanine green near-infrared lymphography to detect sentinel lymph nodes in a dog with a malignant insulinoma: a case report
المؤلفون: Mirja Christine Nolff, Renate Dennler, Matthias Dennler
المصدر: Frontiers in Veterinary Science. 10
بيانات النشر: Frontiers Media SA, 2023.
سنة النشر: 2023
مصطلحات موضوعية: General Veterinary
الوصف: Malignant insulinoma is the most common type of neuroendocrine tumor found in the pancreas of dogs. Canine insulinoma displays malignant behavior with a high rate of metastasis. The most common sites of metastases are the draining lymph nodes, which are also the primary location sites for the recurrence of functional disease. However, identifying metastatic nodes can often be complicated, as the pancreas is drained by numerous lymphatic centers, and clinical enlargement or structural changes may not always be present in metastatic nodes. Additionally, unaltered nodes are frequently small (a few millimeters) and can be hard to distinguish from the surrounding tissues. Therefore, lymphadenectomy is generally recommended for affected dogs. Unlike in human medicine, there are currently no established strategies for lymph node resection in dogs with malignant insulinoma. This report presents a technique for identifying and removing sentinel nodes using indocyanine green and near-infrared lymphography (NIRFL) during surgery. A total of six sentinel nodes were detected and resected with this method. This technique could provide a more structured approach for lymph node resection in affected dogs and potentially in humans in the future. However, its therapeutic benefits must be evaluated in a larger cohort of cases.
تدمد: 2297-1769
الوصول الحر: https://explore.openaire.eu/search/publication?articleId=doi_________::6481f0ef5881b195ff12d4aa98bc8e07Test
https://doi.org/10.3389/fvets.2023.1178454Test
حقوق: OPEN
رقم الانضمام: edsair.doi...........6481f0ef5881b195ff12d4aa98bc8e07
قاعدة البيانات: OpenAIRE