Comparison of avascular lymph node fragment transplantation techniques to optimize lymphangiogenesis in the minipig model

Abstract

Background Secondary lymphoedema is a challenging pandemic. This condition may arise after oncologic resection of tumor-draining lymph nodes and/or radiation. Plastic-surgical procedures for lymphoedema comprise transplantation of vascularized lymph node flaps, which are, however, technically challenging and difficult to implement on a global level due to the scarcity of microsurgery facilities in some countries. To improve this situation, comparative research in valid animal models is needed. Methods A total of 33 minipigs were subjected to lymphatic resection in the hind limbs. This large animal model was used in a first phase to compare different lymph node fragmentation methods and assess lymphatic regeneration after avascular transplantation. In a second phase, several stimulants were tested for their effect on lymphatic regeneration after fragment transplantation. In a third phase, animals additionally received irradiation of the groin. In this novel animal model, autologous avascular lymph node fragment transplantation was complemented by peripheral injections of vascular endothelial growth factor-C (VEGF-C). Finally, regeneration rates were quantified in relative numbers (percentage) in the irradiated tissue. Results In the first phase, transversal lymph node fragmentation under preservation of the nodal capsule showed the best percentage of regeneration (62.5%). Peripheral intradermal administration of VEGF-C enhanced lymph node fragment regeneration (70.8%) better than injections of tetanus toxoid (41.6%) or Streptococcus suis (62.5%). Lymph node fragment regeneration also occurred in an irradiated porcine model of lymphadenectomy under VEGF-C administration (66.6%). Conclusions The present findings provide a pre-clinical proof-of-concept for a possible simplification strategy for current operative procedures of autologous lymph node transplantation. Level of evidence : Not gradable