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<p>Autoimmune pancreatitis (AIP) and pancreatic neuroendocrine neoplasia (pNET) are two diseases with distinct pathophysiological mechanisms. However, the phenomenon of their coexistence in the same patient is increasingly gaining clinical attention. Although the mechanism behind this co-occurrence is not yet fully understood, the chronic inflammatory microenvironment may play a key role. This review aims to discuss the potential pathogenetic links between AIP and pNET coexistence, focusing on analysing the unique challenges and corresponding strategies in imaging diagnosis. Furthermore, the multidisciplinary team (MDT) collaborative model was used to construct a personalized treatment framework guided primarily by pNET risk stratification while also considering AIP disease activity. A deep understanding of this coexistence is crucial for clinicians to achieve accurate diagnoses, optimize treatment decisions, and improve patient prognosis.</p>

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Diagnosis and treatment strategies for autoimmune pancreatitis combined with pancreatic neuroendocrine tumors

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年2月10日

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  • Dongxue Geng,
  • Wenjie Gao,
  • Yi Miao

摘要

Autoimmune pancreatitis (AIP) and pancreatic neuroendocrine neoplasia (pNET) are two diseases with distinct pathophysiological mechanisms. However, the phenomenon of their coexistence in the same patient is increasingly gaining clinical attention. Although the mechanism behind this co-occurrence is not yet fully understood, the chronic inflammatory microenvironment may play a key role. This review aims to discuss the potential pathogenetic links between AIP and pNET coexistence, focusing on analysing the unique challenges and corresponding strategies in imaging diagnosis. Furthermore, the multidisciplinary team (MDT) collaborative model was used to construct a personalized treatment framework guided primarily by pNET risk stratification while also considering AIP disease activity. A deep understanding of this coexistence is crucial for clinicians to achieve accurate diagnoses, optimize treatment decisions, and improve patient prognosis.