Objective: To explore the value of dynamic contrast enhanced ultrasound (DCE-US) in preoperative differential diagnosis of focal-type autoimmune pancreatitis (AIP) and pancreatic ductal adenocarcinoma (PDAC).
Patients and methods: From May 2016 to March 2020, patients with biopsy and histopathologically confirmed focal-type AIP (n = 9) were retrospectively included. All patients received contrast enhanced ultrasound (CEUS) examinations one week before surgery/biopsy. Dynamic analysis was performed by VueBox® software (Bracco, Italy). Eighteen cases of resection and histopathologically proved PDAC lesions were also included as control group. B mode ultrasound (BMUS) features, CEUS enhancement patterns, time intensity curves (TICs) and CEUS quantitative parameters were obtained and compared between AIP and PDAC lesions.
Results: After injection of ultrasound contrast agents, most focal-type AIP lesions displayed hyper-enhancement (2/9, 22.2%) or iso-enhancement (6/9, 66.7%) during arterial phase of CEUS, while most of PDAC lesions showed hypo-enhancement (88.9%) (P < 0.01). During late phase, most of AIP lesions showed iso-enhancement (8/9, 88.9%), while most of PDAC lesions showed hypo-enhancement (94.4%) (P < 0.001). Compared with PDAC lesions, TICs of AIP lesions showed delayed and higher enhancement. Among all CEUS perfusion parameters, ratio of PE (peak enhancement), WiAUC (wash-in area under the curve), WiR (wash-in rate), WiPI (wash-in perfusion index, WiPI = WiAUC/ rise time), WoAUC (wash-out area under the curve), WiWoAUC (wash-in and wash-out area under the curve) and WoR (wash-out rate) between pancreatic lesion and surrounding normal pancreatic tissue were significantly higher in AIP lesions than PDAC lesions (P < 0.05).
Conclusion: DCE-US with quantitative analysis has the potential to make preoperative differential diagnosis between focal-type AIP and PDAC non-invasively.
Keywords: Dynamic contrast enhanced ultrasound (DCE-US); autoimmune pancreatitis (AIP); preoperative; quantitative parameters; time intensity curves (TICs).