Department of Radiology, West China Hospital, Sichuan University, Chengdu, China.
Department of Nephrology, Sichuan Academy of Medical Sciences and Sichuan Provincial People' s Hospital, University of Electronic Science and Technology of China, Chengdu, China.
Br J Radiol. 2021 Feb 1;94(1118):20200802. doi: 10.1259/bjr.20200802. Epub 2020 Nov 27.
Acute kidney injury (AKI) is a common complication of acute pancreatitis (AP) that is associated with increased mortality. Conventional assessment of AKI is based on changes in serum creatinine concentration and urinary output. However, these examinations have limited accuracy and sensitivity for the diagnosis of early-stage AKI. This review summarizes current evidence on the use of advanced imaging approaches and artificial intelligence (AI) for the early prediction and diagnosis of AKI in patients with AP. CT scores, CT post-processing technology, Doppler ultrasound, and AI technology provide increasingly valuable information for the diagnosis of AP-induced AKI. Magnetic resonance imaging (MRI) also has potential for the evaluation of AP-induced AKI. For the accurate diagnosis of early-stage AP-induced AKI, more studies are needed that use these new techniques and that use AI in combination with advanced imaging technologies.
急性肾损伤（AKI）是急性胰腺炎（AP）的常见并发症，与死亡率增加有关。AKI 的常规评估基于血清肌酐浓度和尿量的变化。然而，这些检查对于早期 AKI 的诊断准确性和灵敏度有限。本综述总结了目前关于使用先进的成像方法和人工智能（AI）对 AP 患者 AKI 进行早期预测和诊断的证据。CT 评分、CT 后处理技术、多普勒超声和 AI 技术为诊断 AP 引起的 AKI 提供了越来越有价值的信息。磁共振成像（MRI）也具有评估 AP 引起的 AKI 的潜力。为了准确诊断早期 AP 引起的 AKI，需要更多使用这些新技术并结合先进成像技术使用 AI 的研究。
