He Jia-Jia, Xiong Wei-Lv, Sun Wei-Qi, Pan Qun-Yan, Xie Li-Ting, Jiang Tian-An
Department of Ultrasound Medicine, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou 310003, China; Department of Ultrasound Medicine, Beilun District People's Hospital, Ningbo 315800, China.
Department of Ultrasound Medicine, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou 310003, China; Department of Ultrasound Medicine, Huzhou Central Hospital, Huzhou 313000, China.
Hepatobiliary Pancreat Dis Int. 2025 Jun;24(3):239-251. doi: 10.1016/j.hbpd.2024.09.011. Epub 2024 Oct 4.
Gallbladder cancer (GBC) is the most common malignant tumor in the biliary system, characterized by high malignancy, aggressiveness, and poor prognosis. Early diagnosis holds paramount importance in ameliorating therapeutic outcomes. Presently, the clinical diagnosis of GBC primarily relies on clinical-radiological-pathological approach. However, there remains a potential for missed diagnosis and misdiagnose in the realm of clinical practice. We firstly analyzed the blood-based biomarkers, such as carcinoembryonic antigen and carbohydrate antigen 19-9. Subsequently, we evaluated the diagnostic performance of various imaging modalities, including ultrasound (US), endoscopic ultrasound (EUS), computed tomography (CT), magnetic resonance imaging (MRI), positron emission tomography/computed tomography (PET/CT) and pathological examination, emphasizing their strengths and limitations in detecting early-stage GBC. Furthermore, we explored the potential of emerging technologies, particularly artificial intelligence (AI) and liquid biopsy, to revolutionize GBC diagnosis. AI algorithms have demonstrated improved image analysis capabilities, while liquid biopsy offers the promise of non-invasive and real-time monitoring. However, the translation of these advancements into clinical practice necessitates further validation and standardization. The review highlighted the advantages and limitations of current diagnostic approaches and underscored the need for innovative strategies to enhance diagnostic accuracy of GBC. In addition, we emphasized the importance of multidisciplinary collaboration to improve early diagnosis of GBC and ultimately patient outcomes. This review endeavoured to impart fresh perspectives and insights into the early diagnosis of GBC.
胆囊癌(GBC)是胆道系统中最常见的恶性肿瘤,其特点是恶性程度高、侵袭性强且预后差。早期诊断对于改善治疗效果至关重要。目前,GBC的临床诊断主要依靠临床-放射-病理方法。然而,在临床实践中仍存在漏诊和误诊的可能性。我们首先分析了基于血液的生物标志物,如癌胚抗原和糖类抗原19-9。随后,我们评估了各种成像模态的诊断性能,包括超声(US)、内镜超声(EUS)、计算机断层扫描(CT)、磁共振成像(MRI)、正电子发射断层扫描/计算机断层扫描(PET/CT)以及病理检查,强调了它们在检测早期GBC方面的优势和局限性。此外,我们探索了新兴技术,特别是人工智能(AI)和液体活检在革新GBC诊断方面的潜力。AI算法已显示出改进的图像分析能力,而液体活检有望实现非侵入性和实时监测。然而,将这些进展转化为临床实践需要进一步验证和标准化。该综述强调了当前诊断方法的优缺点,并强调需要创新策略来提高GBC的诊断准确性。此外,我们强调了多学科协作对于改善GBC早期诊断并最终改善患者结局的重要性。本综述旨在为GBC的早期诊断提供新的视角和见解。