Department of Radiology, The Ohio State University Wexner Medical Center, Columbus, OH 43210, USA.
Tomography. 2024 Nov 18;10(11):1814-1831. doi: 10.3390/tomography10110133.
Advancements in artificial intelligence (AI) have significantly transformed the field of abdominal radiology, leading to an improvement in diagnostic and disease management capabilities. This narrative review seeks to evaluate the current standing of AI in abdominal imaging, with a focus on recent literature contributions. This work explores the diagnosis and characterization of hepatobiliary, pancreatic, gastric, colonic, and other pathologies. In addition, the role of AI has been observed to help differentiate renal, adrenal, and splenic disorders. Furthermore, workflow optimization strategies and quantitative imaging techniques used for the measurement and characterization of tissue properties, including radiomics and deep learning, are highlighted. An assessment of how these advancements enable more precise diagnosis, tumor description, and body composition evaluation is presented, which ultimately advances the clinical effectiveness and productivity of radiology. Despite the advancements of AI in abdominal imaging, technical, ethical, and legal challenges persist, and these challenges, as well as opportunities for future development, are highlighted.
人工智能 (AI) 的进步极大地改变了腹部放射学领域，提高了诊断和疾病管理能力。本叙述性综述旨在评估 AI 在腹部成像中的当前地位，重点关注近期文献的贡献。这项工作探讨了肝、胆、胰、胃、结肠和其他病变的诊断和特征描述。此外，AI 还被观察到有助于区分肾、肾上腺和脾脏疾病。此外，还强调了用于测量和描述组织特性的工作流程优化策略和定量成像技术，包括放射组学和深度学习。评估这些进步如何实现更精确的诊断、肿瘤描述和身体成分评估，从而提高放射学的临床效果和生产力。尽管 AI 在腹部成像方面取得了进步，但技术、道德和法律挑战仍然存在，突出了这些挑战以及未来发展的机会。
