肾上腺结节影像报告和数据系统的分类建议及进展

Classification Suggestions and Progress of Adrenal Nodules Imaging Reporting and Data Systems

肾上腺结节是一种常见的肾上腺疾病,其影像学诊断在临床中起重要作用。目前,对肾上腺结节在影像学上的良恶性风险评估分类并不统一,通过探索肾上腺结节影像报告和数据系统(AI-RADS)的分类方法,可将肾上腺结节按大小及影像学特征分为微小、小、中等、大结节以及良、恶性结节。当结节为良性且为微小或小结节时,无须进行随访;但若结节表现出恶性特征且为中等或大结节时,则应考虑影像随访或进一步手术治疗。AI-RADS作为一种新兴的影像学评估系统,为肾上腺结节的规范化诊断提供了新的途径。未来建议集中优化AI-RADS,提高其准确性和可靠性,同时探索AI-RADS的进一步应用和推广,以促进肾上腺结节的早期诊断和个性化治疗。

Adrenal nodules are a common adrenal disease,and their imaging diagnosis plays an important role in clinical practice.Currently,there is no unified classification for the benign and malignant risk assessment of adrenal nodules in imaging.By exploring the classification method of adrenal nodules based on size and imaging characteristics in adrenal nodules imaging reporting and data systems(AI-RADS),adrenal nodules can be categorized into tiny,small,moderate,and large nodules,as well as benign and malignant nodules.When nodules are benign and tiny or small,follow-up is not necessary;however,if nodules exhibit malignant features and are moderate or large,imaging follow-up or further surgical treatment should be considered.AI-RADS,as an emerging imaging evaluation system,offers a new approach for standardized diagnosis of adrenal nodules.Future suggestions focus on optimizing the AI-RADS to enhance its accuracy and reliability,as well as exploring further applications and promotion of the AI-RADS to facilitate early diagnosis and individualized treatment of adrenal nodules.