|
| 基于人工智能的影像组学在肝癌筛查诊疗及预后的研究进展 |
| Research progress of artificial intelligence-based radiomics in screening, diagnosis, treatment and prognosis of liver cancer |
| 投稿时间：2025-03-26 修订日期：2025-09-26 |
| DOI： |
| 中文关键词: 人工智能；影像组学；肝癌；深度学习算法 |
| 英文关键词: Radiomics; Artificial intelligence; Liver cancer; Deep learning algorithm |
| 基金项目:济宁医学院大学生创新训练计划资助项目（cx2023247） |
| 作者 | 单位 | 邮编 | | 李倍佳 | 济宁医学院医学影像与检验学院 | 272067 | | 朱来敏 | 济宁医学院附属医院医学影像科 | | | 赵琪 | 济宁医学院医学影像与检验学院 | | | 刘佳鑫 | 济宁医学院医学影像与检验学院 | | | 陈梦娜 | 济宁医学院医学影像与检验学院 | | | 刘议咛 | 济宁医学院医学影像与检验学院 | | | 余青青 | 济宁医学院医学影像与检验学院 | | | 张会如* | 济宁医学院医学影像与检验学院 | 272067 |
|
| 摘要点击次数: 0 |
| 全文下载次数: 0 |
| 中文摘要: |
| 肝癌的传统影像学诊断通常依赖诊断医师的肉眼观察，所获信息大多具有主观性和局限性，使得早期精准诊断面临巨大挑战。影像组学通过高通量提取定量的特征信息，运用高维数据描绘医学图像，从而高效且准确识别病变特征。将影像组学高通量提取的大量图像数据与人工智能算法结合后建立模型，可进一步实现对数据库中最优选择的自动化筛选及其特征信息提取,并进行预测分析，从而构建精准化的诊疗体系，例如使腹腔镜解剖肝切除术（LAH）患者个性化定制手术方案及术中精准定位导航等成为可能。并且该模型具有协助临床决策、减少活检和手术侵入性检查开展次数等优势。目前，影像组学人工智能模型在肝癌方面的应用涵盖肿瘤病灶的筛查、诊断、病理分型分级、治疗、疗效评估及预测复发等诸多方面。该文综述了基于人工智能的超声、CT、MRI多领域影像组学在肝癌临床应用中的研究进展。 |
| 英文摘要: |
| The traditional imaging diagnosis of liver cancer usually relies on the visual observation of the diagnostician, and the information obtained is subjective and limited, which makes the early accurate diagnosis face great challenges. By extracting quantitative feature information with high throughput and using high-dimensional data to depict medical images, radiomics can identify pathological features efficiently and accurately. By combining image data extracted by radiomics with artificial intelligence algorithm, the model can be further realized to automatically screen the best selection in the database and extract the feature information, and perform predictive analysis. And then a precise diagnosis and treatment system can be built, for example, making it possible for laparoscopic anatomic hepatectomy (LAH) patients to customize surgical plans and accurate intraoperative positioning and navigation. Moreover, the model has the advantages of assisting clinical decision making and reducing the number of biopsies and invasive surgical examinations.At present, the application of radiomics artificial intelligence model in liver cancer covers the screening, diagnosis, treatment, efficacy evaluation and recurrence prediction of tumor lesions. This paper reviews the progress of artificial intelligence-based ultrasound, CT and MRI in the clinical application of liver cancer. |
|
View Fulltext
查看/发表评论 下载PDF阅读器 |
