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针对瘤的人工智能 [¹⁸F]FDG PET成像:进展和未来趋势 - 第二部分

Alireza Safarian¹, Seyed Ali Mirshahvalad², Abolfazl Farbod³

¹Division of Molecular Imaging & Theranostics, Department of Nuclear Medicine, University Hospital, Paracelsus Medical University, Salzburg, Austria; Rajaie Cardiovascular Medical and Research Center, Rajaie Cardiovascular Institute, Iran University of Medical Sciences, Tehran, Iran.

Seminars in nuclear medicine

|July 19, 2025

概括

人工智能 (AI) 增强了FDG PET/CT扫描用于各种瘤类型的癌症评估. 进一步的研究和标准化对于这些AI工具的广泛临床采用至关重要.

科学领域:

核医学和分子成像技术
人工智能在瘤学中的应用
射电学和机器学习应用程序

背景情况:

人工智能 (AI) 在[¹⁸F]FDG PET/CT成像中的整合正在推动瘤学评估.
本综述的第二部分涵盖了血液学,泌尿生殖系统,黑色素瘤,中枢神经系统瘤和儿科瘤学的AI创新.
人工智能为提高诊断准确度和个性化治疗策略提供了潜力.

研究的目的:

在各种恶性瘤中探索AI驱动的[¹⁸F]FDG PET/CT创新.
评估人工智能应用在改善诊断准确性,减少变异性和为临床决策提供信息方面.
评估AI在预测治疗反应和生存结果方面的作用.

主要方法:

审查人工智能应用程序,包括放射学和机器学习算法.
分析人工智能辅助的病变细分,特征提取和异质性分析.
评估AI在特定癌症类型和临床决策场景中的实用性.

主要成果:

人工智能在识别耐火性淋巴瘤,评估黑色素瘤伪进展和预测大脑转移方面表现出潜力.
人工智能辅助技术提高了对治疗反应和长期生存的预测.
目前的人工智能应用有希望,但在可复制性方面面临挑战.

结论:

在[¹⁸F]FDG PET/CT中整合人工智能为瘤学提供了重大前景.
协议和验证策略的变化阻碍了临床翻译.
在临床实践中,标准化和前性验证对于可复制和通用的人工智能工具至关重要.

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