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在[¹⁸F]PSMA-1007 PET/CT中基于人工智能自动测量分裂功能

Kristian Valind^1,2,3, Johannes Ulén⁴, Anni Gålne^5,6

¹Department of Translational Medicine, Wallenberg Centre for Molecular Medicine, Lund University, Malmö, Sweden. kristian.valind@med.lu.se.

|June 15, 2025

概括

人工智能模型可以在PSMA PET扫描中自动细分脏,以测量分裂功能 (SRF). 这种人工智能工具提供了与手工方法相比较准确的测量,提高了脏成像的效率.

科学领域:

核医学是一种核医学.
放射性药物成像技术的成像技术
医疗成像中的人工智能

背景情况:

前列腺特异性膜抗原 (PSMA) 在前列腺癌中过度表达,也存在于脏近壁管道中.
目前正在探索PSMA PET成像用于功能评估.
从PSMA PET测量分裂功能 (SRF) 的手动细分是耗时且不切实际的.

研究的目的:

设计,训练和验证人工智能 (AI) 模型用于自动脏细分.
在[18F]PSMA-1007 PET/CT图像中使用人工智能模型测量SRF.
评估AI驱动的SRF测量的可行性和准确性.

主要方法:

开发了一个AI模型,用于在[18F]PSMA-1007 PET/CT图像中自动细分脏.
人工智能模型在135个PET/CT研究中接受了训练,并在40个独立研究中得到了验证.
人工智能模型对左功能百分比 (LRF%) 的测量与三个人类读者的测量进行了比较.

主要成果:

在40个测试研究中进行了人工智能驱动的细分和LRF%测量.
对LRF%的测量显示出与人类读者有很强的相关性 (斯皮尔曼系数0.98-0.99).
人工智能和人类测量之间的LRF%的最大差异为3个百分点,表明高度一致.

结论:

使用PSMA PET自动测量SRF是可行的AI.
这种人工智能工具可以有效地提供数据来评估功能障碍,特别是在为前列腺癌治疗的患者中.

关键词:

在这里,我们可以看到AIAIAI.在美国,CNN是CNN.在这里,PET是PET.在PSMA上,PSMA可以在PSMA上进行交易.功能功能功能专项融资基金 (SRF) 是一个专项融资基金.分段化分段化分段化分段化

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