通过变压器架构实现全面的多模式深度学习生存预测:在质母细胞瘤中的多中心研究
Ahmed Gomaa1,2,3, Yixing Huang1,2,3, Amr Hagag1,2
1Department of Radiation Oncology, University Hospital Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany.
Neuro-oncology advances
|August 19, 2024
概括
本研究引入了一个用于预测质母细胞瘤存活率的变压器模型,集成MR图像和临床数据. 该模型在多个数据集中显示了改进的准确性和通用性,优于现有方法.
科学领域:
- 人工智能的人工智能
- 医疗成像医学成像
- 在瘤学瘤学.
背景情况:
- 由于数据异质性,质母细胞瘤生存预测仍然具有挑战性.
- 整合各种数据源,如MRI图像,临床和分子病理学数据,对于提高预测准确性至关重要.
- 现有的模型往往在不同数据集和机构的概括性方面扎.
研究的目的:
- 开发和评估基于变压器的深度学习模型,用于预测质母细胞瘤存活率.
- 整合多式联运数据,包括MR图像和非成像数据,以提高预测性能.
- 评估模型在独立的多中心数据集中的通用性.
主要方法:
- 提出了一个基于变压器的非线性和非比例的生存预测模型.
- 自主监督学习被用来编码高维的MRI数据.
- 交叉注意力机制集成成像和非成像数据,在三个独立的测试集上使用时间依赖一致性指数 (Cdt) 进行评估.
主要成果:
- 变压器模型在整合成像和非成像数据方面取得了卓越的性能,超过了最先进的3D-CNN模型 (例如,UCSF-PDGM测试组:成像Cdt 0.578,多式联络Cdt 0.672).
- 在三个独立的多中心测试集中观察到一致的性能 (Cdt值:0.707,0.672,0.618).
- 该模型显示了有利和不利生存率的患者之间存在显著的歧视 (所有数据集的逻辑等级P<0.05).
结论:
- 拟议的变压器模型有效地整合了来自不同数据模式的互补信息,从而改善了质母细胞瘤生存预测.
- 该模型在多个机构的一致表现验证了它的通用性.
- 这种方法比目前最先进的质母细胞瘤预后方法提供了有前途的进步.
相关概念视频
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Adaptive Mechanisms in Cancer Cells
Cancer cells accumulate genetic changes at an abnormally rapid rate due to the defects in the DNA repair mechanisms. From an evolutionary perspective, such genetic instability is advantageous for cancer development. Mutant cell lines accumulate a series of beneficial mutations that contribute to their progression into cancer.
Some of the advantages that cancer cells have on normal cells include - enhanced ability to divide without terminally differentiating, induce new blood vessel formation,...
Some of the advantages that cancer cells have on normal cells include - enhanced ability to divide without terminally differentiating, induce new blood vessel formation,...
Cancer Stem Cells and Tumor Maintenance
Early diagnosis and treatment can often cure cancer. However, even with treatment, residual cells called cancer stem cells (CSC) might remain, often causing tumor recurrence. These cancer stem cells possess the potential for self-renewal and multi-lineage differentiation and are often responsible for the therapeutic resistance displayed in most cancers.
Cancer stem cells are thought to originate from tissue-specific normal stem cells or progenitor cells. The normal stem cells usually reside in...
Cancer stem cells are thought to originate from tissue-specific normal stem cells or progenitor cells. The normal stem cells usually reside in...
Mouse Models of Cancer Study
Mice have long served as models for studying human biology and pathology because of their phylogenetic and physiological similarity with humans. They are also easy to maintain and breed in the laboratory, and hence, many inbred strains are now available for research. Studies on mice have contributed immeasurably to our understanding of cancer biology.
The development of transgenic, knockout, and knock-in mice has led to an exponential increase in their use as model organisms in research,...
The development of transgenic, knockout, and knock-in mice has led to an exponential increase in their use as model organisms in research,...


