使用人工智能对乳腺癌瘤内部异质性的表征
Ayat G Lashen1,2, Noorul Wahab3, Michael Toss1
1Breast Cancer Research Unit, University of Nottingham, Nottingham NG7 2RD, UK.
Cancers
|November 27, 2024
概括
乳腺癌 (BC) 中的瘤内部异质性 (ITH) 是复杂的. 深度学习模型准确地评估了ITH,揭示它预测了瘤的攻击性行为和早期光BC患者的不良结果.
科学领域:
- 在瘤学瘤学.
- 计算病理学计算病理学
- 医疗成像医学成像
背景情况:
- 瘤内部异质性 (ITH) 是乳腺癌 (BC) 的一个关键特征,影响疾病进展,预后和治疗疗效.
- 由于其固有的复杂性,在BC中对ITH的准确表征仍然是一个重大挑战.
研究的目的:
- 利用深度学习 (DL) 技术对早期光线乳腺癌中ITH进行全面评估.
- 用先进的计算方法阐明ITH对瘤行为和患者结果的影响.
主要方法:
- 分析了2561例早期发光性BC病例的大队伍,使用整个幻灯片图像 (WSIs).
- 来自瘤和 stromal 组件的形态特征被注释,并开发了一个DL模型来量化异质性.
- 产生了整体异质性得分,并与临床病理特征和患者结局相关联.
主要成果:
- 量化了162个形态特征,显示出显著的特征间相关性.
- 高ITH显着与较大的瘤大小,差异化,高增殖,无特殊类型 (NST) 瘤和低雌激素受体 (ER) 表达相关.
- 高整体异质性得分独立预测患者的不良结果,并与瘤的攻击性行为有关.
结论:
- 深度学习模型提供了一种强大的方法,可以准确地解读乳腺癌中瘤内部异质性的复杂性.
- DL衍生异质度指标为预测早期光BC患者的结果提供了宝贵的补充信息.
相关概念视频
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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.
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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,...
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