Ki-67作为甲状腺皮层癌转移的预测器:从回顾成像数据的人工智能见解
Andrew J Goulian1, David S Yee1,2
1College of Medicine, California Northstate University, Elk Grove, CA 95757, USA.
Journal of clinical medicine
|July 29, 2025
概括
基-67增殖指数预测了上腺皮层癌 (ACC) 的转移. 整合Ki-67与瘤大小和年龄的人工智能模型显著提高了ACC管理的预测准确性.
科学领域:
- 在瘤学瘤学.
- 放射学 放射学是一门学科.
- 人工智能的人工智能
背景情况:
- 皮上腺癌 (ACC) 是一种罕见的,具有不良预后的侵袭性癌症,特别是在转移性病例中.
- 基-67增殖指数是已知的瘤侵略性的标志物,但其在预测转移和指导管理方面的作用尚未完全理解.
- 需要个性化,最少侵入性的策略来管理ACC.
研究的目的:
- 在ACC诊断时评估Ki-67扩散指数对转移的预测值.
- 利用人工智能 (AI) 来改善ACC转移的预测.
- 为个性化和最少侵入性的ACC管理策略提供信息.
主要方法:
- 来自癌症成像档案 (上腺-ACC-Ki67-Seg数据集) 的53名ACC患者的回顾性分析.
- 从手术样本和手术前对比度增强CT扫描中评估Ki-67指数.
- 与Ki-67单独模型相比,开发带有和没有SMOTE的随机森林分类器来预测转移.
主要成果:
- 转移性ACC患者的Ki-67指数显著更高 (39.4%与21.6%,p <0.05).
- 基-67是后勤回归中转移的唯一显著预测因子 (OR = 1.06).
- 一个SMOTE增强的随机森林模型实现了0.994的AUC,显著超过仅Ki-67模型 (AUC = 0.637).
结论:
- 在ACC诊断时,Ki-67与转移显著相关,并且具有独立的预测价值.
- 将Ki-67与结合瘤大小和年龄的AI模型集成,大大提高了转移性预测的准确性.
- 人工智能辅助的风险分层和精确成像策略可以增强上腺癌护理.
关键词:
这就是Ki-67的原因.上皮层癌 (adrenocortical carcinoma) 是一种上皮层癌.人工智能的人工智能是人工智能.转移预测转移的预测微创手术是最少的侵入性手术.精确瘤学 精确瘤学无线电学 (radiomics) 是一种无线电学.随机的森林随机的森林风险分层的风险分层.更多相关视频
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