乳腺癌的呼吸痕迹:评估BI-RADS的非侵入性方法 4在初步研究中的风险分层
Ashok Prabhu Masilamani1, Jayden K Hooper1, Md Hafizur Rahman1
1Noze, 4920 Pl. Olivia, Saint-Laurent, QC H4R 2Z8, Canada.
Cancers
|January 28, 2026
概括
呼气分析显示,在BI-RADS 4患者中识别乳腺癌是有前途的,这可能会减少不必要的活检. 这种非侵入性方法实现了高精度,为诊断决策提供了一个新的工具.
科学领域:
- 在瘤学瘤学.
- 医学诊断 医学诊断 医学诊断
- 生物技术是生物技术.
背景情况:
- 乳腺癌是妇女死亡的主要原因,需要准确的早期检测方法.
- 乳腺成像报告和数据系统 (BI-RADS) 分类有助于报告,但BI-RADS 4由于恶性瘤风险范围广泛 (2-95%) 造成诊断挑战.
- 许多BI-RADS 4发现的患者进行了不必要的活检,增加了医疗保健成本和患者负担.
研究的目的:
- 在BI-RADS 4分类的患者中,评估呼气分析在区分恶性和良性乳腺病变方面的有效性.
- 评估呼吸分析作为一种非侵入性工具的潜力,以减少不必要的侵入性手术.
主要方法:
- 从85名参与者 (BI-RADS 3-5) 使用电子鼻子 (eNose) 气息测试仪收集了呼吸痕迹.
- 一个自编码模型将呼吸数据与BI-RADS评分集成在一起,用于恶性瘤预测.
- 模型性能通过交叉验证得到验证,优先考虑高灵敏度以最大限度地减少虚假阴性.
主要成果:
- 该研究分析了68例良性和17例恶性BI-RADS 4病例的呼吸样本.
- 呼吸分析模型显示平均灵敏度为88%,特异性为75%,负预测值 (NPV) 为97%.
- 在BI-RADS 4子类别中,表现保持一致,高风险组的敏感性显著.
结论:
- 呼气分析可以有效地区分 BI-RADS 4 患者的恶性和良性发现.
- 高的NPV表明这种方法可以作为一种可靠的非侵入性工具来排除恶性瘤,减少不必要的活检.
- 建议进行进一步的多中心研究,以验证这些发现并探索临床实施.
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