提高甲状腺结节恶性瘤预测:整合光声成像衍生的SO2与临床和超声数据
Shuzhen Tang1, Zhibin Huang1, Jing Chen1
1Department of Ultrasound, The Second Clinical Medical College, Jinan University (Shenzhen People's Hospital), No. 1017, Dongmen North Road, Luohu District, Shenzhen 518020, China.
Postgraduate medical journal
|May 30, 2025
概括
光声成像 (PAI) 为诊断甲状腺结节提供了一种定量,非侵入性的方法. 将PAI与临床和超声波数据相结合,可显著提高预测恶性瘤的准确性.
科学领域:
- 医疗成像医学成像
- 在瘤学瘤学.
- 诊断技术 诊断技术的使用
背景情况:
- 目前的甲状腺结节诊断依赖于主观评估,缺乏定量准确性.
- 光声成像 (PAI) 显示了客观甲状腺结节评估的潜力.
研究的目的:
- 评估PAI在区分良性与恶性甲状腺结节的诊断准确性.
- 将PAI与超声波和临床数据相结合,以提高恶性瘤预测.
主要方法:
- 分析了407个甲状腺结节,使用双波长PAI测量氧和 (SO2).
- 开发了三种预测模型,包括临床,超声波和PAI衍生的SO2因素.
- 使用曲线下的面积 (AUC) 和DeLong测试评估诊断性能.
主要成果:
- 与良性相比,恶性结节的SO2值明显较低 (65.08比77.25,P<.01).
- 综合模型 (Mod-3) 整合了PAI衍生的SO2在测试队列中实现了最高的AUC (0.974),超过了只有临床 (0.696) 或临床+超声数据 (0.947) 的模型.
结论:
- 由PAI衍生的SO2为甲状腺结节诊断提供了量化,非侵入性的指标.
- 将PAI与临床和超声数据相结合,可显著提高甲状腺结节恶性瘤的诊断准确度.
- 这种综合方法支持个性化的患者管理策略.
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