肺癌风险的手术内活检成像
Shuhao Qian1, Lu Yang1, Jia Meng1
1State Key Laboratory of Extreme Photonics and Instrumentation, College of Optical Science and Engineering, International Research Center for Advanced Photonics, Zhejiang University, Hangzhou, Zhejiang, China.
Communications medicine
|February 6, 2026
概括
这项研究引入了一种新的多光子显微镜 (MPM) 方法,通过分析细胞外矩阵 (ECM) 改造来精确检测肺癌. 由人工智能驱动的成像提供高灵敏度和视觉线索,以改善外科活检和患者的治疗结果.
科学领域:
- 生物医学成像技术 生物医学成像技术
- 癌症的诊断 癌症的诊断
- 细胞外矩阵研究 细胞外矩阵研究
背景情况:
- 精确的肺瘤鉴定和边界确定对于手术切除至关重要,但与当前的活检技术具有挑战性.
- 瘤发生与细胞外基质 (ECM) 组件的重塑有关,特别是原和弹性纤维.
研究的目的:
- 开发一种定量多光子显微镜 (MPM) 成像方法,用于敏感和高效的肺癌检测.
- 描述ECM重塑,以改善在手术内活检期间的瘤识别和边界确定.
主要方法:
- 建立了一种定量多光子显微镜 (MPM) 成像技术,用于同时,无标签地获取原蛋白和弹性纤维图像.
- 开发了一种相似系数 (SC) 度量来量化纤维相互作用,以及使用无监督学习进行癌症风险评估的AI-ECM框架.
主要成果:
- 在ex vivo人类肺癌诊断中达到99.37%的灵敏度,准确识别瘤边界.
- 通过在人肺癌小鼠模型的体内成像来证明翻译潜力.
结论:
- 开发的AI-ECM框架为外科医生提供了可解释的视觉线索,使得活检和手术干预更精确.
- 这项技术有可能显著提高手术精度和肺癌治疗患者的治疗结果.
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