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Nature:人工智能大大提高肠镜的结直肠病变检出率

2021-05-23 MedSci原创 MedSci原创

新的算法改进了从内窥镜视频片段中识别癌症的能力。

在结肠镜检查后死于结直肠癌的人中,约有60%是因为筛查过程中遗漏了病变。为此,两名日本研究人员花了8年时间专门开发人工智能(AI)技术,以帮助内窥镜医生。

昭和大学北横滨医院消化疾病中心主任、该项目的联合负责人工藤信荣认为大约25%的结直肠肿瘤被通过微型摄像机寻找它们的专家忽视了。然而,如果输入正确的数据,深度学习算法可以提高人类的检测能力。自2013年以来,工藤的团队一直在与名古屋大学信息技术中心主任森健作领导的团队合作,开发结肠镜人工智能技术。

该小组设计了一种称为EndoBRAIN- eye的计算机辅助检测(CADe)系统,以减少被忽视的结直肠肿瘤的数量,以及一种称为EndoBRAIN的计算机辅助鉴定(CADx)工具,它提供了更准确的类型评估。

这两个系统的基本人工智能技术是相同的。CADe将神经网络应用于视频框结肠息肉(异常肿块)的特征提取。CADx使用同样的特征提取过程来帮助对病变进行分类,以便在实验室中进行更详细的病理诊断

这两种技术都为检测带来了显著的改进。在一个包含日本五个学术中心数据的大型公开结肠镜检查数据库中进行测试时,CADe系统以98%的敏感性和93.7%的特异性识别结直肠病变。腺瘤检出率(ADR)是结肠镜检查的一项已建立的质量指标,研究人员及其合作者最近发表的一项关于CADe使用的meta分析显示,与标准人体筛查相比,ADR增加了50%;ADR每增加1%,结直肠癌相关死亡则减少3%

细微但重要的癌症

在结肠镜检查中很容易漏诊扁平或凹陷(相当扁平)的肿瘤(称为非息肉样病变)。征象很微小,可能仅是粘膜颜色的轻微变化和上皮下毛细血管的偏移。工藤解释说,不管它们的大小如何,凹陷型病变在本质上也更有可能具有侵袭性。

凹陷型和横向扩散肿瘤通常是结肠镜检查中最容易被忽视的结直肠病变,它具有恶性潜力。2017年,早期版本的CADx在诊断侵袭性结直肠癌方面准确率高达94%。如果与超放大观察结合使用,CADx也被证明在体内侵袭性癌症识别中具有特别强的能力。超放大结肠镜通过可视化体内肿瘤表面的细胞核,可以更容易地描述肿瘤的特征。窄波段成像,其中特定的蓝色和绿色波长用于增强微血管细节,亚甲蓝染色,这有助于可视化肿瘤的细胞核,也提高了在超放大内窥镜检查中的诊断精度。超放大图像和染色镜技术还有助于人工智能区分肿瘤性和非肿瘤性息肉,以及大规模侵袭性和其他肿瘤性病变。因此,人工智能,结合放大和染色,可以使内窥镜医生在现场预测病变病理。

(左图)人工智能帮助检测肿瘤,(右图)染色内窥镜显示肿瘤。

降低成本

人工智能提供的额外速度和准确性将降低活检和重复结肠镜检查的成本、时间和风险。精确的诊断也将减少多余治疗。

工藤等人的研究表明,在内窥镜中实时使用CADx可以满足小型、非肿瘤性直肠乙状息肉的诊断。2020年进行的一项研究发现,CADx可能会将结肠镜相关成本降低7 - 20%

当屏幕上出现疑似结肠病变时,实时人工智能系统应该很快就能立即通知内窥镜医生,这将为观察、切除或活检提供更多时间。另外,该研究小组还发现通过使用实时三维重建技术,可以减少结肠镜检查中的盲点,从而更好地监测难以可视化的区域。

原文出处

https://www.nature.com/articles/d42473-020-00551-9

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    2021-07-09 liye789132251
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    2021-05-25 zhouqu_8
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    2021-05-23 wxl882001

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人工智能、5G、物联网、可穿戴设备、AR、云计算、大数据、精准医疗、AR/VR、3D打印、虚拟现实等诸多新兴技术与医疗健康深度融合,带来了整个医疗生态和效率变革。

胃癌有无转移?影像检查+人工智能可准确预测,避免“白挨一刀”

5月14——15日,2021年中国研究型医院学会数字智能化外科专业委员会学术年会暨第二届国际数字智能化诊疗技术大会在广州召开。中国科学院院士刘允怡、陈孝平及来自国内外的80余位

Radiology:人工智能,实现脑转移瘤的“一站式”检测

脑转移发生在约20%-40%的癌症患者中,且由于治疗手段的不断进步,癌症患者的存活期明显延长,因此发病率可能进一步上升。

飞利浦亮相2021春季CMEF,展现“升级版”整体解决方案

随着城市化和老龄化的进程,冠心病患病率和死亡率逐年升高,已成为重大公共卫生问题

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