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Radiology：对比增强CT图像深度学习系统在肝硬化分级的价值

2019-04-03 shaosai MedSci原创

对比增强CT深度学习肝硬化
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本研究旨在建立并验证CT图像深度学习系统（DLS）在肝硬化分级中的价值。

本研究旨在建立并验证CT图像深度学习系统（DLS）在肝硬化分级中的价值。

利用包括门静脉期CT图像的7461例病理证实为肝硬化患者的数据建立基于CT肝硬化分级的DLS。利用额外891例患者数据进行验证DLS的诊断能力。利用Logistic回归分析评价患者特征及CT技术对DLS分级准确性的影响。在421例患者的亚组中，利用ROC曲线下面积和Obuchowski指数比较DLS与放射科医生、转氨酶-血小板比例指数（APRI0）肝硬化-4指数对肝硬化分级的诊断能力。

结果为，在测试组，DLS的分级准确率为79.4% (707 of 891)，对诊断明显肝硬化(F2-4)、肝硬化晚期 (F3-4)、重度肝硬化(F4)的ROC曲线下面积分别为0.96、0.97、0.95。在多元分析中，仅有病理纤维化分级能够影响F1和F2 DLS的准确性(与F4比较，F1与F2的P值分别为.016 、.013)，而CT技术和肝脏基础病变并不能影响DLS分级诊断性。DLS(Obuchowski指数为0.94)要优于放射科医生的评价、APRI和肝硬化-4指数(Obuchowski指数范围为0.71-0.81； P ？ .001)。

本研究表明，CT图像深度学习系统能够准确对肝硬化进行分级。

原始出处：


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    2019-07-11 guguangxiang

    #深度学习系统#

    0

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    2019-07-23 bnurmamat

    #增强CT#

    0

  3. [GetPortalCommentsPageByObjectIdResponse(id=2009023, encodeId=e3b92009023eb, content=<a href='/topic/show?id=9034661260c' target=_blank style='color:#2F92EE;'>#深度学习系统#</a>, beContent=null, objectType=article, channel=null, level=null, likeNumber=66, replyNumber=0, topicName=null, topicId=null, topicList=[TopicDto(id=66126, encryptionId=9034661260c, topicName=深度学习系统)], attachment=null, authenticateStatus=null, createdAvatar=http://thirdwx.qlogo.cn/mmopen/vi_32/iaP1mV9qBwx5tE2F4xcG1r4x1PibWvluIFLB8VsViakqNMBia2Z0wFibVrYwDEILvHB1OomzzTAAGy5MVl5BrdEv9Bw/132, createdBy=e11f100, createdName=guguangxiang, createdTime=Thu Jul 11 07:59:00 CST 2019, time=2019-07-11, status=1, ipAttribution=), GetPortalCommentsPageByObjectIdResponse(id=1987057, encodeId=e8f7198e05787, content=<a href='/topic/show?id=a498422e7e6' target=_blank style='color:#2F92EE;'>#增强CT#</a>, beContent=null, objectType=article, channel=null, level=null, likeNumber=74, replyNumber=0, topicName=null, topicId=null, topicList=[TopicDto(id=42277, encryptionId=a498422e7e6, topicName=增强CT)], attachment=null, authenticateStatus=null, createdAvatar=, createdBy=fc0372, createdName=bnurmamat, createdTime=Tue Jul 23 23:59:00 CST 2019, time=2019-07-23, status=1, ipAttribution=), GetPortalCommentsPageByObjectIdResponse(id=1994277, encodeId=059819942e7b5, content=<a href='/topic/show?id=db8b46645ee' target=_blank style='color:#2F92EE;'>#对比增强CT#</a>, beContent=null, objectType=article, channel=null, level=null, likeNumber=56, replyNumber=0, topicName=null, topicId=null, topicList=[TopicDto(id=46645, encryptionId=db8b46645ee, topicName=对比增强CT)], attachment=null, authenticateStatus=null, createdAvatar=, createdBy=909c71, createdName=shijzhiewnjhch, createdTime=Sat Oct 12 04:59:00 CST 2019, time=2019-10-12, status=1, ipAttribution=), GetPortalCommentsPageByObjectIdResponse(id=364095, encodeId=1d893640958d, content=学习, beContent=null, objectType=article, channel=null, level=null, likeNumber=85, replyNumber=0, topicName=null, topicId=null, topicList=[], attachment=null, authenticateStatus=null, createdAvatar=https://wx.qlogo.cn/mmopen/vi_32/iaAVWEsIJUkA1ITy3uL0lhHUhyaJibWgFtH4KbJuaLbY2WUK33jgCFyoZ8Eqx7eE7hCuZhytc1C5GRrfjVXN8lYg/0, createdBy=fcb82149579, createdName=183****7028, createdTime=Thu Apr 04 07:20:51 CST 2019, time=2019-04-04, status=1, ipAttribution=), GetPortalCommentsPageByObjectIdResponse(id=1046387, encodeId=32ad104638e41, content=谢谢！最新的信息读起来就是收获大, beContent=null, objectType=article, channel=null, level=null, likeNumber=78, replyNumber=0, topicName=null, topicId=null, topicList=[], attachment=null, authenticateStatus=null, createdAvatar=null, createdBy=f0620, createdName=guging, createdTime=Thu Apr 04 00:59:00 CST 2019, time=2019-04-04, status=1, ipAttribution=)]
    2019-10-12 shijzhiewnjhch

    #对比增强CT#

    0

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    2019-04-04 183****7028

    学习

    0

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    2019-04-04 guging

    谢谢！最新的信息读起来就是收获大

    0

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