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首页> 外文会议>International Workshop on Breast Imaging >Personalised breast cancer screening with selective addition of digital breast tomosynthesis through artificial intelligence
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Personalised breast cancer screening with selective addition of digital breast tomosynthesis through artificial intelligence

机译：通过人工智能选择性添加数字化乳房断层合成进行个性化乳腺癌筛查

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Breast cancer screening is predominantly performed using digital mammography (DM), but higher sensitivity has been demonstrated with digital breast tomosynthesis (DBT). A partial DBT screening in selected groups with a clear benefit from DBT might be more feasible than a full implementation, and using artificial intelligence (AI) to select women for DBT might be a possibility.This study used data from Malmo Breast Tomosynthesis Screening Trial, where all women prospectively were examined with separately read DM and DBT. We retrospectively analysed DM examinations (n= 14768) with a breast cancer detection software and used the provided risk score (1-10) for risk stratification. We tested how different score thresholds for adding DBT to an initial DM affects the number of detected cancers, additional DBT examinations needed, detection rate, and false positives.If using a threshold of 9.0, 25 (26 %) more cancers would be detected compared to using DM alone. Of the 41 cancers only detected on DBT, 61 % would be detected, with only 1797 (12 %) of the women examined with both DM and DBT. The detection rate for the added DBT would be 14/1000 women, while the false positive recalls would be increased with 58 (21 %).Using DBT only for selected high gain cases could be an alternative to a complete DBT screening. AI could be used for analysing DM to identify high gain cases, where DBT can be added during the same visit. There might be logistical challenges and further studies in a prospective setting are necessary.
机译：乳腺癌筛查主要使用数字乳腺X线摄影术（DM）进行，但数字乳腺断层合成（DBT）已证明具有更高的敏感性。在特定人群中进行DBT筛查并从DBT中获得明显收益可能比完全实施更可行，并且可能使用人工智能（AI）选择女性进行DBT。这项研究使用了来自Malmo乳房断层合成筛查试验的数据，分别使用DM和DBT对所有女性进行了前瞻性检查。我们使用乳腺癌检测软件对DM检查（n = 14768）进行了回顾性分析，并使用提供的风险评分（1-10）进行了风险分层。我们测试了将DBT添加到初始DM中的不同分数阈值如何影响检测到的癌症数量，需要进行额外的DBT检查，检测率和假阳性率。如果使用9.0阈值，则可以检测到更多25种癌症（26％）单独使用DM。在仅通过DBT检出的41种癌症中，将检出61％，只有DM和DBT检出的女性只有1797名（12％）。增加的DBT的检出率将是14/1000名女性，而假阳性召回率将增加58（21％）。仅对选定的高收益病例使用DBT可以代替完整的DBT筛查。 AI可以用于分析DM来识别高增益情况，在同一次访问中可以添加DBT。可能会遇到后勤方面的挑战，因此有必要在前瞻性背景下进行进一步研究。

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