Samantha J Smith, Sally Anne Bradley, Katie Walker-Stabeler, Michael Siafakas
{"title":"对人工智能召回和未召回的筛查出的癌症进行前瞻性分析。","authors":"Samantha J Smith, Sally Anne Bradley, Katie Walker-Stabeler, Michael Siafakas","doi":"10.1093/jbi/wbae027","DOIUrl":null,"url":null,"abstract":"<p><strong>Objective: </strong>The use of artificial intelligence has potential in assisting many aspects of imaging interpretation. We undertook a prospective service evaluation from March to October 2022 of Mammography Intelligent Assessment (MIA) operating \"silently\" within our Breast Screening Service, with a view to establishing its performance in the local population and setting. This evaluation addressed the performance of standalone MIA vs conventional double human reading of mammograms.</p><p><strong>Methods: </strong>MIA analyzed 8779 screening events over an 8-month period. The MIA outcome did not influence the decisions made on the clinical pathway. Cases were reviewed approximately 6 weeks after the screen reading decision when human reading and/or MIA indicated a recall.</p><p><strong>Results: </strong>There were 146 women with positive concordance between human reading and MIA (human reader and MIA recalled) in whom 58 breast cancers were detected. There were 270 women with negative discordance (MIA no recall, human reader recall) for whom 19 breast cancers and 1 breast lymphoma were detected, with 1 cancer being an incidental finding at assessment. Six hundred and four women had positive discordance (MIA recall, human reader no recall) in whom 2 breast cancers were detected at review. The breast cancers demonstrated a wide spectrum of mammographic features, sites, sizes, and pathologies, with no statistically significant difference in features between the negative discordant and positive concordant cases.</p><p><strong>Conclusion: </strong>Of 79 breast cancers identified by human readers, 18 were not identified by MIA, and these had no specific features or site to suggest a systematic error for MIA analysis of 2D screening mammograms.</p>","PeriodicalId":43134,"journal":{"name":"Journal of Breast Imaging","volume":null,"pages":null},"PeriodicalIF":2.0000,"publicationDate":"2024-07-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A Prospective Analysis of Screen-Detected Cancers Recalled and Not Recalled by Artificial Intelligence.\",\"authors\":\"Samantha J Smith, Sally Anne Bradley, Katie Walker-Stabeler, Michael Siafakas\",\"doi\":\"10.1093/jbi/wbae027\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Objective: </strong>The use of artificial intelligence has potential in assisting many aspects of imaging interpretation. We undertook a prospective service evaluation from March to October 2022 of Mammography Intelligent Assessment (MIA) operating \\\"silently\\\" within our Breast Screening Service, with a view to establishing its performance in the local population and setting. This evaluation addressed the performance of standalone MIA vs conventional double human reading of mammograms.</p><p><strong>Methods: </strong>MIA analyzed 8779 screening events over an 8-month period. The MIA outcome did not influence the decisions made on the clinical pathway. Cases were reviewed approximately 6 weeks after the screen reading decision when human reading and/or MIA indicated a recall.</p><p><strong>Results: </strong>There were 146 women with positive concordance between human reading and MIA (human reader and MIA recalled) in whom 58 breast cancers were detected. There were 270 women with negative discordance (MIA no recall, human reader recall) for whom 19 breast cancers and 1 breast lymphoma were detected, with 1 cancer being an incidental finding at assessment. Six hundred and four women had positive discordance (MIA recall, human reader no recall) in whom 2 breast cancers were detected at review. The breast cancers demonstrated a wide spectrum of mammographic features, sites, sizes, and pathologies, with no statistically significant difference in features between the negative discordant and positive concordant cases.</p><p><strong>Conclusion: </strong>Of 79 breast cancers identified by human readers, 18 were not identified by MIA, and these had no specific features or site to suggest a systematic error for MIA analysis of 2D screening mammograms.</p>\",\"PeriodicalId\":43134,\"journal\":{\"name\":\"Journal of Breast Imaging\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":2.0000,\"publicationDate\":\"2024-07-30\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Breast Imaging\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1093/jbi/wbae027\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"ONCOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Breast Imaging","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1093/jbi/wbae027","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"ONCOLOGY","Score":null,"Total":0}
引用次数: 0
摘要
目的:人工智能的使用在协助影像解读的许多方面都具有潜力。从 2022 年 3 月到 10 月,我们对乳腺筛查服务中 "静默 "运行的乳腺智能评估(MIA)进行了前瞻性服务评估,以确定其在当地人群和环境中的表现。这项评估针对独立的 MIA 与传统的双人乳房 X 光检查读片的性能进行了比较:方法:MIA 对 8 个月内的 8779 例筛查事件进行了分析。MIA 的结果不会影响临床路径的决策。当人工读片和/或 MIA 显示需要召回时,在做出筛查决定约 6 周后对病例进行复查:结果:146 名妇女的人工读片与 MIA 呈阳性一致(人工读片和 MIA 均显示召回),其中有 58 例检测出乳腺癌。有 270 名妇女的不一致性为阴性(MIA 不显示召回,人类阅读器显示召回),其中检测出 19 例乳腺癌和 1 例乳腺淋巴瘤,1 例癌症是评估时偶然发现的。有 64 名妇女的不一致性为阳性(MIA 可回忆,人类读者不可回忆),在复查时发现了 2 例乳腺癌。这些乳腺癌在乳腺 X 线摄影特征、部位、大小和病理方面表现出广泛的多样性,阴性不一致和阳性一致病例在特征方面没有显著的统计学差异:结论:在人类阅读器识别出的 79 例乳腺癌中,有 18 例未被 MIA 识别,这些乳腺癌没有特定的特征或部位,表明对二维筛查乳房 X 光片进行 MIA 分析存在系统误差。
A Prospective Analysis of Screen-Detected Cancers Recalled and Not Recalled by Artificial Intelligence.
Objective: The use of artificial intelligence has potential in assisting many aspects of imaging interpretation. We undertook a prospective service evaluation from March to October 2022 of Mammography Intelligent Assessment (MIA) operating "silently" within our Breast Screening Service, with a view to establishing its performance in the local population and setting. This evaluation addressed the performance of standalone MIA vs conventional double human reading of mammograms.
Methods: MIA analyzed 8779 screening events over an 8-month period. The MIA outcome did not influence the decisions made on the clinical pathway. Cases were reviewed approximately 6 weeks after the screen reading decision when human reading and/or MIA indicated a recall.
Results: There were 146 women with positive concordance between human reading and MIA (human reader and MIA recalled) in whom 58 breast cancers were detected. There were 270 women with negative discordance (MIA no recall, human reader recall) for whom 19 breast cancers and 1 breast lymphoma were detected, with 1 cancer being an incidental finding at assessment. Six hundred and four women had positive discordance (MIA recall, human reader no recall) in whom 2 breast cancers were detected at review. The breast cancers demonstrated a wide spectrum of mammographic features, sites, sizes, and pathologies, with no statistically significant difference in features between the negative discordant and positive concordant cases.
Conclusion: Of 79 breast cancers identified by human readers, 18 were not identified by MIA, and these had no specific features or site to suggest a systematic error for MIA analysis of 2D screening mammograms.