Article(id=1320381073465397937, tenantId=1146029695717560320, journalId=1319373289681944729, issueId=1320381045866873144, articleNumber=null, orderNo=null, doi=10.11876/mimt202601015, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=null, receivedDateStr=null, revisedDate=null, revisedDateStr=null, acceptedDate=null, acceptedDateStr=null, onlineDate=1792732979408, onlineDateStr=2026-10-23, pubDate=1770652800000, pubDateStr=2026-02-10, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1792732979408, onlineIssueDateStr=2026-10-23, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1792732979408, creator=13701087609, updateTime=1792732979408, updator=13701087609, issue=Issue{id=1320381045866873144, tenantId=1146029695717560320, journalId=1319373289681944729, year='2026', volume='32', issue='1', pageStart='1', pageEnd='106', issueExtLink='null', onlineDate='null', pubDate='1770652800000', pubDateStr='2026-02-10', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=null, createTime=1792732972828, creator='13701087609', updateTime=1792746352003, updator='13701087609', preIssue=null, nextIssue=null, articleTotal=null, ext={EN=IssueExt(id=1320437162382840024, tenantId=1146029695717560320, journalId=1319373289681944729, issueId=1320381045866873144, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1320437162382840025, tenantId=1146029695717560320, journalId=1319373289681944729, issueId=1320381045866873144, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null, downloadFileDto=null}, startPage=97, endPage=101, ext={EN=ArticleExt(id=1320381073612198578, articleId=1320381073465397937, tenantId=1146029695717560320, journalId=1319373289681944729, language=EN, title=Application value of low-dose CT scan combined with AI analysis in screening and tracking of pulmonary nodules, columnId=null, journalTitle=Modern Instruments & Medical Treatment, columnName=null, runingTitle=null, highlight=null, articleAbstract=
Objective To evaluate the value of low-dose CT (LDCT) scan combined with artificial intelligence (AI) analysis in the screening and follow-up of pulmonary nodules.
Methods A total of 160 patients with pulmonary nodules who underwent LDCT screening and completed at least one follow-up between January 2023 and June 2025 were selected. All of them underwent LDCT examination and the lung nodule artificial intelligence imaging-assisted diagnosis system was used. The pathological results were used as the gold standard to compare the detection rates of different diameter nodules, the tracking success rates of the same nodules, and the time spent on reading films between AI reading and manual reading.
Results AI reading showed higher detection rates for nodule diameter <3 mm and [3, 5) mm than manual reading (P<0.05). During follow-up, AI achieved higher tracking success rates of the same nodule (P<0.05). AI also required markedly less reading time (P<0.001).
Conclusion The LDCT scan combined with AI analysis has significant application value in the diagnosis of pulmonary nodules, especially in the identification of changes in small nodules before and after re-examination, it demonstrates high sensitivity and efficiency. It has unique advantages in saving time and standardizing the diagnostic process, and is worthy of clinical promotion.
, authors=Maohua Huang, Xiao Huang, Maoyun Du, authorsList=Maohua Huang, Xiao Huang, Maoyun Du, authorCompany=null, correspAuthors=null, authorNote=null, correspAuthorsNote=null, copyrightStatement=
All copyrights in 2026 belong to the sponsor of the journal.Not content published by the journal may be reproduced or abridged without authorization., copyrightOwner=null, extLink=null, articleAbsUrl=null, sourceXml=null, magXml=null, pdfUrl=null, pdf=null, pdfFileSize=null, pdfExtLink=null, richHtmlUrl=null, mobilePdfUrl=null, reviewReport=null, pdfFirstPage=null, abstractGraph=null, abstractGraphContent=null, abstractVideo=null, citation=null, cebUrl=null, magXmlContent=null, mapNumber=null, fund=null), CN=ArticleExt(id=1320381073859662515, articleId=1320381073465397937, tenantId=1146029695717560320, journalId=1319373289681944729, language=CN, title=低剂量CT扫描联合AI分析在肺结节筛查与追踪中的应用价值, columnId=1320381058969883180, journalTitle=现代仪器与医疗, columnName=临床研究, runingTitle=null, highlight=null, articleAbstract=
目的 探讨低剂量螺旋CT（low-dose computed tomography，LDCT）扫描联合人工智能（artificial intelligence，AI）分析在肺结节首次筛查及随访复查中的应用价值。
方法 选取2023年1月至2025年6月期间在我院接受LDCT筛查并至少完成1次随访复查的160例肺结节患者作为研究对象，均接受LDCT检查，并采用肺结节人工智能影像辅助诊断系统，将病理结果作为金标准，比较AI阅片与人工阅片对不同直径结节的检出率、同一结节追踪成功率和阅片耗时。
结果 AI阅片对直径<3 mm和3 mm≤直径<5 mm的微小结节的检出率高于人工阅片（P<0.05）；在随访复查阶段，AI阅片对同一结节的追踪成功率高于人工阅片（P<0.05）；AI阅片平均耗时显著短于人工阅片（P<0.001）。
结论 LDCT扫描技术联合AI智能诊断分析在肺结节诊断中具有明显的应用价值，尤其在微小结节复查前后变化识别方面展现出高灵敏度和高效率，在节省时间、标准化诊断流程上具有独特优势，值得临床推广。
, authors=黄茂华, 黄晓, 杜茂云, authorsList=黄茂华, 黄晓, 杜茂云, authorCompany=null, correspAuthors=null, authorNote=
黄茂华，男，本科，副主任技师，研究方向：医学影像技术应用及质量控制
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2026年版权归本刊主办单位所有未经本刊书面许可, 不得转载、摘编本刊所有文章内容。, copyrightOwner=中国科学器材公司, extLink=null, articleAbsUrl=null, sourceXml=haNMx+9IRSoQICgpFrak7A==, magXml=LhjiLMHO0eSfeHBCTNlByw==, pdfUrl=null, pdf=yFCDxnYlIz86zXHhuqu+wQ==, pdfFileSize=1607621, pdfExtLink=null, richHtmlUrl=null, mobilePdfUrl=null, reviewReport=null, pdfFirstPage=null, abstractGraph=null, abstractGraphContent=null, abstractVideo=null, citation=null, cebUrl=null, magXmlContent=ANYCFoovf6h5aOATjBsTag==, mapNumber=null, fund=null)}, authors=[Author(id=1320381074174235320, tenantId=1146029695717560320, journalId=1319373289681944729, articleId=1320381073465397937, orderNo=0, firstName=null, middleName=null, lastName=null, nameCn=null, orcid=null, stid=null, country=null, authorPic=null, dead=0, email=null, emailSecond=null, emailThird=null, correspondingAuthor=0, authorType=1, ext={EN=AuthorExt(id=1320381074283287226, tenantId=1146029695717560320, journalId=1319373289681944729, articleId=1320381073465397937, authorId=1320381074174235320, language=EN, stringName=Maohua Huang, firstName=Maohua, middleName=null, lastName=Huang, prefix=null, suffix=null, authorComment=null, nameInitials=null, affiliation=null, department=null, xref=null, address=Radiology Department, Baise People's Hospital, Baise 533000, China, bio=null, bioImg=null, bioContent=null, aboutCorrespAuthor=null), CN=AuthorExt(id=1320381074358784699, tenantId=1146029695717560320, journalId=1319373289681944729, articleId=1320381073465397937, authorId=1320381074174235320, language=CN, stringName=黄茂华, firstName=null, middleName=null, lastName=null, prefix=null, suffix=null, authorComment=null, nameInitials=null, affiliation=null, department=null, xref=null, address=广西百色市人民医院放射科，百色 533000, bio={"content":"
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