Ricardo E Gonzalez Valenzuela, Pascal Mettes, Bruno G Loos, Henk Marquering, Erwin Berkhout
{"title":"增强射线照片中的早期近端龋注释:引入微计算机断层扫描(ACTA-DIRECT)射线早期龋诊断洞察数据集。","authors":"Ricardo E Gonzalez Valenzuela, Pascal Mettes, Bruno G Loos, Henk Marquering, Erwin Berkhout","doi":"10.1186/s12903-024-05076-x","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>Proximal caries datasets for training artificial intelligence (AI) algorithms commonly include clinician-annotated radiographs. These conventional annotations are susceptible to observer variability, and early caries may be missed. Micro-computed tomography (CT), while not feasible in clinical applications, offers a more accurate imaging modality to support the creation of a reference-standard dataset for caries annotations. Herein, we present the Academic Center for Dentistry Amsterdam-Diagnostic Insights for Radiographic Early-caries with micro-CT (ACTA-DIRECT) dataset, which is the first dataset pairing dental radiographs and micro-CT scans to enable higher-quality annotations.</p><p><strong>Methods: </strong>The ACTA-DIRECT dataset encompasses 179 paired micro-CT scans and radiographs of early proximal carious teeth, along with three types of annotations: conventional annotations on radiographs, micro-CT-assisted annotations on radiographs, and micro-CT annotations (reference standard). Three dentists independently annotated proximal caries on radiographs, both with and without micro-CT assistance, enabling determinations of interobserver agreement and diagnostic accuracy. To establish a reference standard, one dental radiologist annotated all caries on the related micro-CT scans.</p><p><strong>Results: </strong>Micro-CT support improved interobserver agreement (Cohen's Kappa), averaging 0.64 (95% confidence interval [CI]: 0.59-0.68) versus 0.46 (95% CI: 0.44-0.48) in its absence. Likewise, average sensitivity and specificity increased from 42% (95% CI: 34-51%) to 63% (95% CI: 54-71%) and from 92% (95% CI: 88-95%) to 95% (95% CI: 92-97%), respectively.</p><p><strong>Conclusion: </strong>The ACTA-DIRECT dataset offers high-quality images and annotations to support AI-based early caries diagnostics for training and validation. This study underscores the benefits of incorporating micro-CT scans in lesion assessments, providing enhanced precision and reliability.</p>","PeriodicalId":9072,"journal":{"name":"BMC Oral Health","volume":"24 1","pages":"1325"},"PeriodicalIF":2.6000,"publicationDate":"2024-10-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11526566/pdf/","citationCount":"0","resultStr":"{\"title\":\"Enhancement of early proximal caries annotations in radiographs: introducing the Diagnostic Insights for Radiographic Early-caries with micro-CT (ACTA-DIRECT) dataset.\",\"authors\":\"Ricardo E Gonzalez Valenzuela, Pascal Mettes, Bruno G Loos, Henk Marquering, Erwin Berkhout\",\"doi\":\"10.1186/s12903-024-05076-x\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Background: </strong>Proximal caries datasets for training artificial intelligence (AI) algorithms commonly include clinician-annotated radiographs. These conventional annotations are susceptible to observer variability, and early caries may be missed. Micro-computed tomography (CT), while not feasible in clinical applications, offers a more accurate imaging modality to support the creation of a reference-standard dataset for caries annotations. Herein, we present the Academic Center for Dentistry Amsterdam-Diagnostic Insights for Radiographic Early-caries with micro-CT (ACTA-DIRECT) dataset, which is the first dataset pairing dental radiographs and micro-CT scans to enable higher-quality annotations.</p><p><strong>Methods: </strong>The ACTA-DIRECT dataset encompasses 179 paired micro-CT scans and radiographs of early proximal carious teeth, along with three types of annotations: conventional annotations on radiographs, micro-CT-assisted annotations on radiographs, and micro-CT annotations (reference standard). Three dentists independently annotated proximal caries on radiographs, both with and without micro-CT assistance, enabling determinations of interobserver agreement and diagnostic accuracy. To establish a reference standard, one dental radiologist annotated all caries on the related micro-CT scans.</p><p><strong>Results: </strong>Micro-CT support improved interobserver agreement (Cohen's Kappa), averaging 0.64 (95% confidence interval [CI]: 0.59-0.68) versus 0.46 (95% CI: 0.44-0.48) in its absence. Likewise, average sensitivity and specificity increased from 42% (95% CI: 34-51%) to 63% (95% CI: 54-71%) and from 92% (95% CI: 88-95%) to 95% (95% CI: 92-97%), respectively.</p><p><strong>Conclusion: </strong>The ACTA-DIRECT dataset offers high-quality images and annotations to support AI-based early caries diagnostics for training and validation. This study underscores the benefits of incorporating micro-CT scans in lesion assessments, providing enhanced precision and reliability.</p>\",\"PeriodicalId\":9072,\"journal\":{\"name\":\"BMC Oral Health\",\"volume\":\"24 1\",\"pages\":\"1325\"},\"PeriodicalIF\":2.6000,\"publicationDate\":\"2024-10-30\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11526566/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"BMC Oral Health\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1186/s12903-024-05076-x\",\"RegionNum\":2,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"DENTISTRY, ORAL SURGERY & MEDICINE\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"BMC Oral Health","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1186/s12903-024-05076-x","RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"DENTISTRY, ORAL SURGERY & MEDICINE","Score":null,"Total":0}
Enhancement of early proximal caries annotations in radiographs: introducing the Diagnostic Insights for Radiographic Early-caries with micro-CT (ACTA-DIRECT) dataset.
Background: Proximal caries datasets for training artificial intelligence (AI) algorithms commonly include clinician-annotated radiographs. These conventional annotations are susceptible to observer variability, and early caries may be missed. Micro-computed tomography (CT), while not feasible in clinical applications, offers a more accurate imaging modality to support the creation of a reference-standard dataset for caries annotations. Herein, we present the Academic Center for Dentistry Amsterdam-Diagnostic Insights for Radiographic Early-caries with micro-CT (ACTA-DIRECT) dataset, which is the first dataset pairing dental radiographs and micro-CT scans to enable higher-quality annotations.
Methods: The ACTA-DIRECT dataset encompasses 179 paired micro-CT scans and radiographs of early proximal carious teeth, along with three types of annotations: conventional annotations on radiographs, micro-CT-assisted annotations on radiographs, and micro-CT annotations (reference standard). Three dentists independently annotated proximal caries on radiographs, both with and without micro-CT assistance, enabling determinations of interobserver agreement and diagnostic accuracy. To establish a reference standard, one dental radiologist annotated all caries on the related micro-CT scans.
Results: Micro-CT support improved interobserver agreement (Cohen's Kappa), averaging 0.64 (95% confidence interval [CI]: 0.59-0.68) versus 0.46 (95% CI: 0.44-0.48) in its absence. Likewise, average sensitivity and specificity increased from 42% (95% CI: 34-51%) to 63% (95% CI: 54-71%) and from 92% (95% CI: 88-95%) to 95% (95% CI: 92-97%), respectively.
Conclusion: The ACTA-DIRECT dataset offers high-quality images and annotations to support AI-based early caries diagnostics for training and validation. This study underscores the benefits of incorporating micro-CT scans in lesion assessments, providing enhanced precision and reliability.
期刊介绍:
BMC Oral Health is an open access, peer-reviewed journal that considers articles on all aspects of the prevention, diagnosis and management of disorders of the mouth, teeth and gums, as well as related molecular genetics, pathophysiology, and epidemiology.