Carina Nogueira Garcia , Christoph Wies , Katja Hauser , Titus J. Brinker
{"title":"诊断鳞状细胞癌的非侵入性技术系统回顾与荟萃分析","authors":"Carina Nogueira Garcia , Christoph Wies , Katja Hauser , Titus J. Brinker","doi":"10.1016/j.xjidi.2024.100303","DOIUrl":null,"url":null,"abstract":"<div><p>Early cutaneous squamous cell carcinoma (cSCC) diagnosis is essential to initiate adequate targeted treatment. Noninvasive diagnostic technologies could overcome the need of multiple biopsies and reduce tumor recurrence. To assess performance of noninvasive technologies for cSCC diagnostics, 947 relevant records were identified through a systematic literature search. Among the 15 selected studies within this systematic review, 7 were included in the meta-analysis, comprising of 1144 patients, 224 cSCC lesions, and 1729 clinical diagnoses. Overall, the sensitivity values are 92% (95% confidence interval [CI] = 86.6–96.4%) for high-frequency ultrasound, 75% (95% CI = 65.7–86.2%) for optical coherence tomography, and 63% (95% CI = 51.3–69.1%) for reflectance confocal microscopy. The overall specificity values are 88% (95% CI = 82.7–92.5%), 95% (95% CI = 92.7–97.3%), and 96% (95% CI = 94.8–97.4%), respectively. Physician’s expertise is key for high diagnostic performance of investigated devices. This can be justified by the provision of additional tissue information, which requires physician interpretation, despite insufficient standardized diagnostic criteria. Furthermore, few deep learning studies were identified. Thus, integration of deep learning into the investigated devices is a potential investigating field in cSCC diagnosis.</p></div>","PeriodicalId":73548,"journal":{"name":"JID innovations : skin science from molecules to population health","volume":"4 6","pages":"Article 100303"},"PeriodicalIF":0.0000,"publicationDate":"2024-07-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S266702672400050X/pdfft?md5=e2d200dbc371629064d1b3b62bc3f822&pid=1-s2.0-S266702672400050X-main.pdf","citationCount":"0","resultStr":"{\"title\":\"Noninvasive Technologies for the Diagnosis of Squamous Cell Carcinoma: A Systematic Review and Meta-Analysis\",\"authors\":\"Carina Nogueira Garcia , Christoph Wies , Katja Hauser , Titus J. Brinker\",\"doi\":\"10.1016/j.xjidi.2024.100303\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>Early cutaneous squamous cell carcinoma (cSCC) diagnosis is essential to initiate adequate targeted treatment. Noninvasive diagnostic technologies could overcome the need of multiple biopsies and reduce tumor recurrence. To assess performance of noninvasive technologies for cSCC diagnostics, 947 relevant records were identified through a systematic literature search. Among the 15 selected studies within this systematic review, 7 were included in the meta-analysis, comprising of 1144 patients, 224 cSCC lesions, and 1729 clinical diagnoses. Overall, the sensitivity values are 92% (95% confidence interval [CI] = 86.6–96.4%) for high-frequency ultrasound, 75% (95% CI = 65.7–86.2%) for optical coherence tomography, and 63% (95% CI = 51.3–69.1%) for reflectance confocal microscopy. The overall specificity values are 88% (95% CI = 82.7–92.5%), 95% (95% CI = 92.7–97.3%), and 96% (95% CI = 94.8–97.4%), respectively. Physician’s expertise is key for high diagnostic performance of investigated devices. This can be justified by the provision of additional tissue information, which requires physician interpretation, despite insufficient standardized diagnostic criteria. Furthermore, few deep learning studies were identified. Thus, integration of deep learning into the investigated devices is a potential investigating field in cSCC diagnosis.</p></div>\",\"PeriodicalId\":73548,\"journal\":{\"name\":\"JID innovations : skin science from molecules to population health\",\"volume\":\"4 6\",\"pages\":\"Article 100303\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-07-20\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.sciencedirect.com/science/article/pii/S266702672400050X/pdfft?md5=e2d200dbc371629064d1b3b62bc3f822&pid=1-s2.0-S266702672400050X-main.pdf\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"JID innovations : skin science from molecules to population health\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S266702672400050X\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"JID innovations : skin science from molecules to population health","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S266702672400050X","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Noninvasive Technologies for the Diagnosis of Squamous Cell Carcinoma: A Systematic Review and Meta-Analysis
Early cutaneous squamous cell carcinoma (cSCC) diagnosis is essential to initiate adequate targeted treatment. Noninvasive diagnostic technologies could overcome the need of multiple biopsies and reduce tumor recurrence. To assess performance of noninvasive technologies for cSCC diagnostics, 947 relevant records were identified through a systematic literature search. Among the 15 selected studies within this systematic review, 7 were included in the meta-analysis, comprising of 1144 patients, 224 cSCC lesions, and 1729 clinical diagnoses. Overall, the sensitivity values are 92% (95% confidence interval [CI] = 86.6–96.4%) for high-frequency ultrasound, 75% (95% CI = 65.7–86.2%) for optical coherence tomography, and 63% (95% CI = 51.3–69.1%) for reflectance confocal microscopy. The overall specificity values are 88% (95% CI = 82.7–92.5%), 95% (95% CI = 92.7–97.3%), and 96% (95% CI = 94.8–97.4%), respectively. Physician’s expertise is key for high diagnostic performance of investigated devices. This can be justified by the provision of additional tissue information, which requires physician interpretation, despite insufficient standardized diagnostic criteria. Furthermore, few deep learning studies were identified. Thus, integration of deep learning into the investigated devices is a potential investigating field in cSCC diagnosis.