{"title":"使用多中心细胞学切片进行甲状腺癌无注释基因突变估计。","authors":"Siping Xiong, Shuguang Liu, Wei Zhang, Chao Zeng, Degui Liao, Tian Tang, Shimin Wang, Yimin Guo","doi":"10.1186/s13000-025-01618-1","DOIUrl":null,"url":null,"abstract":"<p><p>Thyroid cancer is the most common form of endocrine malignancy and fine needle aspiration (FNA) cytology is a reliable method for clinical diagnosis. Identification of genetic mutation status has been proved efficient for accurate diagnosis and prognostic risk stratification. In this study, a dataset with thyroid cytological images of 310 indeterminate (TBS3 or 4) and 392 PTC (TBS5 or 6) was collected. We introduced a multimodal cascaded network framework to estimate BARF V600E and RAS mutations directly from thyroid cytological slides. The area under the curve in the external testing set achieved 0.902 ± 0.063 and 0.801 ± 0.137 AUCs for BRAF, and RAS, respectively. The results demonstrated that deep neural networks have the potential in cytologically predicting valuable diagnosis and comprehensive genetic status.</p>","PeriodicalId":11237,"journal":{"name":"Diagnostic Pathology","volume":"20 1","pages":"22"},"PeriodicalIF":2.4000,"publicationDate":"2025-02-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11846261/pdf/","citationCount":"0","resultStr":"{\"title\":\"Annotation-free genetic mutation estimation of thyroid cancer using cytological slides from multi-centers.\",\"authors\":\"Siping Xiong, Shuguang Liu, Wei Zhang, Chao Zeng, Degui Liao, Tian Tang, Shimin Wang, Yimin Guo\",\"doi\":\"10.1186/s13000-025-01618-1\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>Thyroid cancer is the most common form of endocrine malignancy and fine needle aspiration (FNA) cytology is a reliable method for clinical diagnosis. Identification of genetic mutation status has been proved efficient for accurate diagnosis and prognostic risk stratification. In this study, a dataset with thyroid cytological images of 310 indeterminate (TBS3 or 4) and 392 PTC (TBS5 or 6) was collected. We introduced a multimodal cascaded network framework to estimate BARF V600E and RAS mutations directly from thyroid cytological slides. The area under the curve in the external testing set achieved 0.902 ± 0.063 and 0.801 ± 0.137 AUCs for BRAF, and RAS, respectively. The results demonstrated that deep neural networks have the potential in cytologically predicting valuable diagnosis and comprehensive genetic status.</p>\",\"PeriodicalId\":11237,\"journal\":{\"name\":\"Diagnostic Pathology\",\"volume\":\"20 1\",\"pages\":\"22\"},\"PeriodicalIF\":2.4000,\"publicationDate\":\"2025-02-21\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11846261/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Diagnostic Pathology\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1186/s13000-025-01618-1\",\"RegionNum\":3,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"PATHOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Diagnostic Pathology","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1186/s13000-025-01618-1","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"PATHOLOGY","Score":null,"Total":0}
Annotation-free genetic mutation estimation of thyroid cancer using cytological slides from multi-centers.
Thyroid cancer is the most common form of endocrine malignancy and fine needle aspiration (FNA) cytology is a reliable method for clinical diagnosis. Identification of genetic mutation status has been proved efficient for accurate diagnosis and prognostic risk stratification. In this study, a dataset with thyroid cytological images of 310 indeterminate (TBS3 or 4) and 392 PTC (TBS5 or 6) was collected. We introduced a multimodal cascaded network framework to estimate BARF V600E and RAS mutations directly from thyroid cytological slides. The area under the curve in the external testing set achieved 0.902 ± 0.063 and 0.801 ± 0.137 AUCs for BRAF, and RAS, respectively. The results demonstrated that deep neural networks have the potential in cytologically predicting valuable diagnosis and comprehensive genetic status.
期刊介绍：
Diagnostic Pathology is an open access, peer-reviewed, online journal that considers research in surgical and clinical pathology, immunology, and biology, with a special focus on cutting-edge approaches in diagnostic pathology and tissue-based therapy. The journal covers all aspects of surgical pathology, including classic diagnostic pathology, prognosis-related diagnosis (tumor stages, prognosis markers, such as MIB-percentage, hormone receptors, etc.), and therapy-related findings. The journal also focuses on the technological aspects of pathology, including molecular biology techniques, morphometry aspects (stereology, DNA analysis, syntactic structure analysis), communication aspects (telecommunication, virtual microscopy, virtual pathology institutions, etc.), and electronic education and quality assurance (for example interactive publication, on-line references with automated updating, etc.).
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