{"title":"人工智能全血膜扫描在明显白细胞减少血膜中爆炸检测中的优势。","authors":"Geng Wang, Lin Zheng, Zhejun Fang, Guoju Luo, Qian Chen, Qi Qi Zhang, Bo Shen Wu, Xin Wang, Rongrong Cheng, Ping Deng, Binyao Zhang, Jing Jin, Wei Wu","doi":"10.1007/s00277-025-06473-0","DOIUrl":null,"url":null,"abstract":"<p><p>To evaluate performance of AI-assisted blast detection via whole blood film scanning in cases of severe leukopenia. From August to October 2023, we collected 157 patient specimens with white blood cell (WBC) counts of ≤2.0 × 10⁹/L. We then evaluated and compared the blast detection capabilities of an artificial intelligence-based system (Cygnus instrument) against the CellaVision DI-60 for WBC analysis. Additionally, this study aimed to assess the comparative performance of these two automated blood cell morphology analyzers based on their underlying operational principles. Following manual microscopy confirmation, 17 cases showing ≥ 1 blast cell in peripheral blood smear were identified among 157 specimens with WBC ≤ 2.0 × 10⁹/L. The Cygnus whole-slide scanning mode detected all 17 cases (sensitivity: 100%), whereas the Cygnus 200-cell mode detected only 9 cases (9/17), and the CellaVision DI-60 200-cell mode detected 8 cases (8/17). In leukopenic patients (WBC ≤2.0×10⁹/L), utilizing Cygnus' whole-slide scanning capability substantially improves blast identification rates, potentially enabling earlier detection of hematologic abnormalities.</p>","PeriodicalId":8068,"journal":{"name":"Annals of Hematology","volume":" ","pages":""},"PeriodicalIF":3.0000,"publicationDate":"2025-07-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Advantages of AI-based whole blood film scanning for blast detection in markedly leucopenic blood films.\",\"authors\":\"Geng Wang, Lin Zheng, Zhejun Fang, Guoju Luo, Qian Chen, Qi Qi Zhang, Bo Shen Wu, Xin Wang, Rongrong Cheng, Ping Deng, Binyao Zhang, Jing Jin, Wei Wu\",\"doi\":\"10.1007/s00277-025-06473-0\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>To evaluate performance of AI-assisted blast detection via whole blood film scanning in cases of severe leukopenia. From August to October 2023, we collected 157 patient specimens with white blood cell (WBC) counts of ≤2.0 × 10⁹/L. We then evaluated and compared the blast detection capabilities of an artificial intelligence-based system (Cygnus instrument) against the CellaVision DI-60 for WBC analysis. Additionally, this study aimed to assess the comparative performance of these two automated blood cell morphology analyzers based on their underlying operational principles. Following manual microscopy confirmation, 17 cases showing ≥ 1 blast cell in peripheral blood smear were identified among 157 specimens with WBC ≤ 2.0 × 10⁹/L. The Cygnus whole-slide scanning mode detected all 17 cases (sensitivity: 100%), whereas the Cygnus 200-cell mode detected only 9 cases (9/17), and the CellaVision DI-60 200-cell mode detected 8 cases (8/17). In leukopenic patients (WBC ≤2.0×10⁹/L), utilizing Cygnus' whole-slide scanning capability substantially improves blast identification rates, potentially enabling earlier detection of hematologic abnormalities.</p>\",\"PeriodicalId\":8068,\"journal\":{\"name\":\"Annals of Hematology\",\"volume\":\" \",\"pages\":\"\"},\"PeriodicalIF\":3.0000,\"publicationDate\":\"2025-07-15\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Annals of Hematology\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1007/s00277-025-06473-0\",\"RegionNum\":3,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"HEMATOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Annals of Hematology","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1007/s00277-025-06473-0","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"HEMATOLOGY","Score":null,"Total":0}
Advantages of AI-based whole blood film scanning for blast detection in markedly leucopenic blood films.
To evaluate performance of AI-assisted blast detection via whole blood film scanning in cases of severe leukopenia. From August to October 2023, we collected 157 patient specimens with white blood cell (WBC) counts of ≤2.0 × 10⁹/L. We then evaluated and compared the blast detection capabilities of an artificial intelligence-based system (Cygnus instrument) against the CellaVision DI-60 for WBC analysis. Additionally, this study aimed to assess the comparative performance of these two automated blood cell morphology analyzers based on their underlying operational principles. Following manual microscopy confirmation, 17 cases showing ≥ 1 blast cell in peripheral blood smear were identified among 157 specimens with WBC ≤ 2.0 × 10⁹/L. The Cygnus whole-slide scanning mode detected all 17 cases (sensitivity: 100%), whereas the Cygnus 200-cell mode detected only 9 cases (9/17), and the CellaVision DI-60 200-cell mode detected 8 cases (8/17). In leukopenic patients (WBC ≤2.0×10⁹/L), utilizing Cygnus' whole-slide scanning capability substantially improves blast identification rates, potentially enabling earlier detection of hematologic abnormalities.
期刊介绍：
Annals of Hematology covers the whole spectrum of clinical and experimental hematology, hemostaseology, blood transfusion, and related aspects of medical oncology, including diagnosis and treatment of leukemias, lymphatic neoplasias and solid tumors, and transplantation of hematopoietic stem cells. Coverage includes general aspects of oncology, molecular biology and immunology as pertinent to problems of human blood disease. The journal is associated with the German Society for Hematology and Medical Oncology, and the Austrian Society for Hematology and Oncology.
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