{"title":"B-014 用于白细胞差异计数的 DI-60 自动细胞图像分析仪的性能评估","authors":"S Chang, E Kim, Y Kim, D Won","doi":"10.1093/clinchem/hvae106.378","DOIUrl":null,"url":null,"abstract":"Background The Sysmex DI-60 system (Sysmex, kobe, Japan) is an automated cell image analyzer that captures cell images and analyzes them. The aim of this study was to evaluate the performance of DI-60 for leukocyte differential count in comparison with manual differential count or XN-20. Methods A total of 205 samples were analyzed. The agreement between DI-60 pre-classification and post-verification by medical technicians was determined. The correlation and ability to identify clinically important abnormal cells of DI-60 post-verification were evaluated. Results The overall agreement of DI-60 pre-classification was 84.7% (Table 1). The correlation between DI-60 post-verification and manual differential counts were exellent (r2 > 0.85) for neutrophil, lymphocyte, monocyte and eosinophil, but was very low for basophil (r2 = 0.3759). The correlation between DI-60 post-verification and leukocyte differential counts by XN-20 were exellent (r2 > 0.90) for neutrophil, lymphocyte and eosinophil. However, monocyte and basophil showed a relatively low correlation of r2 = 0.6343 and r2 = 0.3118, respectively but was very low for basophil (r2 0.3759). The ability of DI-60 post-verification to identify clinically important abnormal cells including blast, promyelocyte, myelocyte, metamyelocyte and NRBC demonstrated excellent efficiency (80.8 to 96.3%) except for NRBC (51.0%). Overall sensitivity was 63.7-88.2%, and specificity was 84.3-95.5% excluding NRBC (43.7%). Conclusions DI-60 showed excellent pre-classification and generally high correlation compared to manual leukocyte differential counts. Although additional verification with PBS review by experienced medical technician may still be required, the performance DI-60 makes it an efficient screening tool in clinical laboratories.","PeriodicalId":10690,"journal":{"name":"Clinical chemistry","volume":"14 1","pages":""},"PeriodicalIF":7.1000,"publicationDate":"2024-10-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"B-014 Performance evaluation of the automated cell image analyzer DI-60 for leukocyte differential count\",\"authors\":\"S Chang, E Kim, Y Kim, D Won\",\"doi\":\"10.1093/clinchem/hvae106.378\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Background The Sysmex DI-60 system (Sysmex, kobe, Japan) is an automated cell image analyzer that captures cell images and analyzes them. The aim of this study was to evaluate the performance of DI-60 for leukocyte differential count in comparison with manual differential count or XN-20. Methods A total of 205 samples were analyzed. The agreement between DI-60 pre-classification and post-verification by medical technicians was determined. The correlation and ability to identify clinically important abnormal cells of DI-60 post-verification were evaluated. Results The overall agreement of DI-60 pre-classification was 84.7% (Table 1). The correlation between DI-60 post-verification and manual differential counts were exellent (r2 > 0.85) for neutrophil, lymphocyte, monocyte and eosinophil, but was very low for basophil (r2 = 0.3759). The correlation between DI-60 post-verification and leukocyte differential counts by XN-20 were exellent (r2 > 0.90) for neutrophil, lymphocyte and eosinophil. However, monocyte and basophil showed a relatively low correlation of r2 = 0.6343 and r2 = 0.3118, respectively but was very low for basophil (r2 0.3759). The ability of DI-60 post-verification to identify clinically important abnormal cells including blast, promyelocyte, myelocyte, metamyelocyte and NRBC demonstrated excellent efficiency (80.8 to 96.3%) except for NRBC (51.0%). Overall sensitivity was 63.7-88.2%, and specificity was 84.3-95.5% excluding NRBC (43.7%). Conclusions DI-60 showed excellent pre-classification and generally high correlation compared to manual leukocyte differential counts. Although additional verification with PBS review by experienced medical technician may still be required, the performance DI-60 makes it an efficient screening tool in clinical laboratories.\",\"PeriodicalId\":10690,\"journal\":{\"name\":\"Clinical chemistry\",\"volume\":\"14 1\",\"pages\":\"\"},\"PeriodicalIF\":7.1000,\"publicationDate\":\"2024-10-02\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Clinical chemistry\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1093/clinchem/hvae106.378\",\"RegionNum\":2,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"MEDICAL LABORATORY TECHNOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Clinical chemistry","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1093/clinchem/hvae106.378","RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"MEDICAL LABORATORY TECHNOLOGY","Score":null,"Total":0}
B-014 Performance evaluation of the automated cell image analyzer DI-60 for leukocyte differential count
Background The Sysmex DI-60 system (Sysmex, kobe, Japan) is an automated cell image analyzer that captures cell images and analyzes them. The aim of this study was to evaluate the performance of DI-60 for leukocyte differential count in comparison with manual differential count or XN-20. Methods A total of 205 samples were analyzed. The agreement between DI-60 pre-classification and post-verification by medical technicians was determined. The correlation and ability to identify clinically important abnormal cells of DI-60 post-verification were evaluated. Results The overall agreement of DI-60 pre-classification was 84.7% (Table 1). The correlation between DI-60 post-verification and manual differential counts were exellent (r2 > 0.85) for neutrophil, lymphocyte, monocyte and eosinophil, but was very low for basophil (r2 = 0.3759). The correlation between DI-60 post-verification and leukocyte differential counts by XN-20 were exellent (r2 > 0.90) for neutrophil, lymphocyte and eosinophil. However, monocyte and basophil showed a relatively low correlation of r2 = 0.6343 and r2 = 0.3118, respectively but was very low for basophil (r2 0.3759). The ability of DI-60 post-verification to identify clinically important abnormal cells including blast, promyelocyte, myelocyte, metamyelocyte and NRBC demonstrated excellent efficiency (80.8 to 96.3%) except for NRBC (51.0%). Overall sensitivity was 63.7-88.2%, and specificity was 84.3-95.5% excluding NRBC (43.7%). Conclusions DI-60 showed excellent pre-classification and generally high correlation compared to manual leukocyte differential counts. Although additional verification with PBS review by experienced medical technician may still be required, the performance DI-60 makes it an efficient screening tool in clinical laboratories.
期刊介绍:
Clinical Chemistry is a peer-reviewed scientific journal that is the premier publication for the science and practice of clinical laboratory medicine. It was established in 1955 and is associated with the Association for Diagnostics & Laboratory Medicine (ADLM).
The journal focuses on laboratory diagnosis and management of patients, and has expanded to include other clinical laboratory disciplines such as genomics, hematology, microbiology, and toxicology. It also publishes articles relevant to clinical specialties including cardiology, endocrinology, gastroenterology, genetics, immunology, infectious diseases, maternal-fetal medicine, neurology, nutrition, oncology, and pediatrics.
In addition to original research, editorials, and reviews, Clinical Chemistry features recurring sections such as clinical case studies, perspectives, podcasts, and Q&A articles. It has the highest impact factor among journals of clinical chemistry, laboratory medicine, pathology, analytical chemistry, transfusion medicine, and clinical microbiology.
The journal is indexed in databases such as MEDLINE and Web of Science.