{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,7]],"date-time":"2026-10-07T04:58:15Z","timestamp":1791349095304,"version":"4.3.1"},"reference-count":24,"publisher":"Walter de Gruyter GmbH","issue":"6","funder":[{"DOI":"10.13039\/501100002641","name":"Konkuk University","doi-asserted-by":"crossref","id":[{"id":"10.13039\/501100002641","id-type":"DOI","asserted-by":"crossref"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2021,5,26]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:sec id=\"j_cclm-2020-1701_abs_001\">\n                  <jats:title>Objectives<\/jats:title>\n                  <jats:p>Vision Pro (West Medica, Perchtoldsdorf, Austria) is a recently developed digital morphology analyzer. We evaluated the performance of Vision Pro on white blood cell (WBC) differentials.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec id=\"j_cclm-2020-1701_abs_002\">\n                  <jats:title>Methods<\/jats:title>\n                  <jats:p>In a total of 200 peripheral blood smear samples (100 normal and 100 abnormal samples), WBC preclassification and reclassification by Vision Pro were evaluated and compared with manual WBC count, according to the Clinical and Laboratory Standards Institute guidelines (H20-A2).<\/jats:p>\n               <\/jats:sec>\n               <jats:sec id=\"j_cclm-2020-1701_abs_003\">\n                  <jats:title>Results<\/jats:title>\n                  <jats:p>The overall sensitivity was high for normal WBCs and nRBCs (80.1\u201398.0%). The overall specificity and\u00a0overall efficiency were high for all cell classes (98.1\u2013100.0% and 97.7\u201399.9%, respectively). The absolute values of mean differences between Vision Pro and manual count ranged from 0.01 to 1.31. In leukopenic samples, those values ranged from 0.09 to 2.01. For normal WBCs, Vision Pro preclassification and manual\u00a0count showed moderate or high correlations (r=0.52\u20130.88) except for basophils (r=0.34); after reclassification, the correlation between Vision Pro and manual count was improved (r=0.36\u20130.90).<\/jats:p>\n               <\/jats:sec>\n               <jats:sec id=\"j_cclm-2020-1701_abs_004\">\n                  <jats:title>Conclusions<\/jats:title>\n                  <jats:p>This is the first study that evaluated the performance of Vision Pro on WBC differentials. Vision Pro showed reliable analytical performance on WBC differentials with improvement after reclassification. Vision Pro could help improve laboratory workflow.<\/jats:p>\n               <\/jats:sec>","DOI":"10.1515\/cclm-2020-1701","type":"journal-article","created":{"date-parts":[[2021,1,23]],"date-time":"2021-01-23T06:34:37Z","timestamp":1611383677000},"page":"1099-1106","source":"Crossref","is-referenced-by-count":20,"title":["Performance of digital morphology analyzer Vision Pro on white blood cell differentials"],"prefix":"10.1515","volume":"59","author":[{"given":"Sumi","family":"Yoon","sequence":"first","affiliation":[{"name":"Department of Laboratory Medicine , Chung-Ang University College of Medicine , Seoul , Republic of Korea"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4429-9978","authenticated-orcid":false,"given":"Mina","family":"Hur","sequence":"additional","affiliation":[{"name":"Department of Laboratory Medicine , Konkuk University School of Medicine , Seoul , Republic of Korea"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Mikyoung","family":"Park","sequence":"additional","affiliation":[{"name":"Department of Laboratory Medicine , Yeungnam University College of Medicine , Daegu , Republic of Korea"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hanah","family":"Kim","sequence":"additional","affiliation":[{"name":"Department of Laboratory Medicine , Konkuk University School of Medicine , Seoul , Republic of Korea"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Seung Wan","family":"Kim","sequence":"additional","affiliation":[{"name":"Department of Laboratory Medicine , Konkuk University School of Medicine , Seoul , Republic of Korea"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Tae-Hwan","family":"Lee","sequence":"additional","affiliation":[{"name":"Department of Laboratory Medicine , Konkuk University School of Medicine , Seoul , Republic of Korea"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3542-3487","authenticated-orcid":false,"given":"Minjeong","family":"Nam","sequence":"additional","affiliation":[{"name":"Department of Laboratory Medicine , Konkuk University School of Medicine , Seoul , Republic of Korea"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hee-Won","family":"Moon","sequence":"additional","affiliation":[{"name":"Department of Laboratory Medicine , Konkuk University School of Medicine , Seoul , Republic of Korea"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yeo-Min","family":"Yun","sequence":"additional","affiliation":[{"name":"Department of Laboratory Medicine , Konkuk University School of Medicine , Seoul , Republic of Korea"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"374","published-online":{"date-parts":[[2021,1,20]]},"reference":[{"key":"2021082201593402356_j_cclm-2020-1701_ref_001","unstructured":"Clinical and Laboratory Standards Institute (CLSI). Reference leukocytes (WBC) differential count (proportional) and evaluation of instrumental methods: approval standard, 2nd ed. CLSI Document H20-A2. Wayne, PA: CLSI; 2007."},{"key":"2021082201593402356_j_cclm-2020-1701_ref_002","doi-asserted-by":"crossref","unstructured":"Da Costa, L. Digital image analysis of blood cells. Clin Lab Med 2015;35:105\u201322. https:\/\/doi.org\/10.1016\/j.cll.2014.10.005.","DOI":"10.1016\/j.cll.2014.10.005"},{"key":"2021082201593402356_j_cclm-2020-1701_ref_003","doi-asserted-by":"crossref","unstructured":"Briggs, C, Longair, I, Slavik, M, Thwaite, K, Mills, R, Thavaraja, V, et al.. Can automated blood film analysis replace the manual differential? An evaluation of the CellaVision DM96 automated image analysis system. 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