{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,2]],"date-time":"2026-09-02T02:57:00Z","timestamp":1788317820457,"version":"build-2803163510"},"reference-count":19,"publisher":"Wiley","issue":"4","license":[{"start":{"date-parts":[[2023,2,23]],"date-time":"2023-02-23T00:00:00Z","timestamp":1677110400000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/onlinelibrary.wiley.com\/termsAndConditions#vor"}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Cytometry Part B Clinical"],"published-print":{"date-parts":[[2024,7]]},"abstract":"<jats:title>Abstract<\/jats:title><jats:p>Detection of measurable residual disease (MRD) in chronic lymphocytic leukemia (CLL) is an important prognostic marker. The most common CLL MRD method in current use is multiparameter flow cytometry, but availability is limited by the need for expert manual analysis. Automated analysis has the potential to expand access to CLL MRD testing. We evaluated the performance of an artificial intelligence (AI)\u2010assisted multiparameter flow cytometry (MFC) workflow for CLL MRD. We randomly selected 113 CLL MRD FCS files and divided them into training and validation sets. The training set (<jats:italic>n<\/jats:italic>\u00a0=\u200941) was gated by expert manual analysis and used to train the AI model. We then compared the validation set (<jats:italic>n<\/jats:italic>\u00a0=\u200972) MRD results obtained by the AI\u2010assisted analysis versus those by expert manual analysis using the Pearson correlation coefficient and Bland\u2013Altman plot method. In the validation set, the AI\u2010assisted analysis correctly categorized cases as MRD\u2010negative versus MRD\u2010positive in 96% of cases. When comparing the AI\u2010assisted analysis versus the expert manual analysis, the Pearson <jats:italic>r<\/jats:italic> was 0.8650, mean bias was 0.2237 log<jats:sub>10<\/jats:sub> units, and the 95% limit of agreement (LOA) was \u00b11.0282 log<jats:sub>10<\/jats:sub> units. The AI\u2010assisted analysis performed sub\u2010optimally in atypical immunophenotype CLL and in cases lacking residual normal B cells. When excluding these outlier cases, the mean bias improved to 0.0680 log<jats:sub>10<\/jats:sub> units and the 95% LOA to \u00b10.2926 log<jats:sub>10<\/jats:sub> units. An automated AI\u2010assisted workflow allows for the quantification of MRD in CLL with typical immunophenotype. Further work is required to improve performance in atypical immunophenotype CLL.<\/jats:p>","DOI":"10.1002\/cyto.b.22116","type":"journal-article","created":{"date-parts":[[2023,2,24]],"date-time":"2023-02-24T07:20:04Z","timestamp":1677223204000},"page":"264-271","update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":19,"title":["Automated quantification of measurable residual disease in chronic lymphocytic leukemia using an artificial <scp>intelligence\u2010assisted<\/scp> workflow"],"prefix":"10.1002","volume":"106","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-5538-4943","authenticated-orcid":false,"given":"Alexandre","family":"Bazinet","sequence":"first","affiliation":[{"name":"Department of Leukemia University of Texas MD Anderson Cancer Center  Houston Texas United States"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Alan","family":"Wang","sequence":"additional","affiliation":[{"name":"DeepCyto LLC  West Linn Oregon United States"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xinmei","family":"Li","sequence":"additional","affiliation":[{"name":"DeepCyto LLC  West Linn Oregon United States"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Fuli","family":"Jia","sequence":"additional","affiliation":[{"name":"Department of Hematopathology University of Texas MD Anderson Cancer Center  Houston Texas United States"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Huan","family":"Mo","sequence":"additional","affiliation":[{"name":"Department of Hematopathology University of Texas MD Anderson Cancer Center  Houston Texas United States"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Wei","family":"Wang","sequence":"additional","affiliation":[{"name":"Department of Hematopathology University of Texas MD Anderson Cancer Center  Houston Texas United States"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Sa 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