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. 2022 Mar;196(5):1175-1183.
doi: 10.1111/bjh.17933. Epub 2021 Nov 3.

Accurate classification of plasma cell dyscrasias is achieved by combining artificial intelligence and flow cytometry

Valentin Clichet  1 , Véronique Harrivel  1 , Caroline Delette  2 , Eric Guiheneuf  1 , Murielle Gautier  1 , Pierre Morel  2 , Déborah Assouan  2 , Lavinia Merlusca  2 , Marie Beaumont  2 , Delphine Lebon  2   3 , Alexis Caulier  2   3 , Jean-Pierre Marolleau  2   3 , Thomas Matthes  4 , François Vergez  5 , Loïc Garçon  1   3 , Thomas Boyer  1   3
Affiliations

Accurate classification of plasma cell dyscrasias is achieved by combining artificial intelligence and flow cytometry

Valentin Clichet et al. Br J Haematol. 2022 Mar.

Abstract

Monoclonal gammopathy of unknown significance (MGUS), smouldering multiple myeloma (SMM), and multiple myeloma (MM) are very common neoplasms. However, it is often difficult to distinguish between these entities. In the present study, we aimed to classify the most powerful markers that could improve diagnosis by multiparametric flow cytometry (MFC). The present study included 348 patients based on two independent cohorts. We first assessed how representative the data were in the discovery cohort (123 MM, 97 MGUS) and then analysed their respective plasma cell (PC) phenotype in order to obtain a set of correlations with a hypersphere visualisation. Cluster of differentiation (CD)27 and CD38 were differentially expressed in MGUS and MM (P < 0·001). We found by a gradient boosting machine method that the percentage of abnormal PCs and the ratio PC/CD117 positive precursors were the most influential parameters at diagnosis to distinguish MGUS and MM. Finally, we designed a decisional algorithm allowing a predictive classification ≥95% when PC dyscrasias were suspected, without any misclassification between MGUS and SMM. We validated this algorithm in an independent cohort of PC dyscrasias (n = 87 MM, n = 41 MGUS). This artificial intelligence model is freely available online as a diagnostic tool application website for all MFC centers worldwide (https://aihematology.shinyapps.io/PCdyscrasiasToolDg/).

Keywords: artificial intelligence; monoclonal gammopathy of undetermined significance; multiparametric flow cytometry; multiple myeloma.

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References

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