Red blood cell size differential method for time-series detailed monitoring of anemic disorders with RBC size abnormalities in mean corpuscular volume (MCV) and/or red blood cell distribution width (RDW)

Abstract

Background: Size heterogeneity in red blood cells (RBCs), as indicated by elevated RBC distribution width (RDW), is increasingly considered a prognostic factor in various diseases. However, the semi-quantitative nature of the RDW value appears limited when evaluating quantitative changes in time-series RBC size distributions over a clinical course. Methods: We developed a time-series anemia monitoring program by displaying progressive differences between six size fractions in an RBC size distribution. To standardize each variation precisely, our program includes an angular transformation that is applied to all measured count ratio data. Results: By representing microcytic and/or macrocytic changes in time series independently, this method appears to improve evaluations of anisocytosis, reflecting the responsiveness of treatments and effects, such as deficiencies in iron or vitamin B12. Time-series displays of RBC size changes also appear to enable verification of latent clinical developments at earlier stages and the characterization of imbalances between RBC supply and RBC loss in anemic pathologies. Conclusions: By displaying linear relationships between RBC size categories on a time scale, our proposed monitoring method quantifies potentially applicable pathological information. This mode of representation appears to offer details about high RDW values and latent adverse outcomes related to anemic pathogenesis.

Keywords:

• anemia monitoring
• flow cytometry
• measurement uncertainty
• MCV
• RDW

Public Interest Statement

Flow cytometry count data, such as complete blood cell counts, have been widely used in clinical laboratories. We usually must use non-parametric statistical analysis to compare such cell count data, but quantitative evaluations employing some type of computed index from count data in time series can at times be necessary for making key clinical decisions. Therefore, we studied the characteristics of both precision and accuracy and the instability of uncertainty in count ratio variables for improved clarity in flow cytometry analysis. Through our proposed control of uncertainty propagation in computed indices from a hematology analyzer’s cell count data, we hope that our clinical evaluation method might contribute to an easy-to-visualize, programmable, and real-time detailed anemia interface. We also hope that our report’s case studies on tracking various types of anemia might indicate such a method’s potential applicability to routine medical care.

Competing Interests

The authors declare no competing interest.

Acknowledgments

We express our thanks to professor Yoshiyuki Yamashita, Department of Information Science at Saga University; and Dr Takashi Kanematsu, Director of Nagasaki Harbor Medical Center City Hospital, for their constant support of this study.

Additional information

Funding

Funding. The authors received no direct funding for this research.

Notes on contributors

Sunao Atogami

Sunao Atogami’s interest in a parametric analysis method by flow cytometry-measured histograms in time series came from past research of DNA aneuploidy changes in adult T-cell leukemia cells, over the course of monitoring ATL patients under the direction of Nagasaki University professor Emeritus Shimeru Kamihira. His research currently focuses on applying the same parametric analysis to a monitoring method of anisocytosis or elevated RBC distribution width (RDW), a more common clinical finding which relates to the various pathogeneses of anemic disorders as apparent in time series.

Charles de Kerckhove

Charles de Kerckhove is a Mechanical Engineer keen to build on the Engineering approach and related distant memories of Statistics for a thorough understanding and communication of how to display hematological change in time series.

Katsunori Yanagihara

Katsunori Yanagihara, professor at Nagasaki University and Head of the Nagasaki University Hospital Department of Laboratory Medicine, and Shimeru Kamihira are both supervisors of this study.