Development of a Novel Flow Cytometry-Based System for White Blood Cell Differential Counts: 10-color LeukoDiff.

BACKGROUND: Flow cytometry (FCM) is commonly used to identify many cell populations. We developed a white blood cell (WBC) differential counting system for detecting abnormal cells using FCM incorporating 10 colors and 11 antibodies in a single tube, called "10-color LeukoDiff," and evaluated its performance. METHODS: Ninety-one EDTA-anti-coagulated peripheral blood samples from 76 patients were analyzed using 10-color LeukoDiff. We compared 10 color LeukoDiff results with the results of manual differential count (manual diff). WBCs were classified into 17 cell populations: neutrophils, total lymphocytes, T lymphocytes, B lymphocytes, CD5 and CD19 co-expressing lymphocytes, natural killer cells, total monocytes, 16+ monocytes, eosinophils, immature granulocytes, basophils, myeloblasts, B-blasts, T-blasts, myeloid antigen-positive B-blasts, CD19- plasma cells, and 19+ plasma cells. RESULTS: The correlations between the 10-color LeukoDiff and manual diff results were strong (r>0.9) for mature neutrophils, lymphocytes, eosinophils, immature granulocytes, and blasts and moderate for monocytes and basophils (r=0.86 and 0.74, respectively). There was no discrepancy in blast detection between 10-color LeukoDiff and manual diff results. Furthermore, 10-color LeukoDiff could differentiate the lineage of the blasts and separately count chronic lymphocytic leukemic cells and multiple myeloma cells. CONCLUSIONS: The 10-color LeukoDiff provided an accurate and comprehensive WBC differential count. The most important ability of 10-color LeukoDiff is to detect blasts accurately. This system is clinically useful, especially for patients with hematologic diseases, such as acute leukemia, chronic lymphocytic leukemia, and multiple myeloma. Application of this system will improve the development of FCM gating strategy designs.

Quantitative detection of target cells using unghosted cells (UGCs) of DxH 800 (Beckman Coulter).

BACKGROUND: In the Retic channel of DxH 800 (Beckman Coulter), the red blood cells (RBCs) resistant to hemoglobin clearing are counted as unghosted cells (UGCs). The aim of this study was to evaluate that the UGC is a surrogate marker for both the detection and counting of target cells. METHODS: In total, 1181 samples including 22 from iron deficiency anemia (IDA) patients, 95 from jaundice, 2 from sickle cell anemia, 3 from thalassemia, 1 cord blood, and 269 from normal controls were analyzed. Slides were prepared from all samples except normal controls and target cells were counted for correlation analysis of target cell counts to UGCs. RESULTS: The normal control samples showed 0.01% (0%-0.01%) UGCs, and the reference range was set at ≤0.02%. The IDA samples showed 0.015% (0.01%-0.03%) UGC count and 0.05% (0%-0.2%) target cell count. The jaundice samples showed 0.98% (0.1%-5.36%) UGC count, and 1.4% (0.1%-7.0%) target cell count. The two sickle cell anemia samples showed 0.41% and 3.74% UGC counts and 0.4% and 11.5% target cell counts. A cord blood sample showed 0.01% UGCs and 0% target cells. The three thalassemia samples showed 0.01%, 1.99%, and 7.82% UGC counts and 0%, 1.4%, and 15.5% target cell counts. The samples showing poikilocytosis other than target cells showed normal UGC count (≤0.02%). The positive predictive value of UGCs was 58.2% (124/213) and the negative predictive value was 96.8% (674/696). The UGC counts were well correlated to the manual target cell counts (r=0.944, p=0.000). CONCLUSIONS: This study demonstrates for the first time in the literature that a hematological parameter obtained automatically every time a reticulocyte counting is performed can be used to both screen for the presence of target cells and reliably quantify them.

Comparative quantitative analysis of cluster of differentiation 45 antigen expression on lymphocyte subsets.

BACKGROUND: Since the recent introduction of radioimmunotherapy (RIT) using antibodies against cluster of differentiation (CD) 45 for the treatment of lymphoma, the clinical significance of the CD45 antigen has been increasing steadily. Here, we analyzed CD45 expression on lymphocyte subsets using flow cytometry in order to predict the susceptibility of normal lymphocytes to RIT. METHODS: Peripheral blood specimens were collected from 14 healthy individuals aged 25-54 yr. The mean fluorescence intensity (MFI) of the cell surface antigens was measured using a FACSCanto II system (Becton Dickinson Bioscience, USA). MFI values were converted into antibody binding capacity values using a Quantum Simply Cellular microbead kit (Bangs Laboratories, Inc., USA). RESULTS: Among the lymphocyte subsets, the expression of CD45 was the highest (725,368±42,763) on natural killer T (NKT) cells, 674,030±48,187 on cytotoxic/suppressor T cells, 588,750±48,090 on natural killer (NK) cells, 580,211±29,168 on helper T (Th) cells, and 499,436±21,737 on B cells. The Th cells and NK cells expressed a similar level of CD45 (P=0.502). Forward scatter was the highest in NKT cells (P<0.05), whereas side scatter differed significantly between each of the lymphocyte subsets (P<0.05). CD3 expression was highest in the Th and NKT cells. CONCLUSIONS: NKT cells express the highest levels of CD45 antigen. Therefore, this lymphocyte subset would be most profoundly affected by RIT or pretargeted RIT. The monitoring of this lymphocyte subset during and after RIT should prove helpful.

[Bone marrow cellularity measurement by myelocrit].

BACKGROUND: The bone marrow (BM) cellularity has been used as a major index for the evaluation of hematologic diseases and malignancies. However, the microscopic evaluation lacks objectivity because of considerable variations among different observers. We measured myelocrit cellularity as an objective method to evaluate the cellularity. METHODS: Between November 2007 and January 2008, 489 consecutive BM aspirates including 25 cases of AML D7 marrow (7 days after initiation of chemotherapy) were examined. The conventional BM cellularity was evaluated using BM needle biopsies after hematoxylin-eosin stain. EDTA-anticoagulated BM aspirates were put into the Wintrobe tubes, centrifuged and the thickness of 5 layers from the bottom was measured: RBC, buffy coat (BC), plasma, BM particle, and fat layers. The myelocrit cellularity was defined as the ratio of BC to the BC plus fat layers. RESULTS: Both of the thickness of BC layer (r=0.721, P=0.000) and the myelocrit cellularity (r=0.735, P=0.000) correlated well with the conventional cellularity. However, the AML D7 BM cellularity correlated with BC layer (r=0.589, P=0.002), but not with the myelocrit cellularity (r=0.281, P=0.231). The cellularity of the BM other than AML D7 marrow showed a better correlation with the myelocrit cellularity (r=0.826, P=0.000) than the BC layer (r=0.713, P=0.000). CONCLUSIONS: The myelocrit is a simple, reproducible and objective method to determine the BM cellularity. For accurate assessment of BM cellularity, measurement of the thickness of BC layer in AML D7 BM and of the myelocrit cellularity in other BM samples has better be used.