• Users Online: 969
  • Home
  • Print this page
  • Email this page
Home About us Editorial board Search Ahead of print Current issue Archives Submit article Instructions Subscribe Contacts Login 

 Table of Contents  
Year : 2021  |  Volume : 12  |  Issue : 2  |  Page : 83-89

Scattergram patterns of hematological malignancies on sysmex XN-series analyzer

1 Department of Laboratory Medicine, All India Institute of Medical Sciences, New Delhi, India
2 Department of Laboratory Oncology, All India Institute of Medical Sciences, New Delhi, India

Date of Submission16-Sep-2020
Date of Decision12-Dec-2020
Date of Acceptance12-Dec-2020
Date of Web Publication06-Aug-2021

Correspondence Address:
Dr. Abhirup Sarkar
Department of Laboratory Medicine, All India Institute of Medical Sciences, New Delhi - 110 029
Login to access the Email id

Source of Support: None, Conflict of Interest: None

DOI: 10.4103/joah.joah_176_20

Rights and Permissions

BACKGROUND: Automated hematology analyzers effectively reduce turnaround time and generates scattergrams which can be used to screen for different hematological conditions.
AIMS: We wish to study the scattergrams generated by the Sysmex XN-series analyzer for confirmed cases of hematological malignancies and evaluate for the specific patterns to these malignancies.
METHODS: Two hundred and ninety-one newly diagnosed cases of various hematological malignancies were included in the study. All these cases were diagnosed and classified in accordance with flow cytometry, bone marrow morphological study, immunohistochemistry, and molecular studies. Forty-eight cases of leukemoid reaction were also included in the study. We retrieved the scattergrams and complete blood count data of all these cases which were processed in the Sysmex XN-analyzer before their diagnosis. Along with scattergrams, the peripheral blood smear findings of all the cases were extracted too. The scattergram patterns in the white blood cell differential (WDF) and white cell nucleated region (WNR) channels were evaluated and correlated with their peripheral blood smear findings.
RESULTS: All the scattergrams in the WDF and WNR channels were studied. Patterns seen in acute lymphoblastic leukemia (ALL) and acute myeloid leukemia (AML) were striking and distinctly separate. After correlating with the peripheral smear and immunophenotyping, AML patterns were subtyped by the French American British classification. Acute promyelocytic leukemia as well as different phases of chronic myeloid leukemia had unique patterns. Scattergram patterns of ALL had minute difference with that of chronic lymphoproliferative disorder.
CONCLUSION: In high-volume laboratories, the patterns on Sysmex XN-series analyzer scattergrams can be used as a valuable aid for suspecting and triaging cases of hematological malignancies.

Keywords: Autoanalyzer, Flow Cytometry Standard, hematology, leukemia, sysmex

How to cite this article:
Ningombam A, Acharya S, Sarkar A, Kumar K, Chopra A. Scattergram patterns of hematological malignancies on sysmex XN-series analyzer. J Appl Hematol 2021;12:83-9

How to cite this URL:
Ningombam A, Acharya S, Sarkar A, Kumar K, Chopra A. Scattergram patterns of hematological malignancies on sysmex XN-series analyzer. J Appl Hematol [serial online] 2021 [cited 2023 Sep 22];12:83-9. Available from: https://www.jahjournal.org/text.asp?2021/12/2/83/323329

  Introduction Top

Complete blood count with differential (CBC w/diff) is an essential part of routine laboratory workup to evaluate various conditions comprising of infection, inflammatory disorders, and hematological malignancies. Automated hematology analyzers and their advanced technology have improved accuracy of cell analysis as well as effectively reduced the turnaround time by high throughput capabilities.[1] Analyzers are multichannel instruments which work on the variety of principles depending on the manufacturers.

Modern hematology analyzers with scattergrams and histograms have previously been studied for their ability to differentiate between acute and chronic leukemias.[2],[3],[4],[5],[6],[7] XN-2000 white pathological cell (WPC) channel flagging has been studied to differentiate reactive and neoplastic leukocytosis.[8]

The characterization of acute leukemia by various hematology analyzers has been previously documented. Krause JR et al. evaluated the use of Technicon H-1 (Technicon Instruments Corporation, Tarrytown, NY, USA) for the characterization of acute leukemias. Based on myeloperoxidase activity and nuclear characteristics of the cells, they were able to separate out acute myeloid leukemia (AML) and acute lymphoblastic leukemia (ALL). Among the AML, they suggested that French-American-British (FAB) type AML-M3, M4, and M5 had characteristic cytograms. Chronic myeloid leukemia (CML) also was considered to have a distinctive pattern.[3] Similarly, Kawarabayashi et al. studied the usefulness of Technicon H-1 (Technicon Instruments Corporation, Tarrytown, NY, USA) to detect blast cells.[5]

Hoyer et al. studied the ability of the Coulter STKS hematology analyzer to differentiate the acute leukemias. They concluded that using a set of suspect or definitive flags as screening criteria for microscopic review would be the best approach to correctly identify leukemias. They further concluded that scattergram patterns were not distinctive to classify acute leukemias.[2] Bruno et al. in 1994 and Pettit et al. in 1995 also studied the scattergram patterns of acute leukemias using the Coulter STKS hematology analyzer.[9],[10] Virk et al. studied the utility of the cell population data (VCS parameters) given by the Coulter LH 780 automated hematology analyzer as a rapid screening tool for AML in resource-constrained laboratories. They concluded that the cell population data along with the scattergrams and flags can provide an economic and rapid initial diagnosis of acute leukemias. These parameters can then be used to screen out malignant hematological disorders from nonmalignant ones.[7]

The Sysmex hematology analyzers have been studied for their ability to characterize leukemias.[4],[6] Except for Schuff-Werner et al. who evaluated the performance ability of WPC channel of XN-analyzer to differentiate reactive and neoplastic leukocytosis, the remaining studies were conducted on the previous models of Sysmex analyser.[8] As the WPC channel is not utilized in every laboratory setup, the ability of the white blood cell differential (WDF) and white cell nucleated region (WNR) to pick up pathological cell needs to be analyzed.

The Sysmex XN modular analyzer (Sysmex, Kobe, Japan) was introduced in 2011. It is an automated analyzer using linear sheath flow and direct current impedance to count red blood cells (RBCs) and platelet and measure hematocrit. It uses fluorescence flow cytometry for leukocyte differential, nucleated RBC, reticulocytes, and fluorescence platelet count.[1] WDF count is done by flow cytometry, after analyzing their cell-specific information such as size, internal complexity, and nucleic acid content. A polymethine dye is used to stain the deoxyribonucleic acid and ribonucleic acid content of the cell. A semiconductor diode laser scatters the light in 90° giving Side Scattered Light (SSC) assigning information on internal complexity of the cell, 0° giving forward scattered light (FSC) providing information on size of the cell and the side fluorescent light (SFL), dispensing information on total nucleic acid content of the cells. WDF channel distinguishes all the WBC population except basophils and the WNR channel distinguishes nucleated RBCs and basophils from the other nucleated cells.[1] The WDF scattergrams have the combinations of SSC-SFL, SSC-FSC, and FSC-SFL, and the WNR scattergrams have SFL-FSC, SSC-FSC, and SFL-SSC. [Figure 1]a and [Figure 1]d shows normal scattergram pattern in WDF (SSC-SFL) and WNR (SFL-FSC) respectively.
Figure 1: (a) Representative normal WDF (SSC-SFL), (b) Representative ALL WDF (SSC-SFL), (c) Representative CLPD WDF (SSC-SFL), (d) Representative normal WNR (SFL-FSC), (e) Representative ALL WNR (SFL-FSC), (f) Representative CLPD WNR (SFL-FSC). WDF = White blood cell differential; SSC = Side scattered light; SFL = Side fluorescent light; ALL = Acute lymphoblastic leukemia; CLPD = Chronic lymphoproliferative disorder; WNR = White cell nucleated region

Click here to view

As CBC w/diff is done for all samples of hematological malignancies, we aimed to study the patterns of scattergrams of various primary hematological malignancies in the WDF and WNR channel of the Sysmex XN-analyzer. We also aimed to evaluate the ability of Sysmex XN-analyzer in detecting abnormal cells. The objective behind this study was to observe whether specific hematological malignancies create specific scattergram patterns, irrespective of the age of the patient, and total leucocyte count at the time of presentation. Any dissimilarity of patterns in comparison to mostly observed patterns for a specific malignancy was noted. In resource-constrained laboratories and those with high sample load, the established patterns can then be used as a tool for the suspicion of hematological malignancies while screening. Further, laboratory technologist and personnel can be trained to raise an alarm on the observation of such patterns. Necessary tests can then be expedited. These patterns can hence be used as a premicroscopic screening tool for hematological conditions.

  Materials and Methods Top

This was a retrospective study. We collected the details of 291 newly diagnosed cases of hematological malignancies. All these cases were already diagnosed and classified in accordance with flow cytometry, bone marrow morphology study, immunohistochemistry, and molecular studies. Also included were 48 cases of leukemoid reaction. We retrieved the pretreatment CBC w/diff data of these patients. Peripheral blood samples in K2-ethylenediaminetetraacetic acid anticoagulated vacutainer (Beckton Dickinson, San Jose, California, USA) were analyzed in the Sysmex XN-10 hematology analyzer, before their diagnosis. All the samples were processed in CBC w/diff mode within 4 h of collection. The analyzer was maintained with internal quality checks on all levels (low, normal, and high), calibration done once a year and manufacturer-based standard operating procedures followed. We also extracted and compiled the peripheral blood smear report of the cases on the same day that the samples were processed in the analyzer. All of the acute leukemia cases had greater than 20% blast in peripheral smear. All the monocytic leukemias were separated as M5a and M5b depending on the peripheral blood smear findings. The scattergrams in the WDF (SSC-SFL), WDF (SSC-FSC), WDF (FSC-SFL), WNR (SFL-FSC), WNR (SSC-FSC), and WNR (SFL-SSC) were analyzed. Peripheral blood smear evaluation from Giemsa-stained smears was done for all samples. Chronic lymphoproliferative disorders (CLPDs) of only chronic lymphocytic leukemia (CLL) were considered as a single entity. Flags were not considered in our study as it is a retrospective study and also because, without the WPC channel, the utility of flags depends on the personalized laboratory screening protocol.


The present study involved anonymized records and datasets from which it is not possible to identify individuals. Data used in this study were collected retrospectively, and the data were generated for the routine diagnosis and clinical management of patients at a tertiary care hospital in North India, and no additional intervention was made on patients for research purposes. Appropriate individual consents were taken from patients at the time of bone marrow procedures and other molecular tests.

  Results Top

We found different scattergram pattern as follows:

ALL (n = 51) – In 45 cases of ALL, in the WDF (SSC-SFL) plot, we found a single smooth continuous cluster which started from the lymphocyte region moving slightly toward the monocyte region without notching and rising toward the area of higher SFL, as shown in [Figure 1]b and [Figure 2]a. The WNR (SFL-FSC) plot showed cells with clustering of uniform size cells and some cells going toward area of higher FSC region, as shown in [Figure 1]e. Six cases of ALL showed a pattern slightly different from the rest.
Figure 2: (a) Representative ALL WDF (SSC-SFL), (b) Representative AML WDF (SSC-SFL), (c) Representative AML-M3 WDF (SSC-SFL), (d) Representative AML-M4 WDF (SSC-SFL), (e) Representative AML M5a WDF (SSC-SFL), (f) Representative AML M5b WDF (SSC-SFL). ALL = Acute lymphoblastic leukemia; WDF = White blood cell differential; SSC = Side scattered light; SFL = Side fluorescent light; AML = Acute myeloid leukemia

Click here to view

CLPDs (n = 53) – In all the 53 cases of CLPD of CLL type only, in the WDF (SSC-SFL) plot showed a compact cluster which starts at the lymphocyte region and did not rise much to the areas of higher SFL. In 42 out of 53 cases, a small cluster was seen, just below the compact cluster and lying above the area of debris, as shown in [Figure 1]c. As smudge cells were seen in these 42 cases, we conjectured that the cluster probably represents smudge cells. In the WNR (SFL-FSC) plot, as depicted in [Figure 1]f, we found a cluster forming an “inverted comma” shape with trailing of events toward higher FSC. This cluster was seen in 38 out of 53 cases. In all these cases, we found prolymphocyte in the peripheral smear, and so, we hypothesized that these represent prolymphocytic population which showed higher SFL signal.

AML – We found the following AML patterns:

M1 (n = 6) and M2 (n = 14) – In the WDF (SSC-SFL) plot, we found no difference in the patterns of clusters between M1 and M2 cases. It showed two overlapping clusters, one smaller falling in the lymphocyte region and a larger cluster, probably representing blast was lying between the lymphocyte and monocyte region, as shown in [Figure 2]b. The events probably representing blast were showing moderate SFL signal similar in intensity to that of monocyte.

M3 (n = 23) – In all the 23 cases of M3, we saw a similar pattern. Two distinct clusters were seen. One smaller in the lymphocyte region representing normal lymphocyte and a larger cluster, similar to a “tear drop” with a broad base representing the abnormal promyelocytes, as shown in [Figure 2]c. We found no difference in this typical pattern in both hypergranular and microgranular acute promyelocytic leukemia (APL).

M4 (n = 20) – In all the 20 cases, in the WDF (SSC-SFL) plot, we found one large abnormal cluster, which probably represents two overlapping cluster representing myeloblast and monoblast. Some of the events were in the same location as M1/M2, while some events were showing very high-SFL signal touching the top margin of the plot probably representing the monoblasts. The myelocytes and metamyelocytes found in M4 were represented in the immature granulocyte region which falls above the normal neutrophil area in the WDF (SSC-SFL). Representative scattergram is shown in [Figure 2]d.

M5 (n = 42): M5a – In all 27 cases, we saw similar pattern. In the WDF (SSC-SFL) plot, we observed a large cluster at the monocyte region which infringed toward the top margin of the plot indicating events with high-SFL signal. This cluster probably represented the monoblast population. Representative scattergram is shown in [Figure 2]e.

M5b – In all 15 cases, we saw similar pattern in the WDF (SSC-SFL) plot. We observed a cluster which not only included the monocyte region which infringed toward the top margin of the plot indicating events with high-SFL signal, another adjoining cluster below the monoblast cluster, having events with lower-SFL signal was observed which probably represented promonocyte population. Representative scattergram is shown in [Figure 2]f.

CML – In all 53 cases of CML – chronic phase (CP), in the WDF (SSC-SFL) plot, we found significant cluster above the normal neutrophil population. These events represent the myelocyte, metamyelocytes, and band neutrophils. Also seen were excess events in the monocyte region which probably represented early myeloid precursor. Another population typical to the CML cases were seen to the left of the neutrophil toward the area of low side scatter. This cluster probably represents basophil population. [Figure 3]a and [Figure 4]a and [Figure 4]c show representative scattergram of CML-CP in WDF (SSC-SFL) and WNR (SFL-FSC). A total of 16 cases of CML – accelerated phase (AP) and 13 cases of CML – blast phase (BP) were included in the study. [Figure 3]b depicts CML – AP case which showed more than 20% basophil in the peripheral smear, with a prominent cluster in this “basophil region.” In CML – AP and BP, an additional cluster was seen more prominently which represents the blast population. Moreover, according to the different types of blast, the location of the cluster varied which corroborated with the patterns of cluster as described previously for the acute leukemia cases. Representative [Figure 3]c showed monoblast in peripheral smear and also the plot corroborated with the location of blast cluster as described previously for AML M5a pattern.
Figure 3: (a) Representative CML-CP WDF (SSC-SFL), (b) Representative CML-AP WDF (SSC-SFL), (c) Representative CML-BP WDF (SSC-SFL)

Click here to view
Figure 4: (a) Representative CML-CP WDF (SSC-SFL), (b) Representative leukemoid reaction WDF (SSC-SFL), (c) Representative CML-CP WNR (SFL-FSC), (d) Representative leukemoid reaction WNR (SFL-FSC). CML-CP = Chronic myeloid leukemia-chronic phase; WDF = White blood cell differential; SSC = Side scattered light; SFL = Side fluorescent light

Click here to view

Leukemoid reaction – In all 48 cases, in the WDF (SSC-SFL) plot, a prominent cluster was seen above the neutrophil area in the region of immature granulocytes. There was no prominent cluster in the “basophil region.” Representative scattergram pattern is shown in [Figure 4]b for WDF (SSC-SFL), [Figure 4]c for CML-CP WNR (SFL-FSC), and [Figure 4]d for WNR (SFL-FSC).

The findings are summarized in [Table 1].
Table 1: Scattergram patterns on Sysmex XN-analyzer of different hematological conditions

Click here to view

  Discussion Top

Our findings concurred with the findings of Gupta et al. with relation to the patterns of AML in WDF channel of both higher and low to normal total leukocyte count.[6] The blast population were distinctively picked up by the analyzer. In AML M1 and M2 cases, we were not able to differentiate the plot patterns. In the cases of APL, the pattern is found to be definitive in both hypergranular and microgranular APL. This unique pattern will be useful for premicroscopic screening as well as for monitoring the cases of APL on therapy. We were able to further distinguish the patterns of AML FAB type M4 and M5. Even before the examination of peripheral smear microscopy and procedure of immunophenotyping, we can get an initial suspicion of particular type of blast as myeloblast, lymphoblast, and monoblast on observing the location of the particular cluster or events. Furthermore, the abnormal promyelocyte, the promonocyte (i.e., the blast equivalent) were typically found in respective regions and can give us valuable clues while screening.

In cases of CML, we were able to separate the various phase patterns by observing the WDF (SSC-SFL) scattergrams. We also found that CML-CP patterns are different from leukemoid reaction. The major difference lies in the “basophil region” of the WDF (SSC-SFL) scattergram and by the excessive events in the monocyte region which represent abundance of early precursors. Transformation of CML-CP to AP and BP phases can also be suspected from the events in the respective blast regions and the “basophil region” in the WDF (SSC-SFL) scattergram.

ALL and CLPD plot patterns appear similar in some cases. However, in the 51 cases of ALL we studied, the events with higher SFL signal in the WDF (SSC-SFL) were seen in 45 cases than in the CLPD (38 cases had few events with high SFL). Only when prolymphocytic population was more in the peripheral blood smear of CLL, these events with high-SFL signal will be more. It is therefore hypothesized that in cases of diffuse large B-cell lymphomas and other non-Hodgkin lymphoma spill over like in prolymphocytic leukemia/lymphoma, marginal zone lymphoma, and hairy cell leukemia variant, these events with high SFL signal may be more. In our study population, the CLPDs included were only of CLL. Almost all of the 53 cases had compacted clusters with 38 of them showing “inverted comma” trailing toward high SFL in the WNR (SFL-FSC). Furthermore, the presence of a small cluster of cells just below a larger cluster of cells in the lymphocyte region, which is probably the “smudge cell region” is more commonly seen in CLPD than ALL. 42 out of 53 cases showed this cluster.

Scattergrams are characteristically distinctive and when properly observed can be used as screening aid in differentiating various reactive and neoplastic conditions. The pattern analysis of already diagnosed cases of various acute and chronic leukemias confirms the fact that all of these cases do have an individualized plot pattern. The plot patterns can be used for proper triaging of cases for further molecular and cytogenetic evaluation. These patterns with definitive morphological assessment of peripheral blood and bone marrow examination also can be used in monitoring cases on therapy, whether they are in remission or relapse. Our study did not include posttreatment patients. Hence, we cannot opine if treatment might affect these patterns.

  Conclusion Top

The most definitive role and usefulness of these pattern analyses will be in preliminary diagnosis of acute and chronic leukemias in resource-constrained laboratories and also in centers where large sample size is processed everyday. If properly trained to technological staff, the need of evaluation of such cases can be paramount and further tests can then be expedited.


We wish to acknowledge the Department of Laboratory Medicine and the technological staff especially Debashish Jash, Hari Om Mishra, Ambika, Asha, Narayan and Madan Lal. We also wish to acknowledge the technological staff at the Department of Laboratory Oncology, AIIMS, New Delhi, India. We are grateful to Dr. Irshad for his support and encouragement.

Financial support and sponsorship


Conflicts of interest

There are no conflicts of interest.

  References Top

Briggs C, Longair I, Kumar P, Singh D, Machin SJ. Performance evaluation of the Sysmex haematology XN modular system. J Clin Pathol 2012;65:1024-30.  Back to cited text no. 1
Hoyer JD, Fisher CP, Soppa VM, Lantis KL, Hanson CA. Detection and classification of acute leukemia by the Coulter STKS Hematology Analyzer. Am J Clin Pathol 1996;106:352-8.  Back to cited text no. 2
Krause JR, Costello RT, Krause J, Penchansky L. Use of the Technicon H-1 in the characterization of leukemias. Arch Pathol Lab Med 1988;112:889-4.  Back to cited text no. 3
van der Meer W, Swinkels DW, Willems HL. The characterisation of leukaemias with the Sysmex NE-8000. Acta Haematol 1997;98:195-8.  Back to cited text no. 4
Kawarabayashi K, Tsuda I, Tatsumi N, Okuda K. Leukemic blasts detected by the Technicon H-1® blood cell counter. Am J Clin Pathol 1987;88:624-27.  Back to cited text no. 5
Gupta M, Chauhan K, Singhvi T, Kumari M, Grover RK. Useful information provided by graphic displays of automated cell counter in hematological malignancies. J Clin Lab Anal 2018;32:e22392.  Back to cited text no. 6
Virk H, Varma N, Naseem S, Bihana I, Sukhachev D. Utility of cell population data (VCS parameters) as a rapid screening tool for Acute Myeloid Leukemia (AML) in resource-constrained laboratories. J Clin Lab Anal 2019;33:e22679.  Back to cited text no. 7
Schuff-Werner P, Kohlschein P, Maroz A, Linssen J, Dreißiger K, Burstein C. Performance of the XN-2000 WPC channel-flagging to differentiate reactive and neoplastic leukocytosis. Clin Chem Lab Med 2016;54:1503-10.  Back to cited text no. 8
Bruno A, Del Poeta G, Venditti A, Stasi R, Adorno G, Aronica G, et al. Diagnosis of acute myeloid leukemia and system Coulter VCS. Haematologica 1994;79:420-8.  Back to cited text no. 9
Pettitt AR, Grace P, Chu P. An assessment of the Coulter VCS automated differential counter scatterplots in the recognition of specific acute leukaemia variants. Clin Lab Haematol 1995;17:125-9.  Back to cited text no. 10


  [Figure 1], [Figure 2], [Figure 3], [Figure 4]

  [Table 1]

This article has been cited by
1 Identifying Neutrophil Extracellular Traps (NETs) in Blood Samples Using Peripheral Smear Autoanalyzers
Kateryna Fedorov, Mohammad Barouqa, David Yin, Margarita Kushnir, Henny H. Billett, Morayma Reyes Gil
Life. 2023; 13(3): 623
[Pubmed] | [DOI]


Similar in PUBMED
   Search Pubmed for
   Search in Google Scholar for
 Related articles
Access Statistics
Email Alert *
Add to My List *
* Registration required (free)

  In this article
Materials and Me...
Article Figures
Article Tables

 Article Access Statistics
    PDF Downloaded924    
    Comments [Add]    
    Cited by others 1    

Recommend this journal