International Journal of Laboratory Hematology最新文献

Introduction

Of all the cells identified in peripheral blood smears, reactive lymphocytes (RLs) and blasts are considered especially difficult to differentiate. Blasts and RLs are present in distinct diseases that carry unique prognoses and treatments; however, there are currently no definitive methods to distinguish these cells morphologically.

Methods

We developed a method to distinguish between blasts and RLs based on the quantification of fractal chromatin patterns. Nuclei from white blood cell images were isolated, and the fractal patterns were quantified using The Workflow of Matrix Biology Informatics (TWOMBLI) software. Quantified fractals were compared using the t-test. The data was further split into training and testing sets. Models (random forest and k-nearest neighbors) were selected through cross-validation on the training sets. Performance metrics, including area under the curve (AUC), accuracy, precision, specificity, and sensitivity, were determined for the selected models on the testing sets. Principal component analysis (PCA) was also performed.

Results

Our most general model was able to identify RLs and blast subtypes with an average 84.2% accuracy and an AUC of 0.844. Testing on the holdout set gave every model an area under the curve greater than 0.815. PCA revealed two components that account for 50% of the data's variance.

Conclusion

Our results suggest that a classification algorithm can effectively distinguish between blasts and RLs based solely on fractal chromatin patterns. It is possible that a similar algorithm could be utilized in the clinical hematology laboratory to assist in distinguishing RLs and blasts in peripheral blood smears.

Introduction

Plasma mixing tests are frequently performed in haemostasis laboratories to aid in the determination of the cause of prothrombin time or activated partial thromboplastin time (APTT) prolongation. The International Council for Standardization in Haematology (ICSH) has recently published recommendations for performing and interpreting mixing test; we evaluated the ICSH recommendations for APTT mixing tests on patient samples using automated mixing on a Sysmex CN-series analyser.

Methods

Samples from patients with haemophilia A with and without inhibitors, or patients with positive lupus anticoagulant, or patients on rivaroxaban/edoxaban, with an APTT ≥ 4 s above normal, were tested using five different APTT reagents: Siemens Actin FS, Actin FSL, and Pathromtin SL; and Hyphen Biomed Cephen and Cephen-LS.

Results

A likely/possible inhibitor was erroneously diagnosed in all haemophilia patients when assessed using the ICSH criteria, except with Actin FS (erroneous diagnosis in 95%). Using CN-series parameters with locally-derived reference ranges, ≤ 15% of haemophilia patients were erroneously diagnosed.

Only Cephen-LS reliably detected lupus anticoagulant by any algorithm.

Conclusions

When using lupus-insensitive reagents, APTT-mixing tests are of limited value in discriminating between factor deficiencies, lupus anticoagulants, or inhibitors. Incubated mixing tests are essential when diagnosing a FVIII-inhibitor.

Rather than perform mixing tests, it is better to be guided by clinical presentation and perform further investigations as appropriate, including analysis of anti-Xa activity for the presence of a direct factor-Xa inhibiting anticoagulant, factor assays in patients with bleeding (or with suspected acquired haemophilia A), and lupus anticoagulant assays in patients with no bleeding.

Background

Early diagnosis plays a crucial role in improving the survival rate of acute leukemia (AL) patients. This study aims to develop a warning model for the detection of acute leukemia (AL) using complete blood count (CBC) and cell population data (CPD), which could aid in clinical diagnosis.

Methods

In this study, CBC and CPD were utilized to develop a warning model for assisting clinical diagnosis of AL. Clinical characteristics and peripheral blood data were retrospectively collected from 262 AL patients and 280 non-AL patients at the Second Hospital of Lanzhou University; they were randomly divided into a training set and a test set in a ratio of 7:3. The training set was used to establish support vector machine (SVM), random forest (RF), and logistic regression (LR) models for AL. The validation set consisted of 357 cases (97 AL, 260 non-AL) collected from the General Hospital of Ningxia Medical University to verify the warning efficacy of the optimal model in conjunction with the test set.

Results

The comparative analysis revealed that the SVM model outperformed the RF and LR models in terms of diagnostic accuracy. In the training set, the accuracy was 92.93%; the area under the ROC curve (AUC) and 95% confidence interval (95% CI) were 0.981 (0.970, 0.992). For the test set, the accuracy was 89.66%; the AUC and 95% CI were 0.959 (0.931, 0.988). As for the validation set, the accuracy was 76.34%; the AUC and 95% CI were 0.841 (0.789, 0.893). Additionally, the calibration curve and decision curve analysis (DCA) demonstrated that the SVM model exhibited satisfactory effectiveness and feasibility.

Conclusion

The SVM model shows significant potential as a clinical screening tool for AL.

Introduction

Imaging flow cytometry (IFC) is a unique method combining multiparameter flow cytometry (MFC) with morphological evaluation of single cells. Since both analyses are integrated in the diagnostic work-up of myelodysplastic neoplasms (MDS), we wanted to explore the possibilities of IFC as a diagnostic tool for MDS, with focus on dyserythropoiesis.

Methods

We analysed fresh bone marrow (BM) aspirates from 26 patients with untreated MDS and MDS/MPN and compared them with 12 normal BM specimens (NBM) exploring the cytoplasmic compartment, nuclear abnormalities, and megaloblastoid changes.

Results

The cytoplasmic compartment in MDS showed higher contrast and variance values compared to NBM (p < 0.001). Cells with abnormal nuclei and binucleated forms were significantly increased in MDS compared to NBM (p < 0.05 for both features). Most binucleated forms were found in the mature compartment, and many of them were G1 phase arrested. All maturation stages showed a significant increase in cell size in MDS compared to NBM (p < 0.001). In addition, we found decreased nuclear condensation combined with increased cell size for all erythropoietic maturation stages in MDS compared to NBM (p < 0.001). Finally, our previously described MDS-specific aberrant population of mature erythroblasts with decreased expression of CD36 and/or CD71 showed denser chromatin than both the mature erythropoietic MDS cells without immunophenotypic aberrancies (p < 0.001) and NBM (p = 0.024).

Conclusion

IFC can detect the major morphological changes associated with dyserythropoiesis in MDS, including the novel findings of increased cytoplasmic texture and bilobated non-proliferating erythroblasts, allowing for objectivity and standardization.

Purpose

This study examines the protein expression and mRNA levels of myeloperoxidase (MPO) in patients with Kikuchi's disease, and explores the association between the MPO-463G/A polymorphism and Kikuchi's disease.

Methods

Paraffin blocks from 43 patients with Kikuchi's disease were collected, and paraffin blocks from patients with reactive hyperplastic lymph nodes, granulomatous inflammation, and myeloid sarcoma were used as controls. Immunohistochemistry (IHC), quantitative reverse transcription polymerase chain Reaction (qRT-PCR) and Sanger sequencing were used to detect the relevant variants.

Results

The positive rate of MPO protein expression in the Kikuchi's disease group was 100% by IHC. In comparison to the control group, patients with Kikuchi's disease exhibited elevated MPO mRNA expression levels, which demonstrated a positive correlation with protein expression levels. Kikuchi's disease and reactive hyperplastic lymph nodes displayed distinct genotypes at the MPO-463 locus, with mutation phenotypes of 7% and 30%, respectively. The G allele at this locus emerged as a risk factor.

Conclusions

In Kikuchi's disease, both the protein and mRNA expression levels of MPO are elevated, and the high expression of mRNA is positively correlated with the protein expression levels. The polymorphism at the MPO-463 locus may be associated with the occurrence of Kikuchi's disease.

Introduction

The clinical diagnosis of hematological diseases depends on the differential count of nucleated cells on the bone marrow (BM) smears, and an artificial intelligence (AI)-based system was applied to automatically classify BM nucleated cells in pediatric hematological disease samples in this study.

Methods

The BM aspirate smears were collected from 213 pediatric patients (under 18 years old) at Harbin Medical University Affiliated Sixth Hospital from October 2023 to June 2024. The entire smear of BM was scanned by a ×40 objective lens to obtain complete digital images using an automated analysis method named Morphogo. Next, Morphogo was used to capture nucleated cells in an area of BM smears that was selected by hematopathologists, with a magnification of ×100 objective lens.

Results

Morphogo demonstrated a high overall accuracy (> 87.8%) in pre-classifying nucleated cells in BM aspirate smears obtained from masked pediatric patients. In addition, the average values of sensitivity and accuracy in Morphogo cell classification were remarkably high. Moreover, Morphogo could reduce the time costs on classifying BM nucleated cells. Besides, there were positive correlations between Morphogo and manual categorization for immunologic thrombocytopenic purpura, BM failure, hyperplastic anemia, acute leukemia, chronic myeloid leukemia, and other hematological diseases.

Conclusion

This research demonstrated the clinical potential of the Morphogo in early screening of pediatric hematological diseases and its reliability as an automated tool for differential counting and analysis of BM nucleated cells.

Introduction

KMT2A-Partial Tandem Duplication (KMT2A-PTD) is a recurrent gene mutation present in acute myeloid leukemia (AML) and its prognostic significance needs to be clarified.

Methods

Three hundred and eighty-seven consecutive adult newly diagnosed AML patients with non-favorable cytogenetic risk were tested for KMT2A-PTD by real-time quantitative PCR. All patients were screened for AML-related gene fusions and mutations.

Results

Thirty-two (8.3%) patients were identified as KMT2A-PTD (+). KMT2A-PTD significantly co-occurred with FLT3-ITD, RUNX1, and DNMT3A mutation and tended to be related to normal karyotype (p < 0.0001, p = 0.0001, 0.019, and 0.062). Furthermore, none of the KMT2A-PTD (+) patients had NPM1 mutation, CEBPA bZIP in-frame mutation (p = 0.0005 and 0.0009), and none of them had KMT2A-rearrangement and other gene fusions (p = 0.16). As a result, all KMT2A-PTD (+) patients were categorized into ELN2022-intermediate or adverse groups (p < 0.0001). KMT2A-PTD was not related to patients' age, sex, white blood cell (WBC) counts, hemoglobin (Hb) level, platelet (PLT) counts, percentage of bone marrow blast cells, and FAB subtypes (all p > 0.05). KMT2A-PTD had no effect on complete remission achievement after 1 and 2 courses of induction therapy, relapse-free survival, and overall survival in both the entire cohort and within the following five subgroups: FLT3-ITD (+), RUNX1 mutation, DNMT3A mutation, ELN2022-intermediate, and ELN2022-adverse categories, respectively (all p > 0.05). Moreover, KMT2A-PTD (+) patients also could not be stratified by them (all p > 0.05).

Conclusion

KMT2A-PTD harbored its distinct genetic characteristics and had no prognostic impacts in AML.

Introduction

Discordant fibrinogen antigen to activity ratios are utilized by clinicians as evidence of dysfibrinogenemia. Abnormal ratio cutoffs implemented by clinical laboratories are typically determined by validation studies that include limited numbers of samples. We here utilize large datasets of stored clinical results and apply indirect reference interval (RI) methodology to determine fibrinogen ratio cutoffs suggestive of dysfibrinogenemia.

Methods

Panel results comprised of fibrinogen antigen and activity measurements and calculated ratios of antigen to activity were retrieved for analysis. Two datasets were analyzed: (1) 3693 unique patient results in which antigen concentrations were measured by radial immunodiffusion (RID) from January 2019 to April 2023, and (2) 2192 patient results with antigen concentrations measured using turbidimetry immunoassay between April 2024 and March 2025. Both datasets were analyzed using the RefineR algorithm to estimate the corresponding RI of fibrinogen activity and antigen, and ratio cutoffs.

Results

Estimated fibrinogen antigen/activity ratio cutoffs were within close range (< 8% difference) to the validated cutoffs used by our laboratory: 1.17 versus 1.23 and 1.06 versus 1.01 using antigen RID and turbidimetry assays, respectively. Contrarily, estimated upper RI limits of antigen and activity were higher by 38.4%–57.2% than validated limits, and RI was wider by 41.8%–76%.

Conclusion

The RefineR algorithm could be used to determine fibrinogen ratio cutoffs with the advantage of including significantly larger numbers of available clinical results. For antigen and activity, the algorithm could not separate out acute-phase elevated fibrinogen (activity and antigen) results and overestimated the upper RI limits relative to the clinically validated cutoffs.