BACKGROUND: This UK-based pilot study explores a hybrid approach integrating virtual (VM) and light microscopy (LM), using partial-slide imaging (PSI) at ×20 magnification (equivalent to approximately ×58 effective outpu...BACKGROUND: This UK-based pilot study explores a hybrid approach integrating virtual (VM) and light microscopy (LM), using partial-slide imaging (PSI) at ×20 magnification (equivalent to approximately ×58 effective output magnification). METHOD: This study utilised a 3D Histech Pannoramic MIDI II Slide scanner to digitise 50 peripheral blood smears. PSI was specifically defined by capturing the feathered edge and monolayer regions of the smears. A diverse range of 44 conditions, characterised by distinct morphological features across red blood cell, white blood cell and platelet lineages, was investigated. A comparative analysis between traditional LM and VM was then performed, alongside assessment of scan times and storage requirements, with statistical analyses using Student's t-tests, where a p ≤ 0.05 was considered statistically significant. RESULTS: Excluding parasites, the critical morphological features were reliably assessed, with diagnostic images from VM judged comparable and adequate to LM: the three subcellular features-Döhle bodies, basophilic stippling and Auer rods-were verified side-by-side, while overall 44 features were assessed using a three-point graded scale. Operationally, PSI at ×20 magnification demonstrated substantial efficiency, with a mean scan time of 4 min 17 s and storage of 1.18 GB per slide, representing statistically significant reductions (p < 0.05) in both scanning time and storage compared to whole-slide imaging. CONCLUSION: This pilot-scale study supports a hybrid model, demonstrating that PSI at 20× shows promising feasibility for morphological assessment within a hybrid VM-LM model, but further validation is required to confirm diagnostic equivalence with LM. This study offers significantly reduced scan times and storage requirements compared to whole-slide imaging.
Heritable platelet function disorders (HPFD) are a diverse group of bleeding disorders characterised by a primary qualitative defect in platelet function rather than platelet number. HPFD may be broadly categorised accor...Heritable platelet function disorders (HPFD) are a diverse group of bleeding disorders characterised by a primary qualitative defect in platelet function rather than platelet number. HPFD may be broadly categorised according to the severity of bleeding, with Glanzmann thrombasthenia and Bernard Soulier syndrome classically considered severe HPFD, with well-described clinical and laboratory phenotypes. The remaining non-severe HPFD are less completely characterised and provide additional challenges in diagnosis despite advances in standardising diagnostic approaches for HPFD. Distinguishing patients with non-severe HPFD from patients who do not have a bleeding disorder may be aided by employing bleeding assessment tools early in patient assessment, although there may be limitations according to patient factors. Distinguishing patients with non-severe HPFD from those with acquired platelet function disorders and from those with other heritable disorders of haemostasis (including bleeding disorder of unknown cause) requires more sophisticated clinical and laboratory tools, including platelet light transmission aggregometry, secretion and flow cytometry assays, which can categorise many HPFD to the level of the defective platelet pathway and some to the level of an individual protein. The increasing availability of high-throughput genetic sequencing has made genetic diagnosis possible for some patients with non-severe HPFD; however, this is limited by difficulties with standardisation of laboratory phenotyping and the challenges of distinguishing pathogenic from benign genetic variation. This review will focus on updates in diagnostic approaches for patients with non-severe HPFD since the last IJLH education article on this topic in 2014.
BACKGROUND: Moderate-to-severe thrombocytopenia (platelet count < 100 × 10/L) occurs in fewer than 1% of pregnancies, posing management challenges, particularly surrounding eligibility for neuraxial anesthesia. Although...BACKGROUND: Moderate-to-severe thrombocytopenia (platelet count < 100 × 10/L) occurs in fewer than 1% of pregnancies, posing management challenges, particularly surrounding eligibility for neuraxial anesthesia. Although recent anesthesia guidelines recommend a platelet threshold ≥ 70 × 10/L, outcomes data applying these recommendations in moderate-to-severe thrombocytopenia remain limited. METHODS: We conducted a retrospective study of 306 pregnancy encounters at a tertiary U.S. center (January 2018-December 2022) with ≥ 1 documented platelet count < 100 × 10/L. Etiology, platelet nadir, hematology consultation, treatment patterns, and neuraxial anesthesia (NA) use were assessed from antepartum through postpartum discharge. RESULTS: Gestational thrombocytopenia (gTCP) was the most common etiology (29%, n = 92). Thrombocytopenia severity differed across etiology, with higher platelet nadirs in gTCP (mean 84, median 88.5 × 10/L) compared with ITP (mean 62, median 66 × 10/L). Overall, 15% of pregnancies received hematology consultation, the majority of which were for individuals with ITP, and 78% underwent NA. Among pregnancies complicated by ITP, 71% received NA. Hematology consultation in ITP was associated with lower platelet nadirs and higher treatment rates. CONCLUSIONS: In this cohort of moderate-to-severe thrombocytopenia, institutional adherence to guideline-recommended platelet thresholds was high and associated with excellent neuraxial safety outcomes. These findings provide real-world support for current anesthesia recommendations in a higher-risk obstetric population.
Artificial intelligence (AI) is reshaping every stage of leukemia diagnostics, from digital morphology and multiparameter flow cytometry to next-generation sequencing, multi-omics analysis, and emerging computational fro...Artificial intelligence (AI) is reshaping every stage of leukemia diagnostics, from digital morphology and multiparameter flow cytometry to next-generation sequencing, multi-omics analysis, and emerging computational frontiers such as quantum-inspired feature selection. This review outlines how contemporary AI tools can automate labor-intensive quantitation, flag diagnostically salient patterns, and standardize interpretation, while the pathologist or hematologist retains authority over validation, context-specific integration, and clinical decision-making. We present an illustrative "human-in-the-loop" workflow that embeds AI modules within current laboratory information systems, emphasizing points where expert oversight mitigates algorithmic bias and resolves discordant findings. We further map the validator-integrator role across morphology, flow cytometry, and genomic/multi-omic interpretation and provide practical training competencies and use cases for AI-assisted hematopathology. Beyond technical deployment, the article addresses the educational transformation required for sustainable adoption. Drawing on international competency frameworks, including the Digital Health Competencies in Medical Education Framework and recently proposed AI-specific Entrustable Professional Activities, we map core skills that future hematopathologists must master: data-science literacy, critical appraisal of AI outputs, and ethical governance. We highlight evaluated training models such as the Pathology Informatics Essentials for Residents curriculum, Stanford Artificial Intelligence in Machine and Imaging workshops, and College of American Pathologists bootcamps and propose integration strategies adaptable across resource settings. By pairing rigorous validation with targeted education, AI can elevate rather than eclipse the diagnostic role of the leukemia specialist, enabling more timely, reproducible, and personalized patient care.
Avci Durmusalioglu E, Isik E, Durmus Ozen B
… +11 more, Topaloglu MM, Karadas N, Kavakli K, Sezgin Evim M, Aslan T, Kavak E, Gunes AM, Tayfun Kupesiz F, Kupesiz A, Sahin F, Atik T
Int J Lab Hematol
· 2026 Jun · PMID 42381363
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BACKGROUND: Hemophilia A, an X-linked bleeding disorder caused by pathogenic variants in the F8 gene, requires precise genetic diagnosis for optimal management. Conventional stepwise sequence and copy number variation (C...BACKGROUND: Hemophilia A, an X-linked bleeding disorder caused by pathogenic variants in the F8 gene, requires precise genetic diagnosis for optimal management. Conventional stepwise sequence and copy number variation (CNV) analyses are time-consuming and may leave some cases unresolved. OBJECTIVES: To evaluate the effectiveness of combining next-generation sequencing (NGS)-based sequence and CNV analysis in a single step for resolving previously undiagnosed Hemophilia A cases and identifying differential diagnoses. METHODS: A cohort of 578 male patients with Factor VIII deficiency was assessed. Initial analyses included intron 22/intron 1 inversion testing and/or F8 sequencing. Twenty-seven unresolved cases underwent a targeted 57-gene coagulopathy panel using NGS with CNV analysis; CNVs were confirmed by multiplex ligation-dependent probe amplification (MLPA). RESULTS: The integrated NGS approach resolved 19 of 27 unresolved cases, increasing the overall diagnostic yield from 95.3% to 98.6%. Ten CNVs in F8 (8 deletions, 2 duplications) were identified and confirmed by MLPA. Variants in VWF and LMAN1 genes led to diagnoses of von Willebrand disease (n = 6) and combined Factor V/VIII deficiency (n = 1). One F8 intronic variant was detected, while 8 cases remained unresolved by the NGS-based approach. CONCLUSIONS: Integrating NGS-based CNV analysis into genetic diagnostic workflows enables simultaneous detection of sequence variants and CNVs, improves diagnostic yield, and facilitates identification of related bleeding disorders. This streamlined approach supports adoption as a first-line test for mild/moderate Hemophilia A and a secondary test for severe cases.
Int J Lab Hematol
· 2026 Jun · PMID 42373096
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OBJECTIVE: This study aims to explore the application of BT50-based automatic quality control in the XN9000 hematology analyzer line, comparing its benefits and limitations with manual QC procedures, and to identify pote...OBJECTIVE: This study aims to explore the application of BT50-based automatic quality control in the XN9000 hematology analyzer line, comparing its benefits and limitations with manual QC procedures, and to identify potential improvements, thereby providing a reference for the development of automated QC in clinical laboratories. METHODS: Both manual and automatic QC procedures were performed for blood cell analysis. Manual QC data (January 1, 2024, to July 31, 2024) and automatic QC data (August 1, 2024, to February 28, 2025) were collected from the Department of Clinical Laboratory, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology. SPSS 18.0 software was used for the statistical analysis. The parameters analyzed included the coefficient of variation (CV), daily QC completion time, first sample review time, and staff workload. RESULTS: (1) Compared to manual QC, no statistically significant differences were observed in the CV values of any parameters between the two methods (Mann-Whitney U test, p > 0.05 for all). (2) The median completion time for automatic QC was 42 min earlier than that for manual QC, with automatic QC finishing at 07:48:47 (IQR: 07:47:55, 07:48:46) and manual QC finishing at 08:30:34 (IQR: 08:24:17, 08:37:32). (3) With a daily work start time of 08:00, the median first sample review time was advanced by 20 min under automatic QC, with manual QC reviewed at 08:48:00 (IQR: 08:36:00, 08:50:30) and automatic QC reviewed at 08:28:00 (IQR: 08:21:30, 09:07:30). (4) The automatic QC system significantly reduced the number of manual steps, including those for storage, rewarming, mixing, and post-analysis storage. CONCLUSION: Implementing the automatic QC system facilitates earlier report review, reduces workload, enhances operational efficiency, and maintains CV values within acceptable laboratory standards.
Limpornpugdee O, Kaewkhruawan J, Riyagoon P
… +8 more, Laiklang W, Masalae W, Tanticharoenkarn S, Chaiwong K, Pipatnavakij P, Limprasert P, Ketloy C, Prompetchara E
Int J Lab Hematol
· 2026 Jun · PMID 42362477
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OBJECTIVES: Centrifugation requirements differ between coagulation and clinical chemistry testing, potentially limiting workflow efficiency and total laboratory automation (TLA). Coagulation assays typically require stan...OBJECTIVES: Centrifugation requirements differ between coagulation and clinical chemistry testing, potentially limiting workflow efficiency and total laboratory automation (TLA). Coagulation assays typically require standard centrifugation at 1500 g for 15 min, whereas chemistry samples use a rapid protocol at 2300 g for 5 min. This study evaluated the impact of rapid centrifugation on prothrombin time (PT), activated partial thromboplastin time (APTT), and D-dimer results. METHODS: Blood samples were prospectively collected from volunteers in 3, 2, and pediatric 1 mL citrate tubes and were processed using standard or rapid centrifugation. Testing was performed for PT, APTT, and D-Dimer on Sysmex CN3000 and ACL-TOP 750 analyzers, with residual platelet counts assessed. RESULTS: A total of 130 samples were analyzed (41 from 3 mL tubes, 41 from 2 mL tubes, and 39 from 1 mL tubes). Rapid centrifugation produced significantly higher residual platelet counts than the standard protocol (39.2 × 10/L vs. 18.8 × 10/L, p < 0.0001). Strong correlations (r > 0.9) were observed for PT and APTT across analyzers, while D-dimer results on ACL-TOP 750 showed slightly lower correlation (r = 0.830). Bland-Altman analysis demonstrated small mean biases (< 1% for PT and APTT). D-dimer biases from CN3000 and ACL-TOP 750 were 1.06% and -2.70%, respectively, which remained within the predefined total allowable error. Residual platelets showed no impact on test results. CONCLUSIONS: Rapid centrifugation at 2300 g for 5 min provides coagulation results comparable to the standard protocol and may facilitate integration of coagulation testing into TLA workflows.
Int J Lab Hematol
· 2026 Jun · PMID 42350267
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INTRODUCTION: Hypobaric hypoxia at higher residential altitudes may modify routine laboratory parameters and complicate their interpretation in emergency care. We examined associations between altitude (0-2500 m) and lab...INTRODUCTION: Hypobaric hypoxia at higher residential altitudes may modify routine laboratory parameters and complicate their interpretation in emergency care. We examined associations between altitude (0-2500 m) and laboratory findings and developed a hemoglobin estimation model. METHODS: This single-center, retrospective cross-sectional study included 2302 patients aged ≥ 1 year admitted to the Emergency Department of Kars Harakani State Hospital on January 1-3 and July 1-3, 2024. Patients were categorized as children (1-17 years) or adults (≥ 18 years). Hematological and biochemical results were retrieved from electronic records. Altitude-laboratory associations were analyzed using correlation and linear regression. A multivariable regression model was constructed to identify determinants of hemoglobin variation. RESULTS: Among 2302 admissions, 30.8% were pediatric. Hemoglobin, hematocrit, erythrocyte indices, pO, and SaO demonstrated the most consistent altitude-related patterns. In adults, altitude showed positive associations with glucose, urea, creatinine, COHb, MetHb, calcium, ALT, AST, bilirubin, and selected erythrocyte and platelet indices, and negative associations with SaO, pO, PLT, PCT, GFR, and HCO (all p < 0.05). Most parameters were not significantly associated with altitude in children. SaO and pO were lower in summer than winter (p < 0.05). The final model explained 83% of hemoglobin variability, incorporating altitude, age, sex, smoking, pregnancy, malignancy, and chronic disease. CONCLUSION: Residential altitude was associated with measurable variation in hematological, biochemical, and oxygenation parameters among emergency department patients. Altitude should be considered when interpreting laboratory results in clinical practice. The proposed hemoglobin model integrates altitude and clinical variables to characterize hemoglobin variability within this cohort.
Int J Lab Hematol
· 2026 Jun · PMID 42332980
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Clonal hematopoiesis (CH) is increasingly recognized as a significant biological phenomenon in aging and cancer, marked by the expansion of hematopoietic stem and progenitor cells harboring somatic mutations in genes ass...Clonal hematopoiesis (CH) is increasingly recognized as a significant biological phenomenon in aging and cancer, marked by the expansion of hematopoietic stem and progenitor cells harboring somatic mutations in genes associated with myeloid neoplasms. While CH is strongly linked to a spectrum of inflammatory diseases and hematologic malignancies, its role in shaping responses to cancer immunotherapy-especially chimeric antigen receptor (CAR) T cell therapy-has only recently begun to emerge. This review explores the interplay between CH and CAR T cell therapy, highlighting CH prevalence in treated populations, post-therapy clonal dynamics, inflammatory toxicities, and risk of therapy-related myeloid neoplasms. We also discuss the differential effects of specific CH mutations on hematopoiesis, immune cell function, and CAR T cell persistence. Understanding the functional implications of CH in the context of CAR T cell therapy holds the potential to refine patient selection, tailor toxicity management, and develop personalized immunotherapeutic approaches.
Int J Lab Hematol
· 2026 Jun · PMID 42332924
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INTRODUCTION: This study aimed to evaluate the analytical performance and screening performance of fragmented red cell (FRC) enumeration by the reticulocyte (RET) channel of the Sysmex XN-9000 automated hematology analyz...INTRODUCTION: This study aimed to evaluate the analytical performance and screening performance of fragmented red cell (FRC) enumeration by the reticulocyte (RET) channel of the Sysmex XN-9000 automated hematology analyzer and to determine its correlation with manual microscopy with a specific focus on the confounding effects of microcytosis and hypochromia. METHODS: Peripheral blood samples from 209 patients with anemia who had positive FRC% flagged by the analyzer and 200 healthy individuals were analyzed. The FRC percentage (FRC%) was measured both by the automated analyzer and by standard manual microscopy. Statistical analyses, including correlation studies, receiver operating characteristic (ROC) curve, and Bland-Altman agreement analysis, were performed. RESULTS: The area under the ROC curve for instrument-measured FRC% was 0.927, indicating potential diagnostic screening performance. Using manual microscopy as the reference method, the correlation coefficient for FRC% measured by the RET channel was 0.66, indicating a moderate correlation between the two methods. Bland-Altman analysis revealed a mean bias of -0.91% (limits of agreement: -4.61% to 2.79%) with 78.9% of instrument results reading higher than microscopy. The upper reference limit for FRC% in the healthy cohort was established at 0.17%. CONCLUSION: The automated FRC% measurement on the XN-9000 serves as an effective screening tool. However, confirmatory manual microscopic review remains essential for samples with positive automated results or those exhibiting abnormal MicroR% and Hypo-He% values.
Int J Lab Hematol
· 2026 Jun · PMID 42332409
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INTRODUCTION: Multiple myeloma (MM) is a heterogeneous plasma cell (PC) malignancy in both clinical presentation and genetic profile. Cytogenetic characterization, particularly by interphase fluorescence in situ hybridiz...INTRODUCTION: Multiple myeloma (MM) is a heterogeneous plasma cell (PC) malignancy in both clinical presentation and genetic profile. Cytogenetic characterization, particularly by interphase fluorescence in situ hybridization (FISH), is critical for risk stratification and treatment decisions. FISH results depend on the PC infiltration rate in bone marrow (BM); therefore, CD138-positive immunoselection is required to overcome reduced FISH sensitivity due to low infiltration. We evaluated the performance of automated PC immunoselection compared to the manual method. METHODS: We retrospectively analyzed data from 715 BM samples sent for routine FISH testing between 2019 and 2024. PCs were isolated manually (n = 351) or automatically (n = 364). BM infiltration was assessed by flow cytometry (FC) and/or cytomorphology. FISH analysis was performed using a primary panel with three DNA probes or an expanded panel with additional probes. Confirmed diagnoses were obtained from clinical records. RESULTS: FISH was successfully performed in 81% of samples, with automated processing achieving a higher success rate (86% vs. 75%, p < 0.001). Automated processing provided higher PC yields, enabling testing with expanded probe sets. Chromosomal abnormalities were detected in more than 90% of confirmed MM cases, regardless of isolation method. PC infiltration strongly predicted FISH success, with infiltration of ≥ 3% corresponding to an 80% probability of successful FISH. CONCLUSIONS: Automated immunoselection improves PC yield, enabling broader FISH testing compared to manual processing. Information on PC infiltration obtained by cytomorphology or FC, which indicates sample quality, can support quality assessment in the cytogenetics laboratory.
Int J Lab Hematol
· 2026 Jun · PMID 42322062
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INTRODUCTION: Morphologic evaluation of peripheral blood (PB) smears and bone marrow aspirates (BMA) remains central to the diagnosis of acute leukemias, particularly for the identification and quantification of blasts....INTRODUCTION: Morphologic evaluation of peripheral blood (PB) smears and bone marrow aspirates (BMA) remains central to the diagnosis of acute leukemias, particularly for the identification and quantification of blasts. However, this process is time-consuming, operator-dependent, and subject to inter-observer variability. Recent advances in artificial intelligence (AI), particularly deep learning, have enabled the development of automated systems for leukocyte classification and blast detection. METHODS: We performed a narrative review of the literature on AI-based approaches for morphologic evaluation in hematology, focusing on blast recognition and leukemia screening. Both classical machine learning and deep learning methodologies were analyzed, along with their application to PB smears and BMA samples. In addition, currently available commercial digital morphology platforms were reviewed with respect to their performance in blast detection. RESULTS: Classical machine learning approaches demonstrated good performance on maturing cells of most lineages, and moderate performance in blast recognition, limited by reliance on manually selected features. Deep learning models, particularly convolutional neural networks, achieved improved accuracy and near-human performance in PB smear analysis, with reported sensitivities and specificities often exceeding 90% for blast detection. However, performance in BMA analysis remains more variable due to increased cellular complexity. Commercial platforms show high concordance with manual microscopy for mature leukocyte classification, but more modest accuracy for immature and neoplastic cells, including blasts. CONCLUSION: AI-based digital morphology systems are promising tools for supporting morphologic evaluation in hematology laboratories. While current platforms improve efficiency and standardization, limitations in blast detection accuracy and generalizability prevent their use as standalone diagnostic tools. Further development, including large-scale validation and improved model interpretability, will be essential for their integration into routine clinical practice. The International Council for Standardization in Haematology (ICSH) presently suggests prudence in the widespread clinical adoption of AI-driven bone marrow analysis systems, except within environments that are properly validated, approved by regulatory authorities, and supported by rigorous quality assurance measures. Their integration into routine practice will require broader validation, regulatory approval, and quality assurance frameworks.