Bone marrow aspirate (BMA) analysis remains a fundamental pillar of hematological diagnosis, routinely used for diagnosis, assessment of treatment response, and follow up of a wide range of adults and pediatric benign and malignant hematological conditions. ¹ Despite its crucial importance and the recent changes in digital workflows and processes, the workflow surrounding BMA review has changed little over the years. BMA remains heavily dependent on manual microscopy, which is time-consuming, labor-intensive, and vulnerable to variability in technique and expertise. These factors can introduce inconsistency in classification and interpretation. ^{1, 2} To understand the slow transformation it is important to go back to the basics of understanding the BMA workflow, identifying the clinical and operational pain points, identifying key gaps where digital solutions can accelerate progress and early adoption.

The Multi-Step, High-Stakes Process

The BMA workflow begins at the bedside, where a clinician aspirates the sample and prepares slides for staining and review. Screening is often carried out by a clinical laboratory scientist, followed by detailed evaluation at 100× oil immersion by a hematologist or pathologist. ^{2, 3} 

A typical manual assessment includes: ⁴

• Differential counts of 500–1,000 nucleated cells
• Identification of myeloid and erythroid lineages
• Megakaryocyte evaluation
• Cellularity assessment
• Iron stain interpretation
• Reporting of morphology, abnormalities, and relevant clinical impressions, often by two separate specialists, particularly in life-threatening or difficult cases.

Clinical and Operational Pain Points

While effective in principle, this traditional process faces an increasing number of systemic constraints. 

Workforce limitations

• A shrinking pool of experienced specialists ^{5, 6, 7}
• Increasingly complex morphological assessment across numerous cell types ^{8, 9}
• Growing diagnostic demand that outpaces available expertise ^{6, 10}

Technical and operational factors

• Variability in slide preparation, staining, and selection of regions of interest ³
• Significant time required to review hundreds of cells per case ⁵
• Long-term physical storage requirements for slides ³

Workflow Variability Across Institutions

Approaches to BMA review differ from one institution to the next, depending also on their physical location, whether in a resource-heavy big city or a resource-depleted rural area. Turnaround times may range from two hours to several days. Some laboratories rely on technicians to screen and perform differentials, whereas others require full review by hematopathologists. Preparation methods (smear, squash, imprint), and staining practices also vary widely. ^{3, 11, 12} This variability, coupled with microscope dependency and staff shortages, impacts consistency, efficiency, and diagnostic accuracy.

The Case for Digital BMA Hematology Solutions

Scopio Labs’ Full-Field Bone Marrow Aspirate Platform introduces a digital hematology workflow that directly addresses these challenges. It represents the first platform to deliver: ^{1, 13}

• 100x digital slide scanning with full-field navigation and review
• AI-powered decision support for 500-cell differentials across 16 categories
• Remote review capabilities within secure hospital networks
• Standardized reporting integrated with LIS systems
• Quality control tools for particle and precursor cell assessment

Rather than limiting users to predefined regions, the system allows comprehensive slide review, mimicking the manual workflow while providing enhanced control, flexibility, and precision.

Evidence-Based Performance in Digital BMA Microscopy

In a 2024 multicenter study spanning 795 BMA specimens across three clinical sites, Scopio’s digital pathology platform was evaluated against manual microscopy and demonstrated high accuracy and reproducibility: ¹ 

• 1,385 cell analysis per case on average, exceeding diagnostic standards
• Above 90 % efficiency: for Romanowsky and Prussian Blue staining
• Approximately 82 % sensitivity and above 92 % specificity 
• 91.1 % Inter-operator agreement, reflecting consistency across users

These results support the platform’s ability to improve diagnostic quality while enhancing specialized clinical judgment and expert collaboration.

Designed for Modern Laboratory Realities

Digitizing the BMA workflow helps address longstanding issues such as microscope dependency, variable technical quality, limits on remote collaboration, and fragmented communication between teams. Features like adjustable analysis zones, multi-slide case management, and customizable reporting allow the system to fit easily into existing routines while improving throughput and reproducibility. ^{1, 13}

The Future of Hematology Diagnostics

The clinical relevance of bone marrow aspirate analysis is undeniable, but the methodology needs to rapidly evolve. Digital hematology offers a clear path forward: reducing variability, enhancing collaboration, and supporting more confident and timely clinical decisions. For hematologists, pathologists, and lab leaders alike, the case for transformation is clear and already underway.

Ready to learn more about digital bone marrow analysis? Contact us to see how Scopio’s platform can transform your hematology workflow.

Disclaimer: Scopio’s Full-Field Bone Marrow Aspirate Application is CE-marked and cleared  for sales in additional regions. Not commercially available in the US for in vitro diagnostic procedures 

References: 

1. Bagg A, Raess PW, Rund D, Bhattacharyya S, Wiszniewska J, Horowitz A, et al. Performance Evaluation of a Novel Artificial Intelligence-Assisted Digital Microscopy System for the Routine Analysis of Bone Marrow Aspirates. Mod Pathol. 2024;37(9):100542. doi: 10.1016/j.modpat.2024.100542. https://pubmed.ncbi.nlm.nih.gov/38897451/
2. Zhou S, Ran L, Yao Y, Wu X, Liu Y, Wang C, et al. VFM-SSL-BMADCC-Framework: vision foundation model and self-supervised learning based automated framework for differential cell counts on whole-slide bone marrow aspirate smears. Front Med (Lausanne). 2025;12:1624683. doi: 10.3389/fmed.2025.1624683.
3. Rindy LJ, Chambers AR. Bone Marrow Aspiration and Biopsy. [Updated 2023 May 29]. In: StatPearls [Internet]. Treasure Island (FL): StatPearls Publishing; 2025 Jan-. Available from: https://www.ncbi.nlm.nih.gov/books/NBK559232/
4. Lee SH, Erber WN, Porwit A, Tomonaga M, Peterson LC; International Council for Standardization In Hematology. ICSH guidelines for the standardization of bone marrow specimens and reports. Int J Lab Hematol. 2008;30(5):349-64. doi: 10.1111/j.1751-553X.2008.01100.x. https://pubmed.ncbi.nlm.nih.gov/18822060/
5. Garcia E, Kundu I, Kelly M, Soles R. The American Society for Clinical Pathology 2022 Vacancy Survey of medical laboratories in the United States. Am J Clin Pathol. 2024;161(3):289-304. doi: 10.1093/ajcp/aqad149 https://pubmed.ncbi.nlm.nih.gov/37936416/
6. Garcia E, Diaz J, Kundu I, Kelly M, Soles R. The American Society for Clinical Pathology 2024 Vacancy Survey of medical laboratories in the United States. Am J Clin Pathol. 2025 Nov 19;164(5):759-777. doi: 10.1093/ajcp/aqaf101 https://pubmed.ncbi.nlm.nih.gov/41017742/
7. Sharma D, Wallace N, Levinsohn EA, Marshall AL, Kayoumi K, Madero J, et al. Trends and factors affecting the US adult hematology workforce: a mixed methods study. Blood Adv. 2019;3(22):3550-3561. doi: 10.1182/bloodadvances.2019000307 https://pubmed.ncbi.nlm.nih.gov/31738829/
8. Lewis JE, Pozdnyakova O. Digital assessment of peripheral blood and bone marrow aspirate smears. Int J Lab Hematol. 2023;45 Suppl 2:50-58. doi: 10.1111/ijlh.14082. https://pubmed.ncbi.nlm.nih.gov/37211430/ 
9. Katz BZ, Moshe Y, Bensity D, Luttwak E, Brazilai M, Oster HS, et al. Next-generation morphology, a novel multilayer morphometric digital analysis, reveals both the basic topology and new trends of myelodysplasia of peripheral blood specimens. Br J Haematol. 2025. doi: 10.1111/bjh.70110. https://pubmed.ncbi.nlm.nih.gov/40878790/
10. Gedefaw L, Liu CF, Ip RKL, Tse HF, Yeung MHY, Yip SP, Huang CL. Artificial Intelligence-Assisted Diagnostic Cytology and Genomic Testing for Hematologic Disorders. Cells. 2023;12(13):1755. doi: 10.3390/cells12131755 https://pubmed.ncbi.nlm.nih.gov/37443789/
11. Bhatt RD, Shrestha C, Risal P. Factors Affecting Turnaround Time in the Clinical Laboratory of the Kathmandu University Hospital, Nepal. EJIFCC. 2019 Mar 1;30(1):14-24. PMID: 30881271 https://pubmed.ncbi.nlm.nih.gov/30881271/
12. Kim H, Hur M, d’Onofrio G, Zini G. Real-World Application of Digital Morphology Analyzers: Practical Issues and Challenges in Clinical Laboratories. Diagnostics (Basel). 2025;15(6):677. doi: 10.3390/diagnostics15060677 https://pubmed.ncbi.nlm.nih.gov/40150020/
13. Data on file. Scopio Labs Full-Field Bone Marrow AspirateTM Application Product Playbook Nov 2024