Digital morphology analyzers in hematology: ICSH review and recommendations

Abstract

Introduction Morphological assessment of the blood smear has been performed by conventional manual microscopy for many decades. Recently, rapid progress in digital imaging and information technology has led to the development of automated methods of digital morphological analysis of blood smears. Methods A panel of experts in laboratory hematology reviewed the literature on the use of digital imaging and other strategies for the morphological analysis of blood smears. The strengths and weaknesses of digital imaging were determined, and recommendations on improvement were proposed. Results By preclassifying cells using artificial intelligence algorithms, digital image analysis automates the blood smear review process and enables faster slide reviews. Digital image analyzers also allow remote networked laboratories to transfer images rapidly to a central laboratory for review, and facilitate a variety of essential work functions in laboratory hematology such as consultations, digital image archival, libraries, quality assurance, competency assessment, education, and training. Different instruments from several manufacturers are available, but there is a lack of standardization of staining methods, optical magnifications, color and display characteristics, hardware, software, and file formats. Conclusion In order to realize the full potential of Digital Morphology Hematology Analyzers, pre‐analytic, analytic, and postanalytic parameters should be standardized. Manufacturers of new instruments should focus on improving the accuracy of cell preclassifications, and the automated recognition and classification of pathological cell types. Cutoffs for grading morphological abnormalities should depend on clinical significance. With all current devices, a skilled morphologist remains essential for cell reclassification and diagnostic interpretation of the blood smear.

Cross‐evaluation of five slidemakers and three automated image analysis systems: The pitfalls of automation?

“…However, few have considered the field of analytical haematology solution as a whole. [10][11][12][13][14][15][16][17] There is a need for a comprehensive study evaluating slidemakers and stainers associated with digital microscopy available on the market.…”

Green inclusions in neutrophils: A critical finding that must be reported

“…previous review published by Kratz et al10 documented the benefits and limitations of using CellaVision compared with manual slide microscopy for blood smear review. Among the advantages, the excellent performance among the five normal WBC classes, the easy detection of cellular inclusions or abnormal cells using the images provided by the system and its use in training personnel should be highlighted.…”

Morphogo: An Automatic Bone Marrow Cell Classification System on Digital Images Analyzed by Artificial Intelligence

“…In recent years, there has been an increasing interest in developing computational methods to assist pathologists in histological analysis via digital images [4-6] and artificial intelligence (AI) systems [7]. Automated image processing systems have been developed to address the difficulties of cell classification in blood smear [4-6, 8, 9] and bone marrow aspirate smears [8, 10, 11]. Studies have shown that the CellaVision® DM96 [4, 6, 9] and DI-60 [12] digital systems are an efficient tool to perform leukocyte count and differential in clinical laboratories.…”