Alexander Kratz1, Szu-Hee Lee2, Gina Zini3, Jurgen A Riedl4, Mina Hur5, Sam Machin6. 1. Columbia University Medical Center, NewYork-Presbyterian Hospital, New York, New York. 2. St George Hospital, University of New South Wales, Sydney, New South Wales, Australia. 3. Fondazione Policlinico Universitario A. Gemelli IRCCS - Università Cattolica del Sacro Cuore, Rome, Italy. 4. Department of Clinical Chemistry and Haematology, Albert Schweitzer Hospital, Dordrecht, The Netherlands. 5. Department of Laboratory Medicine, Konkuk University School of Medicine, Seoul, Korea. 6. University College, London, UK.
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.
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.
Authors: Marco Rosetti; Barbara De la Salle; Giorgia Farneti; Alice Clementoni; Giovanni Poletti; Romolo M Dorizzi Journal: Ann Hematol Date: 2021-07-10 Impact factor: 3.673
Authors: Yousra El Alaoui; Adel Elomri; Marwa Qaraqe; Regina Padmanabhan; Ruba Yasin Taha; Halima El Omri; Abdelfatteh El Omri; Omar Aboumarzouk Journal: J Med Internet Res Date: 2022-07-12 Impact factor: 7.076
Authors: Shir Ying Lee; Crystal M E Chen; Elaine Y P Lim; Liang Shen; Aneesh Sathe; Aahan Singh; Jan Sauer; Kaveh Taghipour; Christina Y C Yip Journal: J Pathol Inform Date: 2021-04-07