Cellular Morphologic Analysis of Peripheral Blood

Peterson, Powers; McNeill, Sheila; Gulati, Gene

doi:10.1002/9781444398595.ch2

Cited by 14 publications

(15 citation statements)

References 67 publications

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“…Thus, all hematology laboratories must be encouraged to establish locally valid protocols indicating when a BSR and MDLC should be performed. The guidelines suggested by the ISLH can be the starting point as long as they are interpreted in consideration of the experience of the laboratory staff, sophistication of the hematology analyzers and the laboratory's electronic records system, and incidences of abnormalities and variations in reference values of the population being tested 6, 7. Thus, this study evaluated the implementation of the RC suggested by the ISLH in the HC-UFPR Hematology Laboratory in order to determine automated thresholds such that microscopic analyses are performed only under special circumstances.…”

Section: Introductionmentioning

confidence: 99%

Are the review criteria for automated complete blood counts of the International Society of Laboratory Hematology suitable for all hematology laboratories?

Comar

Malvezzi

Pasqüini

2014

Revista Brasileira de Hematologia e Hemoterapia

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Objectiveto verify whether the review criteria for automated blood counts suggested by the International Consensus Group for Hematology Review of the International Society for Laboratory Hematology are suitable for the Hematology Laboratory of Hospital de Clinicas, Universidade Federal do Paraná.Methodsinitially, the review criteria of the International Society for Laboratory Hematology were adapted due to limitations in the Institution's electronic hospital records and interfacing systems. The adapted review criteria were tested using 1977 samples. After this first assessment, an additional 180 inpatient samples were analyzed to evaluate the screening criteria of the review criteria in conjunction with positive smear findings established by the institution. The performance of the review criteria was verified by determining false positive, false negative, true positive and true negative rates, sensitivity, specificity, positive predictive value, negative predictive value, microscopic review rate and efficiency.Resultsinitial analysis showed false negatives = 6.73%, false positives = 23.27%, microscopic review rate = 46.03% and efficiency = 70.0%. An evaluation of the screening criteria adapted from the review criteria together with the positive smear findings of the institution showed false negatives = 15.5%, false positives = 10.5%, microscopic review rate = 37.3% and efficiency = 73.8%. In both situations the safety limit (false negative <5%) recommended by the review criteria was exceeded.Conclusionsthe review criteria adapted from the International Society for Laboratory Hematology are neither suitable nor safe for use in the hematology laboratory of the Hospital de Clinicas. This implies a need to develop and validate institution-specific review criteria in order to decrease false negative results to an acceptable and safe rate for patients.

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Section: Introductionmentioning

confidence: 99%

Are the review criteria for automated complete blood counts of the International Society of Laboratory Hematology suitable for all hematology laboratories?

Comar

Malvezzi

Pasqüini

2014

Revista Brasileira de Hematologia e Hemoterapia

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“…(I) Original image of1 a LGL and2 a villous lymphocyte from a SMZL acquired by the DM96. (II) ‘ u ’ colour component (from the Luv colour space) in greyscale obtained in MATLAB.…”

Section: Methodsmentioning

confidence: 99%

New quantitative features for the morphological differentiation of abnormal lymphoid cell images from peripheral blood

et al. 2017

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“…Modern automated blood analysis instruments include impedance analyzers and flow cytometers. While being very effective in terms of throughput, these instruments offer limited information . For example, while these instruments have the ability measure erythrocyte volume and hemoglobin (Hb) concentrations, they are unable to measure erythrocytic morphologic abnormalities and variations in cell shape .…”

Section: Hematological Diagnosis Using Qpimentioning

confidence: 99%

Quantitative phase imaging for medical diagnosis

Majeed

Sridharan

Mir

et al. 2016

Journal of Biophotonics

148

100

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Optical microscopy is an indispensable diagnostic tool in modern healthcare. As a prime example, pathologists rely exclusively on light microscopy to investigate tissue morphology in order to make a diagnosis. While advances in light microscopy and contrast markers allow pathologists to visualize cells and tissues in unprecedented detail, the interpretation of these images remains largely subjective, leading to inter‐ and intra‐observer discrepancy. Furthermore, conventional microscopy images capture qualitative information which makes it difficult to automate the process, reducing the throughput achievable in the diagnostic workflow. Quantitative Phase Imaging (QPI) techniques have been advanced in recent years to address these two challenges. By quantifying physical parameters of cells and tissues, these systems remove subjectivity from the disease diagnosis process and allow for easier automation to increase throughput. In addition to providing quantitative information, QPI systems are also label‐free and can be easily assimilated into the current diagnostic workflow in the clinic. In this paper we review the advances made in disease diagnosis by QPI techniques. We focus on the areas of hematological diagnosis and cancer pathology, which are the areas where most significant advances have been made to date.

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Cellular Morphologic Analysis of Peripheral Blood

Cited by 14 publications

References 67 publications

Are the review criteria for automated complete blood counts of the International Society of Laboratory Hematology suitable for all hematology laboratories?

Are the review criteria for automated complete blood counts of the International Society of Laboratory Hematology suitable for all hematology laboratories?

New quantitative features for the morphological differentiation of abnormal lymphoid cell images from peripheral blood

Quantitative phase imaging for medical diagnosis

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