Leukocytic Disorders

Hutchison, Robert; Schexneider, Katherine I.

doi:10.1016/b978-1-4377-0974-2.00033-6

Cited by 6 publications

(2 citation statements)

References 337 publications

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“…Thus, a good early stratification is needed to achieve outcome. As it is not a single disease, it may be distinguished from other malignant lymphoid disorders by the immunophenotype of the cells [1,28,[47][48][49][50].…”

Section: Discussion: I-methodsmentioning

confidence: 99%

The genetic abnormalities investigation of leukemia in past few decades

Rahnemoon¹

2021

CRCT

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Cytogenetic and molecular analysis of each patient’s leukemia cells has become an essential component of diagnosis prior to treatment. It has furthered our understanding of leukemogenesis at a molecular level. Specific and well-characterized recurring chromosomal abnormalities facilitate diagnosis, confirm subtype classification, and have major prognostic value for treatment planning. Conventional chromosome analysis is a basic way for diagnosis and treatment. In addition in this way evaluation of disease progression is important and so it is the only method that can identify the presence of clonal evolution, particularly in accelerated and relapse phase in the disease. Also conventional cytogenetic can detect chromosomal abnormality associated with its advanced phase. Anyhow, the value of translocation rates in interphase and metaphase nuclei in monitoring leukemia is at the time of diagnosis and after treatment additionally. Genomic profiling transformed our understanding of the genetic basis of leukemia particularly in acute leukemia, which is a malignant clonal proliferation in lymphoid stem cells or myeloid progenitor cells.

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Section: Discussion: I-methodsmentioning

confidence: 99%

The genetic abnormalities investigation of leukemia in past few decades

Rahnemoon¹

2021

CRCT

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“…There are five major types of white blood cells, lymphocytes, monocytes, neutrophils, eosinophils, and basophils, that can be analyzed independently as part of a WBC differential count. Abnormal numbers of WBCs are often correlated with inflammation, infection, immune deficiencies, and blood disorders . Rare cells (e.g., circulating tumor cells) or infecting species (e.g., bacteria or parasites) can also be found in peripheral blood and are of significant diagnostic interest.…”

Section: Capillary Action Enables Simple Microfluidic Devicesmentioning

confidence: 99%

Beyond Wicking: Expanding the Role of Patterned Paper as the Foundation for an Analytical Platform

et al. 2017

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While a number of assays for soluble analytes have been developed using paper-based microfluidic devices, the detection and analysis of blood cells has remained an outstanding challenge. In this Feature, we discuss how the properties of paper determine the performance of paper-based microfluidic devices and permit the design of cellular assays, which can ultimately impact disparities in healthcare that exist in limited-resource settings.

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White blood cell detection, classification and analysis using phase imaging with computational specificity (PICS)

Fanous

Sengupta

et al. 2022

Sci Rep

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Treatment of blood smears with Wright’s stain is one of the most helpful tools in detecting white blood cell abnormalities. However, to diagnose leukocyte disorders, a clinical pathologist must perform a tedious, manual process of locating and identifying individual cells. Furthermore, the staining procedure requires considerable preparation time and clinical infrastructure, which is incompatible with point-of-care diagnosis. Thus, rapid and automated evaluations of unlabeled blood smears are highly desirable. In this study, we used color spatial light interference microcopy (cSLIM), a highly sensitive quantitative phase imaging (QPI) technique, coupled with deep learning tools, to localize, classify and segment white blood cells (WBCs) in blood smears. The concept of combining QPI label-free data with AI for the purpose of extracting cellular specificity has recently been introduced in the context of fluorescence imaging as phase imaging with computational specificity (PICS). We employed AI models to first translate SLIM images into brightfield micrographs, then ran parallel tasks of locating and labelling cells using EfficientNet, which is an object detection model. Next, WBC binary masks were created using U-net, a convolutional neural network that performs precise segmentation. After training on digitally stained brightfield images of blood smears with WBCs, we achieved a mean average precision of 75% for localizing and classifying neutrophils, eosinophils, lymphocytes, and monocytes, and an average pixel-wise majority-voting F1 score of 80% for determining the cell class from semantic segmentation maps. Therefore, PICS renders and analyzes synthetically stained blood smears rapidly, at a reduced cost of sample preparation, providing quantitative clinical information.

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Leukocytic Disorders

Cited by 6 publications

References 337 publications

The genetic abnormalities investigation of leukemia in past few decades

The genetic abnormalities investigation of leukemia in past few decades

Beyond Wicking: Expanding the Role of Patterned Paper as the Foundation for an Analytical Platform

White blood cell detection, classification and analysis using phase imaging with computational specificity (PICS)

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