Leukocytosis and Leukopenia

Burton, Andrew G.; Jandrey, Karl E.

doi:10.1002/9781119028994.ch64

Cited by 7 publications

(4 citation statements)

References 30 publications

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“…Leukocytosis and leukopenia, which are abnormal values (high/low, respectively) in WBC counts, are frequently associated with neutrophil changes, although other leukocytes and neoplastic cells can also cause fluctuations. Neutrophilia is usually related to inflammation, and neutropenia is usually related to greater peripheral use or reduced bone marrow production [17].…”

Section: White Blood Cells and Blood Spectroscopymentioning

confidence: 99%

Point-of-Care Using Vis-NIR Spectroscopy for White Blood Cell Count Analysis

et al. 2022

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Total white blood cells count is an important diagnostic parameter in both human and veterinary medicines. State-of-the-art is performed by flow cytometry combined with light scattering or impedance measurements. Spectroscopy point-of-care has the advantages of miniaturization, low sampling, and real-time hemogram analysis. While white blood cells are in low proportions, while red blood cells and bilirubin dominate spectral information, complicating detection in blood. We performed a feasibility study for the direct detection of white blood cells counts in canine blood by visible-near infrared spectroscopy for veterinary applications, benchmarking current chemometrics techniques (similarity, global and local partial least squares, artificial neural networks and least-squares support vector machines) with self-learning artificial intelligence, introducing data augmentation to overcome the hurdle of knowledge representativity. White blood cells count information is present in the recorded spectra, allowing significant discrimination and equivalence between hemogram and spectra principal component scores. Chemometrics methods correlate white blood cells count to spectral features but with lower accuracy. Self-Learning Artificial Intelligence has the highest correlation (0.8478) and a small standard error of 6.92 × 109 cells/L, corresponding to a mean absolute percentage error of 25.37%. Such allows the accurate diagnosis of white blood cells in the range of values of the reference interval (5.6 to 17.8 × 109 cells/L) and above. This research is an important step toward the existence of a miniaturized spectral point-of-care hemogram analyzer.

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Section: White Blood Cells and Blood Spectroscopymentioning

confidence: 99%

Point-of-Care Using Vis-NIR Spectroscopy for White Blood Cell Count Analysis

et al. 2022

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“…The main reasons for leucocytosis (increased WBC count) are inflammation, effects of stress, corticosteroids, physical activity, and presence of epinephrine [ 17 ]. High WBC counts are mostly associated with neutrophilia and inflammation, whereas neutropenia is mainly caused by increased peripheral tissue demand during intense inflammation and/or decreased bone marrow production [ 18 ]. Due to a substantial reservoir of neutrophils in the bone marrow, dogs and cats rarely experience leukopenia (low WBC count) [ 17 ].…”

Section: Introductionmentioning

confidence: 99%

Reagentless Vis-NIR Spectroscopy Point-of-Care for Feline Total White Blood Cell Counts

Barroso,

Queirós,

Monteiro-Silva

et al. 2024

Biosensors

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Spectral point-of-care technology is reagentless with minimal sampling (<10 μL) and can be performed in real-time. White blood cells are non-dominant in blood and in spectral information, suffering significant interferences from dominant constituents such as red blood cells, hemoglobin and billirubin. White blood cells of a bigger size can account for 0.5% to 22.5% of blood spectra information. Knowledge expansion was performed using data augmentation through the hybridization of 94 real-world blood samples into 300 synthetic data samples. Synthetic data samples are representative of real-world data, expanding the detailed spectral information through sample hybridization, allowing us to unscramble the spectral white blood cell information from spectra, with correlations of 0.7975 to 0.8397 and a mean absolute error of 32.25% to 34.13%; furthermore, we achieved a diagnostic efficiency between 83% and 100% inside the reference interval (5.5 to 19.5 × 109 cell/L), and 85.11% for cases with extreme high white blood cell counts. At the covariance mode level, white blood cells are quantified using orthogonal information on red blood cells, maximizing sensitivity and specificity towards white blood cells, and avoiding the use of non-specific natural correlations present in the dataset; thus, the specifity of white blood cells spectral information is increased. The presented research is a step towards high-specificity, reagentless, miniaturized spectral point-of-care hematology technology for Veterinary Medicine.

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“…Leukocytosis and leukopenia, which are abnormal values (high/low, respectively) in WBC counts, are more frequently associated with neutrophil changes, although other leukocytes and neoplastic cells can also cause fluctuations. Neutrophilia is usually related to inflammation, and neutropenia to greater peripheral use or reduced bone marrow production [1].…”

Section: Introductionmentioning

confidence: 99%

Feasibility of Total White Blood Cells Counts by Visible-Near Infrared Spectroscopy

Barroso

Ribeiro

Gregório

et al. 2021

The 1st International Electronic Conference on Chemical Sensors and Analytical Chemistry

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Total white blood cells (WBC) count is an important indication for infection diagnosis, in both human and veterinary medicine. State-of-the-art WBC counts are performed by flow cytometry combined with light scattering or impedance measurements, in the clinical analysis laboratory. These technologies are complex and difficult to be miniaturized into a portable point-of-care (POC) system. Spectroscopy is one of the most powerful technologies for POC miniaturization due to its capacity to analyze low sample quantities, little to no sample preparation, and ‘real-time’ results. WBC is in the proportion of 1:1000 to red blood cells (RBC), and the latter dominate visible-near infrared (Vis-NIR) information due to their large quantities and hemoglobin absorbance. WBC are difficult to be detected by traditional spectral analysis because their information is contained within the interference of hemoglobin bands. Herein, we perform a feasibility study for the direct detection of WBC counts in canine blood by Vis-NIR spectroscopy for veterinary applications, benchmarking current chemometrics techniques with self-learning artificial intelligence—a new advanced method for high-accuracy quantification from spectral information. Results show that total WBC counts can be detected by Vis-NIR spectroscopy to an average detection limit of 7.8 ×109 cells/L, with an R2 of 0.9880 between impedance flow cytometry analysis and spectral quantification. This result opens new possibilities for reagent-less POC technology in infection diagnosis. As WBC counts in dogs range from 5 to 45 ×109 cells/L, the detection limit obtained in this research allows concluding that the combined use of spectroscopy with this SL-AI new algorithm is a step towards the existence of portable and miniaturized Spectral POC hemogram analysis.

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Leukocytosis and Leukopenia

Cited by 7 publications

References 30 publications

Point-of-Care Using Vis-NIR Spectroscopy for White Blood Cell Count Analysis

Point-of-Care Using Vis-NIR Spectroscopy for White Blood Cell Count Analysis

Reagentless Vis-NIR Spectroscopy Point-of-Care for Feline Total White Blood Cell Counts

Feasibility of Total White Blood Cells Counts by Visible-Near Infrared Spectroscopy

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