Automatic 3-Dimensional Visualization of Peripheral Blood Slides: A New Approach for the Detection of Infection/Inflammation at the Point of Care

Abstract

Context.—The identification and quantitation of the intensity of the acute-phase response at the point of care might be of clinical relevance. Objective.—To report the possibility of automatic screening of unstained peripheral blood slides by using a 3-dimensional image analysis system. Design.—Peripheral venous blood was obtained from children with acute inflammation/infection and examined by an automatic 3-dimensional image analyzer to detect the number of white blood cells as well as to reveal the degree of erythrocyte aggregation, a marker of the humoral phase response. Results.—We included 66 children with acute bacterial infections and 59 with nonbacterial inflammation/infection; mean ages of the 2 groups were 4.3 ± 3.9 years and 4.2 ± 3.7 years, respectively (P = .91). The percentages of correct classifications based on discriminant analysis in predicting between bacterial and nonbacterial inflammation/infection were 61.3% by using the white blood cell count, 64.5% by using the percentage of granulocytes, 61.6% by using the degree of erythrocyte aggregation, and 59.2% by using the number of leukocytes counted on the unstained slides. The results of the receiver-operated characteristic curve analysis yielded an area under the curve of 0.714 (P < .001) for the number of granulocytes, 0.699 (P < .001) for the white blood cell count, 0.685 (P < .001) for the number of leukocytes on the slides, and 0.685 (P = .001) for the degree of erythrocyte aggregation. The correlation between the number of leukocytes by the electronic cell analyzer and the number of cells counted on the slides was highly significant (r = 0.85, P < .001). Conclusions.—It is feasible to use an automatic 3-dimensional image analyzer to reveal the different intensities of the acute-phase response between a group of children with an acute bacterial infection and another with nonbacterial inflammation/infection. These findings might be relevant for potential application at the point of care.

Quantitative Measurement of Erythrocyte Aggregation as a Systemic Inflammatory Marker by Ultrasound Imaging: A Systematic Review

“…• Among pediatric patients with infection and\or inflammation, n = 125 (Urbach et al 2005). • Among patients with acute ischemic neurologic events, n = 60 (Anuk et al 2002).…”

“…Some studies noted significant reductions in erythrocyte aggregation and improved hemorheological profiles (Allegra et al 1995;Nicolaides 2003) after lowering the inflammatory state through lifestyle modifications (Raz et al 2007;Sandor US assessment of erythrocyte aggregation and inflammation • P. Gyawali et al et al 2014) or by the use of anti-inflammatory therapeutic agents (Ge et al 2016;Jiang and Lian 2015;Kelly and Dominguez 2010;Li et al 2015;Szentkereszty et al 2014). Lastly, some studies (n = 15) underscored erythrocyte aggregation as a superior or independent marker of inflammation (Anuk et al 2002;Assayag et al 2005Assayag et al , 2008Berliner et al 2002Berliner et al , 2005Gyawali et al 2016;Levin et al 2006;Maharshak et al 2002;Rotstein et al 2002a;Sharshun et al 2003;Urbach et al 2002Urbach et al , 2003Urbach et al , 2005Vayá et al 2013b) or sepsis (Yeom et al 2017). Only 1 study reported increased erythrocyte aggregation with aging and associated it with increase in inflammation (Vayá et al 2013a).…”