(228dk) Mechanically Fingerprinting Blood to Predict Pathological and Physiological Conditions | AIChE

(228dk) Mechanically Fingerprinting Blood to Predict Pathological and Physiological Conditions

Authors 

Helton, T. - Presenter, United States Military Academy
Armstrong, M., United States Military Academy
American Institute of Chemical Engineering

Tyler T. Helton and Matthew J. Armstrong

Department of Chemistry and Life Science, United States Military Academy, West Point, NY 10996

Complex, viscoelastic materials exhibit a change in viscosity depending on the extent of shearing forces placed upon them. The study of these materials is called Rheology. Among these types of materials is blood, a well documented viscoelastic material. An underdeveloped area of study in this field analyzing these mechanical measurements of blood for use in clinical diagnoses. Rheologists have long studied a unique condition of shear flow called large amplitude oscillatory shear (LAOS). The challenge of this condition is its nonlinearity, stemming from the difficulty of modeling the unique internal structure of each material. There is a possibility that blood could be classified using its own unique LAOS signature, and with the addition of large quantities of data for comparison, could be used as a method of diagnoses.

Blood is a great example of a non-Newtonian fluid. It is a suspension red blood cells (RBCs), white blood cells, proteins, hormones, platelets, and other ionic solutes in the blood plasma. This internal microstructure affects the dynamic viscosity of blood when forced into flow conditions. The interactions of the microstructure play a major role in determining the viscosity of blood. RBC aggregation, deformability, and membrane rigidity all contribute to the bloodâ??s viscosity [1]. Plasma proteins, most notably fibrinogen, contribute to the interactions among RBCs as well as platelets [2].

Recent work with blood using LAOS has shown that its unique rheological signature can be used as a psuedo- â??fingerprintâ? [3-7], able to clearly show and delineate elastic and viscous regions of the LAOS cycle. Applying large amplitude oscillatory shear (LAOS) to complex fluids induces nonlinear rheological responses, that, with proper LAOS analysis technique, can be used to sensitively probe the underlying microstructure and its dynamics. Using the previously published blood LAOS data of Sousa et al. [10] we compare LAOS using three published LAOS analysis frameworks, including the aforementioned by Bharadwaj and Ewoldt as well as a novel Series of Physical Processes (SPP) framework [8,9] by Rogers. The techniques will be compared and contrasted and respective strengths and weakness discussed.

For many years, the standard means of analyzing LAOS has been the use of discrete Fourier transforms in order to break down the sinusoidal stress signal, Ï?(t), into elastic and viscous components respectively [14,15]. These components can be used to analyze the extent of the elastic and viscous contributions to the stress signal. A new method of analyzing LAOS data, (SPP), uses all the components of LAOS data used by the rheometer and treats the now three dimensional data as a space curve. SPP also allows for a comparison between the Gâ??and Gâ? analog at every given point. With this advantage, the materials movement between the elastic and viscous regimes can be analyzed.

References

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[2] G.D.O. Lowe. Clinical Science. 71 (1986) 137-146.

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[7] N.A. Bharadwaj and R.H. Ewoldt. J.Rheol. 59(2), (2015) 557-592.

[8] S.A. Rogers. J. Rheol. 56(5), (2012) 1129-1151.

[9] S.A. Rogers and M.P. Lettinga. J. Rheol. 56(1), (2012) 1-25.

[10] P. C. Sousa. Biorheology 50 (2013), 269 â?? 282.

[11] Moreno et al., Korea-Australia Rheology Journal Vol. 27, No.1 (2015) 1 â?? 10.

[12] J. Mewis and N. J. Wagner, Colloidal Suspension Rheology, Cambridge Univ. Press, 2012.

[13] O.K. Baskurt, H.J. Meiselman, Seminars in Thrombosis and Hemostasis. 29(5) (2003) 435-450.

[13] G.D.O. Lowe. Clinical Science. 71 (1986) 137-146.

[14] R.H. Ewoldt, A.E. Hasoi, G.H. McKinley. J. Rheol. 52(6). (2008) 1427-1458.

[15] M.J. Armstrong. PhD Thesis, University of Delaware (2015).