Lena Vaclavu^{1}, Zelonna Baldew^{1}, Sanna Gevers^{1}, Veronica van der Land^{2}, Henri JMM Mutsaerts^{3}, Karin Fijnvandraat^{2}, John C Wood^{4}, Charles BLM Majoie^{1}, Ed T vanBavel^{5}, Bart J Biemond^{6}, Aart J Nederveen^{1}, and Pim van Ooij^{1}

Hemodynamic parameters such as wall shear stress(WSS) may be adversely affected in Sickle Cell Disease(SCD). Vaso-occlusion is a common complication leading to ischemic organ damage. We investigated how impaired hemodynamics (velocity, WSS, flow and lumen area) relate to ischemic white matter lesions(WMLs). Our aim was to quantify age-related changes in hemodynamics and to investigate their relationship with WMLs. 14 controls and 69 patients underwent 4D-flow MRI. We assessed intracranial velocity, WSS, flow and lumen area in the circle of Willis. We show that 4D-flow parameters are decreased in patients with WMLs, but age is an important factor in this relationship.

[1] Switzer JA, Hess DC, Nichols FT, Adams RJ (2006) Pathophysiology and treatment of stroke in sickle-cell disease: present and future. The Lancet Neurology, 5:501-512.

[2] Barabino GA, McIntire LV, Eskin SG et al. (1987) Endothelial cell interactions with sickle cell, sickle trait, mechanically injured, and normal erythrocytes under controlled flow. Blood, 70:152-157

[3] Vermeer SE, Longstreth WT, Koudstaal PJ (2007) Silent brain infarcts: a systematic review. The Lancet Neurology, 6:611-619.

[4] Wu C, Honarmand AR, Schnell S, Kuhn R, Schoeneman SE, Ansari SA, Carr J, Markl M, Shaibaniet A (2016) Age-Related Changes of Normal Cerebral and Cardiac Blood Flow in Children and Adults Aged 7 Months to 61 Years. Journal of the American Heart Association 5(1):e002657.

[5] Detterich J, Alexy T, Rabai M, Wenby R, Dongelyan A, Coates T, Wood J, Meiselman H (2013) Low-shear red blood cell oxygen transport effectiveness is adversely affected by transfusion and further worsened by deoxygenation in sickle cell disease patients on chronic transfusion therapy. Transfusion 53: 297-305.

[6] Potters WV, van Ooij P, Marquering H, vanBavel E, Nederveen AJ. (2015) Volumetric arterial wall shear stress calculation based on cine phase contrast MRI. Journal of Magnetic Resonance Imaging 41: 505-516.

[7] Scheltens PH, Barkhof F, Leys D, Pruvo JP, Nauta JJP, Vermersch P, Steinling M, Valk J (1993) A semiquantative rating scale for the assessment of signal hyperintensities on magnetic resonance imaging. Journal of the Neurological Sciences 114:7-12.

[8] Adams RJ, McKie VC, Carl EM, Nichols FT, Perry R, Brock K, McKie K, Figueroa R, Litaker M, Weiner S, Brambilla D (1997) Long-term stroke risk in children with sickle cell disease screened with transcranial Doppler. Annals of Neurology 42:699-704.

Figure 1. A) Hematocrit-dependent viscosity
values used for subject-specific wall shear stress estimation. The viscosity relative
to hematocrit is higher in sickle cell blood than healthy blood, but this
difference is small^{5} at shear rates >1000s-1. B) Flow
and lumen area were calculated from 4D-flow data in single planes placed
perpendicular to the vessels of interest.

Figure 2. Age-related changes in velocity, wall shear stress, flow and lumen area in the MCAs in 69 Sickle Cell Disease (SCD) patients and 14 controls. Data
points are the mean of the left and right MCAs, and the line shows an exponential
fit with correlation coefficients indicated by r-values.

Figure 3. A) shows the FLAIR MRI of a 12-year old patient with Sickle
Cell Disease (SCD) with no white matter lesions(WMLs) and high wall shear
stress(WSS) relative to the entire cohort. B) shows the FLAIR MRI of a 56-year
old patient with SCD with many lesions and relatively low WSS. C) shows that
average WSS in the circle of Willis correlated inversely with the amount of WMLs
in patients with SCD. D) shows that average velocity in the circle of Willis
correlated inversely with the WML score. E) shows the age-related increase in
WMLs in SCD.

Table 1. Subject characteristics and 4D-flow MRI hemodynamic parameters.
P-values show results from a T-test, and from a univariate model with age as a
covariate. The final column provides correlation coefficients (r) for the
age-related decline from a one-term exponential fit with 4D Flow MRI parameters
in patients only.

Table 2. Correlation coefficients for white matter lesion scores and 4D-flow
parameters in 69 patients with Sickle Cell Disease. Correlation coefficients corrected for age are provided in the final column. Note that when age is
taken into account, the relationship between WMLs and velocity and WSS are not
significant.