Project Summary
Silent cerebral infarction is a serious consequence of sickle cell disease (SCD), affecting ~40% of patients by
age 15. Although these injuries accumulate occultly, they are linked with cognitive deficits, diminished school
performance, and increased risk of overt stroke. Our long-term goal is to develop a low-cost brain monitoring
tool that can screen for silent infarct risk in pediatric SCD to facilitate timely therapeutic intervention and that can
optimize these interventions to mitigate adverse events. Silent infarcts in SCD are thought to arise from anemia-
induced microvascular perfusion abnormalities and subsequent reduced cerebrovascular reserve that is
insufficient to meet tissue metabolic demands. Thus, quantification of abnormalities in microvascular cerebral
blood flow, vascular reactivity, and/or oxygen extraction may be useful in identifying infarct risk. Indeed, recent
MRI studies have shown that SCD children with silent infarcts have globally elevated oxygen extraction in both
white and grey matter compared to those without infarct. However, current modalities that quantify microvascular
hemodynamic parameters (e.g., PET, MRI) are prohibitively expensive, have limited availability, and require
anesthesia in children <6y, making them inappropriate as routine screening tools. Transcranial Doppler
ultrasound measures of macrovascular blood flow velocity have had great success in reducing the risk of overt
strokes of the macrovasculature by <80%; however, ultrasound is not sensitive to silent microvascular infarcts.
Thus, there is an unmet clinical need for a low-cost, non-invasive tool sensitive to microvascular, tissue-level
cerebral hemodynamic abnormalities in pediatric SCD to detect children at risk for silent infarcts.
Diffuse optical spectroscopies (namely frequency domain near-infrared spectroscopy combined with diffuse
correlation spectroscopy, FDNIRS/DCS) may provide a user-friendly, cost-effective alternative to current
technologies. These non-invasive techniques use near-infrared light to relate measured changes in light intensity
detected at the tissue surface to hemodynamic properties of the underlying tissue. Combined, FDNIRS/DCS
enable assessment of oxygen extraction, an index of cerebral blood flow, and an index of cerebral oxygen
metabolism. Further, using a simple breath hold challenge, FDNIRS/DCS can assess cerebrovascular reactivity,
the vasculature’s ability to dilate in response to carbon dioxide. Our preliminary results show that FDNIRS/DCS
can detect expected trends in brain oxygen extraction and blood flow in SCD patients (i.e., elevated compared
to controls, inverse correlation with hemoglobin). Moreover, we have developed new analytical strategies that
improve the accuracy of the DCS-measured blood flow index by accounting for the influence of hematocrit.
Building on this preliminary data, the overall objective of this proposal is to validate our DCS hematocrit-
correction against “gold-standard” perfusion MRI, to determine if FDNIRS/DCS is sensitive to cerebral
hemodynamic abnormalities in patients with silent infarcts, and to demonstrate FDNIRS/DCS can assess real-
time changes in cerebral hemodynamics during transfusion, which reduces silent infarct risk in SCD patients.