In the Buckley Lab’s latest publication in Biomedical Optics Express, Vidisha Goyal et al. demonstrate the reliability of Broadband Absorption Spectroscopy (BAS) to measure water content in the adult human head in a variety of different environments. To date, BAS estimates of water have primarily been focused on in vitro validation studies and in vivo breast cancer applications. Recent work has demonstrated that BAS may be sensitive to brain water content in a pig model. While initial studies are promising, BAS has yet to be used to quantify brain water content in the adult human head. In this work, we take the first steps towards demonstrating the feasibility of BAS to reliably measure water content in the adult human head. Demonstrating that BAS can deliver reproducible measurements is crucial for its adoption in both research and clinical settings. Our results suggest the approach is feasible and repeatable, and lay the groundwork for future studies that establish the sensitivity of BAS to cerebral edema.

Congratulations to Vidisha Goyal for being awarded the American Heart Association (AHA) Predoctoral Fellowship for her proposal entitled “Assessment of Cerebral Edema in Subarachnoid Hemorrhage patients using Broadband Absorption Spectroscopy”! After brain injury, the water content in the brain can increase, leading to devastating consequences as the brain compresses within the confines of the skull. This 2yr fellowship will help fund foundational experiments that develop a new non-invasive optical monitor of brain water content that can be used at the bedside to one day help guide patient care.

In the Buckley Lab’s latest publication “Stand-alone segmentation of blood flow pulsatility measured with diffuse correlation spectroscopy,” Srinidhi Bharadwaj and Tara Urner et al. present a signal processing method for isolating blood flow pulses from noisy diffuse correlation spectroscopy (DCS) signals. Importantly, this method does not require the use of an exogenous reference signal – such as from a blood pressure or electrocardiography machine – to identify pulse onsets, which has been the standard approach. When compared to blood pressure-based pulse segmentation in a cohort of 30 subjects, the stand-alone method performed comparably, demonstrating the wide applicability of the technique. Removing the need for an exogenous reference signal will allow broader application of promising pulse analysis techniques to DCS-derived blood flow waveforms, which show promise as biomarkers of cerebrovascular health.  MATLAB code implementing the method is available from the Buckley Lab’s public Github page.

Comparison of BFI segmentation with stand-alone vs. reference-based method. A. Representative DCS-derived blood flow signal (blue), filtered waveform used for stand-alone segmentation (green), and time aligned arterial blood pressure (ABP) signals (red). Dashed vertical lines in green and red represent onsets identified from the filtered signal and ABP, respectively. B. Overlaid pulses from the window in A, normalized to unit length. Green denotes individual pulses segmented with the stand-alone method and red denotes pulses segmented using ABP. Vertical lines denote 20 equally sized bins used for averaging. C. Resulting mean (stdev) BFI waveforms obtained using the filtered DCS signal or ABP as a reference signal. D. Schematic depiction of pulse morphology features quantified. Abbreviations: mean flow (MF), peak systolic flow (PSF), end diastolic flow (EDF), amplitude (AMP), and area under the curve (AUC).