(Tuesday, 7/31/2018) 11:00 AM - 12:15 PM
Room: Davidson Ballroom B
Purpose: To optimize Quantitative Ultrasound techniques to assess microstructural changes in brain tissue with exposure of the young Rhesus macaque to inhaled anesthetics.
Methods: 14, 2-7 day-old Rhesus macaques were exposed for 5hrs to sevoflurane (SEVO). A Siemens Acuson S3000 scanner with a phased-array transducer operated at 10MHz was used to acquire radiofrequency (RF) echo signals from the thalamus at 0hrs and 6hrs after initiating SEVO exposure. QUS biomarkers Effective Scatterer Size (ESS) and Acoustic Concentration (AC) were estimated by fitting a scattering form factor model (FF) to the FF measured from RF signals. Optimization steps included: (1) Identification of high spectral SNR bandwidth of the entire data set, (2) analysis of the frequency-dependence of the measured FF to identify discontinuities related to different scattering sources, (3) selection of the FF model based on a χ² goodness of fit criterion, and (4) comparison of ESS and AC changes after SEVO exposure between the left and right thalamus. The statistical significance of percent changes in ESS and AC between 0hrs and 6hrs was assessed with the Wilcoxon rank-sum test.
Results: Over the high spectral SNR bandwidth (3.2 MHz to 8.7 MHz), average measured FF at 0hrs and 6hrs monotonically decreased with frequency. This justified fitting a single form factor over this bandwidth. χ² values of a continuous Gaussian FF model were 10 times smaller than those of the discrete fluid sphere model. From the 6 subjects that showed agreement between left and right thalamus, 6 showed significant changes in ESS (5 reductions, 1 increase), and 4 showed significant AC changes (3 reductions, 1 increase).
Conclusion: Preliminary results suggest that a continuous scatterer model better represents ultrasound scattering in the young Rhesus brain. Reduction of ESS derived from this model suggests potential to detect changes in brain microstructure related to anesthesia.
Funding Support, Disclosures, and Conflict of Interest: The authors thank Dr. Quinton Guerrero for helping in data acquisition and Dr. Kevin Noguchi for histopathology analysis. Supported by NIH grants R01HD072077 and R01HD083001-01A1; WNPRC pilot award P51OD011106; seed funding from Instituto de Fisica, UNAM; UNAM PAPIIT IA104518 and IN107916. Equipment loan and technical support by SIEMENS Healthcare.
Keywords
Ultrasonics, Brain, Quantitative Imaging
Taxonomy
IM- Ultrasound : Quantitative imaging/analysis
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