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. 2022 Feb 1;13(3):1131-1151.
doi: 10.1364/BOE.449046. eCollection 2022 Mar 1.

Complete head cerebral sensitivity mapping for diffuse correlation spectroscopy using subject-specific magnetic resonance imaging models

Melissa M Wu  1 , Katherine Perdue  2 , Suk-Tak Chan  1 , Kimberly A Stephens  1 , Bin Deng  1 , Maria Angela Franceschini  1 , Stefan A Carp  1
Affiliations

Complete head cerebral sensitivity mapping for diffuse correlation spectroscopy using subject-specific magnetic resonance imaging models

Melissa M Wu et al. Biomed Opt Express. .

Erratum in

Abstract

We characterize cerebral sensitivity across the entire adult human head for diffuse correlation spectroscopy, an optical technique increasingly used for bedside cerebral perfusion monitoring. Sixteen subject-specific magnetic resonance imaging-derived head models were used to identify high sensitivity regions by running Monte Carlo light propagation simulations at over eight hundred uniformly distributed locations on the head. Significant spatial variations in cerebral sensitivity, consistent across subjects, were found. We also identified correlates of such differences suitable for real-time assessment. These variations can be largely attributed to changes in extracerebral thickness and should be taken into account to optimize probe placement in experimental settings.

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Conflict of interest statement

MAF has a financial interest in 149 Medical, Inc., a company developing DCS technology for assessing and monitoring cerebral blood flow in newborn infants. MAF’s interests were reviewed and are managed by Massachusetts General Hospital and Mass General Brigham in accordance with their conflict of interest policies (I).

Figures

Fig. 1.
Fig. 1.
: a) The sagittal line (black) and the coronal line (blue). The nasion, head center, and left ear reference points are shown in red. b) Reduced sagittal and coronal lines. c) Lines are drawn connecting two points from the coronal line and one point from the sagittal line. d) Connecting lines are reduced to points.
Fig. 2.
Fig. 2.
a) Final point placement for an example subject, top view. b) Final point placement for same subject, side view. c) Placement of the virtual 1-source 8-detector probes. Sources are red points while detectors are blue points. The sensitivity locations, located at the midpoint of a probe, are shown in black.
Fig. 3.
Fig. 3.
Group average cerebral sensitivity values plotted for s-d distances between 25- and 40-mm. Sensitivity is defined as the recovered percentage increase in CBF from a ground truth increase of 50%.
Fig. 4.
Fig. 4.
Cerebral sensitivity surface plots at 30-mm detector distance for five subjects.
Fig. 5.
Fig. 5.
Average female cerebral sensitivity and average male cerebral sensitivity at the 30 mm s-d separation.
Fig. 6.
Fig. 6.
Average extracerebral thickness for female, male, and all subjects.
Fig. 7.
Fig. 7.
A binned scatter plot of cerebral sensitivity at 30 mm versus distance to brain. Ordinary least squares regression reveals that 75% of the variation in cerebral sensitivity can be explained by the total extracerebral thickness.
Fig. 8.
Fig. 8.
The fraction of photon path length in the brain versus distance to the brain at 30 mm. The relationship is approximately linear.
Fig. 9.
Fig. 9.
Cerebral sensitivity versus the photon penetration through brain tissue at 30 mm.
Fig. 10.
Fig. 10.
Cerebral sensitivity and photon brain penetration versus source-detector separation.
Fig. 11.
Fig. 11.
Scalp versus cerebral sensitivity at 30 mm.
Fig. 12.
Fig. 12.
Ratio of cerebral to scalp sensitivity for the four longer s-d distances.
Fig. 13.
Fig. 13.
Ratio of long-separation (30 mm) baseline BFi to short-separation (5 mm) baseline BFi versus cerebral sensitivity. A moderate R2 value is observed.
See this image and copyright information in PMC

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