Developing Methods for Precision High-Density Diffuse Optical Tomography

2419 

Abstract Submission 

Aahana Bajracharya¹, Dana Wilhelm², Zachary Markow³, Morgan Fogarty³, Wiete Fehner³, Jonathan Peelle⁴, Tmara Hershey⁵, Joseph Culver²

¹Washington University in St.Louis, St. Louis, MO, ²Washington University School of Medicine, St. Louis, MO, ³Washington University in St. Louis, St. Louis, MO, ⁴Northeastern University, Boston, MA, ⁵Washington University in St. Louis, Saint Louis, MO

Aahana Bajracharya, MA, MS  
Washington University in St.Louis
St. Louis, MO

Dana Wilhelm  
Washington University School of Medicine
St. Louis, MO

Zachary Markow  
Washington University in St. Louis
St. Louis, MO

Morgan Fogarty, MS  
Washington University in St. Louis
St. Louis, MO

Wiete Fehner, MS  
Washington University in St. Louis
St. Louis, MO

Jonathan Peelle, PhD  
Northeastern University
Boston, MA

Tmara Hershey  
Washington University in St. Louis
Saint Louis, MO

Joseph Culver, PhD  
Washington University School of Medicine
St. Louis, MO

Neuroimaging research has traditionally approached data reliability through large-N consortium studies. However, in recent years, precision mapping studies, focusing on obtaining a high signal-to-noise ratio from a small group of individuals, have opened new avenues of exploring brain function [1]. Precision mapping takes a subject-specific approach to localize spatial and organizational variability in brain networks [2,3]. Although widely known in functional magnetic resonance imaging (fMRI) literature, this approach is yet to be established in optical imaging. In this study, we demonstrate the effectiveness of using High-Density Diffuse Optical Tomography (HD-DOT) to generate high-fidelity single-subject cortical maps [4]. HD-DOT is an optical imaging technique that uses dense, regularly spaced arrays of sources and detectors to obtain overlapping measurements of the underlying neuronal activity based on the absorption properties of hemoglobin in the blood [5-8]. We use an imaging system consisting of 128 sources and 125 detectors, with over 2500 measurements providing state-of-the-art HD-DOT image quality and extended cortical coverage (with a flatfield depth sensitivity >50% max, that extends to 20 mm beneath the scalp surface). Unlike fMRI, HD-DOT has a significant advantage of conducting scans while seated comfortably in a quiet and naturalistic environment.

We collected 4-6 hours of data from previously validated tasks (retinotopy, hearing words, finger tapping/tongue movement, and generating verbs) and resting-state paradigms over multiple visits on 4 subjects (2M, 2F) (Fig1A). While fMRI data can be easily co-registered to anatomical scans, HD-DOT depends on measured and simulated cap positions for image reconstruction. To address this issue, we developed an iterative process of comparing cortical activations using functional localizers and photometric validation of cap placement. This process involved placing the cap onto the participant's head by aligning the back row of fiber tips to the inion and symmetrically positioning the side panels over the ear with reference to the tragus (Fig1B). A silicone stencil with cap position marked from the first session was used to register subsequent sessions in addition to photometric references. Data pre-processing was done based on the principles of modeling light emission, diffusion, and detection through the head using the NeuroDOT toolbox [7]. We used global variance of temporal derivative (GVTD) [8] to identify motion artifacts in data frames and the strength of the cardiac pulse signal to assess data quality (Fig 1C). A voxel-wise general linear model framework was used to estimate the task responses and generate statistical maps of cortical activations.

Fig 2A shows task activation maps averaged across all sessions of data in each participant. A spherical seed (radius = 5mm) around the peak activation voxel of the functional localizers was used to generate resting state functional connectivity (RSFC) maps. Fig 2B shows five sessions of unthresholded beta maps while Sub-1 viewed a flashing checkerboard stimulus presented in the bottom right quadrant. Fig 2C shows RSFC map from five rest sessions with a seed placed in the left visual cortex. Fig 2D-E shows the correlation between the maps generated from concatenated sessions of data with smaller windows of this data. The overarching premise of precision mapping is that the maps become more stable as the number of trials or duration of data increases.

Accurate single-subject mapping can inform changes in functional brain activity over time. This valuable resource helps to understand individual brain organization while also improving group-level analyses. We demonstrate the feasibility of using HD-DOT to carry out precision mapping using task-based and resting state paradigms which can cater to a wide variety of participants, including children and individuals with implanted medical devices that are contraindicated by MRI.

Activation (eg. BOLD task-fMRI)

Connectivity (eg. functional, effective, structural)

Cortical Anatomy and Brain Mapping ²

NIRS ¹

OPTICAL

Other - functional brain mapping; precision imaging; high-density diffuse optical tomography; functional near infrared spectroscopy; optical imaging; resting state functional connectivity; single-subject