Neuroimaging During Motion with Portable, Wearable Diffuse Optical Tomography
Presented During:
Thursday, June 27, 2024: 11:30 AM - 12:45 PM
COEX
Room:
Grand Ballroom 104-105
Poster No:
2424
Submission Type:
Abstract Submission
Authors:
Hannah DeVore1, Alvin Agato1, Calamity Svoboda2, William Hamic1, Anthony O'Sullivan2, Michelle Hedlund1, Sean Rafferty2, Jason Trobaugh1, Adam Eggebrecht2, Edward Richter1, Joseph Culver2
Institutions:
1Washington University in St. Louis, St. Louis, MO, 2Washington University School of Medicine, St. Louis, MO
First Author:
Co-Author(s):
Introduction:
While neuroimaging technologies have improved and expanded their capabilities, there has long been a gap in traditional neuroimaging technologies for a noninvasive, high-resolution, portable modality that tolerates participant movement. Established technologies like EEG may be used in real-world settings, but suffer from poor resolution, SNR, and motion susceptibility, while MRI has good spatial resolution, but creates a loud, cramped, unnatural scanning environment. MRI and PET are also stationary, and contraindicated in some populations. Wearable diffuse optical tomography (DOT) systems bridge this gap; our new wearable, high-density (WHD) DOT system offers portability and flexibility like EEG, spatial resolution similar to MRI, and improved robustness against motion artifacts versus fiber-based DOT systems.
DOT is an optical technique that uses multiple, overlapping measurements from high-density imaging arrays to generate 3D tomographic reconstruction of cortical blood oxygenation dynamics (Fig 1a). As with MRI, neuronal activity is inferred from blood oxygenation via neurovascular coupling. While fiber-based DOT systems have been extensively validated against MRI over the last decade, full head fiber DOT systems require that the subject's head remains relatively still. New, wearable DOT systems have recently begun to provide similar imaging performance with the added advantage of permitting subject movement.
DOT is an optical technique that uses multiple, overlapping measurements from high-density imaging arrays to generate 3D tomographic reconstruction of cortical blood oxygenation dynamics (Fig 1a). As with MRI, neuronal activity is inferred from blood oxygenation via neurovascular coupling. While fiber-based DOT systems have been extensively validated against MRI over the last decade, full head fiber DOT systems require that the subject's head remains relatively still. New, wearable DOT systems have recently begun to provide similar imaging performance with the added advantage of permitting subject movement.
Methods:
Our wearable DOT cap houses an array of modules with integrated optoelectronics and mechanics. The fully untethered system communicates with a control computer over Wi-Fi, and power is supplied via a battery in a backpack. Participants can move their head, stand, walk, and perform more complex movements (Fig 1bcd). 98 sources and 98 detectors are arranged in a high-density grid with a field of view covering most of the cortex. Spring-loaded optodes comb through hair to create and maintain scalp coupling. The system was validated both on the bench and in vivo, and compared to a conventional, fiber-based DOT system. In some cases, subjects were scanned while freely walking, which is impossible in MRI or fiber DOT.
Results:
In vivo data from varied behavioral tasks replicate the activation patterns expected from fMRI studies, including visual, auditory, motor, and language processing tasks. The SNR is sufficient for single session individual subject maps without group-averaging. In a 3-way visual decoding task, single-trial responses are robust enough for decoding with up to 100% accuracy.
To verify robustness to subject movement, we used instructed motion from our WHD system and a comparable fiber DOT system. Multiple types of motion were compared, as well as the effects of motion artifacts on task maps and decoding performance. With instructed motion as great as 20 cm added to a visual task, the WHD system still output high quality maps with few motion artifacts, while on the fiber system, activations were completely obscured by motion artifacts (Fig 2a). Even during motion, the WHD system demonstrated high accuracy on a 3-way decoding task, while motion decimated the fiber system's decoding performance (Fig 2b). Quantifying motion artifacts with GVTD, akin to MRI's DVARS, shows rigid body motions on the WHD system gave GVTD values 1/3 of the mean and 1/5 of the amplitude of the GVTD on the fiber system.
To verify robustness to subject movement, we used instructed motion from our WHD system and a comparable fiber DOT system. Multiple types of motion were compared, as well as the effects of motion artifacts on task maps and decoding performance. With instructed motion as great as 20 cm added to a visual task, the WHD system still output high quality maps with few motion artifacts, while on the fiber system, activations were completely obscured by motion artifacts (Fig 2a). Even during motion, the WHD system demonstrated high accuracy on a 3-way decoding task, while motion decimated the fiber system's decoding performance (Fig 2b). Quantifying motion artifacts with GVTD, akin to MRI's DVARS, shows rigid body motions on the WHD system gave GVTD values 1/3 of the mean and 1/5 of the amplitude of the GVTD on the fiber system.
Conclusions:
We developed a WHD DOT system that bridges a gap in neuroimaging technologies, with wearable convenience, high resolution, and resistance to motion artifacts. Bench and in vivo testing demonstrate good performance, and it significantly outperformed fiber DOT systems during instructed motion. The portability and robustness to motion open new worlds of possibilities for scanning during tasks or in settings that were previously intractable; it is compatible with gross motor movement and locomotion, and with non-laboratory environments such as offices. Current work includes expanding the field of view and improving ergonomics.
Modeling and Analysis Methods:
Activation (eg. BOLD task-fMRI)
Classification and Predictive Modeling
Motor Behavior:
Motor Behavior Other 2
Novel Imaging Acquisition Methods:
NIRS 1
Keywords:
Cortex
Motor
Near Infra-Red Spectroscopy (NIRS)
OPTICAL
Other - Motion artifact
1|2Indicates the priority used for review