Multi-subject and multi-task experimental validation of the hierarchical Bayesian diffuse optical tomography algorithm

• Published in: NeuroImage (Orlando, Fla.) Vol. 135; pp. 287 - 299
• Main Authors: Yamashita, Okito, Shimokawa, Takeaki, Aisu, Ryota, Amita, Takashi, Inoue, Yoshihiro, Sato, Masa-aki
• Format: Journal Article
• Language: English
• Published: United States Elsevier Inc 15.07.2016; Elsevier Limited
• Subjects: Adult; Algorithms; Bayes Theorem; Bayesian analysis; Brain Mapping - methods; Case studies; Computer simulation; Diffuse optical tomography; Evoked Potentials, Motor - physiology; Humans; Image Enhancement - methods; Image Interpretation, Computer-Assisted - methods; Image reconstruction; Inverse problems; Magnetic Resonance Imaging - methods; Male; Medical imaging; Middle Aged; Motor Cortex - physiology; Movement - physiology; NIRS; Noise; Pattern Recognition, Automated - methods; Reproducibility of Results; Scalp blood flow; Sensitivity and Specificity; Signal processing; Spectroscopy, Near-Infrared - methods; Tomography; Tomography, Optical - methods; Topography; Young Adult; SS; Scalp blood flow; fNIRS; HbO; FPA; DOT; NIRS; HbR; LE; Diffuse optical tomography; Image reconstruction; AUC
• DOI: 10.1016/j.neuroimage.2016.04.068
• ISSN: 1053-8119

Diffuse optical tomography (DOT) is an emerging technology for improving the spatial resolution and spatial specificity of conventional multi-channel near-infrared spectroscopy (NIRS) by the use of high-density measurements and an image reconstruction algorithm. We recently proposed a hierarchical Bayesian DOT algorithm that allows for accurate simultaneous reconstruction of scalp and cortical hemodynamic changes, and verified its performance with a phantom experiment, a computer simulation, and experimental data from one human subject. We extend our previous human case study to a multi-subject, multi-task study, to demonstrate the validity of the algorithm on a wider population and varied task conditions. We measured brain activity during three graded tasks (hand movement, index finger movement, and no-movement), in 12 subjects, using high-density NIRS and functional magnetic resonance imaging (fMRI), acquired in different sessions. The reconstruction performance of our algorithm, and the current gold-standard method for DOT image reconstruction, were evaluated using the blood-oxygenation-level-dependent (BOLD) signals of the fMRI as a reference. In comparison with the BOLD signals, our method achieved a median localization error of 6 and 8mm, and a spatial-pattern similarity of 0.6 and 0.4 for the hand and finger tasks, respectively. It also did not reconstruct any activity in the no-movement task. Compared with the current gold-standard method, the new method showed fewer false positives, which resulted in improved spatial-pattern similarity, although the localization errors of the main activity clusters were comparable. •Diffuse optical tomography (DOT) is a method to improve spatial resolution of NIRS.•We previously proposed a novel DOT image reconstruction algorithm.•We conducted multi-task and multi-subject experimental validation of our algorithm.•Our method achieved localization error of 6–8mm compared with fMRI.•Our method is robust to false positives compared with the standard DOT method.