Test-retest reliability of neuroimaging measurements is an important concern in the investigation of cognitive functions in the human brain. To date, intraclass correlation coefficients (ICCs), originally used in inter-rater reliability studies in behavioral sciences, have become commonly used metrics in reliability studies on neuroimaging and functional near-infrared spectroscopy (fNIRS). However, as there are six popular forms of ICC, the adequateness of the comprehensive understanding of ICCs will affect how one may appropriately select, use, and interpret ICCs toward a reliability study. We first offer a brief review and tutorial on the statistical rationale of ICCs, including their underlying analysis of variance models and technical definitions, in the context of assessment on intertest reliability. Second, we provide general guidelines on the selection and interpretation of ICCs. Third, we illustrate the proposed approach by using an actual research study to assess intertest reliability of fNIRS-based, volumetric diffuse optical tomography of brain activities stimulated by a risk decision-making protocol. Last, special issues that may arise in reliability assessment using ICCs are discussed and solutions are suggested.
Diffuse optical topography remains a valid tool in functional near infrared spectroscopy (fNIRS) since it avoids solving the forward and inverse computational problems, which are encountered in diffuse optical tomography. Topography is particularly useful when a sparse array of optodes is used and depth specificity is not the primary interest. We have developed an easy toolbox for diffuse optical topography (“EasyTopo”) based on a standard template of brain atlas. EasyTopo approximates the cortical layer of the brain as a hemispherical surface. Therefore, the stereotaxic coordinates of the brain surface and the co-registered fNIRS measurements (channels) are converted into the spherical coordinates, where 2D angular interpolation of the channel-wise data is implemented to obtain a topographic image of brain activation in the latitude-longitude space. Then, the interpolated image is projected back onto the brain surface in the original 3D stereotaxic coordinates. Compared with the existing 3D topography methods, EasyTopo is more computationally efficient and does not require any data extrapolation. Another advantage of EasyTopo is that the data between two spatially adjacent channels are interpolated along their included angles (i.e., along the angular direction) rather than along a straight line going under the brain surface. The former geometry in principle matches better with the realistic brain structure than the latter one. EasyTopo has been validated with both simulation and human experiments. Now this toolbox is publically available.
Investigation of the reliability and reproducibility of the hemodynamic response is important for interpretation
and understanding of the results of functional near-infrared spectroscopy (fNIRS). It measures optical signals
absorbed by the brain tissue and reflects the neuronal activities indirectly. Here we described an fNIRS study
measured in the prefrontal region (Brodman area 9, 10, part of 46)to examine the risk decision-making behavior
in nine young adults. The Balloon Analog Risk Task (BART) is widely used to test the level of risk taking
ability in the field of psychology. BART was a protocol utilized in this study to evoke a risk-taking environment
with a gambling-like balloon game in each subject. Specifically, we recorded the brain oxygenated-hemoglobin
(HbO) and deoxygenated-hemoglobin (HHb) changes during the two repeated measurements within a time
interval of 3 weeks. The results demonstrate that the changes in HbO2 amplitudes have high reliability at the
group level, and that the spatial patterns of the tomographic images have high reproducibility in size and a
moderate degree of overlap. Overall, this study confirms that the hemodynamic response to risk
decision-making (i.e., BART) seen by fNIRS is highly reliable and reproducible.
Functional near-infrared spectroscopy (fNIRS) is a non-invasive imaging technique which measures the hemodynamic changes that reflect the brain activity. Diffuse optical tomography (DOT), a variant of fNIRS with multi-channel NIRS measurements, has demonstrated capability of three dimensional (3D) reconstructions of hemodynamic changes due to the brain activity. Conventional method of DOT image analysis to define the brain activation is based upon the paired t-test between two different states, such as resting-state versus task-state. However, it has limitation because the selection of activation and post-activation period is relatively subjective. General linear model (GLM) based analysis can overcome this limitation. In this study, we combine the 3D DOT image reconstruction with GLM-based analysis (i.e., voxel-wise GLM analysis) to investigate the brain activity that is associated with the risk-decision making process. Risk decision-making is an important cognitive process and thus is an essential topic in the field of neuroscience. The balloon analogue risk task (BART) is a valid experimental model and has been commonly used in behavioral measures to assess human risk taking action and tendency while facing risks. We have utilized the BART paradigm with a blocked design to investigate brain activations in the prefrontal and frontal cortical areas during decision-making. Voxel-wise GLM analysis was performed on 18human participants (10 males and 8females).In this work, we wish to demonstrate the feasibility of using voxel-wise GLM analysis to image and study cognitive functions in response to risk decision making by DOT. Results have shown significant changes in the dorsal lateral prefrontal cortex (DLPFC) during the active choice mode and a different hemodynamic pattern between genders, which are in good agreements with published literatures in functional magnetic resonance imaging (fMRI) and fNIRS studies.
Functional near-infrared spectroscopy (fNIRS) is recently utilized as a new approach to assess resting-state functional connectivity (RSFC) in the human brain. For any new technique or new methodology, it is necessary to be able to replicate similar experiments using different instruments in order to establish its liability and reproducibility. We apply two different diffuse optical tomographic (DOT) systems (i.e., DYNOT and CW5), with various probe arrangements to evaluate RSFC in the sensorimotor cortex by utilizing a previously published experimental protocol and seed-based correlation analysis. Our results exhibit similar spatial patterns and strengths in RSFC between the bilateral motor cortexes. The consistent observations are obtained from both DYNOT and CW5 systems, and are also in good agreement with the previous fNIRS study. Overall, we demonstrate that the fNIRS-based RSFC is reproducible by various DOT imaging systems among different research groups, enhancing the confidence of neuroscience researchers and clinicians to utilize fNIRS for future applications.
The goal for this study is to examine cerebral autoregulation in response to a repeated sit-stand maneuver using
both diffuse functional Near Infrared spectroscopy (fNIRS) and Transcranial Doppler sonography (TCD). While
fNIRS can provide transient changes in hemodynamic response to such a physical action, TCD is a noninvasive
transcranial method to detect the flow velocities in the basal or middle cerebral arteries (MCA). The initial
phase of this study was to measure fNIRS signals from the forehead of subjects during the repeated sit-stand
protocol and to understand the corresponding meaning of the detected signals. Also, we acquired preliminary
data from simultaneous measurements of fNIRS and TCD during the sit-stand protocol so as to explore the
technical difficulty of such an approach. Specifically, ten healthy adult subjects were enrolled to perform the
planned protocol, and the fNIRS array probes with 4 sources and 10 detectors were placed on the subject's
forehead to detect hemodynamic signal changes from the prefrontal cortex. The fNIRS results show that the
oscillations of hemoglobin concentration were spatially global and temporally dynamic across the entire region
of subject's forehead. The oscillation patterns in both hemoglobin concentrations and blood flow velocity
seemed to follow one another; changes in oxy-hemoglobin concentration were much larger than those in deoxyhemoglobin
concentration. These preliminary findings provide us with evidence that fNIRS is an appropriate
means readily for studying cerebral hemodynamics and autoregulation during sit-stand maneuvers.
Stroke, due to ischemia or hemorrhage, is the neurological deficit of cerebrovasculature and is the third leading cause of
death in the United States. More than 80 percent of stroke patients are ischemic stroke due to blockage of artery in the
brain by thrombosis or arterial embolism. Hence, development of an imaging technique to image or monitor the cerebral
ischemia and effect of anti-stoke therapy is more than necessary. Near infrared (NIR) optical tomographic technique has
a great potential to be utilized as a non-invasive image tool (due to its low cost and portability) to image the embedded
abnormal tissue, such as a dysfunctional area caused by ischemia. Moreover, NIR tomographic techniques have been
successively demonstrated in the studies of cerebro-vascular hemodynamics and brain injury. As compared to a fiberbased
diffuse optical tomographic system, a CCD-camera-based system is more suitable for pre-clinical animal studies
due to its simpler setup and lower cost. In this study, we have utilized the CCD-camera-based technique to image the
embedded inclusions based on tissue-phantom experimental data. Then, we are able to obtain good reconstructed
images by two recently developed algorithms: (1) depth compensation algorithm (DCA) and (2) globally convergent
method (GCM). In this study, we will demonstrate the volumetric tomographic reconstructed results taken from tissuephantom;
the latter has a great potential to determine and monitor the effect of anti-stroke therapies.
One of the major challenges in diffuse optical tomography (DOT) is attributed to the severe decay of sensitivity along
depth. In conventional reconstruction method using regularized inversion, it yields significant depth distortion in the
reconstructed image as a cortical activation is always projected into the skull. Recently we developed a depth
compensation algorithm (DCA) to minimize the depth localization error in DOT, which introduces a depth-variant
weight matrix to counterbalance the severe sensitivity decay of A-matrix. The DCA algorithm has been previously
validated in both laboratory phantom experiments and an in vivo human study. In this study, we first present a
comprehensive analysis on how DCA alters the depth localization and spatial resolution in DOT. It reveals that DCA
greatly improves the transverse resolution in sub-cortical region. Second, we present a quantification approach for DCA.
By forming a spatial prior directly from the reconstructed image, this approach greatly improves the quantification
accuracy in DOT.
A depth compensation algorithm (DCA) can effectively improve the depth localization of diffuse optical tomography (DOT) by compensating the exponentially decreased sensitivity in the deep tissue. In this study, DCA is investigated based on computer simulations, tissue phantom experiments, and human brain imaging. The simulations show that DCA can largely improve the spatial resolution of DOT in addition to the depth localization, and DCA is also effective for multispectral DOT with a wide range of optical properties in the background tissue. The laboratory phantom experiment demonstrates that DCA can effectively differentiate two embedded objects at different depths in the medium. DCA is further validated by human brain imaging using a finger-tapping task. To our knowledge, this is the first demonstration to show that DCA is capable of accurately localizing cortical activations in the human brain in three dimensions.
Surgeons often cannot see major vessels embedded in adipose tissue and inadvertently injure them. One such example occurs during surgical removal of the gallbladder, where injury of the nearby common bile duct leads to life-threatening complications. Near-infrared imaging of the intraoperative field may help surgeons localize such critical tissue-embedded vessels. We have investigated how continuous-wave (CW) imaging performs relative to time-gated wide-field imaging, presently a rather costly technology, under broad Gaussian beam-illumination conditions. We have studied the simplified case of an isolated cylinder having bile-duct optical properties, embedded at different depths within a 2-cm slab of adipose tissue. Monte Carlo simulations were preformed for both reflectance and transillumination geometries. The relative performance of CW versus time-gated imaging was compared in terms of spatial resolution and contrast-to-background ratio in the resulting simulated images. It was found that time-gated imaging offers superior spatial resolution and vessel-detection sensitivity in most cases, though CW transillumination measurements may also offer satisfactory performance for this tissue geometry at lower cost. Experiments were performed in reflectance geometry to validate simulation results, and potential challenges in the translation of this technology to the clinic are discussed.
Laparoscopic radical prostatectomy (LRP) has revolutionized the surgical treatment of prostate cancer. This procedure permits complete removal of the prostate and seminal vesicles while minimizing pain and recovery time. However, the laparoscopic approach greatly limits the surgeon's tactile sensation during the procedure. This is particularly true with robot-assisted LRP where no tactile feedback is available forcing the surgeon to rely solely on visual cues. The surgeon and pathologist perform intraoperative frozen section pathologic analysis of a few select tissue fragments, but this is time consuming and costly. Concrete conclusions based on such samples are unreliable as they do not reflect the entire surgical margin status. In this case a conservative approach might dictate removal of more marginal material than necessary, thereby compromising the important nerve-sparing aspects of the procedure. In this study, we demonstrate the feasibility of using multi-modal time-gated optical imaging, i.e. time-resolved light reflectance and auto-fluorescence life-time imaging performed by an ICCD (Intensified Charge-Coupled Device) imaging system to enable clinicians to detect positive tumor margins with high sensitivity and specificity over the prostate. Results from animal experiments present the potential of identifying differences in optical signals between prostate cancer and control tissues. Results also show that the use of classification algorithms can identify cancerous regions with high sensitivity and specificity.
The clinical motivation for our work was to help surgeons see vessels through non-translucent intraoperative tissues
during laparoscopic removal of the gallbladder. Our main focus was to answer the question of how CW imaging
performs relative to ICCD (Intensified Charge-Coupled Device) based time-gated imaging, which is a lot more costly,
under broad Gaussian beam illumination conditions. We have studied the simplified case of an isolated bile duct
embedded at different depths within a 2 cm slab of adipose tissue. Monte Carlo simulations were preformed for both
reflectance and trans-illumination geometries. The relative performance of CW versus time-gated imaging was
compared in terms of spatial resolution and vessel detection sensitivity in the resulting simulated images. Experiments
were performed in reflectance geometry to validate simulation results. It was found that time-gated imaging offers
superior spatial resolution and vessel detection sensitivity in all cases though CW trans-illumination measurements may
also offer satisfactory performance for this tissue geometry at a lower cost.
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