Surface-based integration approach for fNIRS-fMRI reliability assessment.

INTRODUCTION: Studies integrating functional near-infrared spectroscopy (fNIRS) with functional MRI (fMRI) employ heterogeneous methods in defining common regions of interest in which similarities are assessed. Therefore, spatial agreement and temporal correlation may not be reproducible across studies. In the present work, we address this issue by proposing a novel method for integration and analysis of fNIRS and fMRI over the cortical surface. MATERIALS AND METHODS: Eighteen healthy volunteers (age mean±SD 30.55 ± 4.7, 7 males) performed a motor task during non-simultaneous fMRI and fNIRS acquisitions. First, fNIRS and fMRI data were integrated by projecting subject- and group-level source maps over the cortical surface mesh to define anatomically constrained functional ROIs (acfROI). Next, spatial agreement and temporal correlation were quantified as Dice Coefficient (DC) and Pearson's correlation coefficient between fNIRS-fMRI in the acfROIs. RESULTS: Subject-level results revealed moderate to substantial spatial agreement (DC range 0.43 - 0.64), confirmed at the group-level only for blood oxygenation level-dependent (BOLD) signal vs. HbO2 (0.44 - 0.69), while lack of agreement was found for BOLD vs. HbR in some instances (0.05 - 0.49). Subject-level temporal correlation was moderate to strong (0.79 - 0.85 for BOLD vs. HbO2 and -0.62 to -0.72 for BOLD vs. HbR), while an overall strong correlation was found for group-level results (0.95 - 0.98 for BOLD vs. HbO2 and -0.91 to -0.94 for BOLD vs. HbR). CONCLUSION: The proposed method directly compares fNIRS and fMRI by projecting individual source maps to the cortical surface. Our results indicate spatial and temporal correspondence between fNIRS and fMRI, and promotes the use of fNIRS when more ecological acquision settings are required, such as longitudinal monitoring of brain activity before and after rehabilitation.

Impact of Anatomical Variability on Sensitivity Profile in fNIRS-MRI Integration.

Functional near-infrared spectroscopy (fNIRS) is an important non-invasive technique used to monitor cortical activity. However, a varying sensitivity of surface channels vs. cortical structures may suggest integrating the fNIRS with the subject-specific anatomy (SSA) obtained from routine MRI. Actual processing tools permit the computation of the SSA forward problem (i.e., cortex to channel sensitivity) and next, a regularized solution of the inverse problem to map the fNIRS signals onto the cortex. The focus of this study is on the analysis of the forward problem to quantify the effect of inter-subject variability. Thirteen young adults (six males, seven females, age 29.3 ± 4.3) underwent both an MRI scan and a motor grasping task with a continuous wave fNIRS system of 102 measurement channels with optodes placed according to a 10/5 system. The fNIRS sensitivity profile was estimated using Monte Carlo simulations on each SSA and on three major atlases (i.e., Colin27, ICBM152 and FSAverage) for comparison. In each SSA, the average sensitivity curves were obtained by aligning the 102 channels and segmenting them by depth quartiles. The first quartile (depth < 11.8 (0.7) mm, median (IQR)) covered 0.391 (0.087)% of the total sensitivity profile, while the second one (depth < 13.6 (0.7) mm) covered 0.292 (0.009)%, hence indicating that about 70% of the signal was from the gyri. The sensitivity bell-shape was broad in the source-detector direction (20.953 (5.379) mm FWHM, first depth quartile) and steeper in the transversal one (6.082 (2.086) mm). The sensitivity of channels vs. different cortical areas based on SSA were analyzed finding high dispersions among subjects and large differences with atlas-based evaluations. Moreover, the inverse cortical mapping for the grasping task showed differences between SSA and atlas based solutions. In conclusion, integration with MRI SSA can significantly improve fNIRS interpretation.

Whole-Head Functional Near-Infrared Spectroscopy as an Ecological Monitoring Tool for Assessing Cortical Activity in Parkinson's Disease Patients at Different Stages.

Functional near-infrared spectroscopy (fNIRS) is increasingly employed as an ecological neuroimaging technique in assessing age-related chronic neurological disorders, such as Parkinson's disease (PD), mainly providing a cross-sectional characterization of clinical phenotypes in ecological settings. Current fNIRS studies in PD have investigated the effects of motor and non-motor impairment on cortical activity during gait and postural stability tasks, but no study has employed fNIRS as an ecological neuroimaging tool to assess PD at different stages. Therefore, in this work, we sought to investigate the cortical activity of PD patients during a motor grasping task and its relationship with both the staging of the pathology and its clinical variables. This study considered 39 PD patients (age 69.0 ± 7.64, 38 right-handed), subdivided into two groups at different stages by the Hoehn and Yahr (HY) scale: early PD (ePD; N = 13, HY = [1; 1.5]) and moderate PD (mPD; N = 26, HY = [2; 2.5; 3]). We employed a whole-head fNIRS system with 102 measurement channels to monitor brain activity. Group-level activation maps and region of interest (ROI) analysis were computed for ePD, mPD, and ePD vs. mPD contrasts. A ROI-based correlation analysis was also performed with respect to contrasted subject-level fNIRS data, focusing on age, a Cognitive Reserve Index questionnaire (CRIQ), disease duration, the Unified Parkinson's Disease Rating Scale (UPDRS), and performances in the Stroop Color and Word (SCW) test. We observed group differences in age, disease duration, and the UPDRS, while no significant differences were found for CRIQ or SCW scores. Group-level activation maps revealed that the ePD group presented higher activation in motor and occipital areas than the mPD group, while the inverse trend was found in frontal areas. Significant correlations with CRIQ, disease duration, the UPDRS, and the SCW were mostly found in non-motor areas. The results are in line with current fNIRS and functional and anatomical MRI scientific literature suggesting that non-motor areas-primarily the prefrontal cortex area-provide a compensation mechanism for PD motor impairment. fNIRS may serve as a viable support for the longitudinal assessment of therapeutic and rehabilitation procedures, and define new prodromal, low-cost, and ecological biomarkers of disease progression.

Validation of SART 3.5D algorithm for cerebrovascular dynamics and artery versus vein classification in presurgical 3D digital subtraction angiographies.

Classification of arteries and veins in cerebral angiograms can increase the safety of neurosurgical procedures, such as StereoElectroEncephaloGraphy, and aid the diagnosis of vascular pathologies, as arterovenous malformations. We propose a new method for vessel classification using the contrast medium dynamics in rotational digital subtraction angiography (DSA). After 3D DSA and angiogram segmentation, contrast enhanced projections are processed to suppress soft tissue and bone structures attenuation effect and further enhance the CM flow. For each voxel labelled as vessel, a time intensity curve (TIC) is obtained as a linear combination of temporal basis functions whose weights are addressed by simultaneous algebraic reconstruction technique (SART 3.5D), expanded to include dynamics. Each TIC is classified by comparing the areas under the curve in the arterial and venous phases. Clustering is applied to optimize the classification thresholds. On a dataset of 60 patients, a median value of sensitivity (90%), specificity (91%), and accuracy (92%) were obtained with respect to annotated arterial and venous voxels up to branching order 4-5. Qualitative results are also presented about CM arrival time mapping and its distribution in arteries and veins respectively. In conclusion, this study shows a valuable impact, at no protocol extra-cost or invasiveness, concerning surgical planning related to the enhancement of arteries as major organs at risk. Also, it opens a new scope on the pathophysiology of cerebrovascular dynamics and its anatomical relationships.

A Systematic Review of Cerebral Functional Near-Infrared Spectroscopy in Chronic Neurological Diseases-Actual Applications and Future Perspectives.

BACKGROUND: The management of people affected by age-related neurological disorders requires the adoption of targeted and cost-effective interventions to cope with chronicity. Therapy adaptation and rehabilitation represent major targets requiring long-term follow-up of neurodegeneration or, conversely, the promotion of neuroplasticity mechanisms. However, affordable and reliable neurophysiological correlates of cerebral activity to be used throughout treatment stages are often lacking. The aim of this systematic review is to highlight actual applications of functional Near-Infrared Spectroscopy (fNIRS) as a versatile optical neuroimaging technology for investigating cortical hemodynamic activity in the most common chronic neurological conditions. METHODS: We reviewed studies investigating fNIRS applications in Parkinson's Disease (PD), Alzheimer's Disease (AD) and Mild Cognitive Impairment (MCI) as those focusing on motor and cognitive impairment in ageing and Multiple Sclerosis (MS) as the most common chronic neurological disease in young adults. The literature search was conducted on NCBI PubMed and Web of Science databases by PRISMA guidelines. RESULTS: We identified a total of 63 peer-reviewed articles. The AD spectrum is the most investigated pathology with 40 articles ranging from the traditional monitoring of tissue oxygenation to the analysis of functional resting-state conditions or cognitive functions by means of memory and verbal fluency tasks. Conversely, applications in PD (12 articles) and MS (11 articles) are mainly focused on the characterization of motor functions and their association with dual-task conditions. The most investigated cortical area is the prefrontal cortex, since reported to play an important role in age-related compensatory mechanism and neurofunctional changes associated to these chronic neurological conditions. Interestingly, only 9 articles applied a longitudinal approach. CONCLUSION: The results indicate that fNIRS is mainly employed for the cross-sectional characterization of the clinical phenotypes of these pathologies, whereas data on its utility for longitudinal monitoring as surrogate biomarkers of disease progression and rehabilitation effects are promising but still lacking.