Comparison of compartmental analytical Blood-Oxygen-Level-Dependent functional Magnetic Resonance Imaging models against Monte Carlo simulations performed over cortical micro-angiograms.

Blood oxygen level-dependent functional magnetic resonance imaging (BOLD fMRI) arises from a physiological and physical cascade of events taking place at the level of the cortical microvasculature which constitutes a medium with complex geometry. Several analytical models of the BOLD contrast have been developed, but these have not been compared directly against detailed bottom-up modeling methods. Using a 3D modeling method based on experimentally measured images of mice microvasculature and Monte Carlo simulations, we quantified the accuracy of two analytical models to predict the amplitude of the BOLD response from 1.5 to 7 T, for different echo time (TE) and for both gradient echo and spin echo acquisition protocols. We also showed that accounting for the tridimensional structure of the microvasculature results in more accurate prediction of the BOLD amplitude, even if the values for SO2 were averaged across individual vascular compartments. A secondary finding is that modeling the venous compartment as two individual compartments results in more accurate prediction of the BOLD amplitude compared with standard homogenous venous modeling, arising from the bimodal distribution of venous SO2 across the microvasculature in our data.

Social distancing causally impacts the spread of SARS-CoV-2: a U.S. nationwide event study.

We assess the causal impact of social distancing on the spread of SARS-CoV-2 in the U.S. using the quasi-natural experimental setting created by the spontaneous relaxation of social distancing behavior brought on by the protests that erupted across the nation following George Floyd's tragic death on May 25, 2020. Using a difference-in-difference specification and a balanced sample covering the [- 30, 30] day event window centered on the onset of protests, we document an increase of 1.34 cases per day, per 100,000 population, in the SARS-CoV-2 incidence rate in protest counties, relative to their propensity score matching non-protest counterparts. This represents a 26.8% increase in the incidence rate relative to the week preceding the protests. We find that the treatment effect only manifests itself after the onset of the protests and our placebo tests rule out the possibility that our findings are attributable to chance. Our research informs policy makers and provides insights regarding the usefulness of social distancing as an intervention to minimize the spread of SARS-CoV-2.

Modeling of vascular space occupancy and BOLD functional MRI from first principles using real microvascular angiograms.

PURPOSE: The vascular space occupancy (VASO) is a functional MRI technique for probing cerebral blood volume changes noninvasively, including during neuronal activation in humans. An important consideration when implementing VASO is the BOLD effect in the signal. Assessing the physical origin of this BOLD contamination and the capabilities of correction methods could improve the quantification of cerebral blood volume changes with VASO. METHODS: Given the heterogeneity of cerebral microvascular architecture, the vascular geometry within an MRI voxel can influence both BOLD and VASO signals. To investigate this effect, 3D high-resolution images of mouse cerebral vasculature measured with two-photon microscopy were used to model BOLD and VASO signals from first principles using Monte Carlo diffusion of water protons. Quantitative plots of VASO together with intravascular and extravascular BOLD signals as a function of TE at B0 fields 1.5 T to 14 T were obtained. RESULTS: The BOLD contamination of the VASO response was on the order of 50% for gradient echo and 5% for spin echo at 7 T and TE = 6 ms and significantly increased with TE and B0 . Two currently used correction schemes were shown to account for most of this contamination and recover accurate relative signal changes, with optimal correction obtained using TEs as short as possible. CONCLUSION: These results may provide useful information for optimizing sequence parameters in VASO and BOLD functional MRI, leading the way to a wider application of these techniques in healthy and diseased brain.

Design and Characterization of Protein E-PilA, a Candidate Fusion Antigen for Nontypeable Haemophilus influenzae Vaccine.

Nontypeable Haemophilus influenzae (NTHi) is a pathogen known for being a frequent cause of acute otitis media in children and respiratory tract infections in adults with chronic obstructive pulmonary disease. In the present study, a vaccine antigen based on the fusion of two known NTHi adhesive proteins, protein E (PE) and a pilin subunit (PilA), was developed. The quality of the combined antigen was investigated through functional, biophysical, and structural analyses. It was shown that the PE and PilA individual structures are not modified in the PE-PilA fusion and that PE-PilA assembles as a dimer in solution, reflecting PE dimerization. PE-PilA was found to bind vitronectin by enzyme-linked immunosorbent assay, as isolated PE does. Disulfide bridges were conserved and homogeneous, which was determined by peptide mapping and top-down analysis of PE, PilA, and PE-PilA molecules. Finally, the PE-PilA crystal showed a PE entity with a three-dimensional (3D) structure similar to that of the recently published isolated PE, while the structure of the PilA entity was similar to that of a 3D model elaborated from two other type 4 pilin subunits. Taken together, our observations suggest that the two tethered proteins behave independently within the chimeric molecule and display structures similar to those of the respective isolated antigens, which are important characteristics for eliciting optimal antibody-mediated immunity. PE and PilA can thus be further developed as a single fusion protein in a vaccine perspective, in the knowledge that tethering the two antigens does not perceptibly compromise the structural attributes offered by the individual antigens.

Dependence of the MR signal on the magnetic susceptibility of blood studied with models based on real microvascular networks.

PURPOSE: The primary goal of this study was to estimate the value of ß , the exponent in the power law relating changes of the transverse relaxation rate and intra-extravascular local magnetic susceptibility differences as ΔR2∗∝(Δχ)ß . The secondary objective was to evaluate any differences that might exist in the value of ß obtained using a deoxyhemoglobin-weighted Δχ distribution versus a constant Δχ distribution assumed in earlier computations. The third objective was to estimate the value of ß that is relevant for methods based on susceptibility contrast agents with a concentration of Δχ higher than that used for BOLD fMRI calculations. METHODS: Our recently developed model of real microvascular anatomical networks is used to extend the original simplified Monte-Carlo simulations to compute ß from the first principles. RESULTS: Our results show that ß=1 for most BOLD fMRI measurements of real vascular networks, as opposed to earlier predictions of ß=1 .5 using uniform Δχ distributions. For perfusion or fMRI methods based on contrast agents, which generate larger values for Δχ , ß=1 for B0≤ 9.4 T, whereas at 14 T ß can drop below 1 and the variation across subjects is large, indicating that a lower concentration of contrast agent with a lower value of Δχ is desired for experiments at high B0 . CONCLUSION: These results improve our understanding of the relationship between R2* and the underlying microvascular properties. The findings will help to infer the cerebral metabolic rate of oxygen and cerebral blood volume from BOLD and perfusion MRI, respectively.

Early Renal Replacement Therapy Versus Standard Care in the ICU: A Systematic Review, Meta-Analysis, and Cost Analysis.

OBJECTIVE:: Renal replacement therapy (RRT) is the treatment of choice for severe acute kidney injury, but there are no firm guidelines as to the time of initiation of RRT in the critically ill. The primary objective of this study is to determine 1-month mortality rates of early versus late dialysis in critical care. As secondary end points, we provide a cost analysis of early versus late RRT initiation, intensive care unit (ICU) length of stay (LOS), hospital LOS, and number of patients on dialysis at day 60 postrandomization. DATA SOURCES:: We identified all randomized controlled trials (RCTs) through EMLINE and MEDBASE that examined adult patients admitted to critical care who were randomized to receiving early dialysis versus standard of care. STUDY SELECTION:: Inclusion criteria: (1) RCTs conducted after the year 2000, (2) the population evaluated had to be adults admitted to ICU, (3) the intervention had to be early RRT versus standard care, and (4) outcomes had to measure patient mortality. DATA EXTRACTION:: Two independent investigators reviewed search results and identified appropriate studies. Information was extracted using standardized case report forms. DATA SYNTHESIS:: Overall, 7 RCTs were included with a total of 1400 patients. Early RRT showed no survival benefit when compared to standard treatment (odds ratio [OR], 0.90 95% confidence interval [95% CI] 0.70-1.15, P = .39). There was no significant difference in length of hospital stay in patients with early RRT (-1.55 days [95% CI -4.75 to 1.65, P = .34]), in length of ICU stay (-0.79 days [95% CI -2.09 to 0.52], P = .24), or proportion of patients on dialysis at day 60 (OR 0.93 [95% CI 0.62 to 1.43], P = .79). Per patient, there is likely a small increase in costs (

The Impact of Palliative Care Consultation in the ICU on Length of Stay: A Systematic Review and Cost Evaluation.

INTRODUCTION: The intensive care unit (ICU) consumes 20% of hospital expenditures and 1% of gross domestic product. Many strategies have been attempted to reduce ICU costs. A systematic review was conducted to evaluate the effect of palliative care (PC) consultations in the ICU on length of stay (LOS) and costs. METHODS: A literature search was performed using PubMed, MEDLINE, EMBASE, and the Cochrane Library. Randomized controlled trials (RCTs), prospective, and retrospective cohort studies looking at PC consultations in adult ICUs published between January 2000 and February 2016 were selected. Independent reviewers assessed the eligibility of studies, extracted data on ICU, hospital LOS, and mortality, and rated each study's quality. The cost was derived from an existing model in the literature; the primary outcome was ICU LOS and the secondary outcomes were direct variable costs, mortality, and hospital LOS. RESULTS: We reviewed 814 abstracts, but only 8 studies met inclusion criteria and were included. The patients with a PC consultation in the ICU, when compared to those who did not, showed a trend toward reduced LOS. This reduction was statistically significant in the higher quality studies. Mortality was similar in both groups. Palliative care consultations also lead to a reduction in costs in 5 of the 8 eligible trials. On average, ICU costs were USD7533 and USD6406 (control vs PC, P < .05) and hospital direct variable costs were USD9518 and USD8971 ( P < .05) per admission. Due to interstudy heterogeneity, all outcomes were described narratively. CONCLUSION: This review demonstrates a trend that PC consultations reduce LOS and costs without impacting mortality. However, due to the small sample sizes and varying degrees of quality of evidence, many questions remain. A large multicenter RCT and formal economic evaluation would be needed for more definitive results.

Magnetic resonance fingerprinting based on realistic vasculature in mice.

Magnetic resonance fingerprinting (MRF) was recently proposed as a novel strategy for MR data acquisition and analysis. A variant of MRF called vascular MRF (vMRF) followed, that extracted maps of three parameters of physiological importance: cerebral oxygen saturation (SatO2), mean vessel radius and cerebral blood volume (CBV). However, this estimation was based on idealized 2-dimensional simulations of vascular networks using random cylinders and the empirical Bloch equations convolved with a diffusion kernel. Here we focus on studying the vascular MR fingerprint using real mouse angiograms and physiological values as the substrate for the MR simulations. The MR signal is calculated ab initio with a Monte Carlo approximation, by tracking the accumulated phase from a large number of protons diffusing within the angiogram. We first study the identifiability of parameters in simulations, showing that parameters are fully estimable at realistically high signal-to-noise ratios (SNR) when the same angiogram is used for dictionary generation and parameter estimation, but that large biases in the estimates persist when the angiograms are different. Despite these biases, simulations show that differences in parameters remain estimable. We then applied this methodology to data acquired using the GESFIDE sequence with SPIONs injected into 9 young wild type and 9 old atherosclerotic mice. Both the pre injection signal and the ratio of post-to-pre injection signals were modeled, using 5-dimensional dictionaries. The vMRF methodology extracted significant differences in SatO2, mean vessel radius and CBV between the two groups, consistent across brain regions and dictionaries. Further validation work is essential before vMRF can gain wider application.

Quantifying the microvascular origin of BOLD-fMRI from first principles with two-photon microscopy and an oxygen-sensitive nanoprobe.

The blood oxygenation level-dependent (BOLD) contrast is widely used in functional magnetic resonance imaging (fMRI) studies aimed at investigating neuronal activity. However, the BOLD signal reflects changes in blood volume and oxygenation rather than neuronal activity per se. Therefore, understanding the transformation of microscopic vascular behavior into macroscopic BOLD signals is at the foundation of physiologically informed noninvasive neuroimaging. Here, we use oxygen-sensitive two-photon microscopy to measure the BOLD-relevant microvascular physiology occurring within a typical rodent fMRI voxel and predict the BOLD signal from first principles using those measurements. The predictive power of the approach is illustrated by quantifying variations in the BOLD signal induced by the morphological folding of the human cortex. This framework is then used to quantify the contribution of individual vascular compartments and other factors to the BOLD signal for different magnet strengths and pulse sequences.

MR elastography and diffusion-weighted imaging of ex vivo prostate cancer: quantitative comparison to histopathology.

The purpose of this work was (1) to develop a magnetic resonance elastography (MRE) system for imaging of the ex vivo human prostate and (2) to assess the diagnostic power of mono-frequency and multi-frequency MRE and diffusion weighted imaging (DWI) alone and combined as correlated with histopathology in a patient study. An electromagnetic driver was designed specifically for MRE studies in small-bore MR scanners. Ex vivo prostate specimens (post-fixation) of 14 patients who underwent radical prostatectomy were imaged with MRE at 7 T (nine cases had DWI). In six patients, the MRE examination was performed at three frequencies (600, 800, 1000 Hz) to extract the power-law exponent Gamma. The images were registered to wholemount pathology slides marked with the Gleason score. The areas under the receiver-operator-characteristic curves (AUC) were calculated. The methods were validated in a phantom study and it was demonstrated that (i) the driver does not interfere with the acquisition process and (ii) the driver can generate amplitudes greater than 100 µm for frequencies less than 1 kHz. In the quantitative study, cancerous tissue with Gleason score at least 3 + 3 was distinguished from normal tissue in the peripheral zone (PZ) with an average AUC of 0.75 (Gd ), 0.75 (Gl ), 0.70 (Gamma-Gd ), 0.68 (apparent diffusion coefficient, ADC), and 0.82 (Gd + Gl + ADC). The differentiation between PZ and central gland was modest for Gd (p < 0.07), Gl (p < 0.06) but not significant for Gamma (p < 0.2). A correlation of 0.4 kPa/h was found between the fixation time of the prostate specimen and the stiffness of the tissue, which could affect the diagnostic power results. DWI and MRE may provide complementary information; in fact MRE performed better than ADC in distinguishing normal from cancerous tissue in some cases. Multi-frequency (Gamma) analysis did not appear to improve the results. However, in light of the effect of tissue fixation, the clinical implication of our results may be inconclusive and more experiments are needed.

MR elastography of prostate cancer: quantitative comparison with histopathology and repeatability of methods.

The purpose of this work was to assess trans-perineal prostate magnetic resonance elastography (MRE) for (1) repeatability in phantoms/volunteers and (2) diagnostic power as correlated with histopathology in prostate cancer patients. The three-dimensional (3D) displacement field was obtained using a fractionally encoded gradient echo sequence using a custom-made transducer. The repeatability of the method was assessed based on three repeat studies and by changing the driving frequency by 3% in studies on a phantom and six healthy volunteers. Subsequently, 11 patients were examined with MRE prior to radical prostatectomy. The areas under the receiver operating characteristic curves were calculated using a windowed voxel-to-voxel approach by comparing the 2D registered slides, masked with the Gleason score. For the repeatability study, the average intraclass correlation coefficient for elasticity images was 99% for repeat phantom studies, 98% for ±6 Hz phantom studies, 95% for volunteer repeat studies with 2 min acquisition time, 82% for ±2 Hz volunteer studies with 2 min acquisition time and 73% for repeat volunteer studies with 8 min acquisition time. For the patient study, the average elasticity was 8.2 ± 1.7 kPa in the prostate capsule, 7.5 ± 1.9 kPa in the peripheral zone (PZ), 9.7 ± 3.0 kPa in the central gland (CG) and 9.0 ± 3.4 kPa in the transition zone. In the patient study, cancerous tissue with Gleason score at least 3 + 3 was significantly (p < 0.05) different from normal tissue in 10 out of 11 cases with tumors in the PZ, and 6 out of 9 cases with tumors in the CG. However, the overall case-averaged area under the curve was 0.72 in the PZ and 0.67 in the CG. Cancerous tissue was not always stiffer than normal tissue. The inversion algorithm was sensitive to (i) vibration amplitude and displacement nodes and (ii) misalignment of the 3D wave field due to subject movement.

Further improvement in reducing superficial contamination in NIRS using double short separation measurements.

Near-Infrared Spectroscopy (NIRS) allows the recovery of the evoked hemodynamic response to brain activation. In adult human populations, the NIRS signal is strongly contaminated by systemic interference occurring in the superficial layers of the head. An approach to overcome this difficulty is to use additional NIRS measurements with short optode separations to measure the systemic hemodynamic fluctuations occurring in the superficial layers. These measurements can then be used as regressors in the post-experiment analysis to remove the systemic contamination and isolate the brain signal. In our previous work, we showed that the systemic interference measured in NIRS is heterogeneous across the surface of the scalp. As a consequence, the short separation measurement used in the regression procedure must be located close to the standard NIRS channel from which the evoked hemodynamic response of the brain is to be recovered. Here, we demonstrate that using two short separation measurements, one at the source optode and one at the detector optode, further increases the performance of the short separation regression method compared to using a single short separation measurement. While a single short separation channel produces an average reduction in noise of 33% for HbO, using a short separation channel at both source and detector reduces noise by 59% compared to the standard method using a general linear model (GLM) without short separation. For HbR, noise reduction of 3% is achieved using a single short separation and this number goes to 47% when two short separations are used. Our work emphasizes the importance of integrating short separation measurements both at the source and at the detector optode of the standard channels from which the hemodynamic response is to be recovered. While the implementation of short separation sources presents some difficulties experimentally, the improvement in noise reduction is significant enough to justify the practical challenges.

Validation of the hypercapnic calibrated fMRI method using DOT-fMRI fusion imaging.

Calibrated functional magnetic resonance imaging (fMRI) is a widely used method to investigate brain function in terms of physiological quantities such as the cerebral metabolic rate of oxygen (CMRO2). The first and one of the most common methods of fMRI calibration is hypercapnic calibration. This is achieved via simultaneous measures of the blood-oxygenation-level dependent (BOLD) and the arterial spin labeling (ASL) signals during a functional task that evokes regional changes in CMRO2. A subsequent acquisition is then required during which the subject inhales carbon dioxide for short periods of time. A calibration constant, typically labeled M, is then estimated from the hypercapnic data and is subsequently used together with the BOLD-ASL recordings to compute evoked changes in CMRO2 during the functional task. The computation of M assumes a constant CMRO2 during the CO2 inhalation, an assumption that has been questioned since the origin of calibrated fMRI. In this study we used diffuse optical tomography (DOT) together with BOLD and ASL--an alternative calibration method that does not require any gas manipulation and therefore no constant CMRO2 assumption--to cross-validate the estimation of M obtained from a traditional hypercapnic calibration. We found a high correlation between the M values (R=0.87, p<0.01) estimated using these two approaches. The findings serve to validate the hypercapnic fMRI calibration technique and suggest that the inter-subject variability routinely obtained for M is reproducible with an alternative method and might therefore reflect inter-subject physiological variability.

Motion artifacts in functional near-infrared spectroscopy: a comparison of motion correction techniques applied to real cognitive data.

Motion artifacts are a significant source of noise in many functional near-infrared spectroscopy (fNIRS) experiments. Despite this, there is no well-established method for their removal. Instead, functional trials of fNIRS data containing a motion artifact are often rejected completely. However, in most experimental circumstances the number of trials is limited, and multiple motion artifacts are common, particularly in challenging populations. Many methods have been proposed recently to correct for motion artifacts, including principle component analysis, spline interpolation, Kalman filtering, wavelet filtering and correlation-based signal improvement. The performance of different techniques has been often compared in simulations, but only rarely has it been assessed on real functional data. Here, we compare the performance of these motion correction techniques on real functional data acquired during a cognitive task, which required the participant to speak aloud, leading to a low-frequency, low-amplitude motion artifact that is correlated with the hemodynamic response. To compare the efficacy of these methods, objective metrics related to the physiology of the hemodynamic response have been derived. Our results show that it is always better to correct for motion artifacts than reject trials, and that wavelet filtering is the most effective approach to correcting this type of artifact, reducing the area under the curve where the artifact is present in 93% of the cases. Our results therefore support previous studies that have shown wavelet filtering to be the most promising and powerful technique for the correction of motion artifacts in fNIRS data. The analyses performed here can serve as a guide for others to objectively test the impact of different motion correction algorithms and therefore select the most appropriate for the analysis of their own fNIRS experiment.

Quantitative oxygenation venography from MRI phase.

PURPOSE: To demonstrate acquisition and processing methods for quantitative oxygenation venograms that map in vivo oxygen saturation (SvO2 ) along cerebral venous vasculature. METHODS: Regularized quantitative susceptibility mapping (QSM) is used to reconstruct susceptibility values and estimate SvO2 in veins. QSM with ℓ1 and ℓ2 regularization are compared in numerical simulations of vessel structures with known magnetic susceptibility. Dual-echo, flow-compensated phase images are collected in three healthy volunteers to create QSM images. Bright veins in the susceptibility maps are vectorized and used to form a three-dimensional vascular mesh, or venogram, along which to display SvO2 values from QSM. RESULTS: Quantitative oxygenation venograms that map SvO2 along brain vessels of arbitrary orientation and geometry are shown in vivo. SvO2 values in major cerebral veins lie within the normal physiological range reported by (15) O positron emission tomography. SvO2 from QSM is consistent with previous MR susceptometry methods for vessel segments oriented parallel to the main magnetic field. In vessel simulations, ℓ1 regularization results in less than 10% SvO2 absolute error across all vessel tilt orientations and provides more accurate SvO2 estimation than ℓ2 regularization. CONCLUSION: The proposed analysis of susceptibility images enables reliable mapping of quantitative SvO2 along venograms and may facilitate clinical use of venous oxygenation imaging.

Deep Learning Segmentation of Infiltrative and Enhancing Cellular Tumor at Pre- and Posttreatment Multishell Diffusion MRI of Glioblastoma.

Purpose To develop and validate a deep learning (DL) method to detect and segment enhancing and nonenhancing cellular tumor on pre- and posttreatment MRI scans in patients with glioblastoma and to predict overall survival (OS) and progression-free survival (PFS). Materials and Methods This retrospective study included 1397 MRI scans in 1297 patients with glioblastoma, including an internal set of 243 MRI scans (January 2010 to June 2022) for model training and cross-validation and four external test cohorts. Cellular tumor maps were segmented by two radiologists on the basis of imaging, clinical history, and pathologic findings. Multimodal MRI data with perfusion and multishell diffusion imaging were inputted into a nnU-Net DL model to segment cellular tumor. Segmentation performance (Dice score) and performance in distinguishing recurrent tumor from posttreatment changes (area under the receiver operating characteristic curve [AUC]) were quantified. Model performance in predicting OS and PFS was assessed using Cox multivariable analysis. Results A cohort of 178 patients (mean age, 56 years ± 13 [SD]; 116 male, 62 female) with 243 MRI timepoints, as well as four external datasets with 55, 70, 610, and 419 MRI timepoints, respectively, were evaluated. The median Dice score was 0.79 (IQR, 0.53-0.89), and the AUC for detecting residual or recurrent tumor was 0.84 (95% CI: 0.79, 0.89). In the internal test set, estimated cellular tumor volume was significantly associated with OS (hazard ratio [HR] = 1.04 per milliliter; P < .001) and PFS (HR = 1.04 per milliliter; P < .001) after adjustment for age, sex, and gross total resection (GTR) status. In the external test sets, estimated cellular tumor volume was significantly associated with OS (HR = 1.01 per milliliter; P < .001) after adjustment for age, sex, and GTR status. Conclusion A DL model incorporating advanced imaging could accurately segment enhancing and nonenhancing cellular tumor, distinguish recurrent or residual tumor from posttreatment changes, and predict OS and PFS in patients with glioblastoma. Keywords: Segmentation, Glioblastoma, Multishell Diffusion MRI Supplemental material is available for this article. © RSNA, 2024.

A fNIRS investigation of switching and inhibition during the modified Stroop task in younger and older adults.

Brain imaging studies have reported age-related differences in brain activation for attentional control functions, such as inhibition and task-switching. However, age-related differences in brain activation patterns in more than one attentional control task have rarely been studied in the same group of participants. In this study, younger and older adults completed a modified Stroop task with interference and switching conditions, using functional near infra-red spectroscopy. While interference did not reveal any significant activation of the prefrontal cortex in younger adults, switching produced an increased activation bilaterally in both the anterior dorsolateral prefrontal cortex (DLPFC) and the anterior ventrolateral prefrontal cortex (VLPFC). In older adults, an isolated right and left anterior DLPFC activation was observed even in the non-executive conditions of the Stroop task (color denomination) and the interference condition revealed activation mostly in the posterior left DLPFC and bilateral VLPFC with a small right anterior DLPFC component. Specific to older adults, switching induced an increased activation spread out bilaterally over the prefrontal cortex in the bilateral anterior DLPFC, the posterior left DLPFC and bilateral VLPFC. These results suggest that for both older and younger adults, inhibition and switching are associated with distinct patterns of prefrontal activation and that age-related differences exist in these patterns such that prefrontal activation seems to be more spread out at different sites in older adults.

Calibrating the BOLD signal during a motor task using an extended fusion model incorporating DOT, BOLD and ASL data.

Multimodal imaging improves the accuracy of the localization and the quantification of brain activation when measuring different manifestations of the hemodynamic response associated with cerebral activity. In this study, we incorporated cerebral blood flow (CBF) changes measured with arterial spin labeling (ASL), Diffuse Optical Tomography (DOT) and blood oxygen level-dependent (BOLD) recordings to reconstruct changes in oxy- (ΔHbO(2)) and deoxyhemoglobin (ΔHbR). Using the Grubb relation between relative changes in CBF and cerebral blood volume (CBV), we incorporated the ASL measurement as a prior to the total hemoglobin concentration change (ΔHbT). We applied this ASL fusion model to both synthetic data and experimental multimodal recordings during a 2-s finger-tapping task. Our results show that the new approach is very powerful in estimating ΔHbO(2) and ΔHbR with high spatial and quantitative accuracy. Moreover, our approach allows the computation of baseline total hemoglobin concentration (HbT(0)) as well as of the BOLD calibration factor M on a single subject basis. We obtained an average HbT(0) of 71 µM, an average M value of 0.18 and an average increase of 13% in cerebral metabolic rate of oxygen (CMRO(2)), all of which are in agreement with values previously reported in the literature. Our method yields an independent measurement of M, which provides an alternative measurement to validate the hypercapnic calibration of the BOLD signal.