Apodized Aperture Pixel (AAP) design, proposed by Ismailova et. al, is an alternative to the conventional pixel design1. The advantages of AAP processing with a sinc filter in comparison with using other filters include non-degradation of MTF values and elimination of signal and noise aliasing, resulting in an increased performance at higher frequencies, approaching the Nyquist frequency3. If high resolution small field-of-view (FOV) detectors with small pixels used during critical stages of Endovascular Image Guided Interventions (EIGIs) could also be extended to cover a full field-of-view typical of flat panel detectors (FPDs) and made to have larger effective pixels, then methods must be used to preserve the MTF over the frequency range up to the Nyquist frequency of the FPD while minimizing aliasing. In this work, we convolve the experimentally measured MTFs of an Microangiographic Fluoroscope (MAF) detector, (the MAF-CCD with 35μm pixels) and a High Resolution Fluoroscope (HRF) detector (HRF-CMOS50 with 49.5μm pixels) with the AAP filter and show the superiority of the results compared to MTFs resulting from moving average pixel binning and to the MTF of a standard FPD. The effect of using AAP is also shown in the spatial domain, when used to image an infinitely small point object. For detectors in neurovascular interventions, where high resolution is the priority during critical parts of the intervention, but full FOV with larger pixels are needed during less critical parts, AAP design provides an alternative to simple pixel binning while effectively eliminating signal and noise aliasing yet allowing the small FOV high resolution imaging to be maintained during critical parts of the EIGI.

Independent Component Analysis with projection (ICAp) method proposed by Long et al. Hum. Brain Mapp. 30 (2009) 417-431, can solve the interaction among task-related components of multi-task functional magnetic resonance imaging (fMRI) data. However, the departure of the ideal homodynamic response function (HRF) for projection from the true HRF may worse the ICAp results. In order to improve the performance of ICAp, the deconvolved ICAp (DICAp) method is proposed. Both the simulated and real fMRI experiments demonstrate that DICAp can separate more accurate time course corresponding to each task-related components and is more powerful to detect regions activated by each task only than ICAp.

Optical imaging of rat barrel cortex has provided detailed spatio-temporal maps of functional cortical architecture. We describe an event-related procedure (ERP) for optical imaging based on selective signal averaging as reported by Burock et al., using an anti-correlative pseudo-random event sequence. The sequence used 1 s vibrissal stimulation at 5 Hz, with an interevent interval of 2 s. This rapid presentation rate allows for greater statistical power per unit time, and allows for direct comparison of event-related studies with other imaging modalities. The spatio-temporal characteristics of single wavelength and spectrographic results were found to be comparable with those obtained by standard techniques, although a general lessening of haemodynamic response function (HRF) was noted. We also describe a method of locating barrel activity by spectral analysis of summed event data. Using this technique, the power spectrum of remitted light from the barrel region was found to peak within +/- 0.12 Hz of the inter-event interval frequency.

Retinal blood vessel structure is an important indicator of many retinal and systemic diseases, which has motivated the development of various image segmentation methods for the blood vessels. In this study, two supervised and three unsupervised segmentation methods with a publicly available implementation are reviewed and quantitatively compared with each other on five public databases with ground truth segmentation of the vessels. Each method is tested under consistent conditions with two types of preprocessing, and the parameters of the methods are optimized for each database. Additionally, possibility to predict the parameters of the methods by the linear regression model is tested for each database. Resolution of the input images and amount of the vessel pixels in the ground truth are used as predictors. The results show the positive influence of preprocessing on the performance of the unsupervised methods. The methods show similar performance for segmentation accuracy, with the best performance achieved by the method by Azzopardi et al. (Acc 94.0) on ARIADB, the method by Soares et al. (Acc 94.6, 94.7) on CHASEDB1 and DRIVE, and the method by Nguyen et al. (Acc 95.8, 95.5) on HRF and STARE. The method by Soares et al. performed better with regard to the area under the ROC curve. Qualitative differences between the methods are discussed. Finally, it was possible to predict the parameter settings that give performance close to the optimized performance of each method.

Pfeifer, CE, Sacko, RS, Ortaglia, A, Monsma, EV, Beattie, PF, Goins, J, and Stodden, DF. Fit to play? Health-related fitness levels of youth athletes: A pilot study. J Strength Cond Res XX(X): 000-000, 2019-A recent National Strength and Conditioning Association position statement suggests that many youth are not prepared for the physical demands of sport. The purpose of this study was to compare health-related fitness (HRF) of youth athletes with normative findings from the general population. We recruited 136 athletes (63 male and 73 female athletes) aged 11-19 (16.01 ± 1.35) years and collected HRF (body composition, cardiorespiratory endurance, musculoskeletal strength and endurance). Results were categorized based on FITNESSGRAM standards and compared with Canadian youth general population normative data. Most male athletes were classified as "needs improvement" for cardiorespiratory and muscular endurance, and body mass index (BMI). Conversely, most female athletes were at or above the "healthy fitness zone" for all measures. Male athletes at both age groups (11-14, 15-19; p < 0.001) and female athletes aged 11-14 (p < 0.05) demonstrated lower cardiorespiratory endurance compared with Canadian general population. Female athletes (both age groups) demonstrated greater muscular strength, and male athletes (age, 15-19 years) demonstrated lower BMI than the Canadian general population. The results are concerning as male athletes demonstrated poorer HRF compared with the general population. Although most female athletes were within healthy ranges, a portion of them were still at risk. Considering the demands sport places on the body, evaluating HRF is paramount for performance and injury prevention but more importantly for overall health. Youth sport and strength coaches should evaluate and aim to enhance HRF, as participation in sport does not guarantee adequate HRF. Promoting long-term athletic development and life-long health should be a priority in youth.

We present the first demonstration of hydraulic tomography (HT) to estimate the three-dimensional (3D) hydraulic conductivity (K) distribution of a fractured aquifer at high-resolution field scale (HRFS), including the fracture network and connectivity through it. We invert drawdown data collected from packer-isolated borehole intervals during 42 pumping tests in a wellfield at the former Naval Air Warfare Center, West Trenton, New Jersey, in the Newark Basin. Five additional tests were reserved for a quality check of HT results. We used an equivalent porous medium forward model and geostatistical inversion to estimate 3D K at high resolution (K blocks <1 m³ ), using no strict assumptions about K variability or fracture statistics. The resulting 3D K estimate ranges from approximately 0.1 (highest-K fractures) to approximately 10^-13 m/s (unfractured mudstone). Important estimated features include: (1) a highly fractured zone (HFZ) consisting of a sequence of high-K bedding-plane fractures; (2) a low-K zone that disrupts the HFZ; (3) several secondary fractures of limited extent; and (4) regions of very low-K rock matrix. The 3D K estimate explains complex drawdown behavior observed in the field. Drawdown tracing and particle tracking simulations reveal a 3D fracture network within the estimated K distribution, and connectivity routes through the network. Model fit is best in the shallower part of the wellfield, with high density of observations and tests. The capabilities of HT demonstrated for 3D fractured aquifer characterization at HRFS may support improved in situ remediation for contaminant source zones, and applications in mining, repository assessment, or geotechnical engineering.

The purpose of this study was to investigate reciprocal relationships among students' motor competence (MC) (leaping, throwing, catching, jumping skills), perceived physical competence, health-related fitness (HRF) (20 m shuttle run, push-up, abdominal muscles endurance tests) and objectively measured moderate-to-vigorous physical activity (MVPA). Participants included 422 Grade 5 Finnish children (246 girls). Two separate structural equation models investigated paths (a) from MC through both perceived physical competence and HRF to MVPA, and (b) from MVPA through both perceived physical competence and HRF to MC. Model 1 demonstrated an indirect path from MC through HRF to MVPA and a direct path from MC to perceived physical competence for both boys and girls. Additionally, model 1 revealed a direct path from perceived physical competence to MVPA for the girls and from MC to MVPA for the boys. MC, perceived physical competence, and HRF explained 13% of variance in MVPA for the girls and 25% for the boys. Model 2 indicated indirect paths from MVPA through perceived physical competence to MC and from MVPA through HRF to MC for both boys and girls. Additionally, a direct path from MVPA to MC was found in the boys' group. MVPA, perceived physical competence, and HRF explained 48% of variance in MC for the girls and 53% for the boys. Results of this study provide preliminary support for the reciprocal nature of relationships among MC development, perceived physical competence, HRF and MVPA.

The focus of this paper is on evaluating brain responses to different stimuli and identifying brain regions with different responses using multi-subject, stimulus-evoked functional magnetic resonance imaging (fMRI) data. To jointly model many brain voxels' responses to designed stimuli, we present a new low-rank multivariate general linear model (LRMGLM) for stimulus-evoked fMRI data. The new model not only is flexible to characterize variation in hemodynamic response functions (HRFs) across different regions and stimulus types, but also enables information "borrowing" across voxels and uses much fewer parameters than typical nonparametric models for HRFs. To estimate the proposed LRMGLM, we introduce a new penalized optimization function, which leads to temporally and spatially smooth HRF estimates. We develop an efficient optimization algorithm to minimize the optimization function and identify the voxels with different responses to stimuli. We show that the proposed method can outperform several existing voxel-wise methods by achieving both high sensitivity and specificity. We apply the proposed method to the fMRI data collected in an emotion study, and identify anterior dACC to have different responses to a designed threat and control stimuli.

Financial crunch in the present recession results in the non-availability of the right materials at the right time in large hospitals. However due to insufficient impetus towards systems development, situation remains dismal even when funds are galore. Cost incurred on materials account for approximately one-third of the total recurring expenditures in hospitals. Systems development for effective and efficient materials management is thus tantamount to cost-containment and sustainability. This scientific paper describes an innovative model, Hospital Revolving Fund (HRF), developed at a tertiary care research institute in Asia. The main idea behind inception of HRF was to ensure availability of all supplies in the hospital so that the quality of healthcare delivery was not affected. The model was conceptualized in the background of non-availability of consumables in the hospital leading to patient as well as staff dissatisfaction. Hospital supplies have been divided into two parts, approximately 3250 unit items and 1750 miscellaneous items. This division is based on cost, relative-utility and case-specific utilization. 0.1 Million USD, separated from non-planned budget, was initially used as seed money in 1998. HRF procures supplies from reputed firms on concessional rates (8-25%) and make them available to patients at much lesser rates vis-à-vis market rates, levying minimal maintenance charges. In 2009-10, total annual purchases of 14 Million USD were made. The balance sheet reflected 1.4 Million USD as fixed deposit investment. The minimal maintenance charges levied on the patients along with the interest income were sufficient to pay for all recurring expenses related to HRF. Even after these expenses, HRF boosted of 0.2 Million USD as cash-in-hand in financial year 2009-10. In-depth analysis of 'balance sheet' and 'Income and Expenditure' statement of the fund for last five financial years affirms that HRF is a self-sustainable and viable supply chain mechanism to ensure availability of the right materials at the right time at a reasonable cost. Thus innovations like HRF will prove robust in rendering quality healthcare at an affordable cost.

DuPont's HRF-150 photopolymer film is investigated for use in three-dimensional holographic memories. Measurements of sensitivity, hologram persistence, the lateral spread of the photoinitiated reaction, and the variation of diffraction efficiency with modulation depth, spatial frequency and tilt angle, and intensity are reported. We observed that the diffraction efficiency of the HRF-150 photopolymer for a given exposure decreases with increases in intensity and grating tilt angle. The holograms were nondestructively reconstructed for long periods of time at room temperature. The photoinitiated reaction spread less than 100 µm over a period of 16 h.

Heart rate fragmentation (HRF), a marker of abnormal sinoatrial dynamics, was shown to be associated with incident cardiovascular events in the Multi-Ethnic Study of Atherosclerosis (MESA). Here, we test the hypothesis that HRF is also associated with incident atrial fibrillation (AF) in the MESA cohort of participants who underwent in-home polysomnography (PSG) and in two high-risk subgroups: those ≥70 years taking antihypertensive medication and those with serum concentrations of N-terminal prohormone B-type natriuretic peptide (NT-proBNP) >125 pg/ml (top quartile). Heart rate time series (n=1,865) derived from the ECG channel of the PSG were analyzed using newly developed HRF metrics, traditional heart rate variability (HRV) indices and two widely used nonlinear measures. Eighty-three participants developed AF over a median follow-up period of 3.83 ± 0.87 years. A one-SD increase in HRF was associated with a 35% (95% CI: 7%-70%) increase in risk of incident AF, in Cox models adjusted for age, height, NT-proBNP and frequent premature supraventricular complexes. Furthermore, HRF added value to the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE)-AF model. Traditional HRV and nonlinear indices were not significantly associated with incident AF. In the two high-risk subgroups defined above, HRF was also significantly associated with incident AF in unadjusted and adjusted models. These findings support the translational utility of HRF metrics for short-term (approximately four-year) prediction of AF. In addition, they support broadening the concept of atrial remodeling to include electrodynamical remodeling, a term used to refer to pathophysiologic alterations in sinus interbeat interval dynamics.

Keywords: atrial fibrillation; autonomic nervous system; heart rate fragmentation; heart rate variability; sinus node.

Modern 3D printing technology can fabricate vascular phantoms based on an actual human patient with a high degree of precision facilitating a realistic simulation environment for an intervention. We present two experimental setups using 3D printed patient-specific neurovasculature to simulate different disease anatomies. To simulate the human neurovasculature in the Circle of Willis, patient-based phantoms with aneurysms were 3D printed using a Objet Eden 260V printer. Anthropomorphic head phantoms and a human skull combined with acrylic plates simulated human head bone anatomy and x-ray attenuation. For dynamic studies the 3D printed phantom was connected to a pulsatile flow loop with the anthropomorphic phantom underneath. By combining different 3D printed phantoms and the anthropomorphic phantoms, different patient pathologies can be simulated. For static studies a 3D printed neurovascular phantom was embedded inside a human skull and used as a positional reference for treatment devices such as stents. To simulate tissue attenuation acrylic layers were added. Different combinations can simulate different patient treatment procedures. The Complementary-Metal-Oxide-Semiconductor (CMOS) based High Resolution Fluoroscope (HRF) with 75μm pixels offers an advantage over the state-of-the-art 200 μm pixel Flat Panel Detector (FPD) due to higher Nyquist frequency and better DQE performance. Whether this advantage is clinically useful during an actual clinical neurovascular intervention can be addressed by qualitatively evaluating images from a cohort of various cases performed using both detectors. The above-mentioned method can offer a realistic substitute for an actual clinical procedure. Also a large cohort of cases can be generated and used for a HRF clinical utility determination study.

Event-related ICA (eICA) is a partially data-driven analysis method for event-related fMRI that is particularly suited to analysis of simultaneous EEG-fMRI of patients with epilepsy. EEG-fMRI studies in epileptic patients are typically analyzed using the general linear model (GLM), often with assumption that the onset and offset of neuronal activity match EEG event onset and offset, the neuronal activation is sustained at a constant level throughout the epileptiform event and that associated fMRI signal changes follow the canonical HRF. The eICA method allows for less constrained analyses capable of detecting early, non-canonical responses. A key step of eICA is the initial deconvolution which can be confounded by various sources of structured noise present in the fMRI signal. To help overcome this, we have extend the eICA procedure by utilizing a fully standalone and automated fMRI de-noising procedure to process the fMRI data from an EEG-fMRI acquisition prior to running eICA. Specifically we first apply ICA to the entire fMRI time-series and use a classifier to remove noise-related components. The automated objective de-noiser, "Spatially Organized Component Klassificator" (SOCK) is used; it has previously been shown to distinguish a substantial fraction of noise from true activation, without rejecting the latter, in resting-state fMRI. A second ICA is then performed, this time on the event-related response estimates derived from the denoised data (according to the usual eICA procedure). We hypothesize that SOCK + eICA has the potential to be more sensitive than eICA alone. We test the effectiveness of SOCK by comparing activation obtained in an eICA analysis of EEG-fMRI data with and without the use of SOCK for 14 patients with rolandic epilepsy who exhibited stereotypical IEDs arising from a focus in the rolandic fissure.

Recent studies have applied the new magnetic resonance encephalography (MREG) sequence to the study of interictal epileptic discharges (IEDs) in the electroencephalogram (EEG) of epileptic patients. However, there are no criteria to quantitatively evaluate different processing methods, to properly use the new sequence.

We evaluated different processing steps of this new sequence under the common generalized linear model (GLM) framework by assessing the reliability of results. A bootstrap sampling technique was first used to generate multiple replicated data sets; a GLM with different processing steps was then applied to obtain activation maps, and the reliability of these maps was assessed.

We applied our analysis in an event-related GLM related to IEDs. A higher reliability was achieved by using a GLM with head motion confound regressor with 24 components rather than the usual 6, with an autoregressive model of order 5 and with a canonical hemodynamic response function (HRF) rather than variable latency or patient-specific HRFs. Comparison of activation with IED field also favored the canonical HRF, consistent with the reliability analysis.

The reliability analysis helps to optimize the processing methods for this fast fMRI sequence, in a context in which we do not know the ground truth of activation areas. Magn Reson Med 78:370-382, 2017. © 2016 International Society for Magnetic Resonance in Medicine.

We studied the blood oxygen level dependent (BOLD) response to interictal epileptic spikes in a group of patients with focal epilepsy by simultaneous recording of electroencephalography (EEG) and functional magnetic resonance imaging (fMRI). The detection of activated areas was performed by using an approach based on the theory of the General Linear Models (GLM). Since little is know about the haemodynamic response to the interictal epileptiform activity, for each region involved by fMRI response and for each subject we obtained a robust estimation of the haemodynamic response function (HRF) by using a Bayesian approach. We observed important variations in the time course of the haemodynamic response between patients and across the different fMRI areas of a same subject.

Techniques of multivariate pattern analysis (MVPA) can be used to decode the discrete experimental condition or a continuous modulator variable from measured brain activity during a particular trial. In functional magnetic resonance imaging (fMRI), trial-wise response amplitudes are sometimes estimated from the measured signal using a general linear model (GLM) with one onset regressor for each trial. When using rapid event-related designs with trials closely spaced in time, those estimates are highly variable and serially correlated due to the temporally extended shape of the hemodynamic response function (HRF). Here, we describe inverse transformed encoding modelling (ITEM), a principled approach of accounting for those serial correlations and decoding from the resulting estimates, at low computational cost and with no loss in statistical power. We use simulated data to show that ITEM outperforms the current standard approach in terms of decoding accuracy and analyze empirical data to demonstrate that ITEM is capable of visual reconstruction from fMRI signals.

Conserved structural waters trapped within GPCRs may form water networks indispensable for GPCR's signaling functions. Radiolysis-based hydroxyl radical footprinting (HRF) strategies coupled to mass spectrometry have been used to explore the structural waters within rhodopsin in multiple signaling states. These approaches, combined with (18)O labeling, can be used to identify the locations of structural waters in the transmembrane region and measure rates of water exchange with bulk solvent. Reorganizations of structural waters upon activation of signaling can be explicitly observed with this approach, and this provides a unique look at the structural modules driving the signaling process.

Previous works investigated a range of spatio-temporal models for fMRI data analysis to provide robust determination of functional region-of-interest (ROI). We present a novel spatio-temporal fMRI model that is suitable for identifying a number of distinct temporal patterns and their spatial support in the voxel space. Accordingly, fMRI signals on a single voxel are modeled as a probabilistic superposition of those temporal patterns. The spatially varying influence of individual patterns is defined in terms of a parameterised function. The temporal pattern is characterised by both the underlying hemodynamic response function (HRF) and a time series of the individual stimulus-response magnitudes, which makes the proposed model particularly suitable for modeling rapid event-related fMRI data. Moreover, a parametric approach is adopted to represent the HRFs. The resulting methodology is conceptually principled and computationally efficient. We first verify the proposed model in a controlled experimental setting using synthetic data. The model is further applied to analyzing real fMRI data, with focus on functional homogeneity within individual ROIs.

The extraction of information about neural activity timing from BOLD signal is a challenging task as the shape of the BOLD curve does not directly reflect the temporal characteristics of electrical activity of neurons. In this work, we introduce the concept of neural processing time (NPT) as a parameter of the biophysical model of the hemodynamic response function (HRF). Through this new concept we aim to infer more accurately the duration of neuronal response from the highly nonlinear BOLD effect. The face validity and applicability of the concept of NPT are evaluated through simulations and analysis of experimental time series. The results of both simulation and application were compared with summary measures of HRF shape. The experiment that was analyzed consisted of a decision-making paradigm with simultaneous emotional distracters. We hypothesize that the NPT in primary sensory areas, like the fusiform gyrus, is approximately the stimulus presentation duration. On the other hand, in areas related to processing of an emotional distracter, the NPT should depend on the experimental condition. As predicted, the NPT in fusiform gyrus is close to the stimulus duration and the NPT in dorsal anterior cingulate gyrus depends on the presence of an emotional distracter. Interestingly, the NPT in right but not left dorsal lateral prefrontal cortex depends on the stimulus emotional content. The summary measures of HRF obtained by a standard approach did not detect the variations observed in the NPT.

Achieving a uniform fan-out energy distribution is critical to the successful applications of substrate guided-wave optical interconnects. Using Dupont photopolymer film HRF-600X00120, we investigated the optimum recording beam intensity for obtaining a large dynamic region of diffraction efficiency relative to exposure dosage. Based on the experimental diffraction efficiency curve, 1-to-5 and 1-to-9 surface-normal fan-out devices were fabricated that operated at a wavelength of 850nm, and output nonuniformities of +/-4 % and +/-10 % were obtained for the two devices.

Tacrine, a cholinesterase inhibitor for symptomatic treatment of minor to moderate dementia, and its primary metabolites 1-hydroxy-tacrine and 4-hydroxy-tacrine were studied by means of thin-layer chromatography, UV spectroscopy and gas-chromatography/mass spectroscopy. The analytical data (corrected hRf values, UV spectra in solution as well as reflectance spectra, high-pressure liquid chromatography data, GC retention indices and EI mass spectra) including various derivatization methods are described.

Blood oxygen level-dependent functional magnetic resonance imaging (BOLD-fMRI) is a standard clinical tool for the detection of brain activation. In Alzheimer's disease (AD), task-related and resting state fMRI have been used to detect brain dysfunction. It has been shown that the shape of the BOLD response is affected in early AD. To correctly interpret these changes, the mechanisms responsible for the observed behaviour need to be known. The parameters of the canonical hemodynamic response function (HRF) commonly used in the analysis of fMRI data have no direct biological interpretation and cannot be used to answer this question. We here present a model that allows relating AD-specific changes in the BOLD shape to changes in the underlying energy metabolism. According to our findings, the classic view that differences in the BOLD shape are only attributed to changes in strength and duration of the stimulus does not hold. Instead, peak height, peak timing and full width at half maximum are sensitive to changes in the reaction rate of several metabolic reactions. Our systems-theoretic approach allows the use of patient-specific clinical data to predict dementia-driven changes in the HRF, which can be used to improve the results of fMRI analyses in AD patients.