Robust estimation of quantitative perfusion from multi-phase pseudo-continuous arterial spin labeling.

PURPOSE: Multi-phase PCASL has been proposed as a means to achieve accurate perfusion quantification that is robust to imperfect shim in the labeling plane. However, there exists a bias in the estimation process that is a function of noise in the data. In this work, this bias is characterized and then addressed in animal and human data. METHODS: The proposed algorithm to overcome bias uses the initial biased voxel-wise estimate of phase tracking error to cluster regions with different off-resonance phase shifts, from which a high-SNR estimate of regional phase offset is derived. Simulations were used to predict the bias expected at typical SNR. Multi-phase PCASL in 3 rat strains (n = 21) at 9.4 T was considered, along with 20 human subjects previously imaged using ASL at 3 T. The algorithm was extended to include estimation of arterial blood flow velocity. RESULTS: Based on simulations, a perfusion estimation bias of 6-8% was expected using 8-phase data at typical SNR. This bias was eliminated when a high-precision estimate of phase error was available. In the preclinical data, the bias-corrected measure of perfusion (107 ± 14 mL/100g/min) was lower than the standard analysis (116 ± 14 mL/100g/min), corresponding to a mean observed bias across strains of 8.0%. In the human data, bias correction resulted in a 15% decrease in the estimate of perfusion. CONCLUSIONS: Using a retrospective algorithmic approach, it was possible to exploit common information found in multiple voxels within a whole region of the brain, offering superior SNR and thus overcoming the bias in perfusion quantification from multi-phase PCASL.

ICA-based denoising for ASL perfusion imaging.

Arterial Spin Labelling (ASL) imaging derives a perfusion image by tracing the accumulation of magnetically labeled blood water in the brain. As the image generated has an intrinsically low signal to noise ratio (SNR), multiple measurements are routinely acquired and averaged, at a penalty of increased scan duration and opportunity for motion artefact. However, this strategy alone might be ineffective in clinical settings where the time available for acquisition is limited and patient motion are increased. This study investigates the use of an Independent Component Analysis (ICA) approach for denoising ASL data, and its potential for automation. 72 ASL datasets (pseudo-continuous ASL; 5 different post-labeling delays: 400, 800, 1200, 1600, 2000 m s; total volumes = 60) were collected from thirty consecutive acute stroke patients. The effects of ICA-based denoising (manual and automated) where compared to two different denoising approaches, aCompCor, a Principal Component-based method, and Enhancement of Automated Blood Flow Estimates (ENABLE), an algorithm based on the removal of corrupted volumes. Multiple metrics were used to assess the changes in the quality of the data following denoising, including changes in cerebral blood flow (CBF) and arterial transit time (ATT), SNR, and repeatability. Additionally, the relationship between SNR and number of repetitions acquired was estimated before and after denoising the data. The use of an ICA-based denoising approach resulted in significantly higher mean CBF and ATT values (p < 0.001), lower CBF and ATT variance (p < 0.001), increased SNR (p < 0.001), and improved repeatability (p < 0.05) when compared to the raw data. The performance of manual and automated ICA-based denoising was comparable. These results went beyond the effects of aCompCor or ENABLE. Following ICA-based denoising, the SNR was higher using only 50% of the ASL-dataset collected than when using the whole raw data. The results show that ICA can be used to separate signal from noise in ASL data, improving the quality of the data collected. In fact, this study suggests that the acquisition time could be reduced by 50% without penalty to data quality, something that merits further study. Independent component classification and regression can be carried out either manually, following simple criteria, or automatically.

Partial volume correction for quantitative CEST imaging of acute ischemic stroke.

PURPOSE: Contributions of cerebrospinal fluid (CSF) have not been previously taken into account in the quantification of APT CEST effects, and correction for the dilution of CEST effects by CSF may allow for more robust measurement of CEST signals. The objective of this study was to compare the robustness of a partial volume (PV) correction model against a standard (4-pool) multi-pool model as far as their ability to quantify CEST effects in healthy, normal, and pathological tissue. METHODS: MRI data from 12 patients presenting with ischemic stroke, and 6 healthy subjects, were retrospectively analyzed. CEST signals derived from a 4-pool model and a PV correction model were compared for repeatability and pathological tissue contrast. The effect of PV correction (PVC) was assessed within 3 ranges of tissue PV estimate (PVE): high PVE voxels, low PVE voxels, and the whole slice. RESULTS: In voxels with a high tissue PVE, PV correction did not make a significant difference to absolute APTR* . In low PVE voxels, the PVC model exhibited a significantly decreased ischemic core signal. The PVC measures exhibited higher repeatability between healthy subjects (4 pools: 3.4%, PVC: 2.4%) while maintaining a similar ischemic core CNR (0.7) to the 4-pool model. In whole slice analysis it was found that both models exhibited similar results. CONCLUSIONS: PV correction yielded a measure of APT effects that was more repeatable than standard 4-pool analysis while achieving a similar CNR in pathological tissue, suggesting that PV-corrected analysis was more robust at low values of tissue PVE.

A Variational Bayesian inference method for parametric imaging of PET data.

In dynamic Positron Emission Tomography (PET) studies, compartmental models provide the richest information on the tracer kinetics of the tissue. Inverting such models at the voxel level is however quite challenging due to the low signal-to-noise ratio of the time activity curves. In this study, we propose the use of a Variational Bayesian (VB) approach to efficiently solve this issue and thus obtain robust quantitative parametric maps. VB was adapted to the non-uniform noise distribution of PET data. Moreover, we propose a novel hierarchical scheme to define the model parameter priors directly from the images in case such information are not available from the literature, as often happens with new PET tracers. VB was initially tested on synthetic data generated using compartmental models of increasing complexity, providing accurate (%bias<2%±2%, root mean square error<15%±5%) parameter estimates. When applied to real data on a paradigmatic set of PET tracers (L-[1-11C]leucine, [11C]WAY100635 and [18F]FDG), VB was able to generate reliable parametric maps even in presence of high noise in the data (unreliable estimates<11%±5%).

Comparing different analysis methods for quantifying the MRI amide proton transfer (APT) effect in hyperacute stroke patients.

Amide proton transfer (APT) imaging is a pH mapping method based on the chemical exchange saturation transfer phenomenon that has potential for penumbra identification following stroke. The majority of the literature thus far has focused on generating pH-weighted contrast using magnetization transfer ratio asymmetry analysis instead of quantitative pH mapping. In this study, the widely used asymmetry analysis and a model-based analysis were both assessed on APT data collected from healthy subjects (n = 2) and hyperacute stroke patients (n = 6, median imaging time after onset = 2 hours 59 minutes). It was found that the model-based approach was able to quantify the APT effect with the lowest variation in grey and white matter (≤ 13.8 %) and the smallest average contrast between these two tissue types (3.48 %) in the healthy volunteers. The model-based approach also performed quantitatively better than the other measures in the hyperacute stroke patient APT data, where the quantified APT effect in the infarct core was consistently lower than in the contralateral normal appearing tissue for all the patients recruited, with the group average of the quantified APT effect being 1.5 ± 0.3 % (infarct core) and 1.9 ± 0.4 % (contralateral). Based on the fitted parameters from the model-based analysis and a previously published pH and amide proton exchange rate relationship, quantitative pH maps for hyperacute stroke patients were generated, for the first time, using APT imaging.

Optimal sampling schedule for chemical exchange saturation transfer.

The sampling schedule for chemical exchange saturation transfer imaging is normally uniformly distributed across the saturation frequency offsets. When this kind of evenly distributed sampling schedule is used to quantify the chemical exchange saturation transfer effect using model-based analysis, some of the collected data are minimally informative to the parameters of interest. For example, changes in labile proton exchange rate and concentration mainly affect the magnetization near the resonance frequency of the labile pool. In this study, an optimal sampling schedule was designed for a more accurate quantification of amine proton exchange rate and concentration, and water center frequency shift based on an algorithm previously applied to magnetization transfer and arterial spin labeling. The resulting optimal sampling schedule samples repeatedly around the resonance frequency of the amine pool and also near to the water resonance to maximize the information present within the data for quantitative model-based analysis. Simulation and experimental results on tissue-like phantoms showed that greater accuracy and precision (>30% and >46%, respectively, for some cases) were achieved in the parameters of interest when using optimal sampling schedule compared with evenly distributed sampling schedule. Hence, the proposed optimal sampling schedule could replace evenly distributed sampling schedule in chemical exchange saturation transfer imaging to improve the quantification of the chemical exchange saturation transfer effect and parameter estimation.

Quantitative measurement of cerebral physiology using respiratory-calibrated MRI.

Functional magnetic resonance imaging typically measures signal increases arising from changes in the transverse relaxation rate over small regions of the brain and associates these with local changes in cerebral blood flow, blood volume and oxygen metabolism. Recent developments in pulse sequences and image analysis methods have improved the specificity of the measurements by focussing on changes in blood flow or changes in blood volume alone. However, FMRI is still unable to match the physiological information obtainable from positron emission tomography (PET), which is capable of quantitative measurements of blood flow and volume, and can indirectly measure resting metabolism. The disadvantages of PET are its cost, its availability, its poor spatial resolution and its use of ionising radiation. The MRI techniques introduced here address some of these limitations and provide physiological data comparable with PET measurements. We present an 18-minute MRI protocol that produces multi-slice whole-brain coverage and yields quantitative images of resting cerebral blood flow, cerebral blood volume, oxygen extraction fraction, CMRO(2), arterial arrival time and cerebrovascular reactivity of the human brain in the absence of any specific functional task. The technique uses a combined hyperoxia and hypercapnia paradigm with a modified arterial spin labelling sequence.

Partial volume correction of multiple inversion time arterial spin labeling MRI data.

The accuracy of cerebral blood flow (CBF) estimates from arterial spin labeling (ASL) is affected by the presence of both gray matter (GM) and white matter within any voxel. Recently a partial volume (PV) correction method for ASL has been demonstrated (Asllani et al. Magn Reson Med 2008; 60:1362-1371), where PV estimates were used with a local linear regression to separate the GM and white matter ASL signal. Here a new PV correction method for multi-inversion time ASL is proposed that exploits PV estimates within a spatially regularized kinetic curve model analysis. The proposed method exploits both PV estimates and the different kinetics of the ASL signal arising from GM and white matter. The new correction method is shown, on both simulated and real data, to provide correction of GM CBF comparable to a linear regression approach, whilst preserving greater spatial detail in the CBF image. On real data corrected GM CBF values were found to be largely independent of GM PV, implying that the correction had been successful. Increases of mean GM CBF after correction of 69-80% were observed.

Erythropoietin elevates VO2,max but not voluntary wheel running in mice.

Voluntary activity is a complex trait, comprising both behavioral (motivation, reward) and anatomical/physiological (ability) elements. In the present study, oxygen transport was investigated as a possible limitation to further increases in running by four replicate lines of mice that have been selectively bred for high voluntary wheel running and have reached an apparent selection limit. To increase oxygen transport capacity, erythrocyte density was elevated by the administration of an erythropoietin (EPO) analogue. Mice were given two EPO injections, two days apart, at one of two dose levels (100 or 300 microg kg(-1)). Hemoglobin concentration ([Hb]), maximal aerobic capacity during forced treadmill exercise (VO2,max) and voluntary wheel running were measured. [Hb] did not differ between high runner (HR) and non-selected control (C) lines without EPO treatment. Both doses of EPO significantly (P<0.0001) increased [Hb] as compared with sham-injected animals, with no difference in [Hb] between the 100 microg kg(-1) and 300 microg kg(-1) dose levels (overall mean of 4.5 g dl(-1) increase). EPO treatment significantly increased VO2,max by approximately 5% in both the HR and C lines, with no dosexline type interaction. However, wheel running (revolutions per day) did not increase with EPO treatment in either the HR or C lines, and in fact significantly decreased at the higher dose in both line types. These results suggest that neither [Hb] per se nor VO2,max is limiting voluntary wheel running in the HR lines. Moreover, we hypothesize that the decrease in wheel running at the higher dose of EPO may reflect direct action on the reward pathway of the brain.

Fatal myocarditis and rhabdomyositis in a patient with stage IV melanoma treated with combined ipilimumab and nivolumab.

Combination immune checkpoint blockade with concurrent administration of the anti-ctla4 antibody ipilimumab and the anti-PD-1 antibody nivolumab has demonstrated impressive responses in patients with advanced melanoma and other diseases. That combination has also been associated with increased toxicity, including rare immune-related adverse events. Here we describe a case of fatal steroid-refractory myocarditis and panmyositis associated with the use of this combination in a patient with metastatic melanoma. Correlative studies indicated increased levels of serum interleukin 6 in this patient at the onset of toxicity, suggesting a possible role for anti-interleukin 6 receptor antibodies in the treatment of subsequent cases of this rare, but fatal, toxicity.

Quantitative CEST imaging of amide proton transfer in acute ischaemic stroke.

BACKGROUND: Amide proton transfer (APT) imaging may help identify the ischaemic penumbra in stroke patients, the classical definition of which is a region of tissue around the ischaemic core that is hypoperfused and metabolically stressed. Given the potential of APT imaging to complement existing imaging techniques to provide clinically-relevant information, there is a need to develop analysis techniques that deliver a robust and repeatable APT metric. The challenge to accurate quantification of an APT metric has been the heterogeneous in-vivo environment of human tissue, which exhibits several confounding magnetisation transfer effects including spectrally-asymmetric nuclear Overhauser effects (NOEs). The recent literature has introduced various model-free and model-based approaches to analysis that seek to overcome these limitations. OBJECTIVES: The objective of this work was to compare quantification techniques for CEST imaging that specifically separate APT and NOE effects for application in the clinical setting. Towards this end a methodological comparison of different CEST quantification techniques was undertaken in healthy subjects, and around clinical endpoints in a cohort of acute stroke patients. METHODS: MRI data from 12 patients presenting with ischaemic stroke were retrospectively analysed. Six APT quantification techniques, comprising model-based and model-free techniques, were compared for repeatability and ability for APT to distinguish pathological tissue in acute stroke. RESULTS: Robustness analysis of six quantification techniques indicated that the multi-pool model-based technique had the smallest contrast between grey and white matter (2%), whereas model-free techniques exhibited the highest contrast (>30%). Model-based techniques also exhibited the lowest spatial variability, of which 4-pool APTR∗ was by far the most uniform (10% coefficient of variation, CoV), followed by 3-pool analysis (20%). Four-pool analysis yielded the highest ischaemic core contrast-to-noise ratio (0.74). Four-pool modelling of APT effects was more repeatable (3.2% CoV) than 3-pool modelling (4.6% CoV), but this appears to come at the cost of reduced contrast between infarct growth tissue and normal tissue. CONCLUSION: The multi-pool measures performed best across the analyses of repeatability, spatial variability, contrast-to-noise ratio, and grey matter-white matter contrast, and might therefore be more suitable for use in clinical imaging of acute stroke. Addition of a fourth pool that separates NOEs and semisolid effects appeared to be more biophysically accurate and provided better separation of the APT signal compared to the 3-pool equivalent, but this improvement appeared be accompanied by reduced contrast between infarct growth tissue and normal tissue.

Feasibility of Flat Panel Detector CT in Perfusion Assessment of Brain Arteriovenous Malformations: Initial Clinical Experience.

The different results from flat panel detector CT in various pathologies have provoked some discussion. Our aim was to assess the role of flat panel detector CT in brain arteriovenous malformations, which has not yet been assessed. Five patients with brain arteriovenous malformations were studied with flat panel detector CT, DSC-MR imaging, and vessel-encoded pseudocontinuous arterial spin-labeling. In glomerular brain arteriovenous malformations, perfusion was highest next to the brain arteriovenous malformation with decreasing values with increasing distance from the lesion. An inverse tendency was observed in the proliferative brain arteriovenous malformation. Flat panel detector CT, originally thought to measure blood volume, correlated more closely with arterial spin-labeling-CBF and DSC-CBF than with DSC-CBV. We conclude that flat panel detector CT perfusion depends on the time point chosen for data collection, which is triggered too early in these patients (ie, when contrast agent appears in the superior sagittal sinus after rapid shunting through the brain arteriovenous malformation). This finding, in combination with high data variability, makes flat panel detector CT inappropriate for perfusion assessment in brain arteriovenous malformations.

A physiological model of gas pockets in crevices and their behavior under compression.

The formation of bubbles in the body from dissolved gases during decompression causes a range of symptoms, often referred to as Decompression Sickness. It is likely that these bubbles grow from pre-existing nuclei. It has been proposed that such nuclei are pockets of gas that are stabilized against collapse under raised pressure, such as that experienced by deep-sea divers. This work explores the stabilization of gas pockets in crevices, in its application to the nucleation of bubbles in blood vessels. A model has been derived to describe the dynamics of a bubble in a crevice, assuming that gases diffuse in and out of the bubble via the crevice wall from the body tissues surrounding the crevice. The time-varying behavior of the bubble has been examined and it has been shown that a crevice bubble can survive compression by temporary variations in the gas-liquid interface curvature or by shrinking, its behavior being found to be strongly dependent upon the model parameters.

A physiological model of the release of gas bubbles from crevices under decompression.

Moving bubbles have been observed in the blood during or after decompression using ultrasonic techniques. It has been proposed that these may grow from nuclei housed on the blood vessel wall. One candidate for bubble nucleation is hydrophobic crevices. This work explores the growth of gas pockets that might exist in conical crevices and the release of bubbles from these crevices under decompression. An existing dynamic mathematical model for the stability of gas pockets in crevices [Chappell, M.A., Payne, S.J., in press. A physiological model of gas pockets in crevices and their behavior under compression. Respir. Physiol. Neurobiol.] is extended to include the behavior as the gas pocket reaches the crevice mouth and bubbles seed into the bloodstream. The behavior of the crevice bubble is explored for a single inert gas, both alone and with metabolic gases included. It was found that the presence of metabolic gases has a significant effect on the behavior under decompression and that this appears to be due to the high diffusivity of these gases.

A physiological model of the interaction between tissue bubbles and the formation of blood-borne bubbles under decompression.

Under decompression, bubbles can form in the human body, and these can be found both within the body tissues and the bloodstream. Mathematical models for the growth of both types of bubbles have previously been presented, but they have not been coupled together. This work thus explores the interaction between the growth of tissue and blood-borne bubbles under decompression, specifically looking at the extent to which they compete for the common resource of inert gas held in solution in the tissues. The influence of tissue bubbles is found to be significant for densities as low as 10 ml(-1) for tissues which are poorly perfused. However, the effects of formation of bubbles in the blood are not found until the density of bubble production sites reaches 10(6) ml(-1). From comparison of the model predictions with experimental evidence for bubbles produced in animals and man under decompression, it is concluded that the density of tissue bubbles is likely to have a significant effect on the number of bubbles produced in the blood. However, the density of nucleation sites in the blood is unlikely to be sufficiently high in humans for the formation of bubbles in the blood to have a significant impact on the growth of the bubbles in the tissue.

Standard operative temperatures and cost of thermoregulation in the arctic ground squirrel, Spermophilus undulatus.

Body temperatures (T b) and daily activity patterns of free-living arctic ground squirrells (Spermophilus undulatus) were determined via telemetry at a field site in northern Alaska. Simultaneous measurements were made of ambient temperature (T a), wind speed (V), and incident solar radiation. The operative environmental temperature (T e) for ground squirrels was obtained from fur-covered, thin metal taxidermic models of the animals. Standard operative temperature (T es), a comparative index of heat flow, was calculated from T e, V, and laboratory measurements of thermal conductivity.During the period of the study (August), S. undulatus were active for about 14 h per day (06.00 to 20.00 h). T b was high throughout the daily cycle, averaging 38-39°C. Circadian variations in T b were slight; average T b values dropped <1°C at night. Daytime T b fluctuations were not closely correlated to activity or to changes in environmental conditions. Air temperatures during the study were low, usually between 10 and 15°C during the day. However, T es in exposed areas was normally higher, even though skies were generally overcast. During periods of sunshine, T es may be as high as 34°C. The absence of nocturnal activity may result from increased costs of thermoregulation at night, which sharply reduces foraging efficiency. The high and stable body temperatures of S. undulatus probably result from thermoneutral daytime T es, low activity levels, and the use of well-insulated nests.

Weather, microclimate, and energy costs of thermoregulation for breeding Adélie Penguins.

We measured meteorological conditions and estimated the energy costs of thermoregulation for young and adult Adélie Penguins (Pygoscelis adeliae) at a breeding colony near the Antarctic Peninsula. Air temperatures averaged < 5°C and strong winds were frequent. Operative temperatures (Te) for adults ranged from -8 to 28°C, averaging 5-6°C, for the period from courtship to fledging of chicks. The average energy cost of thermoregulation (Cth) for adult penguins was equivalent to 10-16% of basal metabolism. Cth comprised about 15% of the estimated daily energy budget (DEB) of incubating adults, but only about 1% of the DEB of adults feeding chicks. The Te's for chicks older than 14 days ranged from 0 to 31°C, averaging 8.0 C. The Cth for downy chicks ranged from about 31% of minimal metabolic rate (MMR) in 1 kg chicks to about 10% of MMR in 3 kg chicks. Between initial thermal independence (age 12-14 days) and the cessation of parental feeding (age 35-40 days), chicks use about 10-11% of assimilated energy for thermoregulation. Cth is equivalent to about 17% of the MMR of fledglings during their 2-3 week fast. We observed no indication of thermal stress (i.e., conditions in which birds cannot maintain stable Tb) in adults and no indication of cold stress in any age class. However, on clear, calm days when air temperature exceeds 7-10°C for several hours, downy chicks are vulnerable to lethal hyperthermia.

Potentiometric-spectroscopic evaluation of metal-ion complexes by humic fractions extracted from corn tissue.

Humic fraction (HF) functional group-type and content are expected to depend on molecular size, which in turn, is expected to influence formation of heavy-metal complexes. In this study, corn (Zea mays L.) stalks and leaves were decomposed for an 8-month period to produce water-soluble humic substances. These substances were separated into three water-soluble fractions, HF1, HF2 and HF3, from highest to lowest relative molecular size. Functional group determination showed that carboxylic, and phenolic OH acidity increased as relative molecular size of humic fractions decreased. We also observed decreasing C/O ratios from larger to smaller corn tissue-derived humic fractions, whereas N/C and H/C ratios remained relatively unaffected. Furthermore, using potentiometric titration and FTIR spectroscopy we studied formation of Ca2+-, Cd2+-, and Cu2+-humic fraction complexes and how they were affected by pH and molecular size. We determined that metal-humic complexes exhibited at least two types of functional group-sites with respect to Ca2+, Cd2+, and Cu2+ complexation. Strength of metal-ion humic complexes followed the order Cu2+ > Cd2+ > Ca2+ and was affected by pH, especially for low affinity sites. Carboxylic groups were most likely the dominant group-sites involved in complex formation. Magnitude of the metal-humic formation constants in the logarithmic form at the lowest equilibrium metal-ion concentration, under the various pH values tested, varied from 5.39 to 5.90 for Ca2+, 5.36 to 6.01 for Cd2+, and 6.93 to 7.71 for Cu2+. Furthermore, the formation constants appeared to be positively influenced by decreasing molecular size of water-soluble humic fraction, and increasing pH. However, our molecular spectra showed that the pKa of corn humic fractions increased with decreasing relative molecular size and that Cu2+ was more covalently bonded by humic fractions than were Ca2+ and Cd2+, and the nature of the covalent bond character was independent of pH.

Characterization of metals released from coal fly ash during dredging at the Kingston ash recovery project.

A storage-pond dike failure occurred on December 22, 2008 at the Tennessee Valley Authority Kingston Fossil Plant resulting in the release of over 4million cubic meters (5million cubic yards) of fly ash. Approximately half of the released ash was deposited in the main channel of the Emory River, Tennessee, USA. Remediation efforts of the Emory River focused on hydraulic dredging, as well as mechanical excavation in targeted areas. However, agitation of the submerged fly ash during hydraulic dredging introduces river water into the fly ash material, which could promote dissolution and desorption of metals from the solid fly ash material. Furthermore, aeration of the dredge slurry could alter the redox state of metals in the fly ash material and thereby change their sorption, mobility, and toxicity properties. The research presented here focuses on the concentrations and speciation of metals during the fly ash recovery from the Emory River. Our results indicate that arsenite [As(III)] released from the fly ash material during dredging was slowly oxidized to arsenate [As(V)] in the slurry recovery system with subsequent removal through precipitation or sorption reactions with suspended fly ash material. Concentrations of other dissolved metals, including iron and manganese, also generally decreased in the ash recovery system prior to water discharge back to the river.