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.

A nurse-led paediatric oncology fast-track clinic proves a successful ambulatory intervention for patients.

AIM: To assess the impact of a pilot nurse-led paediatric oncology fast-track clinic (OFTC) for complications and side effects following chemotherapy within a paediatric tertiary hospital. METHODS: Prospective clinical data from the first 100 patients seen in the OFTC were compared with retrospective data of oncology patient presentations to the emergency department (ED) (over a 1-year period, n = 196) who would have been eligible for review in the OFTC. Parent and patient satisfaction of clinical care were also assessed via surveys pre- and post-OFTC implementation. RESULTS: Analysis which achieved statistical difference was a reduction in the number of blood tubes taken in OFTC (average 1.9 for those discharged from clinic, 2.9 for those admitted from clinic) in comparison to those seen in the ED (average 3.2) (p = 0.0027). The average number of interventions per patient seen in the ED were 2.1 (standard deviation 1.64) compared with 1.7 (standard deviation 1.55) interventions per patient seen in the OFTC, and who were not admitted following review. This result approached statistical significance with p = 0.0963. Other results which did not meet statistical significance included a reduction in treatment times, hospital admissions and medical oncology reviews. CONCLUSION: Our pilot study implementing an OFTC for the triage and assessment of chemotherapy-related complications has proven successful from an operational and consumer perspective. The clinic improved care by ensuring expedited review, more streamlined interventions, and less overall hospital admissions. The improvements in efficiency were also mirrored by increased parent and patient satisfaction.

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.

Un-yielding: Evidence for the agriculture transformation we need.

There has been a seismic shift in the center of gravity of scientific writing and thinking about agriculture over the past decades, from a prevailing focus on maximizing yields toward a goal of balancing trade-offs and ensuring the delivery of multiple ecosystem services. Maximizing crop yields often results in a system where most benefits accrue to very few (in the form of profits), alongside irreparable environmental harm to agricultural ecosystems, landscapes, and people. Here, we present evidence that an un-yielding, which we define as de-emphasizing the importance of yields alone, is necessary to achieve the goal of a more Food secure, Agrobiodiverse, Regenerative, Equitable and just (FARE) agriculture. Focusing on yields places the emphasis on one particular outcome of agriculture, which is only an intermediate means to the true endpoint of human well-being. Using yields as a placeholder for this outcome ignores the many other benefits of agriculture that people also care about, like health, livelihoods, and a sense of place. Shifting the emphasis to these multiple benefits rather than merely yields, and to their equitable delivery to all people, we find clear scientific evidence of win-wins for people and nature through four strategies that foster FARE agriculture: reduced disturbance, systems reintegration, diversity, and justice (in the form of securing rights to land and other resources). Through a broad review of the current state of agriculture, desired futures, and the possible pathways to reach them, we argue that while trade-offs between some ecosystem services in agriculture are unavoidable, the same need not be true of the end benefits we desire from them.

Curating a Case Catalog: Development and Implementation of a Process for Revising Small Group Teaching Cases for Pre-clerkship Medical Education.

Small group, case-based learning (CBL) is an integral component of many pre-clerkship undergraduate medical education (UME) curricula. We report here an institutional process for curating a catalog of CBL cases utilized in a pre-clerkship curriculum, providing a practical guide for faculty. We describe the structured revision process conducted by a team of foundational and clinical science faculty, which incorporates student and faculty feedback. Revisions take into account core attributes of a case catalog, producing a collection of cases that are more relevant and instructional, realistic, challenging, consistent, current, diverse and inclusive, patient-centered, and mission-centered. Measurable outcomes after implementation of this process include increased focus on primary care as well as humanization and diversification of the case patients.

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.

The use of deconvolution techniques to identify the fundamental mixing characteristics of urban drainage structures.

Mixing and dispersion processes affect the timing and concentration of contaminants transported within urban drainage systems. Hence, methods of characterising the mixing effects of specific hydraulic structures are of interest to drainage network modellers. Previous research, focusing on surcharged manholes, utilised the first-order Advection-Dispersion Equation (ADE) and Aggregated Dead Zone (ADZ) models to characterise dispersion. However, although systematic variations in travel time as a function of discharge and surcharge depth have been identified, the first order ADE and ADZ models do not provide particularly good fits to observed manhole data, which means that the derived parameter values are not independent of the upstream temporal concentration profile. An alternative, more robust, approach utilises the system's Cumulative Residence Time Distribution (CRTD), and the solute transport characteristics of a surcharged manhole have been shown to be characterised by just two dimensionless CRTDs, one for pre- and the other for post-threshold surcharge depths. Although CRTDs corresponding to instantaneous upstream injections can easily be generated using Computational Fluid Dynamics (CFD) models, the identification of CRTD characteristics from non-instantaneous and noisy laboratory data sets has been hampered by practical difficulties. This paper shows how a deconvolution approach derived from systems theory may be applied to identify the CRTDs associated with urban drainage structures.

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.

Delayed immune-related adverse events in assessment for dose-limiting toxicity in early phase immunotherapy trials.

BACKGROUND: Immunotherapy (IO) agents can cause late-onset immune-related adverse events (irAEs). In phase I trials, observation for dose-limiting toxicities (DLTs) is typically limited to the first cycle. The incidence of delayed-onset DLTs and their potential impact on dose determination have not been fully elucidated. PATIENTS AND METHODS: Consecutive patients enrolled in early phase IO trials at Princess Margaret Cancer Centre between August 2012 and September 2016 were retrospectively reviewed, applying trial-specific definitions for DLTs. A clinically significant AE (csAE) was defined as a treatment-related adverse event requiring corticosteroids, hormone replacement, IO delay or discontinuation. RESULTS: A total of 352 consecutive trial enrolments in 21 early phase clinical trials were included. Two-hundred seventy-eight patients (79%) received monotherapy and 74 (21%) received combination IO. Two hundred sixty (74%) patients experienced irAEs. There were two protocol-defined DLTs. Twenty (5.7%) patients had 24 csAEs qualifying as DLTs except for occurrence after the protocol-specified DLT period. One-hundred and six (10%) of irAEs were csAEs, including endocrine (26%), respiratory (14%), gastrointestinal (11%), general (10%), dermatological (8%), hepatic (8%), musculoskeletal (6%), pancreatic (6%), haematological, metabolic, neurological, cardiac (each 2%), infective and ocular (each 1%) events. The highest risk of first-onset csAE was during the first 4 weeks compared with the period from 4 weeks to end of treatment (odds ratio 3.13, 95% confidence interval 1.95-5.02). The median time to first onset csAE was significantly shorter with combination than monotherapy IO (32 vs. 146 days, P < 0.001). CONCLUSIONS: In our series of early phase IO trials, the risk of csAE was highest during the initial 4 weeks on IO treatment, supporting the use of the conventional DLT period for dose escalation decision. However, there were 24 clinically significant late-onset DLTs in 5.7% of patients. Combination IO was associated with greater risk of and also earlier onset for csAE, which may need to be considered for early phase trial design.

A coupled drug kinetics-cell cycle model to analyse the response of human cells to intervention by topotecan.

A model describing the response of the growth of single human cells in the absence and presence of the anti-cancer agent topotecan (TPT) is presented. The model includes a novel coupling of both the kinetics of TPT and cell cycle responses to the agent. By linking the models in this way, rather than using separate (disjoint) approaches, it is possible to illustrate how the drug perturbs the cell cycle. The model is compared to experimental in vitro cell cycle response data (comprising single cell descriptors for molecular and behavioural events), showing good qualitative agreement for a range of TPT dose levels.

Invasive lobular carcinoma of the breast diagnosed from an ovarian tumour.

Invasive lobular carcinoma of breast is well known to be able to metastasise to unusual places, including the gastrointestinal and gynaecological tracts. However, it is very unusual for breast cancer to present in an ovarian Brenner tumour. This case highlights the diagnostic difficulties of patients presenting with unilateral ovarian masses, and the merits of thorough histological assessment of the entire pathological specimen despite the presence of one obvious pathological diagnosis.

Prima facie reasons to question enclosed intellectual property regimes and favor open-source regimes for germplasm.

In principle, intellectual property protections (IPPs) promote and protect important but costly investment in research and development. However, the empirical reality of IPPs has often gone without critical evaluation, and the potential of alternative approaches to lend equal or greater support for useful innovation is rarely considered. In this paper, we review the mounting evidence that the global intellectual property regime (IPR) for germplasm has been neither necessary nor sufficient to generate socially beneficial improvements in crop plants and maintain agrobiodiversity. Instead, based on our analysis, the dominant global IPR appears to have contributed to consolidation in the seed industry while failing to genuinely engage with the potential of alternatives to support social goods such as food security, adaptability, and resilience. The dominant IPR also constrains collaborative and cumulative plant breeding processes that are built upon the work of countless farmers past and present. Given the likely limits of current IPR, we propose that social goods in agriculture may be better supported by alternative approaches, warranting a rapid move away from the dominant single-dimensional focus on encouraging innovation through ensuring monopoly profits to IPP holders.