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BACKGROUND: Dynamic contrast-enhanced MRI (DCE-MRI) parameters have been shown to be biomarkers for treatment response in glioblastoma (GBM). However, variations in analysis and measurement methodology complicate determination of biological changes measured via DCE. The aim of this study is to quantify DCE-MRI variations attributable to analysis methodology and image quality in GBM patients. METHODS: The Extended Tofts model (eTM) and Leaky Tracer Kinetic Model (LTKM), with manually and automatically segmented vascular input functions (VIFs), were used to calculate perfusion kinetic parameters from 29 GBM patients with double-baseline DCE-MRI data. DCE-MRI images were acquired 2-5 days apart with no change in treatment. Repeatability of kinetic parameters was quantified with Bland-Altman and percent repeatability coefficient (%RC) analysis. RESULTS: The perfusion parameter with the least RC was the plasma volume fraction (v p ), with a %RC of 53%. The extra-cellular extra-vascular volume fraction (v e ) %RC was 82% and 81%, for extended Tofts-Kety Model (eTM) and LTKM respectively. The %RC of the volume transfer rate constant (K trans ) was 72% for the eTM, and 82% for the LTKM, respectively. Using an automatic VIF resulted in smaller %RCs for all model parameters, as compared to manual VIF. CONCLUSIONS: As much as 72% change in K trans (eTM, autoVIF) can be attributable to non-biological changes in the 2-5 days between double-baseline imaging. Poor K trans repeatability may result from inferior temporal resolution and short image acquisition time. This variation suggests DCE-MRI repeatability studies should be performed institutionally, using an automatic VIF method and following quantitative imaging biomarkers alliance guidelines.

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Background and aim: Over 80% (365/454) of the nation’s centers participated in the Italian Society of Nephrology COVID-19 Survey. Out of 60,441 surveyed patients, 1368 were infected as of April 23rd, 2020. However, center-specific proportions showed substantial heterogeneity. We therefore undertook new analyses to identify explanatory factors, contextual effects, and decision rules for infection containment. Methods: We investigated fixed factors and contextual effects by multilevel modeling. Classification and Regression Tree (CART) analysis was used to develop decision rules. Results: Increased positivity among hemodialysis patients was predicted by center location [incidence rate ratio (IRR) 1.34, 95% confidence interval (CI) 1.20–1.51], positive healthcare workers (IRR 1.09, 95% CI 1.02–1.17), test-all policy (IRR 5.94, 95% CI 3.36–10.45), and infected proportion in the general population (IRR 1.002, 95% CI 1.001–1.003) (all p < 0.01). Conversely, lockdown duration exerted a protective effect (IRR 0.95, 95% CI 0.94–0.98) (p < 0.01). The province-contextual effects accounted for 10% of the total variability. Predictive factors for peritoneal dialysis and transplant cases were center location and infected proportion in the general population. Using recursive partitioning, we identified decision thresholds at general population incidence ≥ 229 per 100,000 and at ≥ 3 positive healthcare workers. Conclusions: Beyond fixed risk factors, shared with the general population, the increased and heterogeneous proportion of positive patients is related to the center’s testing policy, the number of positive patients and healthcare workers, and to contextual effects at the province level. Nephrology centers may adopt simple decision rules to strengthen containment measures timely.

This contribution describes the implementation of a data--driven shape optimization pipeline in a naval architecture application. We adopt reduced order models (ROMs) in order to improve the efficiency of the overall optimization, keeping a modular and equation-free nature to target the industrial demand. We applied the above mentioned pipeline to a realistic cruise ship in order to reduce the total drag. We begin by defining the design space, generated by deforming an initial shape in a parametric way using free form deformation (FFD). The evaluation of the performance of each new hull is determined by simulating the flux via finite volume discretization of a two-phase (water and air) fluid. Since the fluid dynamics model can result very expensive -- especially dealing with complex industrial geometries -- we propose also a dynamic mode decomposition (DMD) enhancement to reduce the computational cost of a single numerical simulation. The real--time computation is finally achieved by means of proper orthogonal decomposition with Gaussian process regression (POD-GPR) technique. Thanks to the quick approximation, a genetic optimization algorithm becomes feasible to converge towards the optimal shape.

Objectives: To compare Gd-EOB-DTPA dynamic hepatocyte-specific contrast-enhanced MRI (DHCE-MRI) with 99m Tc-mebrofenin hepatobiliary scintigraphy (HBS) as quantitative liver function tests for the preoperative assessment of patients undergoing liver resection. Methods: Patients undergoing liver surgery and preoperative assessment of future remnant liver (FRL) function using 99m Tc-mebrofenin HBS were included. Patients underwent DHCE-MRI. Total liver uptake function was calculated for both modalities: mebrofenin uptake rate (MUR) and Ki respectively. The FRL was delineated with both SPECT-CT and MRI to calculate the functional share. Blood samples were taken to assess biochemical liver parameters. Results: A total of 20 patients were included. The HBS-derived MUR and the DHCE-MRI-derived mean Ki correlated strongly for both total and FRL function (Pearson r = 0.70, p = 0.001 and r = 0.89, p < 0.001 respectively). There was a strong agreement between the functional share determined with both modalities (ICC = 0.944, 95% CI 0.863–0.978, n = 20). There was a significant negative correlation between liver aminotransferases and bilirubin for both MUR and Ki. Conclusions: Assessment of liver function with DHCE-MRI is comparable with that of 99m Tc-mebrofenin HBS and has the potential to be combined with diagnostic MRI imaging. This can therefore provide a one-stop-shop modality for the preoperative assessment of patients undergoing liver surgery. Key Points: • Quantitative assessment of liver function using hepatobiliary scintigraphy is performed in the preoperative assessment of patients undergoing liver surgery in order to prevent posthepatectomy liver failure. • Gd-EOB-DTPA dynamic hepatocyte-specific contrast-enhanced MRI (DHCE-MRI) is an emerging method to quantify liver function and can serve as a potential alternative to hepatobiliary scintigraphy. • Assessment of liver function with dynamic gadoxetate-enhanced MRI is compara, ImPhys/Quantitative Imaging, Applied Sciences

Purpose Pharmacokinetic models facilitate assessment of properties of the micro-vascularization based on DCE-MRI data. However, accurate pharmacokinetic modeling in the liver is challenging since it has two vascular inputs and it is subject to large deformation and displacement due to respiration. Methods We propose an improved pharmacokinetic model for the liver that (1) analytically models the arrival-time of the contrast agent for both inputs separately; (2) implicitly compensates for signal fluctuations that can be modeled by varying applied flip-angle e.g. due to B1-inhomogeneity. Orton’s AIF model is used to analytically represent the vascular input functions. The inputs are independently embedded into the Sourbron model. B1-inhomogeneity-driven variations of flip-angles are accounted for to justify the voxel’s displacement with respect to a pre-contrast image. Results The new model was shown to yield lower root mean square error (RMSE) after fitting the model to all but a minority of voxels compared to Sourbron’s approach. Furthermore, it outperformed this existing model in the majority of voxels according to three model-selection criteria. Conclusion Our work primarily targeted to improve pharmacokinetic modeling for DCE-MRI of the liver. However, other types of pharmacokinetic models may also benefit from our approaches, since the techniques are generally applicable., ImPhys/Quantitative Imaging

Multiparametric magnetic resonance imaging (mpMRI) has emerged as a promising tool for prostate cancer (PCa) localization. Due to the complex acquisition procedure and analysis, along with a questioned diagnostic contribution, the inclusion of DCE-MRI in the updated Prostate Imaging and Reporting Data System (PI-RADS2) has been limited to qualitative assessment only, with a marginal weight on the final score. However, lower diagnostic performance has been reported for PI-RADS2 compared to original PI-RADS, evidencing the need to reconsider the role of DCE-MRI. Recently, magnetic resonance dispersion imaging (MRDI) has shown promise for quantitative DCE-MRI of the prostate. In MRDI, the adopted pharmacokinetic (PK) model includes description of the contrast agent intravascular transport, enabling additional assessment of the microvascular architecture. Compared to standard PK analysis in MRI, separate estimation of an arterial input function is no longer necessary, facilitating the clinical routine. Here we evaluate the diagnostic performance of MRDI for PCa localization compared to standard PK analysis by the Tofts model (TM) in a retrospective study including 80 patients from three different Dutch institutions.

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The Couinaud classification of hepatic anatomy partitions the liver into eight functionally independent segments. Detection and segmentation of the hepatic vein (HV), portal vein (PV) and inferior vena cava (IVC) plays an important role in the subsequent delineation of the liver segments. To facilitate pharmacokinetic modeling of the liver based on the same data, a 4D DCE-MR scan protocol was selected. This yields images with high temporal resolution but low spatial resolution. Since the liver's vasculature consists of many tiny branches, segmentation of these images is challenging. The proposed framework starts with registration of the 4D DCE-MRI series followed by region growing from manually annotated seeds in the main branches of key blood vessels in the liver. It calculates the Pearson correlation between the time intensity curves (TICs) of a seed and all voxels. A maximum correlation map for each vessel is obtained by combining the correlation maps for all branches of the same vessel through a maximum selection per voxel. The maximum correlation map is incorporated in a level set scheme to individually delineate the main vessels. Subsequently, the eight liver segments are segmented based on three vertical intersecting planes fit through the three skeleton branches of HV and IVC's center of mass as well as a horizontal plane fit through the skeleton of PV. Our segmentation regarding delineation of the vessels is more accurate than the results of two state-of-the-art techniques on five subjects in terms of the average symmetric surface distance (ASSD) and modified Hausdorff distance (MHD). Furthermore, the proposed liver partitioning achieves large overlap with manual reference segmentations (expressed in Dice Coefficient) in all but a small minority of segments (mean values between 87% and 94% for segments 2-8). The lower mean overlap for segment 1 (72%) is due to the limited spatial resolution of our DCE-MR scan protocol., ImPhys/Quantitative Imaging, Applied Sciences

Background: Pharmacokinetic (PK) models can describe microvascular density and integrity. An essential component of PK models is the arterial input function (AIF) representing the time-dependent concentration of contrast agent (CA) in the blood plasma supplied to a tissue. Purpose/Hypothesis: To evaluate a novel method for subject-specific AIF estimation that takes inflow effects into account. Study Type: Retrospective study. Subjects: Thirteen clinical patients referred for spine-related complaints; 21 patients from a study into luminal Crohn's disease with known Crohn's Disease Endoscopic Index of Severity (CDEIS). Field Strength/Sequence: Dynamic fast spoiled gradient echo (FSPGR) at 3T. Assessment: A population-averaged AIF, AIFs derived from distally placed regions of interest (ROIs), and the new AIF method were applied. Tofts' PK model parameters (including vp and Ktrans) obtained with the three AIFs were compared. In the Crohn's patients Ktrans was correlated to CDEIS. Statistical Tests: The median values of the PK model parameters from the three methods were compared using a Mann–Whitney U-test. The associated variances were statistically assessed by the Brown-Forsythe test. Spearman's rank correlation coefficient was computed to test the correlation of Ktrans to CDEIS. Results: The median vp was significantly larger when using the distal ROI approach, compared to the two other methods (P < 0.05 for both comparisons, in both applications). Also, the variances in vp were significantly larger with the ROI approach (P < 0.05 for all comparisons). In the Crohn's disease study, the estimated Ktrans parameter correlated better with the CDEIS (r = 0.733, P < 0.001) when the proposed AIF was used, compared to AIFs from the distal ROI method (r = 0.429, P = 0.067) or the population-averaged AIF (r = 0.567, P = 0.011). Data Conclusion: The proposed method yielded realistic PK mode, Green Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public., ImPhys/Quantitative Imaging

The limitations of the available imaging modalities for prostate cancer (PCa) localization result in suboptimal protocols for management of the disease. In response, several dynamic contrast-enhanced imaging modalities have been developed, which aim at cancer detection through the assessment of the changes occurring in the tumor microenvironment due to angiogenesis. In this context, novel magnetic resonance dispersion imaging (MRDI) enables the estimation of parameters related to the microvascular architecture and leakage, by describing the contrast agent kinetics with a dispersion model. Although a preliminary validation of MRDI on PCa has shown promising results, parameter estimation can become burdensome due the convolution integral present in the dispersion model. To overcome this limitation, in this work we provide analytical solutions of the dispersion model in the time and frequency domains, and we implement three numerical methods to increase the time-efficiency of parameter estimation. The proposed solutions are tested for PCa localization. A reduction by about 50% of computation time could be obtained, without significant changes in the estimation performance and in the clinical results. With the continuous development of new technological solutions to boost the spatiotemporal resolution of DCE-MRI, solutions to improve the computational efficiency of parameter estimation are highly required.

In Dynamic Contrast-Enhanced MRI (DCE-MRI) of the liver, a series of images is acquired over a period of 20 minutes. Due to the patient's breathing, the liver is subject to a substantial displacement between acquisitions. Furthermore, due to its location in the abdomen, the liver also undergoes marked deformation. The large deformations combined with variation in image contrast make accurate liver registration challenging. We present a registration framework that incorporates a liver segmentation to improve the registration accuracy. The segmented liver serves as region-of-interest to our in-house developed registration method called ALOST (autocorrelation of local image structure). ALOST is a continuous optimization method that uses local phase features to overcome space-variant intensity distortions. The proposed framework can confine the solution field to the liver and allow for ALOST to obtain a more accurate solution. For the segmentation part, we use a level-set method to delineate the liver in a so-called contrast enhancement map. This map is obtained by computing the difference between the last and registered first volume from the DCE series. Subsequently, we slightly dilate the segmentation, and apply it as the mask to the other DCE-MRI volumes during registration. It is shown that the registration result becomes more accurate compared with the original ALOST approach., ImPhys/Quantitative Imaging

The aim of the present work was to study the adaptability of amaranth in a typical Mediterranean environment of South Italy under changing climate scenarios. In a first stage, experimental data from a field trial conducted during 2009–2010 on the Volturno River Plain (Italy) with grain amaranth grown under different irrigation strategies, were used to define the thermal requirements and the yield response function to soil water availability of amaranth. The observed soil moisture data were used to calculate the relative soil water deficit (RSWD) index and seed yield data were expressed as relative yield (Yr). Yr and RSWD calculated data were then graphically correlated to obtain the amaranth yield response function to soil water availability. In a second stage the SALTMED model was used to simulate impacts of present, past and future climate scenarios on amaranth growth cycle and yield. Climate-change scenarios (Special Report on Emission Scenarios A1B, A2 and B1) data, used as input in the model, were derived from six global circulation models using a weather generator. The results showed that in a changing climate, temperature affects the relative duration of the growth cycle and could be a critical determinant of grain yield. The use of supplemental irrigations could allow the amaranth to guarantee a high seed yield under Mediterranean conditions.

Grain amaranth is an underutilized Andean crop characterized by interesting agronomic and qualitative traits and could represent an important food source in areas with salinity and drought problems like the Mediterranean region. Knowledge of crop growth parameters allows us to parameterize simulation models that are useful tools to study the adaptability of a crop to different environmental and management conditions. In this study, the SALTMED model has been parameterized, calibrated and evaluated for grain amaranth under Mediterranean conditions, with data from a field trial conducted during 2009–2010 in South Italy. The model evaluation was made using seed yield, dry matter and soil moisture data of amaranth irrigated with saline and fresh water. The simulation results showed a high degree of precision of SALTMED in the simulation of the hydrological processes at different soil depths, crop yield and dry matter under different agricultural practices. SALTMED can be used as a useful tool to optimize grain amaranth production in the Mediterranean region.

The climate of Mediterranean region will become drier and hotter, with increased problems of soil salinity. A possible alternative to minimize the effects of climate change is to introduce species with better tolerance to salt and drought stresses. One of the options is quinoa (Chenopodium quinoa Willd.), which was grown in field trials in several Mediterranean countries, to study the effects of drought and salinity on yield and other characters. Drought stress during the vegetative growth stage leads to deep root development, and without stress conditions for the rest of the growing season allowed the plant to be able to optimize its photosynthesis and carbon translocation. Stress during seed filling recorded the lowest yields. The influence of organic matter on yield was more important under deficit irrigation than under full irrigation. The interaction between relative water content and leaf water potential indicated that regulating cellular water deficit and volume is a powerful mechanism for conserving cellular hydration under drought. In all climatic conditions, drought and use of irrigation water with salinity up to 30 dS m−1 caused slightly reduced yield as compared to full irrigation with fresh water. Highest values of water conductivity resulted in higher seed weight, and as a consequence, an increase in fibre and total saponin content, and a small decrease in free phenolic compounds in quinoa seeds. The yield increase in quinoa accessions was less at the highest level of nitrogen application, that is, 200 mg kg−1 soil, compared with other levels of nitrogen application, that is, 50, 100 and 150 mg kg−1 soil., The climate of Mediterranean region will become drier and hotter, with increased problems of soil salinity. A possible alternative to minimize the effects of climate change is to introduce species with better tolerance to salt and drought stresses. One of the options is quinoa (Chenopodium quinoa Willd.), which was grown in field trials in several Mediterranean countries, to study the effects of drought and salinity on yield and other characters. Drought stress during the vegetative growth stage leads to deep root development, and without stress conditions for the rest of the growing season allowed the plant to be able to optimize its photosynthesis and carbon translocation. Stress during seed filling recorded the lowest yields. The influence of organic matter on yield was more important under deficit irrigation than under full irrigation. The interaction between relative water content and leaf water potential indicated that regulating cellular water deficit and volume is a powerful mechanism for conserving cellular hydration under drought. In all climatic conditions, drought and use of irrigation water with salinity up to 30 dS m-1 caused slightly reduced yield as compared to full irrigation with fresh water. Highest values of water conductivity resulted in higher seed weight, and as a consequence, an increase in fibre and total saponin content, and a small decrease in free phenolic compounds in quinoa seeds. The yield increase in quinoa accessions was less at the highest level of nitrogen application, that is, 200 mg kg-1 soil, compared with other levels of nitrogen application, that is, 50, 100 and 150 mg kg-1 soil.

Leaf chlorophyll content provides valuable information about physiological status of plants; it is directly linked to photosynthetic potential and primary production. In vitro assessment by wet chemical extraction is the standard method for leaf chlorophyll determination. This measurement is expensive, laborious, and time consuming. Over the years alternative methods, rapid and non-destructive, have been explored. The aim of this work was to evaluate the applicability of a fast and non-invasive field method for estimation of chlorophyll content in quinoa and amaranth leaves based on RGB components analysis of digital images acquired with a standard SLR camera. Digital images of leaves from different genotypes of quinoa and amaranth were acquired directly in the field. Mean values of each RGB component were evaluated via image analysis software and correlated to leaf chlorophyll provided by standard laboratory procedure. Single and multiple regression models using RGB color components as independent variables have been tested and validated. The performance of the proposed method was compared to that of the widely used non-destructive SPAD method. Sensitivity of the best regression models for different genotypes of quinoa and amaranth was also checked. Color data acquisition of the leaves in the field with a digital camera was quick, more effective, and lower cost than SPAD. The proposed RGB models provided better correlation (highest R 2) and prediction (lowest RMSEP) of the true value of foliar chlorophyll content and had a lower amount of noise in the whole range of chlorophyll studied compared with SPAD and other leaf image processing based models when applied to quinoa and amaranth., Leaf chlorophyll content provides valuable information about physiological status of plants; it is directly linked to photosynthetic potential and primary production. In vitro assessment by wet chemical extraction is the standard method for leaf chlorophyll determination. This measurement is expensive, laborious, and time consuming. Over the years alternative methods, rapid and non-destructive, have been explored. The aim of this work was to evaluate the applicability of a fast and non-invasive field method for estimation of chlorophyll content in quinoa and amaranth leaves based on RGB components analysis of digital images acquired with a standard SLR camera. Digital images of leaves from different genotypes of quinoa and amaranth were acquired directly in the field. Mean values of each RGB component were evaluated via image analysis software and correlated to leaf chlorophyll provided by standard laboratory procedure. Single and multiple regression models using RGB color components as independent variables have been tested and validated. The performance of the proposed method was compared to that of the widely used non-destructive SPAD method. Sensitivity of the best regression models for different genotypes of quinoa and amaranth was also checked. Color data acquisition of the leaves in the field with a digital camera was quick, more effective, and lower cost than SPAD. The proposed RGB models provided better correlation (highest R 2) and prediction (lowest RMSEP) of the true value of foliar chlorophyll content and had a lower amount of noise in the whole range of chlorophyll studied compared with SPAD and other leaf image processing based models when applied to quinoa and amaranth.

Drought and salinity are the most important abiotic stresses that affect plant's growth and productivity. The aim of the present work was to evaluate the effect of salt and water deficit on water relations, growth parameters and capacity to accumulate inorganic solutes in quinoa plants. An irrigation experiment was carried out in 2009 and 2010 in the Volturno river plain. Three treatments irrigated with fresh water (Q100, Q50 and Q25) and three irrigated with saline water (Q100S, Q50S and Q25S) were tested. For saline irrigation, water with an electrical conductivity of 22 dS m−1 was used. Actual evapotranspiration (ETa), water productivity (WP), biomass allocation, relative growth rate (RGR), net assimilation rate (NAR), specific leaf area, leaf area ratio and ions accumulation of quinoa plants were evaluated. WP and plant growth were not influenced by saline irrigation, as quinoa plants incorporated salt ions in the tissues (stems, roots, leaves) preserving seed quality. Treatment with a reduction in the irrigation water to 25 % of full irrigated treatment (Q25) caused an increase in WP and a reduced dry matter accumulation in the leaves. Quinoa plants (Q25) were initially negatively affected by severe drought with RGR and NAR reduction, and then, they adapted to it. Quinoa could be considered a drought tolerant crop that adapt photosynthetic rate to compensate for a reduced growth., Drought and salinity are the most important abiotic stresses that affect plant's growth and productivity. The aim of the present work was to evaluate the effect of salt and water deficit on water relations, growth parameters and capacity to accumulate inorganic solutes in quinoa plants. An irrigation experiment was carried out in 2009 and 2010 in the Volturno river plain. Three treatments irrigated with fresh water (Q100, Q50 and Q25) and three irrigated with saline water (Q100S, Q50S and Q25S) were tested. For saline irrigation, water with an electrical conductivity of 22 dS m-1 was used. Actual evapotranspiration (ETa), water productivity (WP), biomass allocation, relative growth rate (RGR), net assimilation rate (NAR), specific leaf area, leaf area ratio and ions accumulation of quinoa plants were evaluated. WP and plant growth were not influenced by saline irrigation, as quinoa plants incorporated salt ions in the tissues (stems, roots, leaves) preserving seed quality. Treatment with a reduction in the irrigation water to 25 % of full irrigated treatment (Q25) caused an increase in WP and a reduced dry matter accumulation in the leaves. Quinoa plants (Q25) were initially negatively affected by severe drought with RGR and NAR reduction, and then, they adapted to it. Quinoa could be considered a drought tolerant crop that adapt photosynthetic rate to compensate for a reduced growth.

The aim of this research was to calibrate and validate the SALTMED model with soil moisture, total dry matter and yield data of Chenopodium quinoa Willd var. Titicaca grown in a Mediterranean environment of south Italy under different irrigation strategies. For this purpose the data used were obtained from a biannual field trial (2009-2010) performed at the experimental station of the CNR - Institute for Agricultural and Forest Mediterranean Systems (ISAFoM) on the Volturno river plain, an irrigated area of Southern Italy; a control irrigation treatment where water was given to restore the root zone layer (0.00 - 0.36 m) to 100% of its field capacity, and two other treatments where water given represented 50% and 25% of the water volume given for the control treatment. Two water qualities were used, saline and well water. SALTMED model was calibrated using yield, total dry matter (including roots) and soil moisture data from 100% well water treatment in 2009. After the calibration, the model was validated using the same set of crop and soil parameters. The results indicated the model ability to simulate with good precision, soil moisture values, total dry matter and grain yield for quinoa under different irrigation strategies with saline and fresh water for a two years experiment.

Cristina Lavini,1 Maarten S Buiter,2 Mario Maas1 1Department of Radiology, Academic Medical Center, Amsterdam, The Netherlands; 2Department of Radiotherapy, The Netherlands Cancer Institute, Amsterdam, The Netherlands Abstract: The analysis of dynamic contrast enhanced data using the classification of the time intensity curve (TIC) shape is widely employed both in its region of interest and pixel by pixel variants. While its application in breast imaging is established and documented by a large amount of scientific works, its use for other body parts is still scattered and there is no consensus as to whether the method can be used alone to perform differential diagnosis in cancer or in inflammatory diseases. In this review we evaluate all the literature which makes use of TIC shape analysis in tissues other than breast, discuss the results, highlight the possible shortcomings, and suggest directions for future research. Keywords: DCE-MRI, TIC shape, pattern recognition, review

Collaboration is an increasingly popular approach to addressing the multi-faceted needs of youth-at-risk both within academic literature and government policy in New Zealand. Due to being a relevantly new concept, there is limited evidence in the literature regarding how it is being implemented and whether implementations are successful. There is aparticular gap within the literature regarding the experiences of frontline workers and youth themselves. As youth are the key benefactors of youth services it seems important to understand whether and how they perceive the collaborative approach to be working to assist them in their development. To determine this, the following study explores the experiences of nine youth in New Zealand regarding collaborative processes used by services they have been privy to over recent years. Youth participants came from across New Zealand and altogether have experienced a range of youth interventions, from alternative education to Family Group Conferences, aimed at addressing anti-social and criminal behaviours. Taking a phenomenological approach, the study is carried out using concepts from the framework of Appreciative Inquiry (AI). The use of AI ensured the study was strengths focussed and allowed youth to become active agents rather than subjects of enquiry. Furthermore, it has allowed a positive paradigm for discussing ways to ensure that youth services are better focussed on youth's needs, feelings and understandings. Along with the findings regarding collaboration a common theme arose when youth were invited to share their stories which highlighted further areas for discussion when addressing successful service outcomes. That is, the importance of relationship building.

Motoneuron disease is a term encompassing three phenotypes defined largely by the balance of upper versus lower motoneuron involvement, namely amyotrophic lateral sclerosis, primary lateral sclerosis and progressive muscular atrophy. However, neuroradiological and pathological findings in these phenotypes suggest that degeneration may exceed the neuronal system upon which clinical diagnosis is based. To further delineate the phenotypes within the motoneuron disease spectrum, this controlled study assessed the upper- and extra-motoneuron white matter involvement in cohorts of patients with motoneuron disease phenotypes shortly after diagnosis by comparing diffusion tensor imaging data of the different cohorts to those of healthy controls and directly between the motoneuron disease phenotypes (n=12 for each cohort). Furthermore, we acquired follow-up data 6 months later to evaluate fractional anisotropy changes over time. Combined use of dif

Kinematic limits on an invariant mass distribution of bc-pairs for a three-step decay chain A -> bB -> bcC involving all massive particles are found. It is shown that an application of these limits to a stop quark production at the LHC could reduce significantly Standard Model background contribution., Comment: 8 pages, 4 figures, 4 references added

The response of mature olive (Olea europaea L.) trees to both regulated deficit irrigation and fertigation was studied for some consecutive years in sub-humid (Italy) and semi-arid conditions (Spain). All cultivars tested in these experiments were preferentially for table olive consumption (pickling and double-aptitude). Data from these long-term studies on field-grown, mature trees are summarized for assessing common effects of water and nutrient supply on plant behaviour and fruit yield. Seasonal yield variations were observed, and showed that the effect of irrigation treatments was somewhat more gradual in the >on> than in the >off> year. Differences amongst cultivars were always marked. Dry matter accumulation in pulp and pit was positively affected by progressively increasing the amount of water supplied to plants, regardless of years and cultivars. The ratio between pulp and pit fresh weight was negatively affected by irrigation, while fruit size was positively influenced by the gradual increase of irrigation water. Average nitrogen levels in leaves were generally above the deficiency threshold at both experimental plantations. Crop yield was not consistently increased by addition of soil nutrients. The effect of fertigation treatments was relatively uninfluential on oil accumulation in fruits. However, polyphenols in oil samples decreased progressively as the addition of nutrients increased. Critical aspects and strategic decisions in modern olive growing are the selection of cultivar, the supply of water, the option of fertilization, together with other orchard management practices. In this paper we outline various aspects of long-term studies in experimental olive plantations with the aim of highlighting inter-regulatory processes, involving plant growth and crop yield, which must be taken into account when planning future field research and modelling exercises.