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Objectives To investigate the reproducibility of arterial spin labelling (ASL) and dynamic contrast-enhanced (DCE) magnetic resonance imaging (MRI) and quantitatively compare these techniques for the measurement of renal blood flow (RBF). Methods Sixteen healthy volunteers were examined on two different occasions. ASL was performed using a multi-TI FAIR labelling scheme with a segmented 3D-GRASE imaging module. DCE MRI was performed using a 3D-FLASH pulse sequence. A Bland-Altman analysis was used to assess repeatability of each technique, and determine the degree of correspondence between the two methods. Results The overall mean cortical renal blood flow (RBF) of the ASL group was 263 ± 41 ml min −1 [100 ml tissue] −1 , and using DCE MRI was 287 ± 70 ml min −1 [100 ml tissue] −1 . The group coefficient of variation (CV g ) was 18 % for ASL and 28 % for DCE-MRI. Repeatability studies showed that ASL was more reproducible than DCE with CV g s of 16 % and 25 % for ASL and DCE respectively. Bland-Altman analysis comparing the two techniques showed a good agreement. Conclusions The repeated measures analysis shows that the ASL technique has better reproducibility than DCE-MRI. Difference analysis shows no significant difference between the RBF values of the two techniques. Key Points • Reliable non-invasive monitoring of renal blood flow is currently clinically unavailable. • Renal arterial spin labelling MRI is robust and repeatable. • Renal dynamic contrast-enhanced MRI is robust and repeatable. • ASL blood flow values are similar to those obtained using DCE-MRI.

A number of two-compartment models have been developed for the analysis of arterial spin labeling (ASL) data, from which both cerebral blood flow (CBF) and capillary permeability-surface product (PS) can be estimated. To derive values of PS, the volume fraction of the ASL signal arising from the intravascular space (vbw) must be known a priori. We examined the use of diffusion-weighted imaging (DWI) and subsequent analysis using the intravoxel incoherent motion model to determine vbw in the human brain. These data were then used in a two-compartment ASL model to estimate PS. Imaging was performed in 10 healthy adult subjects, and repeated in five subjects to test reproducibility. In gray matter (excluding large arteries), mean voxel-wise vbw was 2.3 ± 0.2 mL blood/100 g tissue (all subjects mean ± s.d.), and CBF and PS were 44 ± 5 and 108 ± 2 mL per 100 g per minute, respectively. After spatial smoothing using a 6-mm full width at half maximum Gaussian kernel, the coefficient of repeatability of CBF, vbw and PS were 8 mL per 100 g per minute, 0.4 mL blood/100 g tissue, and 13 mL per 100 g per minute, respectively. Our results show that the combined use of ASL and DWI can provide a new, noninvasive methodology for estimating vbw and PS directly, with reproducibility that is sufficient for clinical use.

To determine if apparent diffusion coefficients (ADC) can discriminate between posterior fossa brain tumours on a multicentre basis. A total of 124 paediatric patients with posterior fossa tumours (including 55 Medulloblastomas, 36 Pilocytic Astrocytomas and 26 Ependymomas) were scanned using diffusion weighted imaging across 12 different hospitals using a total of 18 different scanners. Apparent diffusion coefficient maps were produced and histogram data was extracted from tumour regions of interest. Total histograms and histogram metrics (mean, variance, skew, kurtosis and 10th, 20th and 50th quantiles) were used as data input for classifiers with accuracy determined by tenfold cross validation. Mean ADC values from the tumour regions of interest differed between tumour types, (ANOVA P  < 0.001). A cut off value for mean ADC between Ependymomas and Medulloblastomas was found to be of 0.984 × 10 −3 mm 2  s −1 with sensitivity 80.8% and specificity 80.0%. Overall classification for the ADC histogram metrics were 85% using Naïve Bayes and 84% for Random Forest classifiers. The most commonly occurring posterior fossa paediatric brain tumours can be classified using Apparent Diffusion Coefficient histogram values to a high accuracy on a multicentre basis.

The human brain changes structurally and functionally during adolescence, with associated alterations in cerebral perfusion. We performed dynamic arterial spin labeling (ASL) magnetic resonance imaging in healthy subjects between 8 and 32 years of age, to investigate changes in cerebral hemodynamics during normal development. In addition, an inversion recovery sequence allowed quantification of changes in longitudinal relaxation time (T1) and equilibrium longitudinal magnetization (M0). We present mean and reference ranges for normal values of T1, M0, cerebral blood flow (CBF), bolus arrival time, and bolus duration in cortical gray matter, to provide a tool for identifying age-matched perfusion abnormalities in this age range in clinical studies. Cerebral blood flow and T1 relaxation times were negatively correlated with age, without gender or hemisphere differences. The same was true for M0 anteriorly, but posteriorly, males but not females showed a significant decline in M0 with increasing age. Two examples of the clinical utility of these data in identifying age-matched perfusion abnormalities, in Sturge–Weber syndrome and sickle cell anemia, are illustrated.

The ability to assess brain tumor perfusion and abnormalities in the vascular structure in vivo could provide significant benefits in terms of lesion diagnosis and assessment of treatment response. Arterial spin labeling (ASL) has emerged as an increasingly viable methodology for non-invasive assessment of perfusion. Although kinetic models have been developed to describe perfusion in healthy tissue, the dynamic behaviour of the ASL signal in the brain tumor environment has not been extensively studied. We show here that dynamic ASL data acquired in brain tumors displays an increased level of 'biphasic' behaviour, compared to that seen in healthy tissue. A new two-stage model is presented which more accurately describes this behaviour, and provides measurements of perfusion, pre-capillary blood volume fraction and transit time, and capillary bolus arrival time. These biomarkers offer a novel contrast in the tumor and surrounding tissue, and provide a means for measuring tumor perfusion and vascular structural abnormalities in a fully non-invasive manner.

Addressing the critical STEM teachers’ shortage in the rural United States requires not only recruiting new teachers but also improving retention and teacher resiliency. This study explores contextual protective factors through the Early Career Teacher Resilience (ECTR) framework. The major objective of this study was to evaluate the impacts of the NSF Noyce Professional Learning Community (PLC) on rural STEM teacher resilience. Key components of the Noyce PLC included scholarship support, pre-service mentoring, attendance at local and regional educational events, active engagement in the program’s annual summer conference, and participation in a closed Facebook group. We developed an ECTR framework-based online instrument with 28 questions and sent it to 311 university alumni, including 44 Noyce alumni. The results suggest that the Noyce PLC has excelled in fostering collaborative learning environments, providing resources that enhance teaching and learning, accommodating new and different ways of thinking, and supporting teachers’ professional growth beyond graduation. The findings underscore the importance of integrating theoretical and practical knowledge, supporting ongoing professional learning, and building strong professional relationships. Several aspects of the Noyce PLC could be replicated in other STEM teacher preparation programs to enhance teacher resilience, effectiveness, and career development.

 This exploratory study of a Title II grant funded project analyzed the design and delivery of online professional learning communities (PLC) for rural STEM teachers. This research identified the frequency a video posting, the type of videos posted, and the style of reflection questions, as critical aspects to the engagement to participating teachers. Additionally, teachers showed an increase in teacher efficacy as a result of being part of the online PLCs and they indicated strong enjoyment and value in participation of the program. 

ObjectivesVolume of necrosis in Wilms tumour is informative of chemotherapy response. Contrast-enhanced T1-weighted MRI (T1w) provides a measure of necrosis using gadolinium. This study aimed to develop a non-invasive method of identifying non-enhancing (necrotic) tissue in Wilms tumour.MethodsIn this single centre, retrospective study, post-chemotherapy MRI data from 34 Wilms tumour patients were reviewed (March 2012–March 2017). Cases with multiple b value diffusion-weighted imaging (DWI) and T1w imaging pre- and post-gadolinium were included. Fractional T1 enhancement maps were generated from the gadolinium T1w data. Multiple linear regression determined whether fitted parameters from a mono-exponential model (ADC) and bi-exponential model (IVIM – intravoxel incoherent motion) (D, D*, f) could predict fractional T1 enhancement in Wilms tumours, using normalised pre-gadolinium T1w (T1wnorm) signal as an additional predictor. Measured and predicted fractional enhancement values were compared using the Bland-Altman plot. An optimum threshold for separating necrotic and viable tissue using fractional T1 enhancement was established using ROC.ResultsADC and D (diffusion coefficient) provided the strongest predictors of fractional T1 enhancement in tumour tissue (p < 0.001). Using the ADC-T1wnorm model (adjusted R2 = 0.4), little bias (mean difference = − 0.093, 95% confidence interval = [− 0.52, 0.34]) was shown between predicted and measured values of fractional enhancement and analysed via the Bland-Altman plot. The optimal threshold for differentiating viable and necrotic tissue was 33% fractional T1 enhancement (based on measured values, AUC = 0.93; sensitivity = 85%; specificity = 90%).ConclusionsCombining ADC and T1w imaging predicts enhancement in Wilms tumours and reliably identifies and measures necrotic tissue without gadolinium.Key Points• Alternative method to identify necrotic tissue in Wilms tumour without using contrast agents but rather using diffusion and T1weighted MRI.• A method is presented to visualise and quantify necrotic tissue in Wilms tumour without contrast.• The proposed method has the potential to reduce costs and burden to Wilms tumour patients who undergo longitudinal follow-up imaging as contrast agents are not used.

Student voice is a difficult concept to capture in research. This study attempts to provide a vehicle for understanding student perceptions about writing and writing instruction through a case study supported by discourse analysis of student talk. The high school students in this study participated in interviews and focus groups about their experiences with writing. The findings reveal deep seeded notions about writing enculturated through their schooling. Students were not likely to take ownership of their writing, rather considering it a teacher construct, and could not typically describe the application of writing skills. Students were optimistic and provided multiple suggestions for improvements to writing instruction with an emphasis on making writing relevant. The implications of this study, while highly contextual, do reveal the significance of systemic conceptualizations born in students through the process of schooling and how language can unpack those schemas.

This paper presents methods to build histo-anatomically detailed individualized cardiac models. The models are based on high-resolution three-dimensional anatomical and/or diffusion tensor magnetic resonance images, combined with serial histological sectioning data, and are used to investigate individualized cardiac function. The current state of the art is reviewed, and its limitations are discussed. We assess the challenges associated with the generation of histo-anatomically representative individualized in silico models of the heart. The entire processing pipeline including image acquisition, image processing, mesh generation, model set-up and execution of computer simulations, and the underlying methods are described. The multifaceted challenges associated with these goals are highlighted, suitable solutions are proposed, and an important application of developed high-resolution structure-function models in elucidating the effect of individual structural heterogeneity upon wavefront dynamics is demonstrated.