Economic analysis of World Bank education projects and project outcomes

Research reported in this paper tests the hypothesis that Bank education projects for which the project appraisal documents are judged"good"have a higher probability of leading to successful outcomes than projects for which the appraisals are judged"poor."The research draws on project document evaluations carried out between 1993 and 1998. Analysis shows a strong relationship between the quality of cost-benefit and cost-effectiveness analysis and the quality of project outcomes. Economic analysis of projects is a tool for weeding out potentially poor investments and selecting potentially worthwhile ones. The economic analysis can be used to select among alternative projects or to redesign project components so that they yield more and produce better outcomes. Good practice education projects require good economic analysis--analysis of demand, of the counterfactual private sector supply, of the project's fiscal impact, of lending fungibility--and strong sector work before project design.Curriculum&Instruction,Urban Services to the Poor,Poverty Assessment,Health Monitoring&Evaluation,Health Economics&Finance

Automatic C-Plane Detection in Pelvic Floor Transperineal Volumetric Ultrasound

Transperineal volumetric ultrasound (US) imaging has become routine practice for diagnosing pelvic floor disease (PFD). Hereto, clinical guidelines stipulate to make measurements in an anatomically defined 2D plane within a 3D volume, the so-called C-plane. This task is currently performed manually in clinical practice, which is labour-intensive and requires expert knowledge of pelvic floor anatomy, as no computer-aided C-plane method exists. To automate this process, we propose a novel, guideline-driven approach for automatic detection of the C-plane. The method uses a convolutional neural network (CNN) to identify extreme coordinates of the symphysis pubis and levator ani muscle (which define the C-plane) directly via landmark regression. The C-plane is identified in a postprocessing step. When evaluated on 100 US volumes, our best performing method (multi-task regression with UNet) achieved a mean error of 6.05 mm and 4.81 ∘ and took 20 s. Two experts blindly evaluated the quality of the automatically detected planes and manually defined the (gold standard) C-plane in terms of their clinical diagnostic quality. We show that the proposed method performs comparably to the manual definition. The automatic method reduces the average time to detect the C-plane by 100 s and reduces the need for high-level expertise in PFD US assessment

Automatic Extraction of Hiatal Dimensions in 3-D Transperineal Pelvic Ultrasound Recordings

The aims of this work were to create a robust automatic software tool for measurement of the levator hiatal area on transperineal ultrasound (TPUS) volumes and to measure the potential reduction in variability and time taken for analysis in a clinical setting. The proposed tool automatically detects the C-plane (i.e., the plane of minimal hiatal dimensions) from a 3-D TPUS volume and subsequently uses the extracted plane to automatically segment the levator hiatus, using a convolutional neural network. The automatic pipeline was tested using 73 representative TPUS volumes. Reference hiatal outlines were obtained manually by two experts and compared with the pipeline's automated outlines. The Hausdorff distance, area, a clinical quality score, C-plane angle and C-plane Euclidean distance were used to evaluate C-plane detection and quantify levator hiatus segmentation accuracy. A visual Turing test was created to compare the performance of the software with that of the expert, based on the visual assessment of C-plane and hiatal segmentation quality. The overall time taken to extract the hiatal area with both measurement methods (i.e., manual and automatic) was measured. Each metric was calculated both for computer–observer differences and for inter-and intra-observer differences. The automatic method gave results similar to those of the expert when determining the hiatal outline from a TPUS volume. Indeed, the hiatal area measured by the algorithm and by an expert were within the intra-observer variability. Similarly, the method identified the C-plane with an accuracy of 5.76 ± 5.06° and 6.46 ± 5.18 mm in comparison to the inter-observer variability of 9.39 ± 6.21° and 8.48 ± 6.62 mm. The visual Turing test suggested that the automatic method identified the C-plane position within the TPUS volume visually as well as the expert. The average time taken to identify the C-plane and segment the hiatal area manually was 2 min and 35 ± 17 s, compared with 35 ± 4 s for the automatic result. This study presents a method for automatically measuring the levator hiatal area using artificial intelligence-based methodologies whereby the C-plane within a TPUS volume is detected and subsequently traced for the levator hiatal outline. The proposed solution was determined to be accurate, relatively quick, robust and reliable and, importantly, to reduce time and expertise required for pelvic floor disorder assessment

Cerebral rituximab uptake in multiple sclerosis: A (89)Zr-immunoPET pilot study

Previous studies have demonstrated that the chimeric monoclonal antibody rituximab significantly reduces clinical and radiological disease activity in relapsing-remitting multiple sclerosis as early as 4 weeks after the first administration. The exact mechanisms leading to this rapid effect have not yet been clarified. The aim of this positron emission tomography study was to assess central nervous system penetration as a possible explanation, using zirconium-89-labelled rituximab. No evidence was found for cerebral penetration of [(89)Zr]rituximab

Repeatability of arterial input functions and kinetic parameters in muscle obtained by dynamic contrast enhanced MR imaging of the head and neck

BACKGROUND: Quantification of pharmacokinetic parameters in dynamic contrast enhanced (DCE) MRI is heavily dependent on the arterial input function (AIF). In the present patient study on advanced stage head and neck squamous cell carcinoma (HNSCC) we have acquired DCE-MR images before and during chemo radiotherapy. We determined the repeatability of image-derived AIFs and of the obtained kinetic parameters in muscle and compared the repeatability of muscle kinetic parameters obtained with image-derived AIF's versus a population-based AIF. MATERIALS AND METHODS: We compared image-derived AIFs obtained from the internal carotid, external carotid and vertebral arteries. Pharmacokinetic parameters (ve, Ktrans, kep) in muscle-located outside the radiation area-were obtained using the Tofts model with the image-derived AIFs and a population averaged AIF. Parameter values and repeatability were compared. Repeatability was calculated with the pre- and post-treatment data with the assumption of no DCE-MRI measurable biological changes between the scans. RESULTS: Several parameters describing magnitude and shape of the image-derived AIFs from the different arteries in the head and neck were significantly different. Use of image-derived AIFs led to higher pharmacokinetic parameters compared to use of a population averaged AIF. Median muscle pharmacokinetic parameters values obtained with AIFs in external carotids, internal carotids, vertebral arteries and with a population averaged AIF were respectively: ve (0.65, 0.74, 0.58, 0.32), Ktrans (0.30, 0.21, 0.13, 0.06), kep (0.41, 0.32, 0.24, 0.18). Repeatability of pharmacokinetic parameters was highest when a population averaged AIF was used; however, this repeatability was not significantly different from image-derived AIFs. CONCLUSION: Image-derived AIFs in the neck region showed significant variations in the AIFs obtained from different arteries, and did not improve repeatability of the resulting pharmacokinetic parameters compared with the use of a population averaged AIF. Therefore, use of a population averaged AIF seems to be preferable for pharmacokinetic analysis using DCE-MRI in the head and neck area

Use of population input functions for reduced scan duration whole-body Patlak F-18-FDG PET imaging

Abstract: Whole-body Patlak images can be obtained from an acquisition of first 6 min of dynamic imaging over the heart to obtain the arterial input function (IF), followed by multiple whole-body sweeps up to 60 min pi. The use of a population-averaged IF (PIF) could exclude the first dynamic scan and minimize whole-body sweeps to 30–60 min pi. Here, the effects of (incorrect) PIFs on the accuracy of the proposed Patlak method were assessed. In addition, the extent of mitigating these biases through rescaling of the PIF to image-derived IF values at 30–60 min pi was evaluated. Methods: Using a representative IF and rate constants from the literature, various tumour time-activity curves (TACs) were simulated. Variations included multiplication of the IF with a positive and negative gradual linear bias over 60 min of 5, 10, 15, 20, and 25% (generating TACs using an IF different from the PIF); use of rate constants (K 1, k 3, and both K 1 and k 2) multiplied by 2, 1.5, and 0.75; and addition of noise (μ = 0 and σ = 5, 10 and 15%). Subsequent Patlak analysis using the original IF (representing the PIF) was used to obtain the influx constant (K i) for the differently simulated TACs. Next, the PIF was scaled towards the (simulated) IF value using the 30–60-min pi time interval, simulating scaling of the PIF to image-derived values. Influence of variabilities in IF and rate constants, and rescaling the PIF on bias in K i was evaluated. Results: Percentage bias in K i observed using simulated modified IFs varied from − 16 to 16% depending on the simulated amplitude and direction of the IF modifications. Subsequent scaling of the PIF reduced these K i biases in most cases (287 out of 290) to < 5%. Conclusions: Simulations suggest that scaling of a (possibly incorrect) PIF to IF values seen in whole-body dynamic imaging from 30 to 60 min pi can provide accurate Ki estimates. Consequently, dynamic Patlak imaging protocols may be performed for 30–60 min pi making whole-body Patlak imaging clinically feasible

International standards for fetal brain structures based on serial ultrasound measurements from the Fetal Growth Longitudinal Study of the INTERGROWTH-21st Project.

OBJECTIVE: To create prescriptive growth standards for five fetal brain structures, measured by ultrasound, from healthy, well-nourished women, at low risk of impaired fetal growth and poor perinatal outcomes, taking part in the Fetal Growth Longitudinal Study (FGLS) of the INTERGROWTH-21st Project. METHODS: This was a complementary analysis of a large, population-based, multicentre, longitudinal study. We measured, in planes reconstructed from 3-dimensional (3D) ultrasound volumes of the fetal head at different time points in pregnancy, the size of the parieto-occipital fissure (POF), Sylvian fissure (SF), anterior horn of the lateral ventricle (AV), atrium of the posterior ventricle (PV) and cisterna magna (CM). The sample analysed was randomly selected from the overall FGLS population, ensuring an equal distribution amongst the eight diverse participating sites and of 3D ultrasound volumes across pregnancy (range: 15 - 36 weeks' gestation). Fractional polynomials were used to the construct standards. Growth and development of the infants were assessed at 1 and 2 years of age to confirm their adequacy for constructing international standards. RESULTS: From the entire FGLS cohort of 4321 women, 451 (10.4%) were randomly selected. After exclusions, 3D ultrasound volumes from 442 fetuses born without congenital malformations were used to create the charts. The fetal brain structures of interest were identified in 90% of cases. All structures showed increasing size with gestation and increasing variability for the POF, SF, PV and CM. The 3rd , 5th , 50th , 95th and 97th smoothed centile are presented. The 5th centile of POF and SF were 2.8 and 4.3 at 22 weeks and 4.2 and 9.4mm at 32 weeks respectively. The 95th centile of PV and CM were 8.5 and 7.4 at 22 weeks and 8.5 and 9.4mm at 32 weeks respectively. CONCLUSIONS: We have produced prescriptive size standards for fetal brain structures based on prospectively enrolled pregnancies at low risk of abnormal outcomes. We recommend these as international standards for the assessment of measurements obtained by ultrasound from fetal brain structures