Optical mesoscopy, machine learning and computational microscopy enable high information content diagnostic imaging of blood films

Automated image-based assessment of blood films has tremendous potential to support clinical haematology within overstretched healthcare systems. To achieve this, efficient and reliable digital capture of the rich diagnostic information contained within a blood film is a critical first step. However, this is often challenging, and in many cases entirely unfeasible, with the microscopes typically used in haematology due to the fundamental trade-off between magnification and spatial resolution. To address this, we investigated three state-of-the-art approaches to microscopic imaging of blood films which leverage recent advances in optical and computational imaging and analysis to increase the information capture capacity of the optical microscope: optical mesoscopy, which uses a giant microscope objective (Mesolens) to enable high resolution imaging at low magnification; Fourier ptychographic microscopy, a computational imaging method which relies on oblique illumination with a series of LEDs to capture high resolution information; and deep neural networks which can be trained to increase the quality of low magnification, low resolution images. We compare and contrast the performance of these techniques for blood film imaging for the exemplar case of Giemsa-stained peripheral blood smears. Using computational image analysis and shape-based object classification we demonstrate their use for automated analysis of red blood cell morphology and visualization and detection of small blood borne parasites such as the malarial parasite Plasmodium falciparum. Our results demonstrate that these new methods greatly increase the information capturing capacity of the light microscope with transformative potential for haematology and more generally across digital pathology. This article is protected by copyright. All rights reserved

Data-driven malaria prevalence prediction in large densely populated urban holoendemic sub-Saharan West Africa

Over 200 million malaria cases globally lead to half-million deaths annually. The development of malaria prevalence prediction systems to support malaria care pathways has been hindered by lack of data, a tendency towards universal "monolithic" models (one-size-fits-all-regions) and a focus on long lead time predictions. Current systems do not provide short-term local predictions at an accuracy suitable for deployment in clinical practice. Here we show a data-driven approach that reliably produces one-month-ahead prevalence prediction within a densely populated all-year-round malaria metropolis of over 3.5 million inhabitants situated in Nigeria which has one of the largest global burdens of P. falciparum malaria. We estimate one-month-ahead prevalence in a unique 22-years prospective regional dataset of > 9 × 10^{4} participants attending our healthcare services. Our system agrees with both magnitude and direction of the prediction on validation data achieving MAE ≤ 6 × 10^{-2}, MSE ≤ 7 × 10^{-3}, PCC (median 0.63, IQR 0.3) and with more than 80% of estimates within a (+ 0.1 to - 0.05) error-tolerance range which is clinically relevant for decision-support in our holoendemic setting. Our data-driven approach could facilitate healthcare systems to harness their own data to support local malaria care pathways

Impact of motion compensation and partial volume correction for ¹⁸F-NaF PET/CT imaging of coronary plaque

Recent studies have suggested that ¹⁸F-NaF-PET enables visualization and quantification of plaque micro-calcification in the coronary tree. However, PET imaging of plaque calcification in the coronary arteries is challenging because of the respiratory and cardiac motion as well as partial volume effects. The objective of this work is to implement an image reconstruction framework, which incorporates compensation for respiratory as well as cardiac motion (MoCo) and partial volume correction (PVC), for cardiac ¹⁸F-NaF PET imaging in PET/CT. We evaluated the effect of MoCo and PVC on the quantification of vulnerable plaques in the coronary arteries. Realistic simulations (Biograph TPTV, Biograph mCT) and phantom acquisitions (Biograph mCT) were used for these evaluations. Different uptake values in the calcified plaques were evaluated in the simulations, while three "plaque-type" lesions of 36, 31 and 18 mm³ were included in the phantom experiments. After validation, the MoCo and PVC methods were applied in four pilot NaF-PET patient studies. In all cases, the MoCo-based image reconstruction was performed using the STIR software. The PVC was obtained from a local projection (LP) method, previously evaluated in preclinical and clinical PET. The results obtained show a significant increase of the measured lesion-to-background ratios (LBR) in the MoCo+PVC images. These ratios were further enhanced when using directly the tissue-activities from the LP method, making this approach more suitable for the quantitative evaluation of coronary plaques. When using the LP method on the MoCo images, LBR increased between 200% and 1119% in the simulated data, between 212% and 614% in the phantom experiments and between 46% and 373% in the plaques with positive uptake observed in the pilot patients. In conclusion, we have built and validated a STIR framework incorporating MoCo and PVC for ¹⁸NaF PET imaging of coronary plaques. First results indicate an improved quantification of plaque-type lesions

Worker Flows in the European Union During the Great Recession

We measure the contribution of worker flows across employment, unemployment, and non-participation to the change in unemployment in eleven EU countries during the period 2006-2012, paying special attention to which socio-demographic groups in each of the countries were mostly affected by job creation and job destruction during the crisis. We find that age, to a larger extent than educational attainments, is the main determinant of flows from employment into unemployment, particularly in those countries where unemployment increased by most. Secondly, we highlight some institutional features of the labour market (employment protection legislation, unemployment insurance, and the incidence of active labor market policies) that help to explain the cross-country differences in flows between employment and unemployment and in their socio-demographic composition. Finally, we examine if the crisis has led to some employment reallocation across sectors, finding that, so far, there is no clear evidence in favor of cleansing effects

Residual stress analysis on tensile MMC specimens after loading/unloading tests in several conditions

ResidualstresseshavebeeninvestigatedinsamplesmadeofAA6061+22%Al2O3inordertocorrelate microstructural characteristics with mechanical performances. In particular, the possible occurrence of a brittle fracture induced by an excessive load transfer from the matrix to the reinforcement was investigated. To this end, macrostresses and microstresses were analysed. A neutron diffraction test on 12 specimens submitted to several loading/unloading conditions at different temperatures was performed. These measurements aimed to establish the optimal temperature for the initial extruded billet in pre-heating stage, before forging the final wheel hub