The Essential Role of Open Data and Software for the Future of Ultrasound-Based Neuronavigation

With the recent developments in machine learning and modern graphics processing units (GPUs), there is a marked shift in the way intra-operative ultrasound (iUS) images can be processed and presented during surgery. Real-time processing of images to highlight important anatomical structures combined with in-situ display, has the potential to greatly facilitate the acquisition and interpretation of iUS images when guiding an operation. In order to take full advantage of the recent advances in machine learning, large amounts of high-quality annotated training data are necessary to develop and validate the algorithms. To ensure efficient collection of a sufficient number of patient images and external validity of the models, training data should be collected at several centers by different neurosurgeons, and stored in a standard format directly compatible with the most commonly used machine learning toolkits and libraries. In this paper, we argue that such effort to collect and organize large-scale multi-center datasets should be based on common open source software and databases. We first describe the development of existing open-source ultrasound based neuronavigation systems and how these systems have contributed to enhanced neurosurgical guidance over the last 15 years. We review the impact of the large number of projects worldwide that have benefited from the publicly available datasets “Brain Images of Tumors for Evaluation” (BITE) and “Retrospective evaluation of Cerebral Tumors” (RESECT) that include MR and US data from brain tumor cases. We also describe the need for continuous data collection and how this effort can be organized through the use of a well-adapted and user-friendly open-source software platform that integrates both continually improved guidance and automated data collection functionalities.publishedVersio

Hessian-based Similarity Metric for Multimodal Medical Image Registration

One of the fundamental elements of both traditional and certain deep learning medical image registration algorithms is measuring the similarity/dissimilarity between two images. In this work, we propose an analytical solution for measuring similarity between two different medical image modalities based on the Hessian of their intensities. First, assuming a functional dependence between the intensities of two perfectly corresponding patches, we investigate how their Hessians relate to each other. Secondly, we suggest a closed-form expression to quantify the deviation from this relationship, given arbitrary pairs of image patches. We propose a geometrical interpretation of the new similarity metric and an efficient implementation for registration. We demonstrate the robustness of the metric to intensity nonuniformities using synthetic bias fields. By integrating the new metric in an affine registration framework, we evaluate its performance for MRI and ultrasound registration in the context of image-guided neurosurgery using target registration error and computation time

Human Exposure Risks Assessment of Heavy Metals in Groundwater within the Amansie and Adansi Districts in Ghana using Pollution Evaluation Indices

Non-carcinogenic risk assessment was done using Hazard Quotient (HQing/derm) and Hazard Index (HIing/derm) following USEPA methodology for a total of 59 boreholes and 12 hand dug wells sampled between July and October 2012. The objective was to assess the potential human health risks caused by exposure to non-carcinogenic heavy metals and estimate the potential environmental risk exposure in order to ensure the health safety of consumers within the Amansie and Adansi Districts. The results shows that, the heavy metal abundance in groundwater within the districts is in the order: Fe > Mn > As > Zn > Cu = Pb > Cd > Hg, for borehole water and Fe > As > Mn > Zn > Cu > Cd > Pb > Hg, for well water. The percentage contributions are: Fe (60%), Mn (20%), As (7%), Zn (5%), Cu (4%), Pb (4%), Cd (0%) and Hg (0%). The results also show that, the potential non-carcinogenic risks of exposure (HQing/derm) posed by Fe, Mn, Cd, Cu, Zn, Pb, As and Hg within a single route of exposure via ingestion or dermal contact is 3.30 x 10-2, 1.40 x 10-1, 5.00 x 10-4, 3.70 x 10-2, 3.00 x 10-1, 3.60 x 10-2, 3.00 x 10-4 and 3.00 x 10-4 respectively for both adults and children, suggesting a decreasing order of Zn > Mn > Cu > Pb > Fe > Cd > As = Hg, for borehole water, and Zn > Mn > Cu > Fe > Cd > As = Hg, for well water. The concerns for potential human health risks caused by exposure to non-carcinogenic heavy metals for Fe, Mn, Cd, Cu,Zn, Pb, As, and Hg are: 6.0 x10-2, 2.56 x 10-1, 9.15 x 10-4, 6.77 x 10-2, 5.49 x 10-1, 6.59 x 10-2, 5.49 x 10-4, 5.49 x 10-4 for boreholes, and 6.46 x 10-2, 2.74 x 10-1, 9.79 x10-4, 7.25 x 10-2, 5.88 x 10-1, 5.88 x 10-4, 5.88 x 10-4 for well water, suggesting that there is no concern for potential human health risks caused by exposure to non-carcinogenic toxic heavy metals in groundwater within the Districts (i.e HQ/HI As > Cd > Pb > Cu > Zn, for borehole water, and As > Cd > Cu > Zn for well water, suggesting that, groundwater within the Districts is potentially threatened by anthropogenic activities primarily, mining activities where, chemicals such as arsenic (As) and mercury (Hg) are used to recover gold from its amalgam. Based on the classification of environmental risk using comprehensive risk factor (CRI), borehole water within the districts could be classified as very high risk, while, well water could be classified as high risk. Generally, the main environmental heavy metals that poses pollution risk in groundwater within the Districts were Hg, As and Cd and contributed mostly to the Risk index factor (Ri)

Comparison of fasting and non-fasting lipid profiles in a large cohort of patients presenting at a community hospital

Objective: To compare the fasting and non-fasting lipid profile including ApoB in a cohort of patients from a community setting. Our purpose was to determine the proportion of results that could be explained by the known biological variation in the fasting state and to examine the additional impact of non-fasting on these same lipid parameters. Methods: 1093 adult outpatients with fasting lipid requests were recruited from February to September 2016 at the blood collection sites of the Moncton Hospital. Participants were asked to come back in the next 3–4 days after having eaten a regular breakfast to have their blood drawn for a non-fasting lipid profile. Results: 91.6% of patients in this study had a change in total cholesterol that fell within the biological variation expected for this parameter. Similar results were seen for HDL-C (94.3%) non-HDL-C (88.8%) and ApoB (93.0%). A smaller number of patients fell within the biological variation expected for TG (78.8%) and LDL-C (74.6%). An average TG increase of 0.3 mmol/L was observed in fed patients no matter the level of fasting TG. A gradual widening in the range of change in TG concentration was observed as fasting TG increased. Similar results were seen in diabetic patients. Conclusion: Outside of LDL-C and TG, little changes were seen in lipid parameters in the postprandial state. A large part of these changes could be explained by the biological variation. We observed a gradual widening in the range of increase in TG for patients with higher fasting TG. Non-HDL-C and ApoB should be the treatment target of choice for patients in the non-fasting state

Migration into Cities in Ghana: The Economic Benefi ts to Migrants and their Households

In the light of the rapid pace of urbanisation and associated challenges such as urban unemployment, urban poverty, and the emergence of slums, policy prescription in Ghana has largely occupied itself with attempts to curb rural-urban migration. There is a widely held perception that rural-urban migration cannot lead to positive outcomes for migrants and their households. Yet, there is little understanding of how rural-urban migrants in Ghana fare in the city relative to how they would have fared had they stayed in their original areas, or how their households would have fared had the migrant not left home. This briefi ng for policy makers is based on research conducted by the Migrating out of Poverty Research Consortium. It argues that while rural-urban migration can cause unemployment and lower income for a minority of migrants, most people who migrate from rural areas to cities in Ghana gain from enhanced incomes and improved wellbeing. The fi ndings indicate that migration from rural areas to cities in Ghana must not always be portrayed as detrimental to socio-economic development. Migration can be employed as a strategy to move out of poverty. The research fi ndings also call for the need to make potential migrants aware of the economic gains and losses associated with rural-urban migration.DFIDMigrating out of Povert

Social Benefits and Losses of Migrating into Cities in Ghana

While the literature tends to focus on the economic impacts of migration into cities, there is little understanding of the social gains and losses associated with migration into the city. As cogently noted by Switek (2012), fi nancial domain is not the only life aspect aff ected by migration. This briefi ng for policy makers provides evidence on the social counterfactuals (i.e. gains and losses) of migration from rural areas to cities in Ghana. It is based on the study ‘Migration into Cities in Ghana: An Analysis of the Counterfactual’ which was conducted by Migrating out of Poverty Research Programme Consortium at the University of Ghana in collaboration with the University of Sussex. The briefi ng argues that migration to the city can aff ect migrants and their households in relation to marriage, child birth, education, and psychological wellbeing. It also argues that these social outcomes of migration into the city can be either positive or negative, depending on particular contexts. And fi nally, it draws attention to policy implications of the social benefi ts and problems of migrating into cities in Ghana.DFIDMigrating out of Povert