NordGen

Computed tomography perfusion imaging allows estimation of tissue status in patients with acute ischemic stroke. We aimed to improve prediction of the final infarct and individual infarct growth rates using a deep learning approach. We trained a deep neural network to predict the final infarct volume in patients with acute stroke presenting with large vessel occlusions based on the native computed tomography perfusion images, time to reperfusion and reperfusion status in a derivation cohort (MR CLEAN trial [Multicenter Randomized Clinical Trial of Endovascular Treatment for Acute Ischemic Stroke in the Netherlands]). The model was internally validated in a 5-fold cross-validation and externally in an independent dataset (CRISP study [CT Perfusion to Predict Response to Recanalization in Ischemic Stroke Project]). We calculated the mean absolute difference between the predictions of the deep learning model and the final infarct volume versus the mean absolute difference between computed tomography perfusion imaging processing by RAPID software (iSchemaView, Menlo Park, CA) and the final infarct volume. Next, we determined infarct growth rates for every patient. We included 127 patients from the MR CLEAN (derivation) and 101 patients of the CRISP study (validation). The deep learning model improved final infarct volume prediction compared with the RAPID software in both the derivation, mean absolute difference 34.5 versus 52.4 mL, and validation cohort, 41.2 versus 52.4 mL (P<0.01). We obtained individual infarct growth rates enabling the estimation of final infarct volume based on time and grade of reperfusion. We validated a deep learning-based method which improved final infarct volume estimations compared with classic computed tomography perfusion imaging processing. In addition, the deep learning model predicted individual infarct growth rates which could enable the introduction of tissue clocks during the management of acute stroke.

Environmental compensation (EC) aims at addressing environmental losses due to development projects and involves a need to compare development losses with compensation gains using relevant metrics. A conceptual procedure for computing no net loss is formulated and used as a point of departure for a comparative analysis of metrics used by five Swedish municipalities as a part of their EC implementation in the spatial planning context of detailed development plans. While Swedish law does not require EC in this context, these municipalities have still decided to introduce EC requirements for development projects that occur on municipality-owned land and to promote voluntary EC among private actors in development projects on private land. There is substantial variation across the municipalities studied with respect to both metrics and attributes subject to measurement, but there are also similarities: The attributes considered when assessing the need for EC in conjunction with development are not only about nature per se, but also about recreational opportunities and other types ecosystem services; semi-quantitative metrics such as scores are common while quantitative or monetary metrics are rare; and metrics are rarely applied to assess compensatory gains, focusing instead on losses from development. Streamlining across municipalities might be warranted for increasing predictability and transparency for developers and citizens, but it also introduces considerable challenges such as a need for developing consistent guidelines for semi-quantitative metrics, and to handle substitutability issues if metrics are not only applied on individual attributes but also on groups of attributes. The broad scope of attributes used by the municipalities is in line with an international tendency to broaden EC to include not only biodiversity aspects but also ecosystem services. Moreover, the EC systems applied by the municipalities are of particular importance for highlighting the crucial role of environmental management for maintaining and enhancing biodiversity and ecosystem services not only in areas having formal protection status but also in the everyday landscape. The municipalities’ experience and strengths and weaknesses associated with their EC systems are therefore relevant also in an international perspective.

Transdisciplinary research and collaboration is widely acknowledged as a critical success factor for solution-oriented approaches that can tackle complex sustainability challenges, such as biodiversity loss, pollution, and climate-related hazards. In this context, city governments’ engagement in transdisciplinarity is generally seen as a key condition for societal transformation towards sustainability. However, empirical evidence is rare. This paper presents a self-assessment of a joint research project on ecosystem services and climate adaptation planning (ECOSIMP) undertaken by four universities and seven Swedish municipalities. We apply a set of design principles and guiding questions for transdisciplinary sustainability projects and, on this basis, identify key aspects for supporting university–municipality collaboration. We show that: (1) selecting the number and type of project stakeholders requires more explicit consideration of the purpose of societal actors’ participation; (2) concrete, interim benefits for participating practitioners and organisations need to be continuously discussed; (3) promoting the ‘inter’, i.e., interdisciplinary and inter-city learning, can support transdisciplinarity and, ultimately, urban sustainability and long-term change. In this context, we found that design principles for transdisciplinarity have the potential to (4) mitigate project shortcomings, even when transdisciplinarity is not an explicit aim, and (5) address differences and allow new voices to be heard. We propose additional guiding questions to address shortcomings and inspire reflexivity in transdisciplinary projects.

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