Deep transformation models for functional outcome prediction after acute ischemic stroke

In many medical applications, interpretable models with high prediction performance are sought. Often, those models are required to handle semi-structured data like tabular and image data. We show how to apply deep transformation models (DTMs) for distributional regression which fulfill these requirements. DTMs allow the data analyst to specify (deep) neural networks for different input modalities making them applicable to various research questions. Like statistical models, DTMs can provide interpretable effect estimates while achieving the state-of-the-art prediction performance of deep neural networks. In addition, the construction of ensembles of DTMs that retain model structure and interpretability allows quantifying epistemic and aleatoric uncertainty. In this study, we compare several DTMs, including baseline-adjusted models, trained on a semi-structured data set of 407 stroke patients with the aim to predict ordinal functional outcome three months after stroke. We follow statistical principles of model-building to achieve an adequate trade-off between interpretability and flexibility while assessing the relative importance of the involved data modalities. We evaluate the models for an ordinal and dichotomized version of the outcome as used in clinical practice. We show that both, tabular clinical and brain imaging data, are useful for functional outcome prediction, while models based on tabular data only outperform those based on imaging data only. There is no substantial evidence for improved prediction when combining both data modalities. Overall, we highlight that DTMs provide a powerful, interpretable approach to analyzing semi-structured data and that they have the potential to support clinical decision making.Comment: Preprint under revie

Labrador Sea freshening at 8.5 ka BP caused by Hudson Bay Ice Saddle collapse

A significant reduction in the Atlantic Meridional Overturning Circulation and rapid northern Hemisphere cooling 8200 years ago have been linked to the final melting of the Laurentide Ice Sheet. Although many studies associated this cold event with the drainage of Lake Agassiz-Ojibway, recent model simulations have shown that the Hudson Bay Ice Saddle collapse would have had much larger effects on the Atlantic Meridional Overturning Circulation than the lake outburst itself. Based on a combination of Mg/Ca and oxygen isotope ratios of benthic foraminifera, this study presents the first direct evidence of a major Labrador shelfwater freshening at 8.5 ka BP, which we associate with the Hudson Bay Ice Saddle collapse. The freshening is preceded by a subsurface warming of the western Labrador Sea, which we link to the strengthening of the West Greenland Current that could concurrently have accelerated the ice saddle collapse in Hudson Bay

Circle of Willis variants and their association with outcome in patients with middle cerebral artery-M1-occlusion stroke.

BACKGROUND An incomplete circle of Willis (CoW) has been associated with a higher risk of stroke and might affect collateral flow in large vessel occlusion (LVO) stroke. We aimed to investigate the distribution of CoW variants in a LVO stroke and transient ischemic attack (TIA) cohort and analyze their impact on 3-month functional outcome. METHODS CoW anatomy was assessed with time-of-flight magnetic resonance angiography (TOF-MRA) in 193 stroke patients with acute middle cerebral artery (MCA)-M1-occlusion receiving endovascular treatment (EVT) and 73 TIA patients without LVO. The main CoW variants were categorized into four vascular models of presumed collateral flow via the CoW. RESULTS 82.4% (n = 159) of stroke and 72.6% (n = 53) of TIA patients had an incomplete CoW. Most variants affected the posterior circulation (stroke: 77.2%, n = 149; TIA: 58.9%, n = 43; p = 0.004). Initial stroke severity defined by the National Institutes of Health Stroke Scale (NIHSS) on admission was similar for patients with and without CoW variants. CoW integrity did not differ between groups with favorable (modified Rankin Scale [mRS]): 0-2) and unfavorable (mRS: 3-6) 3-month outcome. However, we found trends towards a higher mortality in patients with any type of CoW variant (p = 0.08) and a higher frequency of incomplete CoW among patients dying within 3 months after stroke onset (p = 0.119). In a logistic regression analysis adjusted for the potential confounders age, sex and atrial fibrillation, neither the vascular models nor anterior or posterior variants were independently associated with outcome. CONCLUSION Our data provide no evidence for an association of CoW variants with clinical outcome in LVO stroke patients receiving EVT

Circle of Willis variants and their association with outcome in patients with middle cerebral artery-M1-occlusion stroke

BACKGROUND: An incomplete circle of Willis (CoW) has been associated with a higher risk of stroke and might affect collateral flow in large vessel occlusion (LVO) stroke. We aimed to investigate the distribution of CoW variants in a LVO stroke and transient ischemic attack (TIA) cohort and analyze their impact on 3-month functional outcome. METHODS: CoW anatomy was assessed with time-of-flight magnetic resonance angiography (TOF-MRA) in 193 stroke patients with acute middle cerebral artery (MCA)-M1-occlusion receiving endovascular treatment (EVT) and 73 TIA patients without LVO. The main CoW variants were categorized into four vascular models of presumed collateral flow via the CoW. RESULTS: 82.4% (n = 159) of stroke and 72.6% (n = 53) of TIA patients had an incomplete CoW. Most variants affected the posterior circulation (stroke: 77.2%, n = 149; TIA: 58.9%, n = 43; p = 0.004). Initial stroke severity defined by the National Institutes of Health Stroke Scale (NIHSS) on admission was similar for patients with and without CoW variants. CoW integrity did not differ between groups with favorable (modified Rankin Scale [mRS]): 0-2) and unfavorable (mRS: 3-6) 3-month outcome. However, we found trends towards a higher mortality in patients with any type of CoW variant (p = 0.08) and a higher frequency of incomplete CoW among patients dying within 3 months after stroke onset (p = 0.119). In a logistic regression analysis adjusted for the potential confounders age, sex and atrial fibrillation, neither the vascular models nor anterior or posterior variants were independently associated with outcome. CONCLUSION: Our data provide no evidence for an association of CoW variants with clinical outcome in LVO stroke patients receiving EVT

A product-process dependency definition method

The success of most software companies depends largely on software product quality. High product quality is usually a result of advanced software development processes. Hence, improvement actions should be selected based on sound knowledge about the dependencies between software product quality attributes and software development processes. This article describes a method for developing product/process dependency models (PPDMs) for product-driven software process improvement. The basic idea of the PPDM approach is that there are dependencies between product quality attributes, which are examined according to ISO 9126, and the software processes, which are assessed with the BOOTSTRAP methodology for example. The Goal-Question-Metric approach is used for product/process dependency hypothesis generation, analysis, and validation. We claim that after finding and using these dependencies it is possible to focus improvement activities precisely and use resources more efficiently. The approach is currently being applied in three industrial applications in the ESPRIT project PROFES

The role of GQM in the PROFES improvement methodology

In the ESPRIT project PROFES (PROduct-Focused Improvement of Embedded Software processes) a goal-driven process improvement methodology been developed that combines and enhances methods like goal-oriented measurement, product assessment, process assessment, and process modelling. So far, the PROFES improvement methodology has been applied in multiple projects at three industrial embedded software development organisations. In all three organisations considerable product quality and process improvements have been achieved. A fundamental element of the PROFES improvement methodology is goal-oriented measurement conducted according to the principles of the Goal/Question/Metric (GQM) paradigm. In the PROFES improvement methodology GQM is used for several purposes: (1) characterisation and evaluation of product quality, (2) characterisation and evaluation of process performance, (3) modelling and evaluation of product-process dependencies, and (4) facilitation of continuous assessment. In t he course of the PROFES project, GQM was also used to evaluate the PROFES improvement methodology in all three industrial software development organisations. This paper outlines the PROFES improvement methodology and reports experience with its application in three software development organisations. The different roles of GQM in the PROFES improvement methodology are presented in detail