A weak scientific basis for gaming disorder: let us err on the side of caution

We greatly appreciate the care and thought that is evident in the 10 commentaries that discuss our debate paper, the majority of which argued in favor of a formalized ICD-11 gaming disorder. We agree that there are some people whose play of video games is related to life problems. We believe that understanding this population and the nature and severity of the problems they experience should be a focus area for future research. However, moving from research construct to formal disorder requires a much stronger evidence base than we currently have. The burden of evidence and the clinical utility should be extremely high, because there is a genuine risk of abuse of diagnoses. We provide suggestions about the level of evidence that might be required: transparent and preregistered studies, a better demarcation of the subject area that includes a rationale for focusing on gaming particularly versus a more general behavioral addictions concept, the exploration of non-addiction approaches, and the unbiased exploration of clinical approaches that treat potentially underlying issues, such as depressive mood or social anxiety first. We acknowledge there could be benefits to formalizing gaming disorder, many of which were highlighted by colleagues in their commentaries, but we think they do not yet outweigh the wider societal and public health risks involved. Given the gravity of diagnostic classification and its wider societal impact, we urge our colleagues at the WHO to err on the side of caution for now and postpone the formalization

Methods for the consistent follow-up assessment of pleural thickenings in CT volume data

Asbestos is a carcinogenic substance. Till its legal prohibition in the year 1993 it was widely used in Germany, due to its advantageous properties regarding resistance to acid, heat, electricity and alkalis. When working with this material, its fibers can get into the lung by inhalation and can get stuck. As a result, they might result in different types of cancer e.g. malignant pleural mesothelioma (MPM). This is a cancer of the pleura, which is a physical barrier surrounding the lung. An increasing number of MPM cases are expected till the year 2018 in Europe. In other countries, particularly in Asia, asbestos consumption is still rising. With a long latency of ca. 38 years, an increasing number of cases can be expected. Pleural thickenings can act as an indicator for MPM and can be observed in 3D CT image data. Detection of these thickenings at an early stage and the growth rate estimation from a follow-up assessment are essential for a successful treatment.The manual follow-up assessment of pleural thickenings in CT images from two points in time is subject to inter- and intra-reader variability and very time consuming. Existing automated methods have severe limitations considering the 3D coherence of potential findings. Additionally, they mainly ignore the temporal relation of data from consecutive images. With these limitations, the thickening assessment is unstable and is strongly influenced by small changes in the anatomy and the imaging process. In this thesis, a workflow for the stable and consistent follow-up assessment is presented to overcome these limitations.The first step is the localization of thickening regions on the pleura. Because of the fuzzy decision criteria an unambiguous identification of these regions is challenging. Nevertheless, in this thesis relevant features for the decision process are successfully extracted. An innovative combination of neural network-based classification and graph cuts-based segmentation combines the fuzzy, point-wise decision with the identification of coherent thickening regions.To exploit the temporal relation of the images from both points in time, they are aligned with respect to the lung surface. Two methods which explicitly focus on the lungs' surface and its surrounding are proposed. First, the images are rigidly aligned with a registration based on an offline trained Markov-Gibbs random field model of the lung tissue. The resulting lung specific measure outperforms generic similarity measures in terms of precision and reliability when aligning the lung surface. Secondly, a non-rigid registration compensates deformations of the soft tissue. A combination of intensity-based information and additional knowledge about the location of the lung surface improves the image registration in terms of computation time and stability. Finally, a new way of volume preservation in thickening regions is applied to the registration to allow a correct assessment of thickenings which are subject to growth. The registration forms the basis of temporal consistency in all subsequent steps.The extraction of a thickening's front and back requires different approaches: while the front is evident from the image contrast, the back is not directly observable and approximated by the healthy lung shape. The localization of the front can be significantly influenced by image noise and the partial volume effect. These influences are reduced by intensity-based matching of the surfaces in consecutive images. With a phase correlation-based method, sub-voxel accurate localization is achieved. The thickening back is estimated with a radial basis function interpolation, which connects the interpolations from both points in time. Two different connection methods are proposed and evaluated. For both methods, the connected interpolation is more consistent compared to the independent interpolation, without loss in precision.In some cases, the fully automatic segmentation results in unsatisfying boundaries. For this purpose, an intuitive tool which allows correction by simple user interaction is designed and implemented. Precise interaction is only possible in a 2D visualization of the 3D image data. The carefully designed user interface allows a fast and precise interaction. A graph cuts-based segmentation combines the 2D user input with image information in 3D. In comparison to commonly used segmentation tools, the proposed tool speeds up the segmentation process and significantly reduces the variability between different users.Finally, two different visualization concepts are presented. The first is meant to visualize the whole pleura surface at once. Based on multidimensional scaling, a 2D planar visualization with low distortions is estimated from the 3D lung surface. Different features, e.g. the thickening localization and thickness, can be visualized in this planar view. The newly introduced temporal consistency allows direct comparison of the surfaces from multiple points in time. The second visualization concept can be used for the 3D assessment of thickenings. A scattered visualization of the thickening's surface is utilized to convey segmentation uncertainties and the influence of the surface post-processing. This is particularly useful when visualizing follow-up results, which requires the superimposition of thickenings from two points in time. Through the additionally conveyed information, uncertain segmentations can be easier distinguished from actual growth by the observer.To conclude, all these steps form a seamless workflow for the follow-up assessment of MPM targeting four objectives: temporal consistency in consecutive image for a reliable growth assessment; reproducibility for low inter- and intra-reader variability; spatial coherence of thickenings for a profound assessment; and a high degree of automation for a low workload. All methods consider the limited image resolution which is a challenge for the relatively low thickness of the thickenings. To reach these objectives, each step is carefully designed, developed, implemented and evaluated. All methods could improve the temporal consistency by linking both points in time. This is not at the cost of precision, since performance for a single point in time was at least achieved and in most cases even outperformed. The results of all steps are based on each other and without the proposed on-going temporal link; the results at both points in time might drift apart.In contrast to existing approaches, this is the first work which covers the full workflow of processing the images, possible user-interaction and visualization for the assessment of MPM. It is the only approach which guarantees spatial and temporal consistency in each step. Additionally, it is the only method which considers uncertainties in processing and visualization. Consequently, the proposed concept takes MPM follow-up assessment to the next level

3D surface-based detection of pleural thickenings

Pleuramesothelioma is a malignant tumor of the pleura. It evolves from pleural thickenings which are a typical long-term effect of asbestos exposure. A diagnosis is performed by examining CT scans acquired from the patient’s lung. The analysis of the image data is a very time-consuming task and is subject to strong inter- and intra-reader variances. To objectivize the analysis and to speed-up the diagnosis a full automatic system is developed. An essential step in this process is to identify potential thickenings. In this paper we describe the complete system in brief, and then take a closer look on thickening detection. A CT slice based approach is presented here. It is extended by using 3D knowledge of thelung surface which could scarcely have been acquired visually

3D surface-based detection of pleural thickenings

Pleuramesothelioma is a malignant tumor of the pleura. It evolves from pleural thickenings which are a typical long-term effect of asbestos exposure. A diagnosis is performed by examining CT scans acquired from the patient’s lung. The analysis of the image data is a very time-consuming task and is subject to strong inter- and intra-reader variances. To objectivize the analysis and to speed-up the diagnosis a full automatic system is developed. An essential step in this process is to identify potential thickenings. In this paper we describe the complete system in brief, and then take a closer look on thickening detection. A CT slice based approach is presented here. It is extended by using 3D knowledge of thelung surface which could scarcely have been acquired visually