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To facilitate both the detection and the interpretation of findings in chest X-rays, comparison with a previous image of the same patient is very valuable to radiologists. Today, the most common approach for deep learning methods to automatically inspect chest X-rays disregards the patient history and classifies only single images as normal or abnormal. Nevertheless, several methods for assisting in the task of comparison through image registration have been proposed in the past. However, as we illustrate, they tend to miss specific types of pathological changes like cardiomegaly and effusion. Due to assumptions on fixed anatomical structures or their measurements of registration quality, they produce unnaturally deformed warp fields impacting visualization of differences between moving and fixed images. We aim to overcome these limitations, through a new paradigm based on individual rib pair segmentation for anatomy penalized registration. Our method proves to be a natural way to limit the folding percentage of the warp field to 1/6 of the state of the art while increasing the overlap of ribs by more than 25%, implying difference images showing pathological changes overlooked by other methods. We develop an anatomically penalized convolutional multi-stage solution on the National Institutes of Health (NIH) data set, starting from less than 25 fully and 50 partly labeled training images, employing sequential instance memory segmentation with hole dropout, weak labeling, coarse-to-fine refinement and Gaussian mixture model histogram matching. We statistically evaluate the benefits of our method and highlight the limits of currently used metrics for registration of chest X-rays., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier Ltd. All rights reserved.)

Purpose: To investigate the accuracy and total assessment time (TAT) of the "All-in-one" (AIO)-window/level setting for whole-body computed tomography (CT) image compared to multiple tissue-specific window/level settings conventionally used for detection of traumatic injuries., Method: Contrast-enhanced chest, abdomen, and pelvic CT scans of 50 patients who presented to our emergency department (ED) for major trauma were retrospectively selected. In a simulation of a "wet read" performed at the CT scanner console, 6 readers with different levels of experience had up to 3 min to describe any traumatic finding identified on the CTs. The readers reviewed each patient in two different sessions separated by a washout period to suppress any recall bias from one session to the next. Each scan was reviewed once using the AIO-window/level setting and another time using the conventional bone, lung, and soft tissue window/level display settings, in a randomized order. The CT reports were used as reference standard., Results: Overall, there was no statistically significant difference in the assessment accuracy of the review based on the AIO or the conventional window/level settings (0.89 ± 0.09 vs 0.90 ± 0.08). Using the AIO-window/level settings, TAT was 14.3 s faster when compared with the conventional window/level settings (2.33 ± 0.63 vs 2.57 ± 0.51 min; p < 0.001)., Conclusions: In a time-delimited image review, similar diagnostic accuracy was reached faster using the AIO vs the conventional window/level settings. When providing a "wet read" at the CT console, the ability to identify traumatic injury using a single AIO-window/level may help expedite patient management., Competing Interests: Declaration of Competing Interest None., (Copyright © 2022. Published by Elsevier Inc.)

Population aging and declining birth rates are key demographic trends of the 21st century. While the overall life expectancy and healthy life years increase, the quality of life and functional capacity worsens due to non-communicable diseases strongly related to aging. Therefore, aging citizens are often vulnerable to food insecurity. The aim of this paper is to provide insights into the physical accessibility of fresh food and possible alternatives within the setting of an aging society in Antwerp (Belgium), a metropolitan city at the heart of the EU Reference Site 'Three Rivers Food Delta'. We demonstrate that a large number of the Antwerp suburban areas in which 15 to 25% of current inhabitants are already over 65 years old are confronted with problematic physical accessibility of food due to long walking distances to the nearest food shop. E-commerce has the potential to provide better access to fresh food. This is especially relevant for people with specific needs, such as health-related diets, dysphagia, and/or limited mobility. However, e-commerce introduces new inequalities, as those who would benefit the most from digital accessibility currently use it least. Hence, the organization of fresh food access requires a more thoughtful organization of the 'last mile' and possible alternatives to home delivery. This makes food accessibility an urgent factor of concern in public health and healthy aging in the Antwerp suburban areas.

Food deserts and swamps have previously been mostly studied in Anglo-Saxon countries such as the USA and Great Britain. This research is one of the first studies to map food deserts and swamps in a mainland European, densely populated but heavily fragmented region such as Flanders. The evolution of food deserts and swamps between 2008 and 2020 was assessed. Special focus was given to areas where high numbers of elderly, young people and/or families with low income live. Food deserts were calculated based on supermarket access within 1000 m and bus stop availability, while food swamps were calculated using the Modified Food Environment Retail Index. The main cause behind the formation of food deserts in Flanders is its rapidly aging population. Food deserts with a higher number of older people increased from 2.5% to 3.1% of the residential area between 2008 and 2020, housing 2.2% and 2.8% of the population, respectively. Although the area that could become a food desert in the future due to these sociospatial and demographic evolutions is large, food deserts are currently a relatively small problem in Flanders in comparison to the widespread existence of food swamps. Unhealthy retailers outnumbered healthy retailers in 74% of residential areas in 2020, housing 88.2% of the population. These food swamps create an environment where unhealthy food choices predominate. Residential areas with a higher number of elderly people, young people and families with low incomes had healthier food environments than Flanders as a whole, because these areas are mostly found in dense urban centers where the ratio of healthy food retailers to all retailers is higher. This research showed that food deserts and swamps could be a growing problem in European regions with a high population density that experience the high pressures of competing land uses.

Purpose: A newly developed image processing technique fuses conventional windows into a single 'All-In-One' (AIO) window. This study aims to evaluate variability of CT measurement of lesions in thoracic oncology patients on this novel AIO-window., Methods: Six radiologists with different levels of expertise measured 368 lesions of various size, origin and sharpness. All lesions were measured twice on the AIO-window and twice on the conventional window settings. Intraclass correlation coefficients and Bland-Altman plots were used to assess intra- and interobserver variability., Results: Overall intra-observer agreement for lesion diameters on the AIO-window and conventional window settings was 0.986 (95% Confidence interval (CI): 0.983-0.989) and 0.991 (95% CI 0.989-0.993) respectively. For interobserver agreement this was 0.982 (95% CI 0.979-0.985) (AIO) and 0.979 (95% CI 0.957-0.982) (conventional). For both the AIO and conventional windows, intra- and interobserver agreement were dependent on size, sharpness and reader experience. Measurement variability decreased with increasing lesion size. Regarding sharpness, inter- and intra-observer agreement ranged from 0.986-0.989 (AIO) and 0.985-0.992 (conventional) for well-defined lesions and from 0.978-0.983 (AIO) and 0.974-0.991 (conventional) for ill-defined lesions., Conclusions: Lesion diameters were consistently smaller on the AIO-window compared to conventional window settings. Overall intra- and interobserver variability rates were similar for the AIO-window and conventional window settings. We conclude that the AIO-window offers a reliable and reproducible alternative for measurement of thoracic lesions.

Portable bedside chest X-ray (CXR) is an important and frequently used tool in the intensive care unit (ICU). Unfortunately, the diagnostic value of portable CXR is often low due to technical limitations and suboptimal patient positioning. Additionally, abnormalities in the chest may be hidden on the projection image by overlapping anatomy and devices such as endotracheal tubes, lines and catheters. Digital tomosynthesis (DTS) can solve the problem of anatomical overlap. In DTS, several low-dose X-ray images from different angles are acquired and subsequently used by a reconstruction algorithm to compute section images along planes parallel to the detector. However, a portable device to be used for portable bedside chest DTS is not on the market yet. In this work, we discuss modifications to a portable X-ray device to enable portable DTS and illustrate the potential of portable DTS to improve the diagnostic value of bedside CXR in the ICU. A simulation, based on computed tomography scans, is presented. Our experiments comparing portable DTS with conventional bedside CXR showed a substantially improved detection of pneumothorax and other abnormalities., Competing Interests: The need for informed consent was waived by the Ethical Committee.JC and GB are employees of Agfa HealthCare.Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Object reconstruction from a series of projection images, such as in computed tomography (CT), is a popular tool in many different application fields. Existing commercial software typically provides sufficiently accurate and convenient-to-use reconstruction tools to the end-user. However, in applications where a non-standard acquisition protocol is used, or where advanced reconstruction methods are required, the standard software tools often are incapable of computing accurate reconstruction images. This article introduces the ASTRA Toolbox. Aimed at researchers across multiple tomographic application fields, the ASTRA Toolbox provides a highly efficient and highly flexible open source set of tools for tomographic projection and reconstruction. The main features of the ASTRA Toolbox are discussed and several use cases are presented.

Purpose: Projections acquired with continuous gantry rotation may suffer from blurring effects, depending on the rotation speed and the exposure time of each projection. This leads to blurred reconstructions if conventional reconstruction algorithms are applied. In this paper, the authors propose a reconstruction method for fast acquisitions based on a continuously moving and continuously emitting x-ray source. They study the trade-off between total acquisition time and reconstruction quality and compare with conventional reconstructions using projections acquired with a stepwise moving x-ray source., Methods: The authors introduce the algebraic reconstruction technique with angular integration concept, which models the angular integration due to the relative motion of the x-ray source during the projection., Results: Compared to conventional reconstruction from projections acquired with pulsed x-ray emission, the proposed method results in substantially improved reconstruction quality around the center of rotation. Outside this region, the proposed method results in improved radial resolution and a decreased tangential resolution. For a fixed reconstruction quality of this region of interest, the proposed method enables a lower number of projections and thus a faster acquisition., Conclusions: The modeling of the continuous gantry rotation in the proposed method substantially improves the reconstruction quality in a region of interest around the rotation center. The proposed method shows potential for fast region of interest tomography.