Management of sagittal craniosynostosis: morphological comparison of eight surgical techniques

The aim of this study was to carry out a retrospective multicentre study comparing the morphological outcome of 8 techniques used for the management of sagittal synostosis versus a large cohort of control patients. Computed tomographic (CT) images were obtained from children CT-scanned for non-craniosynostosis related events (n = 241) and SS patients at preoperative and postoperative follow-up stages (n = 101). No significant difference in morphological outcomes was observed between the techniques considered in this study. However, the majority of techniques showed a tendency for relapse. Further, the more invasive procedures at older ages seem to lead to larger intracranial volume compared to less invasive techniques at younger ages. This study can be a first step towards future multicentre studies, comparing surgical results and offering a possibility for objective benchmarking of outcomes between methods and centres.     

Comparison of Foaming Properties Between the Shirasu Porous Glass Membrane Device and Tessari’s Three-way Stopcock Technique for Polidocanol and Ethanolamine Oleate Foam Production: A Benchtop Study

PurposeTo compare the characteristics of polidocanol (POL) and ethanolamine oleate (EO) sclerosing foams produced by a Shirasu porous glass membrane (SPGM) device with those made using a 3-way stopcock (3WSC).Materials and MethodsFoam half-life times were measured in an ex-vivo benchtop study. Computed tomography (CT) images of each foam were obtained over the time course, and a CT texture analysis was conducted. The bubble size in each foam was measured by an optical microscope.ResultsMedian foam half-life times were longer in the SPGM group than in the 3WSC group (POL: 198 vs 166 s, P = .02; EO: 640 vs 391 s, P < .01). In the CT texture analysis, median standard deviation (SD) and entropy (randomness) were lower, and median energy (uniformity) and gray-level cooccurrence matrix (GLCM) homogeneity were higher in the SPGM group than in the 3WSC group (POL SD: at 30 s and 50–300 s; POL entropy: at 0–60 s; EO SD: at 0–600 s; EO entropy: at 0–460 s; POL energy: at 0–40 s; POL GLCM homogeneity: at 0–250 s; EO energy: at 0–360 s; EO GLCM homogeneity: at 0–480 s; all P < .05). Median bubble diameters in the SPGM group and in the 3WSC group were 69 and 83 μm (P < .01), respectively, in the POL foam; and 36 and 36 μm (P = .45), respectively, in the EO foam.ConclusionsPOL and EO foams had greater uniformity and longer foam half-life time when prepared with an SPGM device than with a 3WSC.     

Bayesian consensus clustering for multivariate longitudinal data

In clinical and epidemiological studies, there is a growing interest in studying the heterogeneity among patients based on longitudinal characteristics to identify subtypes of the study population. Compared to clustering a single longitudinal marker, simultaneously clustering multiple longitudinal markers allow additional information to be incorporated into the clustering process, which reveals co-existing longitudinal patterns and generates deeper biological insight. In the current study, we propose a Bayesian consensus clustering (BCC) model for multivariate longitudinal data. Instead of arriving at a single overall clustering, the proposed model allows each marker to follow marker-specific local clustering and these local clusterings are aggregated to find a global (consensus) clustering. To estimate the posterior distribution of model parameters, a Gibbs sampling algorithm is proposed. We apply our proposed model to the primary biliary cirrhosis study to identify patient subtypes that may be associated with their prognosis. We also perform simulation studies to compare the clustering performance between the proposed model and existing models under several scenarios. The results demonstrate that the proposed BCC model serves as a useful tool for clustering multivariate longitudinal data.     

Effects of the Cerebral Aneurysm Treatment Method on Coil Packing Density and Its Relationship with the Ostium Area

PurposeTo test the following hypotheses: (a) balloon or stent assistance increases coil packing density (CPD) in the endovascular treatment of intracranial aneurysms, and (b) CPD correlates to ostium area (OA) and aneurysm volume (AV).Materials and MethodsThis retrospective study included 60 aneurysms (54 ruptured and 6 unruptured) treated with simple coiling (SC) (n = 18), balloon-assisted coiling (BAC) (n = 7), or stent-assisted coiling (SAC) (n = 35) at the authors’ institution between August 2017 and December 2019. AV and OA measurements were obtained from 3-dimensional digital subtraction angiography images using commercial software. Coil sizes were retrieved from patient files, and coil volume (CV) measurements were obtained from https://www.angiocalc.com/. Analysis of covariance, multivariate covariance analysis, and Pearson correlation analyses were performed.ResultsThe median value for AV, CV, CPD, and OA was 63.4 mm³ (range, 5.5–1,771.4 mm³), 23.13 mm³ (range, 2.03–296.95 mm³), 33.29% (range, 13.41%–81.02%), and 10.7 mm² (range, 2.7–49.9 mm²), respectively. Multivariate analysis showed that the CPD values were not significantly different among the treatment groups, although OA significantly differed between the SC and SAC groups (P < .05). Pearson correlations showed that similar to AV, OA was negatively correlated with CPD (r = ?0.321, P < .05).ConclusionsThe CPD value in cerebral aneurysms treated with BAC or SAC did not differ from that in aneurysms treated with SC.     

Automatic segmentation of thoracic CT images using three deep learning models

PurposeDeep learning (DL) techniques are widely used in medical imaging and in particular for segmentation. Indeed, manual segmentation of organs at risk (OARs) is time-consuming and suffers from inter- and intra-observer segmentation variability. Image segmentation using DL has given very promising results. In this work, we present and compare the results of segmentation of OARs and a clinical target volume (CTV) in thoracic CT images using three DL models.Materials and methodsWe used CT images of 52 patients with breast cancer from a public dataset. Automatic segmentation of the lungs, the heart and a CTV was performed using three models based on the U-Net architecture. Three metrics were used to quantify and compare the segmentation results obtained with these models: the Dice similarity coefficient (DSC), the Jaccard coefficient (J) and the Hausdorff distance (HD).ResultsThe obtained values of DSC, J and HD were presented for each segmented organ and for the three models. Examples of automatic segmentation were presented and compared to the corresponding ground truth delineations. Our values were also compared to recent results obtained by other authors.ConclusionThe performance of three DL models was evaluated for the delineation of the lungs, the heart and a CTV. This study showed clearly that these 2D models based on the U-Net architecture can be used to delineate organs in CT images with a good performance compared to other models. Generally, the three models present similar performances. Using a dataset with more CT images, the three models should give better results.     

Climate Change: Effects on the Older Adult

The effects of climate change include floods, hurricanes, heat waves, and fires; these natural disasters can result in respiratory, cardiovascular, and psychological harm in older adults, who experience the highest morbidity and mortality during heat waves. Advanced practice registered nurses (APRNs) need education on preparing, assessing, and treating older adults for climate-change disasters, especially heat waves. This article will help APRNs understand the effects of climate-change events on the vulnerable older adults and advocates for the need to integrate health effects of climate change into curricula, practicums, policy, and research agendas.     

Extracellular vesicles: Their emerging roles in the pathogenesis of respiratory diseases

Alveoli are the basic structure of the lungs, consisting of various types of parenchymal and bone marrow-derived cells including alveolar macrophages. These various types of cells have several important functions; thus, communication between these cells plays an important role in homeostasis as well as in the pathophysiology of diseases in the lungs. For a better understanding of the pathophysiology of lung diseases, researchers have isolated each type of lung cell to investigate the changes in their gene expressions, including their humoral factor or adhesion molecules, to reveal the intercellular communication among these cells. In particular, investigations during the past decade have focused on extracellular vesicles, which are lipid bilayer delimited vesicles released from a cell that can move among various cells and transfer substances, including microRNAs, mRNAs and proteins, thus, functioning as intercellular messengers. Extracellular vesicles can be classified into three general groups: apoptotic bodies, exosomes, and microparticles. Extracellular vesicles, especially exosomes and microparticles, are attracting increasing attention from pulmonologists as tools for understanding pathogenesis and disease diagnosis. Here, we review studies, including our own, on exosomes and microparticles and their roles in both lung homeostasis and the pathogenesis of lung diseases such as idiopathic pulmonary fibrosis, chronic obstructive lung diseases, and acute respiratory distress syndrome. This review also addresses the roles of extracellular vesicles in COVID-19, the current global public health crisis.