Functions of the endothelium and its role in hematopoietic cell transplantation

The endothelium is a single-layered structure that responds to physical and chemical signals with various factors it synthesizes. In the early days of its discovery, as the inner wall of the vessels, the endothelium was thought to be a simple barrier that lays on the surface. Over time it is discovered that endothelium maintains body homeostasis with the molecules it synthesizes, despite its simple single-layer structure. It has been accepted as an important organ that contributes to the maintenance of vascular tone, cell adhesion, inflammation, vascular permeability and coagulation. Any imbalance in these physiological and pathological events causes endothelial dysfunction. This can cause many diseases such as atherosclerosis, hypertension, diabetes, or it can occur because of these. Endothelial related disorders may also complicate hematopoietic stem cell transplantation (HSCT), which is used to treat various hematologic and neoplastic diseases. These life-threatening complications include graft-versus-host disease, hepatic veno-occlussive disease, transplant-associated thrombotic microangiopathy and diffuse alveolar hemorrhage. They share a similar pathophysiology involving endothelial cells with different clinical presentations. Therefore, current researche on the issue is putting the endothelium under the spotlight for novel markers and treatment options that should be used to monitor or treat at least some of these complications following HSCT.     

Arterial spin labeling MR image denoising and reconstruction using unsupervised deep learning

Arterial spin labeling (ASL) imaging is a powerful magnetic resonance imaging technique that allows to quantitatively measure blood perfusion non-invasively, which has great potential for assessing tissue viability in various clinical settings. However, the clinical applications of ASL are currently limited by its low signal-to-noise ratio (SNR), limited spatial resolution, and long imaging time. In this work, we propose an unsupervised deep learning-based image denoising and reconstruction framework to improve the SNR and accelerate the imaging speed of high resolution ASL imaging. The unique feature of the proposed framework is that it does not require any prior training pairs but only the subject's own anatomical prior, such as T1-weighted images, as network input. The neural network was trained from scratch in the denoising or reconstruction process, with noisy images or sparely sampled k-space data as training labels. Performance of the proposed method was evaluated using in vivo experiment data obtained from 3 healthy subjects on a 3T MR scanner, using ASL images acquired with 44-min acquisition time as the ground truth. Both qualitative and quantitative analyses demonstrate the superior performance of the proposed txtc framework over the reference methods. In summary, our proposed unsupervised deep learning-based denoising and reconstruction framework can improve the image quality and accelerate the imaging speed of ASL imaging.     

Post-cardiac arrest intensive care in Sweden: A survey of current clinical practice

Background

European guidelines recommend targeted temperature management (TTM) in post-cardiac arrest care. A large multicentre clinical trial, however, showed no difference in mortality and neurological outcome when comparing hypothermia to normothermia with early treatment of fever. The study results were valid given a strict protocol for the assessment of prognosis using defined neurological examinations. With the current range of recommended TTM temperatures, and applicable neurological examinations, procedures may differ between hospitals and the variation of clinical practice in Sweden is not known.

Aim

The aim of this study was to investigate current practice in post-resuscitation care after cardiac arrest as to temperature targets and assessment of neurological prognosis in Swedish intensive care units (ICUs).

Methods

A structured survey was conducted by telephone or e-mail in all Levels 2 and 3 (= 53) Swedish ICUs during the spring of 2022 with a secondary survey in April 2023.

Results

Five units were not providing post-cardiac arrest care and were excluded. The response rate was 43/48 (90%) of the eligible units. Among the responding ICUs, normothermia (36–37.7°C) was applied in all centres (2023). There was a detailed routine for the assessment of neurological prognosis in 38/43 (88%) ICUs. Neurological assessment was applied 72–96 h after return of spontaneous circulation in 32/38 (84%) units. Electroencephalogram and computed tomography and/or magnetic resonance imaging were the most common technical methods available.

Conclusion

Swedish ICUs use normothermia including early treatment of fever in post-resuscitation care after cardiac arrest and almost all apply a detailed routine for the assessment of neurological prognosis. However, available methods for prognostic evaluation varies between hospitals.