Diagnostic and Prognostic Impact of pc-ASPECTS Applied to Perfusion CT in the Basilar Artery International Cooperation Study

BACKGROUND AND PURPOSE The posterior circulation Acute Stroke Prognosis Early CT Score (pc-APECTS) applied to CT angiography source images (CTA-SI) predicts the functional outcome of patients in the Basilar Artery International Cooperation Study (BASICS). We assessed the diagnostic and prognostic impact of pc-ASPECTS applied to perfusion CT (CTP) in the BASICS registry population. METHODS We applied pc-ASPECTS to CTA-SI and cerebral blood flow (CBF), cerebral blood volume (CBV), and mean transit time (MTT) parameter maps of BASICS patients with CTA and CTP studies performed. Hypoattenuation on CTA-SI, relative reduction in CBV or CBF, or relative increase in MTT were rated as abnormal. RESULTS CTA and CTP were available in 27/592 BASICS patients (4.6%). The proportion of patients with any perfusion abnormality was highest for MTT (93%; 95% confidence interval [CI], 76%-99%), compared with 78% (58%-91%) for CTA-SI and CBF, and 46% (27%-67%) for CBV (P < .001). All 3 patients with a CBV pc-ASPECTS < 8 compared to 6/23 patients with a CBV pc-ASPECTS ≥ 8 had died at 1 month (RR 3.8; 95% CI, 1.9-7.6). CONCLUSION CTP was performed in a minority of the BASICS registry population. Perfusion disturbances in the posterior circulation were most pronounced on MTT parameter maps. CBV pc-ASPECTS < 8 may indicate patients with high case fatality.

The Gut Microbiome and Cirrhosis: Basic Aspects

In this chapter the basic aspects helping to understand the microbiome in terms of quantity, diversity, complexity, function, and interaction with the host are discussed. First the nomenclature, definitions of taxa, and measures of diversity as well as methods to unravel this kingdom are outlined. A brief summary on its physiological relevance for general health and the functions exerted specifically by the microbiome is presented. Differences in the composition of the microbiome along the gastrointestinal tract and across the gut wall and its interindividual variations, enterotypes, and stability are highlighted. The reader will be familiarized with all different modulators impacting on the microbiome, namely, intrinsic and extrinsic factors. Intrinsic factors include gastrointestinal secretions (gastric acid, bile, pancreatic juice, mucus), antimicrobial peptides, motility, enteric nervous system, and host genotype. Extrinsic factors are mainly dietary choices, hygiene, stress, alcohol consumption, exercise, and medications. The second part of the chapter focuses on quantitative and qualitative changes in microbiome in liver cirrhosis. The mechanisms contributing to dysbiosis, small intestinal bacterial overgrowth, and bacterial translocation are delineated underscoring their role for the liver-gut axis.

Treatment planning aspects and Monte Carlo methods in proton therapy

Over the last years, the interest in proton radiotherapy is rapidly increasing. Protons provide superior physical properties compared with conventional radiotherapy using photons. These properties result in depth dose curves with a large dose peak at the end of the proton track and the finite proton range allows sparing the distally located healthy tissue. These properties offer an increased flexibility in proton radiotherapy, but also increase the demand in accurate dose estimations. To carry out accurate dose calculations, first an accurate and detailed characterization of the physical proton beam exiting the treatment head is necessary for both currently available delivery techniques: scattered and scanned proton beams. Since Monte Carlo (MC) methods follow the particle track simulating the interactions from first principles, this technique is perfectly suited to accurately model the treatment head. Nevertheless, careful validation of these MC models is necessary. While for the dose estimation pencil beam algorithms provide the advantage of fast computations, they are limited in accuracy. In contrast, MC dose calculation algorithms overcome these limitations and due to recent improvements in efficiency, these algorithms are expected to improve the accuracy of the calculated dose distributions and to be introduced in clinical routine in the near future.