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Cerebral aneurysm blebs generally form at or adjacent to the point of maximal WSS and are aligned with major flow structures. Wall pressure and OSI do not contribute to determining bleb location. The measurement of WSS using CFD models may potentially predict bleb formation and thus improve the assessment of rupture risk in unruptured aneurysms.

Artificial intelligence is a rapidly evolving field, with modern technological advances and the growth of electronic health data opening new possibilities in diagnostic radiology. In recent years, the performance of deep learning (DL) algorithms on various medical image tasks have continually improved. DL algorithms have been proposed as a tool to detect various forms of intracranial hemorrhage on non-contrast computed tomography (NCCT) of the head. In subtle, acute cases, the capacity for DL algorithm image interpretation support might improve the diagnostic yield of CT for detection of this time-critical condition, potentially expediting treatment where appropriate and improving patient outcomes. However, there are multiple challenges to DL algorithm implementation, such as the relative scarcity of labeled datasets, the difficulties in developing algorithms capable of volumetric medical image analysis, and the complex practicalities of deployment into clinical practice. This review examines the literature and the approaches taken in the development of DL algorithms for the detection of intracranial hemorrhage on NCCT head studies. Considerations in crafting such algorithms will be discussed, as well as challenges which must be overcome to ensure effective, dependable implementations as automated tools in a clinical setting.

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Background: The best evidence-enhanced recovery care pathway is yet to be defined for patients undergoing spinal surgery. Minimally invasive surgery, multimodal analgesia, early mobilization, and early postoperative nutrition have been considered as critical components of enhanced recovery in spinal surgery (ERSS). The objective of this study will be to synthesize the evidence underpinning individual components of a proposed multidisciplinary enhanced recovery pathway for patients undergoing spinal surgery. Methods: This is the study protocol for a systematic review of complex interventions. Our team identified 22 individual care components of a proposed pathway based on clinical practice guidelines and published reviews. We will include systematic reviews and meta-analysis, randomized controlled trials, non-randomized controlled trials, and observational studies in adults or pediatric patients evaluating any one of the pre-determined care components. Our primary outcomes will be all-cause mortality, morbidity outcomes (e.g., pulmonary, cardiac, renal, surgical complications), patient-reported outcomes and experiences (e.g., pain, quality of care experience), and health services outcomes (e.g., length of stay and costs). We will search the following databases (1990 onwards) MEDLINE, EMBASE, and Cochrane Library (Cochrane Database of Systematic Reviews and CENTRAL). Two reviewers will independently screen all citations, full-text articles, and abstract data. Potential conflicts will be resolved through discussion. The risk of bias for individual studies will be appraised using appropriate tools. A narrative synthesis will be provided with the information presented in the text and tables to summarize and explain the characteristics and findings of the included studies. Due to clinical and methodological heterogeneity, we do not anticipate to conduct meta-analyses. Confidence in cumulative evidence for each component of care will be classified according to the GRADE system.Discussion: This systematic review will identify, evaluate, and integrate the evidence underpinning individual components of a pathway for patients undergoing spinal surgery. The formation of an evidence-based pathway will allow for the standardization of clinical care delivery within the context of enhanced recovery in spinal surgery. Systematic review registration: PROSPERO CRD42019135289

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How blood was able to reach the heads of the long-necked sauropod dinosaurs has long been a matter of debate and several hypotheses have been presented. For example, it has been proposed that sauropods had exceptionally large hearts, multiple 'normal' sized hearts spaced at regular intervals up the neck or held their necks horizontal, or that the siphon effect was in operation. By means of an experimental model, we demonstrate that the siphon principle is able to explain how blood was able to adequately perfuse the sauropod brain. The return venous circulation may have been protected from complete collapse by a structure akin to the vertebral venous plexus. We derive an equation relating neck height and mean arterial pressure, which indicates that with a mean arterial pressure similar to that of the giraffe, the maximum safe vertical distance between heart and head would have been about 12 m. A hypothesis is presented that the maximum neck length in the fossil record is due to the siphon height limit. The equation indicates that to migrate over high ground, sauropods would have had to either significantly increase their mean arterial pressure or keep their necks below a certain height dependent on altitude.