Suchergebnisse

Advances in structural and functional neuroimaging have occurred at a rapid pace over the past two decades. Novel techniques for measuring cerebral blood flow, metabolism, white matter connectivity, and neural network activation have great potential to improve the accuracy of diagnosis and prognosis for patients with traumatic brain injury (TBI), while also providing biomarkers to guide the development of new therapies. Several of these advanced imaging modalities are currently being implemented into clinical practice, whereas others require further development and validation. Ultimately, for advanced neuroimaging techniques to reach their full potential and improve clinical care for the many civilians and military personnel affected by TBI, it is critical for clinicians to understand the applications and methodological limitations of each technique. In this review, we examine recent advances in structural and functional neuroimaging and the potential applications of these techniques to the clinical care of patients with TBI. We also discuss pitfalls and confounders that should be considered when interpreting data from each technique. Finally, given the vast amounts of advanced imaging data that will soon be available to clinicians, we discuss strategies for optimizing data integration, visualization and interpretation.

Advances in task-based functional MRI (fMRI), resting-state fMRI (rs-fMRI), and arterial-spin labeled (ASL) perfusion MRI have occurred at a rapid pace in recent years. These techniques for measuring brain function have great potential to improve the accuracy of prognostication for civilian and military patients with traumatic coma. In addition, fMRI, rs-fMRI, and ASL have provided novel insights into the pathophysiology of traumatic disorders of consciousness, as well as mechanisms of recovery from coma. However, functional neuroimaging techniques have yet to achieve widespread clinical use as prognostic tests for patients with traumatic coma. Rather, a broad spectrum of methodological hurdles currently limits the feasibility of clinical implementation. In this review, we discuss the basic principles of fMRI, rs-fMRI and ASL and their potential applications as prognostic tools for patients with traumatic coma. We also discuss future strategies for overcoming the current barriers to clinical implementation.

Objective: To determine whether the rich-club organization, essential for information transport in the human connectome, is an important biomarker of functional outcome after acute ischemic stroke (AIS). Methods: Consecutive AIS patients (N = 344) with acute brain magnetic resonance imaging (MRI) (<48 h) were eligible for this study. Each patient underwent a clinical MRI protocol, which included diffusion weighted imaging (DWI). All DWIs were registered to a template on which rich-club regions have been defined. Using manual outlines of stroke lesions, we automatically counted the number of affected rich-club regions and assessed its effect on the National Institute of Health Stroke Scale (NIHSS) and modified Rankin Scale (mRS; obtained at 90 days post-stroke) scores through ordinal regression. Results: Of 344 patients (median age 65, inter-quartile range 54–76 years) with a median DWI lesion volume (DWIv) of 3cc, 64% were male. We established that an increase in number of rich-club regions affected by a stroke increases the odds of poor stroke outcome, measured by NIHSS (OR: 1.77, 95%CI 1.41–2.21) and mRS (OR: 1.38, 95%CI 1.11–1.73). Additionally, we demonstrated that the OR exceeds traditional markers, such as DWIv (ORNIHSS 1.08, 95%CI 1.06–1.11; ORmRS 1.05, 95%CI 1.03–1.07) and age (ORNIHSS 1.03, 95%CI 1.01–1.05; ORmRS 1.05, 95%CI 1.03–1.07). Conclusion: In this proof-of-concept study, the number of rich-club nodes affected by a stroke lesion presents a translational biomarker of stroke outcome, which can be readily assessed using standard clinical AIS imaging protocols and considered in functional outcome prediction models beyond traditional factors. ; This project has received funding from the European Union's Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grant agreement No. 753896 (MS). This study was in part supported by the NIH-NINDS K23NS064052, R01NS082285, and R01NS086905 (NR); American Heart Association/Bugher Foundation Centers for Stroke Prevention Research and ...