OBJECTIVE:To determine the prevalence of diffusion-weighted imaging (DWI)–negative acute ischemic stroke (AIS) and to identify clinical characteristics of patients with DWI-negative AIS.
METHODS:We ...systematically searched PubMed and Ovid/MEDLINE for relevant studies between 1992, the year that the DWI sequence entered clinical practice, and 2016. Studies were included based upon enrollment of consecutive patients presenting with a clinical diagnosis of AIS prior to imaging. Meta-analysis was performed to synthesize study-level data, estimate DWI-negative stroke prevalence, and estimate the odds ratios (ORs) for clinical characteristics associated with DWI-negative stroke.
RESULTS:Twelve articles including 3,236 AIS patients were included. The meta-analytic synthesis yielded a pooled prevalence of DWI-negative AIS of 6.8%, 95% confidence interval (CI) 4.9–9.3. In the 5 studies that reported proportion data for DWI-negative and DWI-positive AIS based on the ischemic vascular territory (n = 1,023 AIS patients), DWI-negative stroke was strongly associated with posterior circulation ischemia, as determined by clinical diagnosis at hospital discharge or repeat imaging (OR 5.1, 95% CI 2.3–11.6, p < 0.001).
CONCLUSIONS:A small but significant percentage of patients with AIS have a negative DWI scan. Patients with neurologic deficits consistent with posterior circulation ischemia have 5 times the odds of having a negative DWI scan compared to patients with anterior circulation ischemia. AIS remains a clinical diagnosis and urgent reperfusion therapy should be considered even when an initial DWI scan is negative.
Substantial progress has been made over the past two decades in detecting, predicting and promoting recovery of consciousness in patients with disorders of consciousness (DoC) caused by severe brain ...injuries. Advanced neuroimaging and electrophysiological techniques have revealed new insights into the biological mechanisms underlying recovery of consciousness and have enabled the identification of preserved brain networks in patients who seem unresponsive, thus raising hope for more accurate diagnosis and prognosis. Emerging evidence suggests that covert consciousness, or cognitive motor dissociation (CMD), is present in up to 15-20% of patients with DoC and that detection of CMD in the intensive care unit can predict functional recovery at 1 year post injury. Although fundamental questions remain about which patients with DoC have the potential for recovery, novel pharmacological and electrophysiological therapies have shown the potential to reactivate injured neural networks and promote re-emergence of consciousness. In this Review, we focus on mechanisms of recovery from DoC in the acute and subacute-to-chronic stages, and we discuss recent progress in detecting and predicting recovery of consciousness. We also describe the developments in pharmacological and electrophysiological therapies that are creating new opportunities to improve the lives of patients with DoC.
•SynthSR turns clinical scans of different resolution and contrast into 1 mm MPRAGEs.•It relies on a CNN trained on fake images synthesized on the fly at every minibatch.•It can be retrained for any ...combination of resolutions / contrasts without new data.•It enables segmentation, registration, etc with existing software (e.g. FreeSurfer) Code is open source.
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Most existing algorithms for automatic 3D morphometry of human brain MRI scans are designed for data with near-isotropic voxels at approximately 1 mm resolution, and frequently have contrast constraints as well-typically requiring T1-weighted images (e.g., MP-RAGE scans). This limitation prevents the analysis of millions of MRI scans acquired with large inter-slice spacing in clinical settings every year. In turn, the inability to quantitatively analyze these scans hinders the adoption of quantitative neuro imaging in healthcare, and also precludes research studies that could attain huge sample sizes and hence greatly improve our understanding of the human brain. Recent advances in convolutional neural networks (CNNs) are producing outstanding results in super-resolution and contrast synthesis of MRI. However, these approaches are very sensitive to the specific combination of contrast, resolution and orientation of the input images, and thus do not generalize to diverse clinical acquisition protocols – even within sites. In this article, we present SynthSR, a method to train a CNN that receives one or more scans with spaced slices, acquired with different contrast, resolution and orientation, and produces an isotropic scan of canonical contrast (typically a 1 mm MP-RAGE). The presented method does not require any preprocessing, beyond rigid coregistration of the input scans. Crucially, SynthSR trains on synthetic input images generated from 3D segmentations, and can thus be used to train CNNs for any combination of contrasts, resolutions and orientations without high-resolution real images of the input contrasts. We test the images generated with SynthSR in an array of common downstream analyses, and show that they can be reliably used for subcortical segmentation and volumetry, image registration (e.g., for tensor-based morphometry), and, if some image quality requirements are met, even cortical thickness morphometry. The source code is publicly available at https://github.com/BBillot/SynthSR.
OBJECTIVE:To characterize a brainstem location specific to coma-causing lesions, and its functional connectivity network.
METHODS:We compared 12 coma-causing brainstem lesions to 24 control brainstem ...lesions using voxel-based lesion-symptom mapping in a case-control design to identify a site significantly associated with coma. We next used resting-state functional connectivity from a healthy cohort to identify a network of regions functionally connected to this brainstem site. We further investigated the cortical regions of this network by comparing their spatial topography to that of known networks and by evaluating their functional connectivity in patients with disorders of consciousness.
RESULTS:A small region in the rostral dorsolateral pontine tegmentum was significantly associated with coma-causing lesions. In healthy adults, this brainstem site was functionally connected to the ventral anterior insula (AI) and pregenual anterior cingulate cortex (pACC). These cortical areas aligned poorly with previously defined resting-state networks, better matching the distribution of von Economo neurons. Finally, connectivity between the AI and pACC was disrupted in patients with disorders of consciousness, and to a greater degree than other brain networks.
CONCLUSIONS:Injury to a small region in the pontine tegmentum is significantly associated with coma. This brainstem site is functionally connected to 2 cortical regions, the AI and pACC, which become disconnected in disorders of consciousness. This network of brain regions may have a role in the maintenance of human consciousness.
IMPORTANCE: Among the most impactful neurologic assessments is that of neuroprognostication, defined here as the prediction of neurologic recovery from disorders of consciousness caused by severe, ...acute brain injury. Across a range of brain injury etiologies, these determinations often dictate whether life-sustaining treatment is continued or withdrawn; thus, they have major implications for morbidity, mortality, and health care costs. Neuroprognostication relies on a diverse array of tests, including behavioral, radiologic, physiological, and serologic markers, that evaluate the brain’s functional and structural integrity. OBSERVATIONS: Prognostic markers, such as the neurologic examination, electroencephalography, and conventional computed tomography and magnetic resonance imaging (MRI), have been foundational in assessing a patient’s current level of consciousness and capacity for recovery. Emerging techniques, such as functional MRI, diffusion MRI, and advanced forms of electroencephalography, provide new ways of evaluating the brain, leading to evolving schemes for characterizing neurologic function and novel methods for predicting recovery. CONCLUSIONS AND RELEVANCE: Neuroprognostic markers are rapidly evolving as new ways of assessing the brain’s structural and functional integrity after brain injury are discovered. Many of these techniques remain in development, and further research is needed to optimize their prognostic utility. However, even as such efforts are underway, a series of promising findings coupled with the imperfect predictive value of conventional prognostic markers and the high stakes of these assessments have prompted clinical guidelines to endorse emerging techniques for neuroprognostication. Thus, clinicians have been thrust into an uncertain predicament in which emerging techniques are not yet perfected but too promising to ignore. This review illustrates the current, and likely future, landscapes of prognostic markers. No matter how much prognostic markers evolve and improve, these assessments must be approached with humility and individualized to reflect each patient’s values.
Consciousness may evade detection by bedside behavioral examination. New research suggests that an electrophysiologic screening tool can identify people with severe brain injuries who are likely to ...be covertly conscious.
Consciousness may evade detection by bedside behavioral examination. New research suggests that an electrophysiologic screening tool can identify people with severe brain injuries who are likely to be covertly conscious.
See Schiff (doi:10.1093/awx209) for a scientific commentary on this article. Patients with acute severe traumatic brain injury may recover consciousness before self-expression. Without behavioural ...evidence of consciousness at the bedside, clinicians may render an inaccurate prognosis, increasing the likelihood of withholding life-sustaining therapies or denying rehabilitative services. Task-based functional magnetic resonance imaging and electroencephalography techniques have revealed covert consciousness in the chronic setting, but these techniques have not been tested in the intensive care unit. We prospectively enrolled 16 patients admitted to the intensive care unit for acute severe traumatic brain injury to test two hypotheses: (i) in patients who lack behavioural evidence of language expression and comprehension, functional magnetic resonance imaging and electroencephalography detect command-following during a motor imagery task (i.e. cognitive motor dissociation) and association cortex responses during language and music stimuli (i.e. higher-order cortex motor dissociation); and (ii) early responses to these paradigms are associated with better 6-month outcomes on the Glasgow Outcome Scale-Extended. Patients underwent functional magnetic resonance imaging on post-injury Day 9.2 ± 5.0 and electroencephalography on Day 9.8 ± 4.6. At the time of imaging, behavioural evaluation with the Coma Recovery Scale-Revised indicated coma (n = 2), vegetative state (n = 3), minimally conscious state without language (n = 3), minimally conscious state with language (n = 4) or post-traumatic confusional state (n = 4). Cognitive motor dissociation was identified in four patients, including three whose behavioural diagnosis suggested a vegetative state. Higher-order cortex motor dissociation was identified in two additional patients. Complete absence of responses to language, music and motor imagery was only observed in coma patients. In patients with behavioural evidence of language function, responses to language and music were more frequently observed than responses to motor imagery (62.5-80% versus 33.3-42.9%). Similarly, in 16 matched healthy subjects, responses to language and music were more frequently observed than responses to motor imagery (87.5-100% versus 68.8-75.0%). Except for one patient who died in the intensive care unit, all patients with cognitive motor dissociation and higher-order cortex motor dissociation recovered beyond a confusional state by 6 months. However, 6-month outcomes were not associated with early functional magnetic resonance imaging and electroencephalography responses for the entire cohort. These observations suggest that functional magnetic resonance imaging and electroencephalography can detect command-following and higher-order cortical function in patients with acute severe traumatic brain injury. Early detection of covert consciousness and cortical responses in the intensive care unit could alter time-sensitive decisions about withholding life-sustaining therapies.
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