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Radiological examination of the brain is a critical determinant of stroke care pathways. Accessible neuroimaging is essential to detect the presence of intracerebral hemorrhage (ICH). Conventional magnetic resonance imaging (MRI) operates at high magnetic field strength (1.5–3 T), which requires an access-controlled environment, rendering MRI often inaccessible. We demonstrate the use of a low-field MRI (0.064 T) for ICH evaluation. Patients were imaged using conventional neuroimaging (non-contrast computerized tomography (CT) or 1.5/3 T MRI) and portable MRI (pMRI) at Yale New Haven Hospital from July 2018 to November 2020. Two board-certified neuroradiologists evaluated a total of 144 pMRI examinations (56 ICH, 48 acute ischemic stroke, 40 healthy controls) and one ICH imaging core lab researcher reviewed the cases of disagreement. Raters correctly detected ICH in 45 of 56 cases (80.4% sensitivity, 95%CI: [0.68–0.90]). Blood-negative cases were correctly identified in 85 of 88 cases (96.6% specificity, 95%CI: [0.90–0.99]). Manually segmented hematoma volumes and ABC/2 estimated volumes on pMRI correlate with conventional imaging volumes (ICC = 0.955, p = 1.69e-30 and ICC = 0.875, p = 1.66e-8, respectively). Hematoma volumes measured on pMRI correlate with NIH stroke scale (NIHSS) and clinical outcome (mRS) at discharge for manual and ABC/2 volumes. Low-field pMRI may be useful in bringing advanced MRI technology to resource-limited settings., Conventional magnetic resonance imaging (MRI) operates at a high magnetic field strength and requires a strict access-controlled environment, making MRI often inaccessible. Here, the authors present a portable low-field MRI device that detects intracerebral hemorrhage with high accuracy.

Brain imaging is essential to the clinical care of patients with stroke, a leading cause of disability and death worldwide. Whereas advanced neuroimaging techniques offer opportunities for aiding acute stroke management, several factors, including time delays, inter-clinician variability, and lack of systemic conglomeration of clinical information, hinder their maximal utility. Recent advances in deep machine learning (DL) offer new strategies for harnessing computational medical image analysis to inform decision making in acute stroke. We examine the current state of the field for DL models in stroke triage. First, we provide a brief, clinical practice-focused primer on DL. Next, we examine real-world examples of DL applications in pixel-wise labeling, volumetric lesion segmentation, stroke detection, and prediction of tissue fate postintervention. We evaluate recent deployments of deep neural networks and their ability to automatically select relevant clinical features for acute decision making, reduce inter-rater variability, and boost reliability in rapid neuroimaging assessments, and integrate neuroimaging with electronic medical record (EMR) data in order to support clinicians in routine and triage stroke management. Ultimately, we aim to provide a framework for critically evaluating existing automated approaches, thus equipping clinicians with the ability to understand and potentially apply DL approaches in order to address challenges in clinical practice. ANN NEUROL 2022;92:574-587.

Brain imaging is essential to the clinical management of patients with ischemic stroke. Timely and accessible neuroimaging, however, can be limited in clinical stroke pathways. Here, portable magnetic resonance imaging (pMRI) acquired at very low magnetic field strength (0.064 T) is used to obtain actionable bedside neuroimaging for 50 confirmed patients with ischemic stroke. Low-field pMRI detected infarcts in 45 (90%) patients across cortical, subcortical, and cerebellar structures. Lesions as small as 4 mm were captured. Infarcts appeared as hyperintense regions on T2-weighted, fluid-attenuated inversion recovery and diffusion-weighted imaging sequences. Stroke volume measurements were consistent across pMRI sequences and between low-field pMRI and conventional high-field MRI studies. Low-field pMRI stroke volumes significantly correlated with stroke severity and functional outcome at discharge. These results validate the use of low-field pMRI to obtain clinically useful imaging of stroke, setting the stage for use in resource-limited environments.

Background and Aims: MRI is critical for diagnosing acute stroke and guiding candidate selection for potential reperfusion therapy. However, rapid stroke evaluation using MRI is often dissuaded by the time required for patients to travel to access-controlled, high-field (1.5-3T) systems. Advances in low-field MRI enable the acquisition of clinically valuable images at the bedside. We report neuroimaging in patients presenting to the Emergency Department (ED) with stroke symptoms using a low-field portable MRI (pMRI) device. Methods: A 64mT pMRI device was deployed in the Yale-New Haven Hospital ED from August 2020 to July 2021. Patients presenting as a “Stroke Code” or “Intracranial Hemorrhage Alert” with no MRI contraindications were scanned. Exams were performed at the bedside, in the vicinity of ED room equipment. Research staff acquired imaging via tablet, with images available immediately after acquisition. Sequences obtained and axial scan times (in minutes) included T1-weighted imaging (4:54), T2-weighted imaging (7:03), fluid-attenuated inversion recovery imaging (9:31), and diffusion-weighed imaging with apparent diffusion coefficient mapping (9:04). Patients’ demographic information, hours from the time of patients' last known normal (LKN) to time of scan, and discharge diagnoses (determined from final imaging interpretation) were assessed. Results: pMRI exams were obtained on 54 patients (28 females, 51.9%; median age 71 years, 20-98 years). Discharge diagnoses included ischemic stroke (42.6%) no intracranial abnormality (31.5%), intraparenchymal hemorrhage (7.4%), atherosclerosis (7.4%), tumor (5.6%), subdural hematoma (3.7%), and intraventricular hemorrhage (1.9%). Patient LKN times ranged from 2 to 144 hours (median of 12 hours; 3 patients with no LKN excluded). The pMRI did not interfere with ED equipment and no significant adverse events occurred. Conclusion: We report the use of a pMRI for bedside neuroimaging in the ED. This approach suggests that pMRI may be viable for supporting rapid diagnosis and treatment candidate selection in patients presenting with stroke symptoms to the ED.

Background and PurposeIn stroke, timely treatment is vital for preserving neurologic function. However, decision-making in neurocritical care is hindered by limited accessibility of neuroimaging and radiological interpretation. We evaluated an artificial intelligence (AI) system for use in conjunction with bedside portable point-of-care (POC)-MRI to automatically measure midline shift (MLS), a quantitative biomarker of stroke severity.Materials and MethodsPOC-MRI (0.064 T) was acquired in a patient cohort (n=94) in the Neurosciences Intensive Care Unit (NICU) of an academic medical center in the follow-up window during treatment for ischemic stroke (IS) and hemorrhagic stroke (HS). A deep-learning architecture was applied to produce AI estimates of midline shift (MLS-AI). Neuroradiologist annotations for MLS were compared to MLS-AI using non-inferiority testing. Regression analysis was used to evaluate associations between MLS-AI and stroke severity (NIHSS) and functional disability (mRS) at imaging time and discharge, and the predictive value of MLS-AI versus clinical outcome was evaluated.ResultsMLS-AI was non-inferior to neuroradiologist estimates of MLS (p1.5 mm was positively predictive of poor discharge outcome in all patients (PPV=70%) and specifically in patients with IS (PPV=77%).ConclusionThe integration of portable POC-MRI and AI provides automatic MLS measurements that were not inferior to time-consuming, manual measurements from expert neuroradiologists, potentially reducing neuroradiological burden for follow-up imaging in acute stroke.

Background and Aims: Advances in low-field MRI have enabled image acquisition at the point-of-care (POC). We aim to characterize ischemic lesions in low-field, POC MRI and assess its relationship with stroke severity in ischemic stroke patients. Methods: We performed POC MRI exams on ischemic stroke patients. T2-weighted (T2W), fluid-attenuated inversion recovery (FLAIR), and diffusion-weighted imaging (DWI) exams were acquired with a 64mT, portable bedside MRI system. Three raters computed signal intensity ratios (SIR) for each sequence. For every slice showing an infarct, an SIR was generated by dividing the mean signal intensity of the lesion by the mean signal intensity of the contralateral hemisphere. Infarct volumes were obtained by multiplying the lesion area of each slice by the slice thickness (5mm) and summing the cross-sectional areas. Volumes were correlated with National Institutes of Health Stroke Scale (NIHSS) scores at the time of scan. Results: We studied 18 ischemic stroke patients (50% women; ages 30-95 years). Two patients were studied at two and three serial timepoints, respectively. POC exams were obtained 2.7 ± 2.2 days after symptom onset. A total of 18 T2W, 17 FLAIR, and 18 DWI exams were obtained. Three exams (1 T2W; 1 FLAIR; 1 DWI) were excluded due to motion degradation. High field MRI exams (19 ± 16 hours from POC exams) demonstrated ischemic infarcts in 15 of the 18 patients. All POC T2W and FLAIR exams revealed infarcts in these patients, and 14 of the 17 DWI exams showed infarcts. Ischemic infarcts were seen as hyperintense lesions (SIR: T2W = 1.19 ± 0.10, FLAIR = 1.15 ± 0.08, DWI = 1.36 ± 0.17). Infarct volume significantly correlated with NIHSS scores (T2W: r = 0.71, p < 0.01; FLAIR: r = 0.65, p < 0.05; DWI: r = 0.65, p < 0.05). Conclusions: These preliminary data suggest that low-field, POC MRI may be useful in the clinical evaluation of ischemic stroke. Further work in larger cohorts is needed to elucidate the appearance of infarction on low-field imaging.

Background: Radiographic diagnosis of intracranial hemorrhage (ICH) is a critical determinant of stroke care pathways requiring patient transport to a neuroimaging suite. Advances in low-field MRI have made it possible to obtain clinically useful imaging at the point of care (POC). Aim: The aim of this study was to obtain preliminary data regarding the ability of a bedside POC MRI scanner to detect ICH. Methods: We studied 36 patients with a diagnosis of ICH (n=18) or ischemic stroke (n=18). Five blinded readers independently evaluated T2W and FLAIR exams acquired prospectively on a 64 mT, portable bedside MRI system (Hyperfine Research, Inc). Kappa coefficients (κ) were calculated to determine inter-rater agreement. Ground truth was obtained from the clinical report of the closest conventional imaging study (17.9 ± 10.4 hours) and verified by a core reader. For each exam, majority consensus among raters was used to determine sensitivity. Results: ICH volume ranged from 4 to 101 cc (median of 13 cc). Exams were acquired within 7 days of symptom onset (51.1 ± 28.8 hours). A pathologic lesion was identified on every exam with 100% sensitivity. Sensitivity for distinguishing any hemorrhage was 89% and specificity was 83%. The mean sensitivity and specificity for individual raters was 79% and 69%, respectively. When limited to supratentorial hemorrhage, consensus sensitivity was 94%. For ICH cases detected by all raters (n=9), there was 100% accuracy for localizing the bleed (lobar vs. non-lobar) with perfect agreement among raters (κ = 1, p Conclusions: These data suggest that low-field, POC MRI may be used to detect hemorrhagic stroke at the bedside. Further work is needed to evaluate this approach in the hyperacute setting and across a wide range of ICH characteristics.

Oscillations in the local field potential (LFP) are widespread throughout the rodent limbic system, including in structures such as the orbitofrontal cortex and nucleus accumbens. Synchrony between LFPs across these structures, as seen during specific behavioral events, is often interpreted as evidence of a functional interaction. However, the source of these oscillations is often tacitly assumed to be local, leading to a potential misattribution of function. Using in vivo simultaneous multisite recordings in freely moving male rats (n = 7) we demonstrate that gamma-band LFP oscillations (45-90 Hz) in multiple anterior limbic structures are highly synchronous not only with each other, but also with those in piriform cortex. Phase reversals across the piriform cortex cell layer and susceptibility to nasal occlusion indicate that piriform cortex is the source of these common gamma oscillations. Thus, gamma-band LFP oscillations seen in brain regions adjacent to the piriform cortex are likely not generated locally, but are instead volume conducted from the piriform cortex. This emerging view of gamma oscillations in anterior limbic circuits highlights the importance of the common piriform cortex input as a major influence and introduces caveats in the interpretation of locally recorded LFPs.

Importance Neuroimaging is a key step in the clinical evaluation of brain injury. Conventional magnetic resonance imaging (MRI) systems operate at high-strength magnetic fields (1.5-3 T) that require strict, access-controlled environments. Limited access to timely neuroimaging remains a key structural barrier to effectively monitor the occurrence and progression of neurological injury in intensive care settings. Recent advances in low-field MRI technology have allowed for the acquisition of clinically meaningful imaging outside of radiology suites and in the presence of ferromagnetic materials at the bedside. Objective To perform an assessment of brain injury in critically ill patients in intensive care unit settings, using a portable, low-field MRI device at the bedside. Design, Setting, and Participants This was a prospective, single-center cohort study of 50 patients admitted to the neuroscience or coronavirus disease 2019 (COVID-19) intensive care units at Yale New Haven Hospital in New Haven, Connecticut, from October 30, 2019, to May 20, 2020. Patients were eligible if they presented with neurological injury or alteration, no contraindications for conventional MRI, and a body habitus not exceeding the scanner’s 30-cm vertical opening. Diagnosis of COVID-19 was determined by positive severe acute respiratory syndrome coronavirus 2 polymerase chain reaction nasopharyngeal swab result. Exposures Portable MRI in an intensive care unit room. Main Outcomes and Measures Demographic, clinical, radiological, and treatment data were collected and analyzed. Brain imaging findings are described. Results Point-of-care MRI examinations were performed on 50 patients (16 women [32%]; mean [SD] age, 59 [12] years [range, 20-89 years]). Patients presented with ischemic stroke (n = 9), hemorrhagic stroke (n = 12), subarachnoid hemorrhage (n = 2), traumatic brain injury (n = 3), brain tumor (n = 4), and COVID-19 with altered mental status (n = 20). Examinations were acquired at a median of 5 (range, 0-37) days after intensive care unit admission. Diagnostic-grade T1-weighted, T2-weighted, T2 fluid-attenuated inversion recovery, and diffusion-weighted imaging sequences were obtained for 37, 48, 45, and 32 patients, respectively. Neuroimaging findings were detected in 29 of 30 patients who did not have COVID-19 (97%), and 8 of 20 patients with COVID-19 (40%) demonstrated abnormalities. There were no adverse events or complications during deployment of the portable MRI or scanning in an intensive care unit room. Conclusions and Relevance This single-center series of patients with critical illness in an intensive care setting demonstrated the feasibility of low-field, portable MRI. These findings demonstrate the potential role of portable MRI to obtain neuroimaging in complex clinical care settings.