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Bedside detection of intracranial midline shift using portable magnetic resonance imaging.

ABSTRACT: Neuroimaging is crucial for assessing mass effect in brain-injured patients. Transport to an imaging suite, however, is challenging for critically ill patients. We evaluated the use of a low magnetic field, portable MRI (pMRI) for assessing midline shift (MLS). In this observational study, 0.064 T pMRI exams were performed on stroke patients admitted to the neuroscience intensive care unit at Yale New Haven Hospital. Dichotomous (present or absent) and continuous MLS measurements were obtained on pMRI exams and locally available and accessible standard-of-care imaging exams (CT or MRI). We evaluated the agreement between pMRI and standard-of-care measurements. Additionally, we assessed the relationship between pMRI-based MLS and functional outcome (modified Rankin Scale). A total of 102 patients were included in the final study (48 ischemic stroke; 54 intracranial hemorrhage). There was significant concordance between pMRI and standard-of-care measurements (dichotomous, κ = 0.87; continuous, ICC = 0.94). Low-field pMRI identified MLS with a sensitivity of 0.93 and specificity of 0.96. Moreover, pMRI MLS assessments predicted poor clinical outcome at discharge (dichotomous: adjusted OR 7.98, 95% CI 2.07-40.04, p = 0.005; continuous: adjusted OR 1.59, 95% CI 1.11-2.49, p = 0.021). Low-field pMRI may serve as a valuable bedside tool for detecting mass effect.

SUBMITTER: Sheth KN

PROVIDER: S-EPMC8742125 | biostudies-literature | 2022 Jan

REPOSITORIES: biostudies-literature

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Bedside detection of intracranial midline shift using portable magnetic resonance imaging.

Sheth Kevin N KN Yuen Matthew M MM Mazurek Mercy H MH Cahn Bradley A BA Prabhat Anjali M AM Salehi Sadegh S Shah Jill T JT By Samantha S Welch E Brian EB Sofka Michal M Sacolick Laura I LI Kim Jennifer A JA Payabvash Seyedmehdi S Falcone Guido J GJ Gilmore Emily J EJ Hwang David Y DY Matouk Charles C Gordon-Kundu Barbara B Rn Adrienne Ward AW Petersen Nils N Schindler Joseph J Gobeske Kevin T KT Sansing Lauren H LH Sze Gordon G Rosen Matthew S MS Kimberly W Taylor WT Kundu Prantik P

Scientific reports 20220107 1

Neuroimaging is crucial for assessing mass effect in brain-injured patients. Transport to an imaging suite, however, is challenging for critically ill patients. We evaluated the use of a low magnetic field, portable MRI (pMRI) for assessing midline shift (MLS). In this observational study, 0.064 T pMRI exams were performed on stroke patients admitted to the neuroscience intensive care unit at Yale New Haven Hospital. Dichotomous (present or absent) and continuous MLS measurements were obtained o ...[more]

PMID: 34996970

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Project description:BackgroundNeuroimaging is essential for detecting spontaneous, nontraumatic intracerebral hemorrhage (ICH). Recent data suggest ICH can be characterized using low-field magnetic resonance imaging (MRI). Our primary objective was to investigate the sensitivity and specificity of ICH on a 0.064T portable MRI (pMRI) scanner using a methodology that provided clinical information to inform rater interpretations. As a secondary aim, we investigated whether the incorporation of a deep learning (DL) reconstruction algorithm affected ICH detection.MethodsThe pMRI device was deployed at Yale New Haven Hospital to examine patients presenting with stroke symptoms from October 26, 2020 to February 21, 2022. Three raters independently evaluated pMRI examinations. Raters were provided the images alongside the patient's clinical information to simulate real-world context of use. Ground truth was the closest conventional computed tomography or 1.5/3T MRI. Sensitivity and specificity results were grouped by DL and non-DL software to investigate the effects of software advances.ResultsA total of 189 exams (38 ICH, 89 acute ischemic stroke, 8 subarachnoid hemorrhage, 3 primary intraventricular hemorrhage, 51 no intracranial abnormality) were evaluated. Exams were correctly classified as positive or negative for ICH in 185 of 189 cases (97.9% overall accuracy). ICH was correctly detected in 35 of 38 cases (92.1% sensitivity). Ischemic stroke and no intracranial abnormality cases were correctly identified as blood-negative in 139 of 140 cases (99.3% specificity). Non-DL scans had a sensitivity and specificity for ICH of 77.8% and 97.1%, respectively. DL scans had a sensitivity and specificity for ICH of 96.6% and 99.3%, respectively.ConclusionsThese results demonstrate improvements in ICH detection accuracy on pMRI that may be attributed to the integration of clinical information in rater review and the incorporation of a DL-based algorithm. The use of pMRI holds promise in providing diagnostic neuroimaging for patients with ICH.

Project description:ImportanceThe magnetic resonance imaging (MRI) criteria currently used to diagnose idiopathic intracranial hypertension (IIH) are based on expert opinion and have limited accuracy. Additional neuroimaging signs have been proposed and used with contradictory results; thus, prospective evidence is needed to improve diagnostic accuracy.ObjectiveTo provide evidence-based, accurate MRI signs for IIH diagnosis.Design, setting, and participantsThis prospective cohort study was conducted from January 2018 to May 2021 with 3 validation cohorts at 2 Danish headache centers and with 3 independent international cohorts. Consecutive patients with suspected IIH were enrolled. Eligibility required the clinical suspicion of IIH, age 18 years or older, and written informed consent. The validation cohorts comprised patients with confirmed IIH from Austria and the US, and patients without IIH from the US. Data analysis was performed from December 2021 to August 2023.ExposureStandardized diagnostic workup was performed to classify cases according to current criteria, and blinded evaluation of cerebral radiological diagnostics and papilledema was performed.Main outcomes and measuresThe primary outcomes were MRI signs associated with IIH as assessed by univariate analyses. An MRI score estimating papilledema was calculated using machine learning. Internal validation of associations with lumbar puncture opening pressure and outcome and external validation of accuracy were performed in 3 cohorts.ResultsOf 192 eligible patients (185 women [96.4%]; median [IQR] age, 28.0 [23.0-35.0] years), 110 were classified as having IIH, 4 as having probable IIH, and 1 as having suspected IIH without papilledema; 77 did not have IIH and served as controls, with corresponding age, sex, and weight. Papilledema at diagnosis was associated with perioptic subarachnoid space distension (56 patients [68.3%] vs 21 patients [41.2%]), posterior globe flattening (53 patients [66.3%] vs 10 patients [21.3%]), optic nerve disc protrusion (35 patients [30.4%] vs 2 patients [2.3%]), and transverse sinus venous stenosis (75 patients [79.8%] vs 29 patients [46.8%]). The papilledema-estimating MRI score showed optimal balance between sensitivity (49%) and specificity (87%) when 2 of the 3 latter signs were present and was associated with the lumbar puncture opening pressure and ophthalmological outcome. The score showed strong diagnostic accuracy in the external validation cohorts (587 patients; area under the receiver operating characteristic curve, 0.86) and outperformed the current (2013) diagnostic MRI criteria.Conclusions and relevanceThe findings of this cohort study of patients with IIH and controls suggest that an evidence-based MRI score including posterior globe flattening, optic nerve disc protrusion, and transverse sinus stenosis can estimate the presence of papilledema more accurately than the current diagnostic criteria.

Project description:PurposeTo explore, at a high field strength of 7T, the performance of various fat spectral models on the quantification of triglyceride composition and proton density fat fraction (PDFF) using chemical-shift encoded MRI (CSE-MRI).MethodsMR data was acquired from CSE-MRI experiments for various fatty materials, including oil and butter samples and in vivo brown and white adipose mouse tissues. Triglyceride composition and PDFF were estimated using various a priori 6- or 9-peak fat spectral models. To serve as references, NMR spectroscopy experiments were conducted to obtain material specific fat spectral models and triglyceride composition estimates for the same fatty materials. Results obtained using the spectroscopy derived material specific models were compared to results obtained using various published fat spectral models.ResultsUsing a 6-peak fat spectral model to quantify triglyceride composition may lead to large biases at high field strengths. When using a 9-peak model, triglyceride composition estimations vary greatly depending on the relative amplitudes of the chosen a priori spectral model, while PDFF estimations show small variations across spectral models. Material specific spectroscopy derived spectral models produce estimations that better correlate with NMR spectroscopy estimations in comparison to those obtained using non-material specific models.ConclusionAt a high field strength of 7T, a material specific 9-peak fat spectral model, opposed to a widely accepted or generic human liver model, is necessary to accurately quantify triglyceride composition when using CSE-MRI estimation methods that assume the spectral model to be known as a priori information. CSE-MRI allows for the quantification of the spatial distribution of triglyceride composition for certain in vivo applications. Additionally, PDFF quantification is shown to be independent of the chosen a priori spectral model, which agrees with previously reported results obtained at lower field strengths (e.g. 3T).

Dataset Information

Bedside detection of intracranial midline shift using portable magnetic resonance imaging.

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Bedside detection of intracranial midline shift using portable magnetic resonance imaging.

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