Journal of neuroimaging : official journal of the American Society of Neuroimaging
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Today, it seems prudent to reconsider how ultrasound technology can be used for providing intraoperative neurophysiologic monitoring that will result in better patient outcomes and decreased length and cost of hospitalization. An extensive and rapidly growing literature suggests that the essential hemodynamic information provided by transcranial Doppler (TCD) ultrasonography neuromonitoring (TCDNM) would provide effective monitoring modality for improving outcomes after different types of vascular, neurosurgical, orthopedic, cardiovascular, and cardiothoracic surgeries and some endovascular interventional or diagnostic procedures, like cardiac catheterization or cerebral angiography. ⋯ The American Society of Neurophysiologic Monitoring and American Society of Neuroimaging Guidelines Committees formed a joint task force and developed updated guidelines to assist in the use of TCDNM in the surgical and intensive care settings. Specifically, these guidelines define (1) the objectives of TCD monitoring; (2) the responsibilities and behaviors of the neurosonographer during monitoring; (3) instrumentation and acquisition parameters; (4) safety considerations; (5) contemporary rationale for TCDNM; (6) TCDNM perspectives; and (7) major recommendations.
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Understanding the pathogenesis of temporal lobe epilepsy (TLE) is essential for its diagnosis and treatment. The study aimed to explore regional homogeneity (ReHo) and changes in effective connectivity (EC) between brain regions in TLE patients, hoping to discover potential abnormalities in certain brain regions in TLE patients. ⋯ The MVPA results indicated that ReHo abnormalities in brain regions may be an important feature in the identification of TLE. The enhanced EC from STG_L to FFG_R and LING_R indicates a shift in language processing to the right hemisphere, and the weakened EC from SOG_R and MOG_R to CUN_R may reveal an underlying mechanism of TLE.
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Intracerebral hemorrhage (ICH) and intraventricular hemorrhage (IVH) clinical trials rely on manual linear and semi-quantitative (LSQ) estimators like the ABC/2, modified Graeb and IVH scores for timely volumetric estimation from CT. Deep learning (DL) volumetrics of ICH have recently approached the accuracy of gold-standard planimetry. However, DL and LSQ strategies have been limited by unquantified uncertainty, in particular when ICH and IVH estimates intersect. Bayesian deep learning methods can be used to approximate uncertainty, presenting an opportunity to improve quality assurance in clinical trials. ⋯ In our validation clinical trial dataset, DL models with Bayesian uncertainty approximation provided superior volumetric estimates to LSQ methods with real-time estimates of model uncertainty.
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The objective is to demonstrate feasibility of separating magnetic sources in quantitative susceptibility mapping (QSM) by incorporating magnitude decay rates R 2 ∗ $R_2^{\rm{*}}$ in gradient echo (GRE) MRI. ⋯ Separation of magnetic sources based solely on GRE complex data is feasible by combining magnitude decay rate modeling and phase-based QSM and χ - ${\chi}^{-}$ change may serve as a biomarker for myelin recovery or damage in acute MS lesions.
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Differentiating paragangliomas from schwannomas and distinguishing sporadic from neurofibromatosis type 2 (NF 2)-related schwannomas is challenging but clinically important. This study aimed to assess the utility of dynamic susceptibility contrast perfusion MRI (DSC-MRI) and diffusion-weighted imaging (DWI) in discriminating infratentorial extra-axial schwannomas from paragangliomas and NF2-related schwannomas. ⋯ DSC-MRI and DWI both can aid in differentiating paragangliomas from schwannomas and sporadic from NF2-related schwannomas.