Journal of neuroimaging : official journal of the American Society of Neuroimaging
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Review
Functional magnetic resonance imaging, deep learning, and Alzheimer's disease: A systematic review.
Alzheimer's disease (AD) is currently diagnosed using a mixture of psychological tests and clinical observations. However, these diagnoses are not perfect, and additional diagnostic tools (e.g., MRI) can help improve our understanding of AD as well as our ability to detect the disease. Accordingly, a large amount of research has been invested into innovative diagnostic methods for AD. ⋯ In turn, we outline the common deep neural network, preprocessing, and classification methods used in the literature. We also discuss the accuracy, strengths, limitations, and future direction of fMRI deep learning methods. In turn, we aim to summarize the current field for new researchers, suggest specific areas for future research, and highlight the potential of fMRI to aid AD diagnoses.
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Many studies have explored the possibility of using cranial ultrasound for discerning intracranial pathologies like tumors, hemorrhagic stroke, or subdural hemorrhage in clinical scenarios where computer tomography may not be accessible or feasible. The visualization of intracranial anatomy on B-mode ultrasound is challenging due to the presence of the skull that limits insonation to a few segments on the temporal bone that are thin enough to allow transcranial transmission of sound. Several artifacts are produced by hyperechoic signals inherent in brain and skull anatomy when images are created using temporal windows. ⋯ We present an illustrated anatomical atlas of cranial ultrasound B-mode images acquired in various pathologies in a critical care environment and compare our findings with published literature by performing a scoping review of literature on the subject.
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Several distinct conditions present as cystic or pseudocystic lesions within the spinal canal. Some of the most common spinal cystic lesions include spinal meningeal cysts, juxtafacet cysts, dermoid/epidermoid cysts, nerve sheath tumors, and syringohydromyelia. Clinical presentation is usually nonspecific and imaging characteristics are frequently overlapping, which may pose a challenging presurgical diagnosis. ⋯ It provides accurate lesion localization and characterization and, most of the times, it will allow a confident differential diagnosis. High-resolution three-dimensional T2-weighted sequences and diffusion-weighted imaging can provide important hints in specific cases. Signal correlation with T1-weighted and fat-saturated sequences allows to differentiate true cystic lesions from hemorrhage or fat tissue.
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Technological advances in the delivery of radiation and other novel cancer therapies have significantly improved the 5-year survival rates over the last few decades. Although recent developments have helped to better manage the acute effects of radiation, the late effects such as impairment in cognition continue to remain of concern. Accruing data in the literature have implicated derangements in hemodynamic parameters and metabolic activity of the irradiated normal brain as predictive of cognitive impairment. ⋯ In this review, we have elaborated on the mechanisms of radiation-induced brain injury and discussed several novel imaging modalities, including MR spectroscopy, MR perfusion imaging, functional MR, SPECT, and PET that provide pathophysiological and functional insights into the postradiation brain, and its correlation with radiation dose as well as clinical neurocognitive outcomes. Additionally, we explored some innovative imaging modalities, such as quantitative blood oxygenation level-dependent imaging, susceptibility-based oxygenation measurement, and T2-based oxygenation measurement, that hold promise in delineating the potential mechanisms underlying deleterious neurocognitive changes seen in the postradiation setting. We aim that this comprehensive review of a range of imaging modalities will help elucidate the hemodynamic and metabolic injury mechanisms underlying cognitive impairment in the irradiated normal brain in order to optimize treatment regimens and improve the quality of life for these patients.
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Mechanical thrombectomy (MT) for ischemic stroke due to large vessel occlusion is standard of care. Evidence-based guidelines on eligibility for MT have been outlined and evidence to extend the treatment benefit to more patients, particularly those at the extreme ends of a stroke clinical severity spectrum, is currently awaited. As patient selection continues to be explored, there is growing focus on procedure selection including the tools and techniques of thrombectomy and associated outcomes. ⋯ Further enhancement of AI techniques to potentially include automated vessel probe tools in suspected large vessel occlusions is proposed. Value of AI may be extended to assist in procedure selection including both the tools and technique of thrombectomy. Delivering personalized medicine is the wave of the future and tailoring the MT treatment to a stroke patient is in line with this trend.