Predicting the prognosis of unilateral spatial neglect using magnetic resonance imaging in patients with stroke: A systematic review

Imura, Takeshi; Mitsutake, Tsubasa; Hori, Tomonari; Tanaka, Ryo

doi:10.1016/j.brainres.2022.147954

Cited by 3 publications

(3 citation statements)

References 65 publications

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“…Present findings also highlight the prognostic value of imaging data for post-stroke recovery of spatial neglect, which is in line with previous outcomes (Kamakura et al, 2017;Karnath et al, 2011;Lunven et al, 2015;Umarova et al, 2016; for review see Imura et al, 2022).…”

Section: Discussionsupporting

confidence: 89%

Predicting individual long-term prognosis of spatial neglect based on acute stroke patient data

Röhrig,

Wiesen,

et al. 2024

Preprint

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One of the most pressing questions after a stroke is whether an individual patient will recover in the long-term. Previous studies demonstrated that spatial neglect - a common behavioral deficit after right hemispheric stroke - is a strong predictor for poor performance on a wide range of everyday tasks and for resistance to rehabilitation. The possibility of predicting long-term prognosis of spatial neglect is therefore of great relevance. The aim of the present study was to test the prognostic value of different imaging and non-imaging features from right hemispheric stroke patients: individual demographics (age, sex), initial neglect severity, and acute lesion information (size, location). Patients' behavior was tested twice in the acute and the chronic phases of stroke and prediction models were built using machine learning-based algorithms with repeated nested cross-validation and feature selection. Model performances indicate that demographic information seemed less beneficial. The best variable combination comprised individual neglect severity in the acute phase of stroke, together with lesion location and size. The latter were based on individual lesion overlaps with a previously proposed chronic neglect region-of-interest (ROI) that covers anterior parts of the superior and middle temporal gyri and the basal ganglia. These variables achieved a remarkably high level of accuracy by explaining 66% of the total variance of neglect patients, making them promising features in the prediction of individual outcome prognosis.

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Section: Discussionsupporting

confidence: 89%

Predicting individual long-term prognosis of spatial neglect based on acute stroke patient data

Röhrig,

Wiesen,

et al. 2024

Preprint

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“…[ 67 ] Various biomarkers from MRI and visual images from stroke patients have also been fed into a deep learning model called a convolutional neural network to predict the final lesion volume and thus the functional recovery of patients. [ 2 , 68 ] MRI-based assessment of images of intra- and interhemispheric neural connections can provide high-quality, high-resolution neuroanatomical information on multiple aspects of neuroanatomy, nerve bundle integrity, and neurofunctional connectivity, [ 69 ] thereby predicting various aspects of prognosis in stroke patients. MRI can be used to assess changes in brain function as the brain performs motor tasks [ 70 ] , or to assess how a particular rehabilitation tool treats changes in brain connectivity in the resting state after a stroke patient, [ 71 ] thus providing further insight into the neurological mechanisms of recovery in the brain after stroke, which is essential for selecting effective rehabilitation tools and developing precise rehabilitation programs.…”

Section: Discussionmentioning

confidence: 99%

Global trends and research hotspots of stroke and magnetic resonance imaging: A bibliometric analysis

Zhang,

Chen,

Liu

et al. 2023

Medicine

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Background: In this study, we used CiteSpace and VOSviewer to create a bibliometric visualization of research papers relating to stroke and magnetic resonance imaging (MRI) between 2000 and 2022. To fully understand the trends and hotspots in MRI and stroke research and provide new perspectives for future studies. Methods: The Web of Science Core Collection was selected as the source of data for this paper. Using CiteSpace and VOSviewer, publications were analyzed for authors, countries, institutions, journals, references, and keywords. Results: We found 1423 papers after searching and removing duplicates, which indicated an upward trend over the previous 23 years. Fiebach J.B. is the most published author (21 publications), Hacke W. is the most cited author (213 citations), and the United States (449 publications) and Harvard University (86 publications) are the most prolific nations and institutions. Stroke is the journal with the most co-citations (1275) and the most papers (171) published. The most representative reference was the 1995 article by Marler et al, which received 115 citations and had the top 3 co-occurring keywords: stroke, magnetic resonance imaging, and MRI. The article by Nogueria et al showed the strongest citation burst at the end of 2022 (strength = 17.32). High-frequency keywords in recent years are time, association, functional connectivity, thrombectomy, and rehabilitation. Conclusion: This study provides a scientific perspective on stroke and MRI research, provides valuable information for researchers to understand the current status of research, hotspots, and trends, and guides future research directions.

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“…Modern research in human neuroscience and radiology relies heavily on magnetic resonance imaging (MRI). MRI is a versatile tool used for a variety of purposes by clinicians and researchers alike, including examination of post-stroke lesions [1,2], reconstruction of white matter tracts [3][4][5] or observation of task-related brain activity through the hemodynamic response [6][7][8].…”

Section: Introductionmentioning

confidence: 99%

MRI noise and auditory health: Can one hundred scans be linked to hearing loss? The case of the Courtois NeuroMod project

Fortier¹,

Bellec²,

Boyle³

et al. 2023

Preprint

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Magnetic resonance imaging (MRI) is one of the most commonly used tools in neuroscience. However, it implies exposure to high noise levels. Exposure to noise can lead to temporary or permanent hearing loss, especially when the exposure is long and/or repeated. Little is known about the hearing risks for people undergoing several MRI examinations, especially in the context of longitudinal studies. The goal of this study was to assess the potential impact of repeated exposure to MRI noise on hearing in research participants undergoing dozens of MRI scans. As part of the Courtois NeuroMod project, six participants were scanned up to twice a week with the use of hearing protection. Their hearing was tested periodically, over a period of 1.5 years. First, baseline pure-tone thresholds and distortion product otoacoustic emission (DPOAE) amplitudes were acquired before the beginning of this study. Hearing tests were then scheduled immediately before/immediately after a scan and with a delay of two to seven days after a scan. Pure-tone thresholds and DPOAE amplitudes showed no scanner noise impact right after the scan session when compared to the values acquired right before the scan session. Pure-tone thresholds and DPOAE amplitudes acquired in the delayed condition and compared to the baseline showed similar results. These results suggest an absence of impact from MRI noise exposure. Overall, our results show that intensive longitudinal MRI studies likely do not cause hearing damage to participants when they properly utilize adequate hearing protection.

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Predicting the prognosis of unilateral spatial neglect using magnetic resonance imaging in patients with stroke: A systematic review

Cited by 3 publications

References 65 publications

Predicting individual long-term prognosis of spatial neglect based on acute stroke patient data

Predicting individual long-term prognosis of spatial neglect based on acute stroke patient data

Global trends and research hotspots of stroke and magnetic resonance imaging: A bibliometric analysis

MRI noise and auditory health: Can one hundred scans be linked to hearing loss? The case of the Courtois NeuroMod project

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