The utility of MRI radiological biomarkers in determining intracranial pressure

Intracranial pressure (ICP) is a physiological parameter that conventionally requires invasive monitoring for accurate measurement. Utilising multivariate predictive models, we sought to evaluate the utility of non-invasive, widely accessible MRI biomarkers in predicting ICP and their reversibility following cerebrospinal fluid (CSF) diversion. The retrospective study included 325 adult patients with suspected CSF dynamic disorders who underwent brain MRI scans within three months of elective 24-h ICP monitoring. Five MRI biomarkers were assessed: Yuh sella grade, optic nerve vertical tortuosity (VT), optic nerve sheath distension, posterior globe flattening and optic disc protrusion (ODP). The association between individual biomarkers and 24-h ICP was examined and reversibility of each following CSF diversion was assessed. Multivariate models incorporating these radiological biomarkers were utilised to predict 24-h median intracranial pressure. All five biomarkers were significantly associated with median 24-h ICP (p < 0.0001). Using a pair-wise approach, the presence of each abnormal biomarker was significantly associated with higher median 24-h ICP (p < 0.0001). On multivariate analysis, ICP was significantly and positively associated with Yuh sella grade (p < 0.0001), VT (p < 0.0001) and ODP (p = 0.003), after accounting for age and suspected diagnosis. The Bayesian multiple linear regression model predicted 24-h median ICP with a mean absolute error of 2.71 mmHg. Following CSF diversion, we found pituitary sella grade to show significant pairwise reversibility (p < 0.001). ICP was predicted with clinically useful precision utilising a compact Bayesian model, offering an easily interpretable tool using non-invasive MRI data. Brain MRI biomarkers are anticipated to play a more significant role in the screening, triaging, and referral of patients with suspected CSF dynamic disorders.

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Publication Details

Journal
Scientific Reports
Published
2024-10-05
DOI
https://doi.org/10.1038/s41598-024-73750-9
Citations
4
Primary Topic
Cerebral Venous Sinus Thrombosis
Type
article
Field-Weighted Citation Impact
1.48

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article

The utility of MRI radiological biomarkers in determining intracranial pressure

Zakee Abdi, Laurence Dale Watkins, Maria Jelen, Parashkev Nachev et al.
4 citations
Scientific Reports
Cerebral Venous Sinus Thrombosis
1.48
article

The utility of MRI radiological biomarkers in determining intracranial pressure

Zakee Abdi, Laurence Dale Watkins, Maria Jelen, Parashkev Nachev, Ahmed K. Toma, Mohammad Alradhawi, Martyna Stasiak, Yousif Aldabbagh, Linda D’Antona, James K. Ruffle, Arif Hanafi Bin Jalal, Lewis W. Thorne, Raunak Jain, Shivani.B. Joshi, Musa China, Fleur C. Yildirim, Anand Pandit, Emily B.C. Tan, Crystallynn Skye, Asif Hasan, Ptolemy D. W. Banks
article en
4 citations

Abstract

Intracranial pressure (ICP) is a physiological parameter that conventionally requires invasive monitoring for accurate measurement. Utilising multivariate predictive models, we sought to evaluate the utility of non-invasive, widely accessible MRI biomarkers in predicting ICP and their reversibility following cerebrospinal fluid (CSF) diversion. The retrospective study included 325 adult patients with suspected CSF dynamic disorders who underwent brain MRI scans within three months of elective 24-h ICP monitoring. Five MRI biomarkers were assessed: Yuh sella grade, optic nerve vertical tortuosity (VT), optic nerve sheath distension, posterior globe flattening and optic disc protrusion (ODP). The association between individual biomarkers and 24-h ICP was examined and reversibility of each following CSF diversion was assessed. Multivariate models incorporating these radiological biomarkers were utilised to predict 24-h median intracranial pressure. All five biomarkers were significantly associated with median 24-h ICP (p < 0.0001). Using a pair-wise approach, the presence of each abnormal biomarker was significantly associated with higher median 24-h ICP (p < 0.0001). On multivariate analysis, ICP was significantly and positively associated with Yuh sella grade (p < 0.0001), VT (p < 0.0001) and ODP (p = 0.003), after accounting for age and suspected diagnosis. The Bayesian multiple linear regression model predicted 24-h median ICP with a mean absolute error of 2.71 mmHg. Following CSF diversion, we found pituitary sella grade to show significant pairwise reversibility (p < 0.001). ICP was predicted with clinically useful precision utilising a compact Bayesian model, offering an easily interpretable tool using non-invasive MRI data. Brain MRI biomarkers are anticipated to play a more significant role in the screening, triaging, and referral of patients with suspected CSF dynamic disorders.

Scientific ReportsVol. 14(1)
Queen Mary University of London (GB), MRC Prion Unit (GB), The London College (GB), National Hospital for Neurology and Neurosurgery (GB), University College London (GB)
Wellcome Trust, Medical Research Council, UCLH Biomedical Research Centre
Good health and well-being
Openalex Percentile: Top 17%
Cerebral Venous Sinus Thrombosis
1.48
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