The utility of MRI radiological biomarkers in determining intracranial pressure.

Humans Magnetic Resonance Imaging / methods Male Female Middle Aged Intracranial Pressure Adult Biomarkers / cerebrospinal fluid Retrospective Studies Aged Optic Nerve / diagnostic imaging
Adult hydrocephalus Bayesian modelling Radiological biomarkers

Journal

Scientific reports
ISSN: 2045-2322
Titre abrégé: Sci Rep
Pays: England
ID NLM: 101563288

Informations de publication

Date de publication:
05 Oct 2024
Historique:
received: 05 02 2024
accepted: 20 09 2024
medline: 6 10 2024
pubmed: 6 10 2024
entrez: 5 10 2024
Statut: epublish

Résumé

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.

Identifiants

DOI: 10.1038/s41598-024-73750-9 PMID: 39369053
pubmed: 39369053
doi: 10.1038/s41598-024-73750-9
pii: 10.1038/s41598-024-73750-9
doi:

Substances chimiques

Biomarkers 0

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

23238

Informations de copyright

© 2024. The Author(s).

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Auteurs

Anand S Pandit (AS)

High-Dimensional Neurology Group, UCL Queen Square Institute of Neurology, University College London, London, UK. a.pandit@ucl.ac.uk.
Victor Horsley Department of Neurosurgery, National Hospital for Neurology and Neurosurgery, London, UK. a.pandit@ucl.ac.uk.

Musa China (M)

Victor Horsley Department of Neurosurgery, National Hospital for Neurology and Neurosurgery, London, UK.
Division of Medicine, University College London, UCL, London, UK.

Raunak Jain (R)

Division of Medicine, University College London, UCL, London, UK.

Arif H B Jalal (AHB)

Division of Medicine, University College London, UCL, London, UK.

Maria Jelen (M)

Department of Psychology and Language Sciences, University College London, London, UK.

Shivani B Joshi (SB)

Division of Medicine, University College London, UCL, London, UK.

Crystallynn Skye (C)

Division of Medicine, University College London, UCL, London, UK.

Zakee Abdi (Z)

School of Medicine, Barts and the London School of Medicine and Dentistry, Queen Mary University of London, London, UK.

Yousif Aldabbagh (Y)

Division of Medicine, University College London, UCL, London, UK.

Mohammad Alradhawi (M)

Division of Medicine, University College London, UCL, London, UK.

Ptolemy D W Banks (PDW)

Victor Horsley Department of Neurosurgery, National Hospital for Neurology and Neurosurgery, London, UK.

Martyna K Stasiak (MK)

Department of Psychology and Language Sciences, University College London, London, UK.

Emily B C Tan (EBC)

Division of Medicine, University College London, UCL, London, UK.

Fleur C Yildirim (FC)

Department of Psychology and Language Sciences, University College London, London, UK.

James K Ruffle (JK)

High-Dimensional Neurology Group, UCL Queen Square Institute of Neurology, University College London, London, UK.

Linda D'Antona (L)

Victor Horsley Department of Neurosurgery, National Hospital for Neurology and Neurosurgery, London, UK.

Hasan Asif (H)

Victor Horsley Department of Neurosurgery, National Hospital for Neurology and Neurosurgery, London, UK.

Lewis Thorne (L)

Victor Horsley Department of Neurosurgery, National Hospital for Neurology and Neurosurgery, London, UK.

Laurence D Watkins (LD)

Victor Horsley Department of Neurosurgery, National Hospital for Neurology and Neurosurgery, London, UK.

Parashkev Nachev (P)

High-Dimensional Neurology Group, UCL Queen Square Institute of Neurology, University College London, London, UK.

Ahmed K Toma (AK)

Victor Horsley Department of Neurosurgery, National Hospital for Neurology and Neurosurgery, London, UK.

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