Evaluating amplified magnetic resonance imaging as an input for computational fluid dynamics models of the cerebrospinal fluid DOI
Sarah Vandenbulcke, Paul Condron, Henri Dolfen

et al.

Interface Focus, Journal Year: 2025, Volume and Issue: 15(1)

Published: April 4, 2025

Computational models that accurately capture cerebrospinal fluid (CSF) dynamics are valuable tools to study neurological disorders and optimize clinical treatments. While CSF interrelate with deformations of the ventricular volumes, these have been simplified even discarded in computational because lack detailed measurements. Amplified magnetic resonance imaging (aMRI) enables visualization complex deformations, but this technique has not used for predicting dynamics. To assess feasibility using aMRI as an input (CFD) CSF, we deduced amplified cerebral ventricles from dataset imposed our CFD model. Then, compared resulting flow rates those measured vivo . The yielded following a pulsatile pattern line were, however, subject noise increased. As result, scaling factor 1/8 was necessary match rates. This is first application modelling flow, demonstrate incorporating non-uniform can contribute more predictions advance understanding

Language: Английский

Exercise modulates brain pulsatility: insights from q-aMRI and MRI-based flow methods DOI Creative Commons
J. Wright,

Emma Clarkson,

Samantha J. Holdsworth

et al.

Interface Focus, Journal Year: 2025, Volume and Issue: 15(1)

Published: April 4, 2025

This study investigates intracranial dynamics following the Monro–Kellie doctrine, depicting how brain pulsatility, cerebrospinal fluid (CSF) flow and cerebral blood (CBF) interact under resting exercise conditions. Using quantitative amplified magnetic resonance imaging (q-aMRI) alongside traditional MRI metrics, we measured analysed flow, CSF displacement in a cohort of healthy adults both at rest during low-intensity handgrip exercise. Exercise was found to reduce pulsatility CBF while increasing eliminating regurgitation, highlighting shift towards more sustained forward patterns (from cranial spinal compartments). Displacement analysis using q-aMRI revealed consistent trend reduced whole motion exercise, though as sample data that met quality control low ( n = 5), this not significant result. There an observable decrease third fourth ventricles, linking ventricular alterations. These findings suggest may only affect rate directionality but also modulate tissue motion, supporting homeostasis. offers insights into adapts dynamically varying conditions, with implications for understanding pressure regulation humans diagnostic contexts.

Language: Английский

Citations

1

The pulsing brain: state of the art and an interdisciplinary perspective DOI Creative Commons
Andrea Lecchini‐Visintini, Jaco J.M. Zwanenburg, Qiuting Wen

et al.

Interface Focus, Journal Year: 2025, Volume and Issue: 15(1)

Published: April 4, 2025

Understanding the pulsing dynamics of tissue and fluids in intracranial environment is an evolving research theme aimed at gaining new insights into brain physiology disease progression. This article provides overview related magnetic resonance imaging, ultrasound medical diagnostics mathematical modelling biological tissues fluids. It highlights recent developments, illustrates current goals emphasizes importance collaboration between these fields.

Language: Английский

Citations

1

Dynamic visualization of brain pulsations using amplified MRI: methodology and applications DOI Creative Commons
Samantha J. Holdsworth, Mehmet Kurt,

Josh McGeown

et al.

Interface Focus, Journal Year: 2025, Volume and Issue: 15(1)

Published: April 4, 2025

Brain pulsatility offers a compelling application in the study of cerebral biomechanics, particularly for mild traumatic brain injury (mTBI) and elevated intracranial pressure (ICP). In this study, we used amplified MRI to quantify tissue pulsations. Dynamic mode decomposition (DMD) processing was then applied provide spatio-temporal analysis motion. Four distinct use cases were examined: (i) resting versus exertion-induced heart rate changes, (ii) pre- post-lumbar puncture (LP), (iii) baseline post-brain injury, (iv) test–retest case. Results demonstrate that motion varies significantly across conditions, with DMD revealing modes frequencies corresponding physiological changes. Notably, mTBI showed an increase pulsatile post-injury, while ICP exhibited altered patterns post-LP, indicating potential biomarker pressure-related This approach new insights into pathological pulsatility; however, study’s limited sample size, reliance on retrospective gating assumptions regarding highlight need larger more diverse cohorts confirm these findings. Despite limitations, our results suggest dynamical could become valuable tool assessing dynamics, applications clinical diagnostics research neurovascular neurological conditions.

Language: Английский

Citations

1

Evaluating amplified magnetic resonance imaging as an input for computational fluid dynamics models of the cerebrospinal fluid DOI
Sarah Vandenbulcke, Paul Condron, Henri Dolfen

et al.

Interface Focus, Journal Year: 2025, Volume and Issue: 15(1)

Published: April 4, 2025

Computational models that accurately capture cerebrospinal fluid (CSF) dynamics are valuable tools to study neurological disorders and optimize clinical treatments. While CSF interrelate with deformations of the ventricular volumes, these have been simplified even discarded in computational because lack detailed measurements. Amplified magnetic resonance imaging (aMRI) enables visualization complex deformations, but this technique has not used for predicting dynamics. To assess feasibility using aMRI as an input (CFD) CSF, we deduced amplified cerebral ventricles from dataset imposed our CFD model. Then, compared resulting flow rates those measured vivo . The yielded following a pulsatile pattern line were, however, subject noise increased. As result, scaling factor 1/8 was necessary match rates. This is first application modelling flow, demonstrate incorporating non-uniform can contribute more predictions advance understanding

Language: Английский

Citations

1