In Silico Trials On RF-Induced Hazards For Patients With Cerebral Stents Exposed to 1.5 T and 3.0 T MRI

Motivation: Lack of research on RF-induced heating in cerebral regions emphasizes the need for investigation, as surface curvature of brain, anatomical differences, and stent orientation across blood vessels in human models affect heating. Goal(s): Study the correlation of RF-induced heating and electric fields in the brain region at 1.5T and 3T MRI. Approach: EM simulations are performed along trajectories of sagittal sinus vein and internal carotid artery, with uniform vessel structures modeled for precision. Results: The heating correlates with tangential electric fields, but correlation coefficients vary between human models. This implies that heating is influenced by vessel anatomy, local tissues, and stent placement. Impact: This study highlights the importance of patient-specific in silico simulations to accurately predict RF-induced heating in cerebral stents during MRI. It demonstrates how anatomical variations, stent placement, and surrounding tissue properties influence heating, crucial for ensuring patient safety.

Authors

Publication Details

Journal
Proceedings on CD-ROM - International Society for Magnetic Resonance in Medicine. Scientific Meeting and Exhibition/Proceedings of the International Society for Magnetic Resonance in Medicine, Scientific Meeting and Exhibition
Published
2025-09-16
DOI
https://doi.org/10.58530/2025/3962
Primary Topic
Cerebrovascular and Carotid Artery Diseases
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

In Silico Trials On RF-Induced Hazards For Patients With Cerebral Stents Exposed to 1.5 T and 3.0 T MRI

Stuart A. Long, Jianfeng Zheng, Ananya Nandikanti, G. J. Shen et al.
Proceedings on CD-ROM - International Society for Magnetic Resonance in Medicine. Scientific Meeting and Exhibition/Proceedings of the International Society for Magnetic Resonance in Medicine, Scientific Meeting and Exhibition
Cerebrovascular and Carotid Artery Diseases
article

In Silico Trials On RF-Induced Hazards For Patients With Cerebral Stents Exposed to 1.5 T and 3.0 T MRI

Stuart A. Long, Jianfeng Zheng, Ananya Nandikanti, G. J. Shen, Ji Chen
article en

Abstract

Motivation: Lack of research on RF-induced heating in cerebral regions emphasizes the need for investigation, as surface curvature of brain, anatomical differences, and stent orientation across blood vessels in human models affect heating. Goal(s): Study the correlation of RF-induced heating and electric fields in the brain region at 1.5T and 3T MRI. Approach: EM simulations are performed along trajectories of sagittal sinus vein and internal carotid artery, with uniform vessel structures modeled for precision. Results: The heating correlates with tangential electric fields, but correlation coefficients vary between human models. This implies that heating is influenced by vessel anatomy, local tissues, and stent placement. Impact: This study highlights the importance of patient-specific in silico simulations to accurately predict RF-induced heating in cerebral stents during MRI. It demonstrates how anatomical variations, stent placement, and surrounding tissue properties influence heating, crucial for ensuring patient safety.

Proceedings on CD-ROM - International Society for Magnetic Resonance in Medicine. Scientific Meeting and Exhibition/Proceedings of the International Society for Magnetic Resonance in Medicine, Scientific Meeting and Exhibition
Openalex Percentile: Top 64%
Cerebrovascular and Carotid Artery Diseases
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.