Multiband Real-Time MRI at high frame rate (80fps) for studying the kinematics of joint movement in health and disease.

Motivation: Our research addresses the need for improved imaging techniques to assess joint kinematics in orthopedic and neuro-pathological conditions, with a focus on osteoarthritis. Goal(s): The goal of this project is to investigate the capability of real-time MRI to assess joint mobility and function to aid clinical diagnosis and health/exercise research. Approach: We use a multi-band real-time MRI sequence, capturing joint movement at 80 frames per second in various body parts, including the mouth, temporo-mandibular joint, thumb, knee, and foot/ankle. Results: We demonstrate the feasibility of real-time MRI, offering detailed kinematic information while retaining soft tissue contrast. Impact: Our real-time MRI technique, capturing joint motion at 80 frames per second, can empower clinical diagnostics and health research related to joint kinematics. It offers precise, dynamic insights into joint function, potentially improving patient care and advancing scientific understanding.

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
2024-11-26
DOI
https://doi.org/10.58530/2024/0502
Primary Topic
Advanced MRI Techniques and Applications
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Multiband Real-Time MRI at high frame rate (80fps) for studying the kinematics of joint movement in health and disease.

Angelika Sebald, Fabio Zambolin, Jamie S. McPhee, Martin A. Trefzer 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
Advanced MRI Techniques and Applications
article

Multiband Real-Time MRI at high frame rate (80fps) for studying the kinematics of joint movement in health and disease.

Angelika Sebald, Fabio Zambolin, Jamie S. McPhee, Martin A. Trefzer, Isaac Watson, Elisa Zamboni, Aneurin J. Kennerley, James McStravick
article en

Abstract

Motivation: Our research addresses the need for improved imaging techniques to assess joint kinematics in orthopedic and neuro-pathological conditions, with a focus on osteoarthritis. Goal(s): The goal of this project is to investigate the capability of real-time MRI to assess joint mobility and function to aid clinical diagnosis and health/exercise research. Approach: We use a multi-band real-time MRI sequence, capturing joint movement at 80 frames per second in various body parts, including the mouth, temporo-mandibular joint, thumb, knee, and foot/ankle. Results: We demonstrate the feasibility of real-time MRI, offering detailed kinematic information while retaining soft tissue contrast. Impact: Our real-time MRI technique, capturing joint motion at 80 frames per second, can empower clinical diagnostics and health research related to joint kinematics. It offers precise, dynamic insights into joint function, potentially improving patient care and advancing scientific understanding.

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 62%
Advanced MRI Techniques and Applications
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.