Quantitative and Comparative Evaluation of 2D Reduced-FOV Multi-shot Diffusion Tensor Imaging in Spinal Cord

Motivation: To our best knowledge, there has yet to be a comprehensive evaluation of the combination of cardiac triggering, reduced-FOV, or multi-shot techniques together for improving spinal cord DTI. Goal(s): This study aims to compare the performances of spinal cord DTI with different parametric combinations. Approach: Extensive and comparative experiments in five aspects were conducted. Results: Results demonstrate that multi-shot DTI with MUSE could achieve better reconstruction in the spinal cord. A combination of reduced-FOV and multi-shot techniques could be adopted simultaneously in pursuit of ultimate distortion correction. In addition, cardiac triggering should be equipped to reduce the influences on cerebrospinal fluid pulsation. Impact: Multi-shot DTI with MUSE and cardiac triggering might be the optimal combination for clinical diagnosis of the spinal cord if available on commercial MRI scanners. Future coil design could focus on customized coil arrangement of the spinal cord for optimization.

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/10.58530/2024/2522
Primary Topic
Advanced Neuroimaging 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

Quantitative and Comparative Evaluation of 2D Reduced-FOV Multi-shot Diffusion Tensor Imaging in Spinal Cord

Hing‐Chiu Chang, Hailin Xiong, Liyuan Liang, Xiaorui Xu et al.
1 links
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 Neuroimaging Techniques and Applications
article

Quantitative and Comparative Evaluation of 2D Reduced-FOV Multi-shot Diffusion Tensor Imaging in Spinal Cord

Hing‐Chiu Chang, Hailin Xiong, Liyuan Liang, Xiaorui Xu, Tian Liu, Yi Li, Shihui Chen, Chenglang Yuan
article en

Abstract

Motivation: To our best knowledge, there has yet to be a comprehensive evaluation of the combination of cardiac triggering, reduced-FOV, or multi-shot techniques together for improving spinal cord DTI. Goal(s): This study aims to compare the performances of spinal cord DTI with different parametric combinations. Approach: Extensive and comparative experiments in five aspects were conducted. Results: Results demonstrate that multi-shot DTI with MUSE could achieve better reconstruction in the spinal cord. A combination of reduced-FOV and multi-shot techniques could be adopted simultaneously in pursuit of ultimate distortion correction. In addition, cardiac triggering should be equipped to reduce the influences on cerebrospinal fluid pulsation. Impact: Multi-shot DTI with MUSE and cardiac triggering might be the optimal combination for clinical diagnosis of the spinal cord if available on commercial MRI scanners. Future coil design could focus on customized coil arrangement of the spinal cord for optimization.

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 65%
Advanced Neuroimaging 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.