Challenges in quantitative MRI
Helms, Gunther LU
(2018)
In Physica Medica, European Journal of Medical Physics
52(Suppl. 1).
p.7-7
- Abstract
- Purpose
Quantitative MRI (qMRI) yields reproducible “maps” of physiological and/or biophysical tissue parameters. These spatially resolved metrics are mainly used in clinical imaging research for cross-sectional and longitudinal studies. The field of qMRI has considerable expanded during the past two decades. Rather than focusing on particular methods, this talk highlights general concepts of accuracy and precision, the relationship to QA, and ongoing endeavors for validation.
Methods
Parameters are derived from models of the MR experiment. They thus share the limited resolution of MRI. At a second level, physiological and microscopic properties of tissue can be derived. Adequate QA has to be performed to control systematic... (More) - Purpose
Quantitative MRI (qMRI) yields reproducible “maps” of physiological and/or biophysical tissue parameters. These spatially resolved metrics are mainly used in clinical imaging research for cross-sectional and longitudinal studies. The field of qMRI has considerable expanded during the past two decades. Rather than focusing on particular methods, this talk highlights general concepts of accuracy and precision, the relationship to QA, and ongoing endeavors for validation.
Methods
Parameters are derived from models of the MR experiment. They thus share the limited resolution of MRI. At a second level, physiological and microscopic properties of tissue can be derived. Adequate QA has to be performed to control systematic error (bias), especially when comparing results obtained on scanners of different makes and model. Increasingly, validation experiments are performed to relate macroscopic maps to underlying microscopic tissue properties.
Results
Flip angle (B1+) mapping is a prime example for bias correction, especially at high and ultra-high magnetic field strength. However, magnetic field strength and model-specific implementations still can be large source of bias. Ideally, individual correction should also comprise control or correction for gross and physiological patient motion. Regular QA is advised to maintain the comparability of metrics over time. Recent progress in validation has mainly focused on tissue iron and myelin for improved interpretation of qMRI metrics as given by ever more-complex models of microscopic tissue properties.
Conclusions
In-depth knowledge of the MR system’s performance increases accuracy and is a prerequisite for validation and interpretation. Quantitative MRI across different platforms and field strengths remain challenging.
(Less)
Please use this url to cite or link to this publication:
https://lup.lub.lu.se/record/dc2e2d00-290f-4642-8a09-7ff27cfc38f9
- author
- Helms, Gunther
LU
- organization
- publishing date
- 2018-08
- type
- Chapter in Book/Report/Conference proceeding
- publication status
- published
- subject
- host publication
- Challenges in quantitative MRI : Abstracts from the 2nd European Congress of Medical Physics - Abstracts from the 2nd European Congress of Medical Physics
- series title
- Physica Medica, European Journal of Medical Physics
- volume
- 52
- issue
- Suppl. 1
- article number
- 7
- pages
- 1 pages
- publisher
- EFOMP European Federation of Organizations for Medical Physics
- ISSN
- 1120-1797
- DOI
- 10.1016/j.ejmp.2018.06.088
- project
- Automated data pipeline for clinical quantitative 7T MRI
- language
- English
- LU publication?
- yes
- id
- dc2e2d00-290f-4642-8a09-7ff27cfc38f9
- date added to LUP
- 2019-02-11 15:06:06
- date last changed
- 2022-10-10 15:08:40
@inproceedings{dc2e2d00-290f-4642-8a09-7ff27cfc38f9,
abstract = {{Purpose<br/>Quantitative MRI (qMRI) yields reproducible “maps” of physiological and/or biophysical tissue parameters. These spatially resolved metrics are mainly used in clinical imaging research for cross-sectional and longitudinal studies. The field of qMRI has considerable expanded during the past two decades. Rather than focusing on particular methods, this talk highlights general concepts of accuracy and precision, the relationship to QA, and ongoing endeavors for validation. <br/>Methods<br/>Parameters are derived from models of the MR experiment. They thus share the limited resolution of MRI. At a second level, physiological and microscopic properties of tissue can be derived. Adequate QA has to be performed to control systematic error (bias), especially when comparing results obtained on scanners of different makes and model. Increasingly, validation experiments are performed to relate macroscopic maps to underlying microscopic tissue properties. <br/>Results<br/>Flip angle (B1+) mapping is a prime example for bias correction, especially at high and ultra-high magnetic field strength. However, magnetic field strength and model-specific implementations still can be large source of bias. Ideally, individual correction should also comprise control or correction for gross and physiological patient motion. Regular QA is advised to maintain the comparability of metrics over time. Recent progress in validation has mainly focused on tissue iron and myelin for improved interpretation of qMRI metrics as given by ever more-complex models of microscopic tissue properties.<br/>Conclusions <br/>In-depth knowledge of the MR system’s performance increases accuracy and is a prerequisite for validation and interpretation. Quantitative MRI across different platforms and field strengths remain challenging.<br/>}},
author = {{Helms, Gunther}},
booktitle = {{Challenges in quantitative MRI : Abstracts from the 2nd European Congress of Medical Physics}},
issn = {{1120-1797}},
language = {{eng}},
number = {{Suppl. 1}},
pages = {{7--7}},
publisher = {{EFOMP European Federation of Organizations for Medical Physics}},
series = {{Physica Medica, European Journal of Medical Physics}},
title = {{Challenges in quantitative MRI}},
url = {{http://dx.doi.org/10.1016/j.ejmp.2018.06.088}},
doi = {{10.1016/j.ejmp.2018.06.088}},
volume = {{52}},
year = {{2018}},
}