Current status in spatiotemporal analysis of contrast‐based perfusion MRI

In perfusion MRI, image voxels form a spatially organized network of systems, all exchanging indicator with their immediate neighbors. Yet the current paradigm for perfusion MRI analysis treats all voxels or regions‐of‐interest as isolated systems supplied by a single global source. This simplificat...

Full description

Saved in:
Bibliographic Details
Published in:Magnetic resonance in medicine Vol. 91; no. 3; pp. 1136 - 1148
Main Authors: Shalom, Eve S., Khan, Amirul, Van Loo, Sven, Sourbron, Steven P.
Format: Journal Article
Language:English
Published: United States Wiley Subscription Services, Inc 01.03.2024
John Wiley and Sons Inc
Subjects:
Computer Processing and Modeling
Contrast Media
DCE‐MRI
DSC‐MRI
Image contrast
Inverse problems
Machine learning
Magnetic resonance imaging
Magnetic Resonance Imaging - methods
Nomenclature
Perfusion
Review
Spatio-Temporal Analysis
spatiotemporal modeling
Systematic errors
tracer kinetics
DCE-MRI
perfusion
DSC-MRI
spatiotemporal modeling
tracer kinetics
ISSN:0740-3194, 1522-2594, 1522-2594
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:In perfusion MRI, image voxels form a spatially organized network of systems, all exchanging indicator with their immediate neighbors. Yet the current paradigm for perfusion MRI analysis treats all voxels or regions‐of‐interest as isolated systems supplied by a single global source. This simplification not only leads to long‐recognized systematic errors but also fails to leverage the embedded spatial structure within the data. Since the early 2000s, a variety of models and implementations have been proposed to analyze systems with between‐voxel interactions. In general, this leads to large and connected numerical inverse problems that are intractible with conventional computational methods. With recent advances in machine learning, however, these approaches are becoming practically feasible, opening up the way for a paradigm shift in the approach to perfusion MRI. This paper seeks to review the work in spatiotemporal modelling of perfusion MRI using a coherent, harmonized nomenclature and notation, with clear physical definitions and assumptions. The aim is to introduce clarity in the state‐of‐the‐art of this promising new approach to perfusion MRI, and help to identify gaps of knowledge and priorities for future research.
Bibliography:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 14
ObjectType-Review-3
content type line 23
ISSN:0740-3194
1522-2594
1522-2594
DOI:10.1002/mrm.29906