Test-retest repeatability of renal MRI parameters in healthy volunteers comparing ROI-based and tissue segmentation based image analysis

Motivation: Multiparametric MRI of the kidneys is a promising technique for renal diagnostics, but the diversity of imaging protocols and analysis strategies hinders clinical translation. Goal(s): Our goal was to assess the repeatability of a multiparametric MRI protocol comparing ROI-based and tissue segmentation based analysis. Approach: Ten volunteers were examined with a multiparametric MRI protocol including ASL, IVIM, BOLD, T1 and T2 mapping twice with one week between visits. Results: Good repeatability of the multiparametric protocol could be achieved. T1 and T2 values showed less variability compared to perfusion and diffusion related functional parameters. Tissue segmentation showed better repeatability compared to ROI-based analysis. Impact: Our study demonstrates relatively high repeatability of multiparametric functional MRI of the kidneys. The results of the image analysis methods suggest, that manual segmentation is to be preferred over ROI-based analysis, if automated segmentation is not available.

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/10.58530/2024/4815
Primary Topic
MRI in cancer diagnosis
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Test-retest repeatability of renal MRI parameters in healthy volunteers comparing ROI-based and tissue segmentation based image analysis

Petros Martirosian, Fritz Schick, Brigitte Gückel, Thomas Küstner 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
MRI in cancer diagnosis
article

Test-retest repeatability of renal MRI parameters in healthy volunteers comparing ROI-based and tissue segmentation based image analysis

Petros Martirosian, Fritz Schick, Brigitte Gückel, Thomas Küstner, Cecilia Liang, Ferdinand Seith, Bernd Kühn, Isabelle Loster
article en

Abstract

Motivation: Multiparametric MRI of the kidneys is a promising technique for renal diagnostics, but the diversity of imaging protocols and analysis strategies hinders clinical translation. Goal(s): Our goal was to assess the repeatability of a multiparametric MRI protocol comparing ROI-based and tissue segmentation based analysis. Approach: Ten volunteers were examined with a multiparametric MRI protocol including ASL, IVIM, BOLD, T1 and T2 mapping twice with one week between visits. Results: Good repeatability of the multiparametric protocol could be achieved. T1 and T2 values showed less variability compared to perfusion and diffusion related functional parameters. Tissue segmentation showed better repeatability compared to ROI-based analysis. Impact: Our study demonstrates relatively high repeatability of multiparametric functional MRI of the kidneys. The results of the image analysis methods suggest, that manual segmentation is to be preferred over ROI-based analysis, if automated segmentation is not available.

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
Good health and well-being
Openalex Percentile: Top 64%
MRI in cancer diagnosis
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.