| Unique ID issued by UMIN | UMIN000062692 |
|---|---|
| Receipt number | R000071769 |
| Scientific Title | A Study to Establish Objective Evaluation Metrics for Determining Reconstruction Parameters in Deep Learning Reconstruction of Magnetic Resonance Imaging |
| Date of disclosure of the study information | 2026/09/01 |
| Last modified on | 2026/08/26 10:25:21 |
A Study on Evaluation Methods for Determining Appropriate Settings for MRI Image Creation Using Deep Learning
Evaluation Study of Appropriate Settings for MRI Image Creation Using Deep Learning
A Study to Establish Objective Evaluation Metrics for Determining Reconstruction Parameters in Deep Learning Reconstruction of Magnetic Resonance Imaging
Objective Evaluation Study for Determining DLR Reconstruction Parameters in MRI
| Japan |
Not applicable
| Adult |
Others
NO
Deep Learning Reconstruction (DLR) in MRI is useful for improving image quality and reducing scan time; however, appropriate reconstruction parameters may vary depending on the imaging sequence. In current clinical practice, reconstruction parameters are mainly determined based on visual assessment of reconstructed images, which is subjective and may have limited reproducibility. Furthermore, no objective and quantitative method for determining appropriate reconstruction parameters has yet been established. The aim of this study is to explore and develop objective evaluation metrics for determining DLR reconstruction parameters in MRI.
Efficacy
Utility of objective evaluation metrics (including histogram analysis of difference images before and after DLR, SNR, and CNR) for evaluating DLR reconstruction parameters, and their association and agreement with visual assessment.
Observational
| 18 | years-old | <= |
| Not applicable |
Male and Female
1.Healthy adults aged 18 years or older at the time of informed consent.
2.Individuals with no metallic implants and no claustrophobia.
3.Individuals who have provided informed consent to participate in this study.
1.Individuals with metallic implants or implanted medical devices.
2.Individuals with claustrophobia.
3.Individuals who are pregnant or may be pregnant.
10
| 1st name | Hiroshi |
| Middle name | |
| Last name | Ito |
Fukushima Medical University
Department of Radiology and Nuclear Medicine, School of Medicine
960-1295
1 Hikariga-Oka, Fukushima 960-1295, Japan
024-547-1111
rad@fmu.ac.jp
| 1st name | Yuma |
| Middle name | |
| Last name | Takahashi |
Fukushima Medical University Hospital
Department of Radiology
960-1295
1 Hikariga-Oka, Fukushima 960-1295, Japan
024-547-1111
yuma-t@fmu.ac.jp
Fukushima Medical University
Yuma Takahashi
None
Self funding
Fukushima Medical University Ethics Committee
1 Hikariga-Oka, Fukushima 960-1295, Japan
0245471111
rs@fmu.ac.jp
NO
| 2026 | Year | 09 | Month | 01 | Day |
Unpublished
Preinitiation
| 2026 | Year | 07 | Month | 10 | Day |
| 2026 | Year | 09 | Month | 01 | Day |
| 2027 | Year | 04 | Month | 30 | Day |
Prospective observational study evaluating the association and agreement between objective evaluation metrics and visual assessment of DLR reconstruction parameters using phantom and healthy volunteer MRI images.
| 2026 | Year | 08 | Month | 26 | Day |
| 2026 | Year | 08 | Month | 26 | Day |
Value
https://center6.umin.ac.jp/cgi-open-bin/ctr_e/ctr_view.cgi?recptno=R000071769