Hemochromatosis, Hemosiderosis, Iron Overload
Conditions
Keywords
MRI, Iron overload
Brief summary
The purpose of this multi-site research is to validate a rapid magnetic resonance based confounder-corrected R-2 mapping method as a quantitative imaging biomarker of liver iron concentrations.
Detailed description
This multi-center, multi-vendor study will validate a rapid magnetic resonance-based confounder-corrected R2\* mapping method as a quantitative imaging biomarker of liver iron concentration (LIC). Excessive accumulation of iron in various organs, including the liver, which affects both adult and pediatric populations, is toxic and requires treatment aimed at reducing body iron stores. Measurement of LIC is critical for detection and staging of iron overload, and for monitoring iron-reducing chelator therapies that are expensive and have side effects. Magnetic Resonance Imaging (MRI) is a widely available, accessible, and safe technology, and it is very sensitive to the presence of iron in tissue. Translation of an MRI biomarker of liver iron concentration into broad clinical use requires that it is clinically feasible, precise, robust to changes in scan parameters, calibrated to a validated reference standard of LIC, and is reproducible across sites and manufacturers. There are currently no available MRI methods that meet these requirements. R2\*-MRI holds the greatest promise to meet these requirements. R2\* mapping can be performed very rapidly with whole-liver 3D coverage in a single 20s breath-hold. Protocol Modification approved to include additional liver susceptibility measurements for approximately 10 participants (already enrolled at the UW) via recently acquired Superconducting Quantum Interference Device (SQUID). The completion of this additional imaging will depend upon the successful set up and installation of this device. Per a protocol amendment approved on 10/11/21, the investigators are re-opening the study and increasing enrollment for control subjects. Up to 20 control subjects (changed from 5) will be enrolled.
Interventions
DEVICEMRI
R2 MRI scan
Sponsors
Johns Hopkins University
Stanford University
University of Texas
National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK)
University of Wisconsin, Madison
Study design
Observational model
COHORT
Time perspective
PROSPECTIVE
Eligibility
Sex/Gender
ALL
Age
8 Years to 89 Years
Healthy volunteers
Yes
Inclusion criteria
* know or suspected iron overload * minimum age: Stanford- 8years , University of Wisconsin - 10 years, John Hopkins follow- 10 years, University of Texas-Southwestern - 18 years
Exclusion criteria
* contraindication to magnetic resonance imaging
Design outcomes
Primary
| Measure | Time frame | Description |
|---|---|---|
| Calibration curve of liver R2* vs LIC measured by Ferriscan at each of the sites | 1 year | The hypothesis is that equivalence between R2 measured with different protocols with higher repeatability than standard MRI iron imaging measurement and with linear calibration to liver iron concentration will be demonstrated. This project will be considered a success if the reproducibility of confounder-corrected R2 MRI is established: the hypothesis is that calibrations at all sites will be equivalent. |
Secondary
| Measure | Time frame | Description |
|---|---|---|
| Precision: Difference in UW-measured R2* vs Average | 2 years | Repeat scans will be used at each site to determine precision of R2 liver iron concentration. Repeat scans on n=25 subjects per site will be used to determine Bland-Altman 95% limits of agreement (LOA) by plotting the difference in UW-measured R2\* vs average. |
| Diagnostic Accuracy | 2 years | In addition to correlation with liver iron concentration (technical accuracy), the diagnostic accuracy through receiver operator characteristic curve analysis will also be determined. |
| Robustness Assessed via Linear Mixed Effects Regression | 2 years | At each site and field strength, R2\* measurements from the eight different protocols will be compared to assess robustness. Robustness will be assessed via linear mixed effects regression. |
Countries
United States
Outcome results
None listed