alternative regression algorithms in assessing iron loaded tissue. Methods. 25 patients had MRI Liver Iron quantification (LIC) by FerriScan iii and liver R2* ...
Estimating R2*. Method Matters Greg Brown, Adip Rad Tech Diag, FSMRT Royal Adelaide Hospital Adelaide South Australia
Background or Purpose
Tissue R2* and T2* values are used in a range of clinical questions. Manufacturers offer methods for acquisition and calculation which clinical users generally assume are accurate for the clinical setting. The author has reported that T2* MAPIT displayed a threshold of T2*i values which limit clinical utility, and literature suggest the common regression algorithm could be responsibleii. This work explores the performance of alternative regression algorithms in assessing iron loaded tissue. Methods
25 patients had MRI Liver Iron quantification (LIC) by FerriScaniii and liver R2* scans on a Siemens Avanto SQ 1.5T scanner using common parametersiv. Four subjects failed to complete the exam; one was excluded due to extreme LIC. MAPIT T2* maps were created using a Log-Linear algorithm. Liver T2* was measured as the mean of liver parenchyma. (L-L Map). ROI based non-linear regression was performed. T2* signal behavior was modeled as (Mono+C). An Excel Solverv calculated values of , R2* & C. for a “free offset” (C>=0), and with no offset (C=0). Three scans were obtained, and results averaged. Liver R2 values and LIC were determined by FerriScan. Results
There was close agreement of methods at low R2* (=0) demonstrate the best performance within a large and clinically relevant range. References i
Brown G,Taylor DJ McRobbieD. Proc ISMRM 2011. 800 Otto R et al Paediatric Radiology DOI 10.1007/s00247-011-2082-7 iii FerriScan registered trademark of Resonance Health Pty Ltd iv Parameters: 12 Echo BH GRE TR200 Flip20, TE 0.99-16.5. Voxel 3.1x3.1x10mm v EXCEL 2007. Microsoft Office 2007. Microsoft ii
