F D Raslau1, L Y Lin2, A H Andersen3, D K Powell3, C D Smith2,4,3, E J Escott2,5. 1. From the Departments of Radiology (F.D.R., L.Y.L., E.J.E., C.D.S.) flavius.raslau@uky.edu. 2. From the Departments of Radiology (F.D.R., L.Y.L., E.J.E., C.D.S.). 3. Neuroscience (A.H.A., D.K.P., C.D.S.). 4. Neurology (C.D.S.). 5. Otolaryngology-Head & Neck Surgery (E.J.E.), University of Kentucky, Lexington, Kentucky.
Abstract
BACKGROUND AND PURPOSE: Interpretation of fMRI depends on accurate functional-to-structural alignment. This study explores registration methods used by FDA-approved software for clinical fMRI and aims to answer the following question: What is the degree of misalignment when registration is not performed, and how well do current registration methods perform? MATERIALS AND METHODS: This retrospective study of presurgical fMRI for brain tumors compares nonregistered images and 5 registration cost functions: Hellinger, mutual information, normalized mutual information, correlation ratio, and local Pearson correlation. To adjudicate the accuracy of coregistration, we edge-enhanced echo-planar maps and rated them for alignment with structural anatomy. Lesion-to-activation distances were measured to evaluate the effects of different cost functions. RESULTS: Transformation parameters were congruent among Hellinger, mutual information, normalized mutual information, and the correlation ratio but divergent from the local Pearson correlation. Edge-enhanced images validated the local Pearson correlation as the most accurate. Hellinger worsened misalignment in 59% of cases, primarily exaggerating the inferior translation; no cases were worsened by the local Pearson correlation. Three hundred twenty lesion-to-activation distances from 25 patients were analyzed among nonregistered images, Hellinger, and the local Pearson correlation. ANOVA analysis revealed significant differences in the coronal (P < .001) and sagittal (P = .04) planes. If registration is not performed, 8% of cases may have a >3-mm discrepancy and up to a 5.6-mm lesion-to-activation distance difference. If a poor registration method is used, 23% of cases may have a >3-mm discrepancy and up to a 6.9-mm difference. CONCLUSIONS: The local Pearson correlation is a special-purpose cost function specifically designed for T2*-T1 coregistration and should be more widely incorporated into software tools as a better method for coregistration in clinical fMRI.
BACKGROUND AND PURPOSE: Interpretation of fMRI depends on accurate functional-to-structural alignment. This study explores registration methods used by FDA-approved software for clinical fMRI and aims to answer the following question: What is the degree of misalignment when registration is not performed, and how well do current registration methods perform? MATERIALS AND METHODS: This retrospective study of presurgical fMRI for brain tumors compares nonregistered images and 5 registration cost functions: Hellinger, mutual information, normalized mutual information, correlation ratio, and local Pearson correlation. To adjudicate the accuracy of coregistration, we edge-enhanced echo-planar maps and rated them for alignment with structural anatomy. Lesion-to-activation distances were measured to evaluate the effects of different cost functions. RESULTS: Transformation parameters were congruent among Hellinger, mutual information, normalized mutual information, and the correlation ratio but divergent from the local Pearson correlation. Edge-enhanced images validated the local Pearson correlation as the most accurate. Hellinger worsened misalignment in 59% of cases, primarily exaggerating the inferior translation; no cases were worsened by the local Pearson correlation. Three hundred twenty lesion-to-activation distances from 25 patients were analyzed among nonregistered images, Hellinger, and the local Pearson correlation. ANOVA analysis revealed significant differences in the coronal (P < .001) and sagittal (P = .04) planes. If registration is not performed, 8% of cases may have a >3-mm discrepancy and up to a 5.6-mm lesion-to-activation distance difference. If a poor registration method is used, 23% of cases may have a >3-mm discrepancy and up to a 6.9-mm difference. CONCLUSIONS: The local Pearson correlation is a special-purpose cost function specifically designed for T2*-T1 coregistration and should be more widely incorporated into software tools as a better method for coregistration in clinical fMRI.
Authors: Ali Gholipour; Nasser Kehtarnavaz; Richard Briggs; Michael Devous; Kaundinya Gopinath Journal: IEEE Trans Med Imaging Date: 2007-04 Impact factor: 10.048
Authors: Ali Gholipour; Nasser Kehtarnavaz; Richard W Briggs; Kaundinya S Gopinath; Wendy Ringe; Anthony Whittemore; Sergey Cheshkov; Khamid Bakhadirov Journal: IEEE Trans Biomed Eng Date: 2008-02 Impact factor: 4.538