Comparison of fMRI coregistration results between human experts and software solutions in patients and healthy subjects

Abstract

Functional magnetic resonance imaging (fMRI) performed by echo-planar imaging (EPI) is often highly distorted, and it is therefore necessary to coregister the functional to undistorted anatomical images, especially for clinical applications. This pilot study provides an evaluation of human and automatic coregistration results in the human motor cortex of normal and pathological brains. Ten healthy right-handed subjects and ten right-handed patients performed simple right hand movements during fMRI. A reference point chosen at a characteristic anatomical location within the fMRI sensorimotor activations was transferred to the high resolution anatomical MRI images by three human fMRI experts and by three automatic coregistration programs. The 3D distance between the median localizations of experts and programs was calculated and compared between patients and healthy subjects. Results show that fMRI localization on anatomical images was better with the experts than software in 70% of the cases and that software performance was worse for patients than healthy subjects (unpaired t-test: P = 0.040). With 45.6 mm the maximum disagreement between experts and software was quite large. The inter-rater consistency was better for the fMRI experts compared to the coregistration programs (ANOVA: P = 0.003). We conclude that results of automatic coregistration should be evaluated carefully, especially in case of clinical application.

Comparison of functional localization accuracy with different co‐registration strategies in presurgical fMRI for brain tumor patients

“…A previous study by Saad et al investigated the registration errors when using several algorithms in a group of normal subjects and found that the registration errors for both CM and AR were within a range of 5 mm. Comparing with the results in normal subjects, Gartus et al found that the AR performed worse in fMRI localization for patients with brain lesions. The disagreement between experts and software in their study had a mean of 7 mm and maximum of 14.6 mm, and the authors concluded that AR techniques should be evaluated carefully, especially in case of clinical application.…”

How much are clinical fMRI reports influenced by standard postprocessing methods? An investigation of normalization and region of interest effects in the medial temporal lobe

“…In general, differences between normalized than nonnormalized data increased with anatomical template normalization, which includes more postprocessing steps than EPI template r Postprocessing Effects on Clinical fMRI r r 1963 r normalization. To our opinion, this argues for minimizing the number of postprocessing steps with clinical data to reduce the probability for adding processing errors related to application of insufficient models [Gartus et al, 2007].…”

“…For ROI definition, the Wake Forest University PickAtlas (WFU) [Maldjian et al, 2003[Maldjian et al, , 2004 or Anatomical Automatic Labeling (AAL) atlas [TzourioMazoyer et al, 2002] are most popular [Branco et al, 2006;Dickie et al, 2008;Frings et al, 2008;Hurt et al, 2008;Ischebeck et al, 2006;Tsukiura and Cabeza, 2008;Watanabe et al, 2008]. Recently, several authors argued that such automated techniques of localizing functional activation to neuroanatomical structures might be problematic [Devlin and Poldrack, 2007;Fadiga, 2007;Gartus et al, 2007;Geissler et al, 2005;Hoeksma et al, 2005;Krishnan et al, 2006;Mitsis et al, 2008;Rodionov et al, 2009; Vandenbroucke et al, 2004]. For instance, Rodionov et al [2009] compared automatic ROI definition techniques for the hippocampus based on three brain atlases (Pick Atlas Brodmann areas, AAL atlas, frequency-based Hammers atlas).…”

“…The authors compared various anatomical and functional ROIs, defined for each subject, at group level or using a Talairach-like atlas. An investigation concerning functional-anatomical coregistration procedures in healthy and pathological brains found errors of centimeters with pathological brains [Gartus et al, 2007]. Clinically relevant mislocalization of activation has also been shown to arise from smoothing .…”

Landmark-free geometric methods in biological shape analysis

“…The task of finding such landmark points is usually performed manually by skilled morphometricians with extensive training. The resulting human choices can lead to error due to the variability and inconsistency of human input [20]. Many methods have been developed to circumvent this inherent limitation, either through automation of the landmark selection process or by eliminating the need to use specific point correspondence in the process of aligning the surface altogether.…”