Effects of interpolation methods in spatial normalization of diffusion tensor imaging data on group comparison of fractional anisotropy.
نویسندگان
چکیده
This study investigated the effects on the measurement of fractional anisotropy (FA) during interpolation of diffusion tensor images in spatial normalization, which is required for voxel-based statistics. Diffusion tensor imaging data were obtained from nine male patients with attention deficit/hyperactivity disorder and nine age-matched control subjects. Regions of interest were selected from the genu of corpus callosum (GCC) and the right anterior corona radiata (RACR), with FA values measured before and after spatial normalization using two interpolation algorithms: linear and rotationally linear. Computer simulations were performed to verify the experimental findings. Between-group difference in FA was observed in the GCC and RACR before spatial normalization (P<.00001). Interpolation reduced the measured FA values significantly (P<.00001 for both algorithms) but did not affect the group difference in the GCC. For the RACR, the between-group difference vanished (P=.968) after linear interpolation but was relatively unaffected by using rotationally linear interpolation (P=.00001). FA histogram analysis and computer simulations confirmed these findings. This work suggests that caution should be exercised in voxel-based group comparisons as spatial normalization may affect the FA value in nonnegligible degrees, particularly in brain areas with predominantly crossing fibers.
منابع مشابه
Evaluation of Soft Tissue Sarcoma Tumors Electrical Conductivity Anisotropy Using Diffusion Tensor Imaging for Numerical Modeling on Electroporation
Introduction: There is many ways to assessing the electrical conductivity anisotropyof a tumor. Applying the values of tissue electrical conductivity anisotropyis crucial in numerical modeling of the electric and thermal field distribution in electroporationtreatments. This study aims to calculate the tissues electrical conductivityanisotropy in patients with sarcoma tumors using diffusion tens...
متن کاملEvaluation of Diffusion Anisotropy and Diffusion Shape in Grading of Glial Tumors
Background: The most common primary tumors of brain are gliomas. Grading of tumor is vital for designing proper treatment plans. The gold standard choice to determine the grade of glial tumor is biopsy which is an invasive method.Objective: In this study, we try to investigate the role of fractional anisotropy (diffusion anisotropy) and linear anisotropy ...
متن کاملSpatial normalization of diffusion models and tensor analysis
Diffusion tensor imaging provides the ability to study white matter connectivity and integrity noninvasively. The information contained in the diffusion tensors is very complex. Therefore a simple way of dealing with tensors is to compute rotationally invariant scalar quantities. These scalar indices have been used to perform population studies between controls and patients with neurological an...
متن کاملCollaborative patch-based super-resolution for diffusion-weighted images
In this paper, a new single image acquisition super-resolution method is proposed to increase image resolution of diffusion weighted (DW) images. Based on a nonlocal patch-based strategy, the proposed method uses a non-diffusion image (b0) to constrain the reconstruction of DW images. An extensive validation is presented with a gold standard built on averaging 10 high-resolution DW acquisitions...
متن کاملDifferentiation of Edematous, Tumoral and Normal Areas of Brain Using Diffusion Tensor and Neurite Orientation Dispersion and Density Imaging
Background: Presurigical planning for glioma tumor resection and radiotherapy treatment require proper delineation of tumoral and peritumoral areas of brain. Diffusion tensor imaging (DTI) is the most common mathematical model applied for diffusion weighted MRI data. Neurite orientation dispersion and density imaging (NODDI) is another mathematical model for DWI data modeling.Objective: We stud...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید
ثبت ناماگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید
ورودعنوان ژورنال:
- Magnetic resonance imaging
دوره 27 5 شماره
صفحات -
تاریخ انتشار 2009