Reliability of the freehand region-of-interest method in quantitative cerebral diffusion tensor imaging (original) (raw)
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BMC Medical Imaging, 2012
Background: Diffusion tensor imaging (DTI) is increasingly used in various diseases as a clinical tool for assessing the integrity of the brain's white matter. Reduced fractional anisotropy (FA) and an increased apparent diffusion coefficient (ADC) are nonspecific findings in most pathological processes affecting the brain's parenchyma. At present, there is no gold standard for validating diffusion measures, which are dependent on the scanning protocols, methods of the softwares and observers. Therefore, the normal variation and repeatability effects on commonly-derived measures should be carefully examined. Methods: Thirty healthy volunteers (mean age 37.8 years, SD 11.4) underwent DTI of the brain with 3T MRI. Region-of-interest (ROI) -based measurements were calculated at eleven anatomical locations in the pyramidal tracts, corpus callosum and frontobasal area. Two ROI-based methods, the circular method (CM) and the freehand method (FM), were compared. Both methods were also compared by performing measurements on a DTI phantom. The intra-and inter-observer variability (coefficient of variation, or CV%) and repeatability (intra-class correlation coefficient, or ICC) were assessed for FA and ADC values obtained using both ROI methods.
Korean Journal of Radiology
Objective: To evaluate the inter-vendor and inter-session reliability of diffusion tensor imaging (DTI) and relevant parameters. Materials and Methods: This prospective study included 10 healthy subjects (5 women and 5 men; age range, 25−33 years). Each subject was scanned twice using 3T magnetic resonance scanners from three different vendors at two different sites. A voxel-wise statistical analysis of diffusion data was performed using Tract-Based Spatial Statistics. Fractional anisotropy (FA), mean diffusivity (MD), and radial diffusivity (RD) values were calculated for each brain voxel using FMRIB's Diffusion Toolbox. Results: A repeated measures analysis of variance revealed that there were no significant differences in FA values across the vendors or between sessions; however, there were significant differences in MD values between the vendors (p = 0.020). Although there were no significant differences in inter-session MD and inter-session/inter-vendor RD values, a significant group x factor interaction revealed differences in MD and RD values between the 1st and 2nd sessions conducted by the vendors (p = 0.004 and 0.006, respectively). Conclusion: Although FA values exhibited good inter-vendor and inter-session reliability, MD and RD values did not show consistent results. Researchers using DTI should be aware of these limitations, especially when implementing DTI in multicenter studies.
Diffusion tensor imaging (DTI) of in-vivo human brain provides insights into white matter anatomical connectivity, but little is known about measurement difference biases and reliability of data obtained with last generation high field scanners (N3 T) as function of MRI acquisition and analyses variables. Here we assess the impact of acquisition (voxel size: 1.8 × 1.8 × 1.8, 2 × 2 × 2 and 2.5 × 2.5 × 2.5 mm 3 , b-value: 700, 1000 and 1300 s/mm 2 ) and analysis variables (within-session averaging and co-registration methods) on biases and test-retest reproducibility of some common tensor derived quantities like fractional anisotropy (FA), mean diffusivity (MD), axial and radial diffusivity in a group of healthy subjects at 4 T in three regions: arcuate fasciculus, corpus callosum and cingulum. Averaging effects are also evaluated on a full-brain voxel based approach. The main results are: i) group FA and MD reproducibility errors across scan sessions are on average double of those found in within-session repetitions (≈1.3 %), regardless of acquisition protocol and region; ii) within-session averaging of two DTI acquisitions does not improve reproducibility of any of the quantities across sessions at the group level, regardless of acquisition protocol; iii) increasing voxel size biased MD, axial and radial diffusivities to higher values and FA to lower values; iv) increasing b-value biased all quantities to lower values, axial diffusivity showing the strongest effects; v) the two co-registration methods evaluated gave similar bias and reproducibility results. Altogether these results show that reproducibility of FA and MD is comparable to that found at lower fields, not significantly dependent on pre-processing and acquisition protocol manipulations, but that the specific choice of acquisition parameters can significantly bias the group measures of FA, MD, axial and radial diffusivities.
Possible confounding factors on cerebral diffusion tensor imaging measurements
Acta radiologica open, 2015
Diffusion tensor imaging (DTI) is prone to numerous systemic confounding factors that should be acknowledged to avoid false conclusions. To investigate the possible effects of age, gender, smoking, alcohol consumption, and education on cerebral DTI parameters in a generally healthy homogenous sample with no neurological or psychiatric diseases. Forty (n = 40) subjects (mean age, 40.3 years; SD, 12.3) underwent brain DTI with 3 T magnetic resonance imaging (MRI). At enrolment, all the subjects were interviewed with respect to general health, education, history of smoking, and alcohol consumption. Studied DTI parameters included: (i) fractional anisotropy (FA); and (ii) apparent diffusion coefficient (ADC). Region-of-interest (ROI)-based measurements were estimated at 13 anatomical locations bilaterally on the axial images, except for the corpus callosum in which the ROIs were placed on the sagittal images. Circular ROI measurements were mainly used. Freehand ROI method was used with ...
NeuroImage, 2014
Brain diffusion tensor imaging Reproducibility Reliability Tract-based spatial statistics Multi-center Multi-site MRI Large-scale longitudinal neuroimaging studies with diffusion imaging techniques are necessary to test and validate models of white matter neurophysiological processes that change in time, both in healthy and diseased brains. The predictive power of such longitudinal models will always be limited by the reproducibility of repeated measures acquired during different sessions. At present, there is limited quantitative knowledge about the across-session reproducibility of standard diffusion metrics in 3 T multi-centric studies on subjects in stable conditions, in particular when using tract based spatial statistics and with elderly people. In this study we implemented a multi-site brain diffusion protocol in 10 clinical 3 T MRI sites distributed across 4 countries in Europe (Italy, Germany, France and Greece) using vendor provided sequences from Siemens (Allegra, Trio Tim, Verio, Skyra, Biograph mMR), Philips (Achieva) and GE (HDxt) scanners. We acquired DTI data (2 × 2 × 2 mm 3 , b = 700 s/mm 2 , 5 b0 and 30 diffusion weighted volumes) of a group of healthy stable elderly subjects (5 subjects per site) in two separate sessions at least a week apart. For each subject and session four scalar diffusion metrics were considered: fractional anisotropy (FA), mean diffusivity (MD), radial diffusivity (RD) and axial (AD) diffusivity. The diffusion metrics from multiple subjects and sessions at each site were aligned to their common white matter skeleton using tract-based spatial statistics. The reproducibility at each MRI site was examined by looking at group averages of absolute changes relative to the mean (%) on various parameters: i) reproducibility of the signal-to-noise ratio (SNR) of the b0 images in centrum semiovale, ii) full brain test-retest differences of the diffusion metric maps on the white matter skeleton, iii) reproducibility of the diffusion metrics on atlas-based white matter ROIs on the white matter skeleton. Despite the differences of MRI scanner configurations across sites (vendors, models, RF coils and acquisition sequences) we found good and consistent test-retest reproducibility. White matter b0 SNR reproducibility was on average 7 ± 1% with no significant MRI site effects. Whole brain analysis resulted in no significant test-retest differences at any of the sites with any of the DTI metrics. The atlas-based ROI analysis showed that the mean reproducibility errors largely remained in the 2-4% range for FA and AD and 2-6% for MD and RD, averaged across ROIs. Our results show reproducibility values comparable to those reported in studies using a smaller number of MRI scanners, slightly different DTI protocols and mostly younger populations. We therefore show that the acquisition and analysis protocols used are appropriate for multi-site experimental scenarios.
A comprehensive reliability assessment of quantitative diffusion tensor tractography
NeuroImage, 2012
Diffusion tensor tractography is increasingly used to examine structural connectivity in the brain in various conditions, but its test-retest reliability is understudied. The main purposes of this study were to evaluate 1) the reliability of quantitative measurements of diffusion tensor tractography and 2) the effect on reliability of the number of gradient sampling directions and scan repetition. Images were acquired from ten healthy participants. Ten fiber regions of nine major fiber tracts were reconstructed and quantified using six fiber variables. Intra-and inter-session reliabilities were estimated using intraclass correlation coefficient (ICC) and coefficient of variation (CV), and compared to pinpoint major error sources. Additional pairwise comparisons were made between the reliability of images with 30 directions and NEX 2 (DTI30-2), 30 directions and NEX 1 (DTI30-1), and 15 directions and NEX 2 (DTI15-2) to determine whether increasing gradient directions and scan repetition improved reliability. Of the 60 tractography measurements, 43 showed intersession CV ≤ 10%, ICC ≥ .70, or both for DTI30-2, 40 measurements for DTI30-1, and 37 for DTI15-2. Most of the reliable measurements were associated with the tracts corpus callosum, cingulum, cerebral peduncular fibers, uncinate fasciculus, and arcuate fasciculus. These reliable measurements included factional anisotropy (FA) and mean diffusivity of all 10 fiber regions. Intersession reliability was significantly worse than intra-session reliability for FA, mean length, and tract volume measurements from DTI15-2, indicating that the combination of MRI signal variation and physiological noise/change over time was the major error source for this sequence. Increasing the number of gradient directions from 15 to 30 while controlling the scan time, significantly affected values for all six variables and reduced intersession variability for mean length and tract volume measurements. Additionally, while increasing scan repetition from 1 to 2 had no significant effect on the reliability for DTI with 30 directions, this significantly reduced the upward bias in FA values from all 10 fiber regions and fiber count, mean length, and tract volume measurements from 5-7 fiber regions. In conclusion, diffusion tensor tractography provided many measurements with high test-retest reliability across different fiber variables and various fiber tracts even for images with 15 directions (NEX 2). Increasing the number of gradient directions from 15 to 30 with equivalent scan time reduced variability whereas increasing repetition from 1 to 2 for 30-direction DTI improved the accuracy of tractography measurements.
Psychiatry Research: Neuroimaging, 2011
Diffusion tensor imaging (DTI) detects white matter damage in neuro-psychiatric disorders, but data on reliability of DTI measures across more than two scanners are still missing. In this study we assessed multicenter reproducibility of DTI acquisitions based on a physical phantom as well as brain scans across 16 scanners. In addition, we performed DTI scans in a group of 26 patients with clinically probable Alzheimer's disease (AD) and 12 healthy elderly controls at one single center. We determined the variability of fractional anisotropy (FA) measures using manually placed regions of interest as well as automated tract based spatial statistics and deformation based analysis. The coefficient of variation (CV) of FA was 6.9% for the physical phantom data. The mean CV across the multicenter brain scans was 14% for tract based statistics, and 29% for deformation based analysis. The degree of variation was higher in less organized fiber tracts. Our findings suggest that a clinical and physical phantom study involving more than two scanners is indispensable to detect potential sources of bias and to reliably estimate effect size in multicenter diagnostic trials using DTI.
Regional distribution of measurement error in diffusion tensor imaging
Psychiatry Research: Neuroimaging, 2006
The characterization of measurement error is critical in assessing the significance of diffusion tensor imaging (DTI) findings in longitudinal and cohort studies of psychiatric disorders. We studied 20 healthy volunteers each one scanned twice (average interval between scans of 51 ± 46.8 days) with a single shot echo planar DTI technique. Inter-session variability for fractional anisotropy (FA) and Trace (D) was represented as absolute variation (standard deviation within subjects: SDw), percent coefficient of variation (CV) and intra-class correlation coefficient (ICC). The values from the two sessions were compared for statistical significance with repeated measures ANOVA or a nonparametric equivalent of a paired t-test. The results show good reproducibility for both FA and Trace (CVs below 10% and ICCs at or above 0.70 in most regions of interest) and evidence of systematic global changes in Trace between scans. The regional distribution of reproducibility described here has implications for interpretation of regional findings and for rigorous pre-processing. The regional distribution of reproducibility measures was different for SDw, CV and ICC. Each one of these measures reveals complementary information that needs to be taken into consideration when performing statistical operations on groups of DTI images.
From diffusion tractography to quantitative white matter tract measures: a reproducibility study
NeuroImage, 2003
The aim of this study is to propose methods for assessing the reproducibility of diffusion tractography algorithms in future clinical studies and to show their application to the tractography algorithm developed in our unit, fast marching tractography (FMT). FMT estimates anatomical connectivity between brain regions using the information provided by diffusion tensor imaging. Three major white-matter pathways were investigated in 11 normal subjects-anterior callosal fibers, optic radiations, and pyramidal tracts. FMT was used to generate maps of connectivity metric, and regions of voxels with highest connectivity metric to an anatomically defined starting point were identified for each tract under investigation. The reproducibilities of tract-"normalized" volume (NV) and fractional anisotropy (FA) measurements were assessed over such regions. The values of tract volumes are consistent with the postmortem data. Coefficients of variation (CVs) for FA and NV ranged from 1.7 to 7.1% and from 2.2 to 18.6%, respectively. CVs were lowest in the anterior callosal fibers (range: 1.7-7.8%), followed by the optic radiations (range: 1.2-18.6%) and pyramidal tracts (range: 2.6 -15.5%), suggesting that fiber organization plays a role in determining the level of FMT reproducibility. In conclusion, these findings underline the importance of assessing the reliability of diffusion tractography before investigating white matter pathology.
Journal of Magnetic Resonance Imaging, 2015
Purpose: To evaluate how retrospective head motion correction strategies affect the estimation of scalar metrics commonly used in clinical diffusion tensor imaging (DTI) studies along with their across-session reproducibility errors. Materials and Methods: Fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity (AD), radial diffusivity (RD), and their respective across-session reproducibility errors were measured on a 4T test-retest dataset of healthy participants using five processing pipelines. These differed in: 1) the number of b0 volumes used for motion correction reference (one or five); 2) the estimations of the gradient matrix rotation (based on 6 or 12 degrees of freedom derived from coregistration); and 3) the software packages used (FSL or DTIPrep). Biases and reproducibility were evaluated in three regions of interest (ROIs) (bilateral arcuate fasciculi, cingula, and the corpus callosum) and also at the full brain level with tract based skeleton images. Results: Preprocessing choices affected DTI measures and their reproducibility. The DTIPrep pipeline exhibited higher DTI metrics: FA/MD and AD (P < 0.05) relative to FSL pipelines both at the ROI and full brain level, and lower RD estimates (P < 0.05) at the ROI level. Within FSL pipelines no such effects were found (P-values ranging between 0.25 and 0.97). The DTIPrep pipeline showed the highest number of white matter skeleton voxels, with significantly higher reproducibility (P < 0.001) relative to the other pipelines (tested on P < 0.01 uncorrected maps). Conclusion: The use of an iteratively averaged b0 image as motion correction reference (as performed by DTIPrep) affects both scalar values and improves test-retest reliability relative to the other tested pipelines. These considerations are potentially relevant for data analysis in longitudinal DTI studies.