Dataset Information

Tract specific reproducibility of tractography based morphology and diffusion metrics.

ABSTRACT:

Introduction

The reproducibility of tractography is important to determine its sensitivity to pathological abnormalities. The reproducibility of tract morphology has not yet been systematically studied and the recently developed tractography contrast Tract Density Imaging (TDI) has not yet been assessed at the tract specific level.

Materials and methods

Diffusion tensor imaging (DTI) and probabilistic constrained spherical deconvolution (CSD) tractography are performed twice in 9 healthy subjects. Tractography is based on common space seed and target regions and performed for several major white matter tracts. Tractograms are converted to tract segmentations and inter-session reproducibility of tract morphology is assessed using Dice similarity coefficient (DSC). The coefficient of variation (COV) and intraclass correlation coefficient (ICC) are calculated of the following tract metrics: fractional anisotropy (FA), apparent diffusion coefficient (ADC), volume, and TDI. Analyses are performed both for proximal (deep white matter) and extended (including subcortical white matter) tract segmentations.

Results

Proximal DSC values were 0.70-0.92. DSC values were 5-10% lower in extended compared to proximal segmentations. COV/ICC values of FA, ADC, volume and TDI were 1-4%/0.65-0.94, 2-4%/0.62-0.94, 3-22%/0.53-0.96 and 8-31%/0.48-0.70, respectively, with the lower COV and higher ICC values found in the proximal segmentations.

Conclusion

For all investigated metrics, reproducibility depended on the segmented tract. FA and ADC had relatively low COV and relatively high ICC, indicating clinical potential. Volume had higher COV but its moderate to high ICC values in most tracts still suggest subject-differentiating power. Tract TDI had high COV and relatively low ICC, which reflects unfavorable reproducibility.

SUBMITTER: Besseling RM

PROVIDER: S-EPMC3317780 | biostudies-literature | 2012

REPOSITORIES: biostudies-literature

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Publications

Tract specific reproducibility of tractography based morphology and diffusion metrics.

Besseling René M H RM Jansen Jacobus F A JF Overvliet Geke M GM Vaessen Maarten J MJ Braakman Hilde M H HM Hofman Paul A M PA Aldenkamp Albert P AP Backes Walter H WH

PloS one 20120402 4

<h4>Introduction</h4>The reproducibility of tractography is important to determine its sensitivity to pathological abnormalities. The reproducibility of tract morphology has not yet been systematically studied and the recently developed tractography contrast Tract Density Imaging (TDI) has not yet been assessed at the tract specific level.<h4>Materials and methods</h4>Diffusion tensor imaging (DTI) and probabilistic constrained spherical deconvolution (CSD) tractography are performed twice in 9 ...[more]

PMID: 22485157

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Project description:BackgroundDiffusion tensor imaging (DTI) has been applied in the lumbar and sacral nerves in vivo, but information about the reproducibility of this method is needed before DTI can be used reliably in clinical practice across centers.PurposeIn this multicenter study the reproducibility of DTI of the lumbosacral nerves in healthy volunteers was investigated.Study typeProspective control series.SubjectsTwenty healthy subjects.Field strength/sequence3T MRI. 3D turbo spin echo, and 3.0 mm isotropic DTI scan.AssessmentThe DTI scan was performed three times (twice in the same session, intrascan reproducibility, and once after an hour, interscan reproducibility). At site 2, 1 week later, the protocol was repeated (interweek reproducibility). Fiber tractography (FT) of the lumbar and sacral nerves (L3-S2) was performed to obtain values for fractional anisotropy, mean, axial, and radial diffusivity.Statistical testsReproducibility was determined using the intraclass correlation coefficient (ICC), and power calculations were performed.ResultsFT was successful and reproducible in all datasets. ICCs for all diffusion parameters were high for intrascan (ranging from 0.70-0.85), intermediate for interscan (ranging from 0.61-0.73), and interweek reliability (ranging from 0.58-0.62). There were small but significant differences between the interweek diffusivity values (P < 0.0005). Depending on the effect size, nerve location, and parameter of interest, power calculations showed that sample sizes between 10 and 232 subjects are needed for cross-sectional studies.Data conclusionWe found that DTI and FT of the lumbosacral nerves have intermediate to high reproducibility within and between scans. Based on these results, 10-58 subjects are needed to find a 10% change in parameters in cross-sectional studies of the lumbar and sacral nerves. The small significant differences of the interweek comparison suggest that results from longitudinal studies need to be interpreted carefully, since small differences may also be caused by factors other than disease progression or therapeutic effects.Level of evidence1 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2018;48:951-963.

Project description:Abstract Along tract statistics enables white matter characterization using various diffusion MRI metrics. These diffusion models reveal detailed insights into white matter microstructural changes with development, pathology and function. Here, we aim at assessing the clinical utility of diffusion MRI metrics along the corticospinal tract, investigating whether motor glioma patients can be classified with respect to their motor status. We retrospectively included 116 brain tumour patients suffering from either left or right supratentorial, unilateral World Health Organization Grades II, III and IV gliomas with a mean age of 53.51 ± 16.32 years. Around 37% of patients presented with preoperative motor function deficits according to the Medical Research Council scale. At group level comparison, the highest non-overlapping diffusion MRI differences were detected in the superior portion of the tracts’ profiles. Fractional anisotropy and fibre density decrease, apparent diffusion coefficient axial diffusivity and radial diffusivity increase. To predict motor deficits, we developed a method based on a support vector machine using histogram-based features of diffusion MRI tract profiles (e.g. mean, standard deviation, kurtosis and skewness), following a recursive feature elimination method. Our model achieved high performance (74% sensitivity, 75% specificity, 74% overall accuracy and 77% area under the curve). We found that apparent diffusion coefficient, fractional anisotropy and radial diffusivity contributed more than other features to the model. Incorporating the patient demographics and clinical features such as age, tumour World Health Organization grade, tumour location, gender and resting motor threshold did not affect the model’s performance, revealing that these features were not as effective as microstructural measures. These results shed light on the potential patterns of tumour-related microstructural white matter changes in the prediction of functional deficits. Shams et al. report that glioma patients’ motor status is predicted accurately by diffusion MRI metrics along the corticospinal tract based on support vector machine method, reaching an overall accuracy of 77%. They show that these metrics are more effective than demographic and clinical variables. Graphical Abstract Graphical abstract

Dataset Information

Tract specific reproducibility of tractography based morphology and diffusion metrics.

Introduction

Materials and methods

Results

Conclusion

Publications

Tract specific reproducibility of tractography based morphology and diffusion metrics.

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