Validation of FreeSurfer-Estimated Brain Cortical Thickness: Comparison with Histologic Measurements (original) (raw)
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Measurement of Cortical Thickness Using an Automated 3-D Algorithm: A Validation Study
NeuroImage, 2001
A validation study was conducted to assess the accuracy of the algorithm developed by MacDonald et al. (1999) for measuring cortical thickness. This algorithm automatically determines the cortical thickness by 3-D extraction of the inner and outer surfaces of the cerebral cortex from an MRI scan. A manual method of tagging the grey-csf and grey-white interface was used on 20 regions (10 cortical areas found in each hemisphere) in 40 MRIs of the brain to validate the algorithm. The regions were chosen throughout the cortex to get broad assessment of the algorithm's performance. Accuracy was determined by an anatomist tagging the csf-grey and grey-white borders of selected gyri and by allowing the algorithm to determine the csf-grey and grey-white borders and the corresponding cortical thickness of the same region. Results from the manual and automatic methods were statistically compared using overall ANOVA and paired t tests for each region. The manual and automatic methods were in agreement for all but 4 of the 20 regions tested. The four regions where there were significant differences between the two methods were the insula left and right, the right cuneus, and the right parahippocampus. We conclude that the automatic algorithm is valid for most of the cortex and provides a viable alternative to manual methods of determining cortical thickness in vivo. However, caution should be taken when measuring the regions mentioned previously where the results of the algorithm can be biased by surrounding grey structures.
Volume Estimation of the Thalamus Using Freesurfer and Stereology: Consistency between Methods
Neuroinformatics, 2012
Freely available automated MR image analysis techniques are being increasingly used to investigate neuroanatomical abnormalities in patients with neurological disorders. It is important to assess the specificity and validity of automated measurements of structure volumes with respect to reliable manual methods that rely on human anatomical expertise. The thalamus is widely investigated in many neurological and neuropsychiatric disorders using MRI, but thalamic volumes are notoriously difficult to quantify given the poor between-tissue contrast at the thalamic gray-white matter interface. In the present study we investigated the reliability of automatically determined thalamic volume measurements obtained using FreeSurfer software with respect to a manual stereological technique on 3D T1-weighted MR images obtained from a 3 T MR system. Further to demonstrating impressive consistency between stereological and FreeSurfer volume estimates of the thalamus in healthy subjects and neurological patients, we demonstrate that the extent of agreeability between stereology and FreeSurfer is equal to the agreeability between two human anatomists estimating thalamic volume using stereological methods. Using patients with juvenile myoclonic epilepsy as a model for thalamic atrophy, we also show that both automated and manual methods provide very similar ratios of thalamic volume loss in patients. This work promotes the use of FreeSurfer for reliable estimation of global volume in healthy and diseased thalami.
A comparison of voxel and surface based cortical thickness estimation methods
NeuroImage, 2011
Cortical thickness estimation performed in-vivo via magnetic resonance imaging is an important technique for the diagnosis and understanding of the progression of neurodegenerative diseases. Currently, two different computational paradigms exist, with methods generally classified as either surface or voxel-based. This paper provides a much needed comparison of the surface-based method FreeSurfer and two voxel-based methods using clinical data. We test the effects of computing regional statistics using two different atlases and demonstrate that this makes a significant difference to the cortical thickness results. We assess reproducibility, and show that FreeSurfer has a regional standard deviation of thickness difference on same day scans that is significantly lower than either a Laplacian or Registration based method and discuss the trade off between reproducibility and segmentation accuracy caused by bending energy constraints. We demonstrate that voxel-based methods can detect similar patterns of group-wise differences as well as FreeSurfer in typical applications such as producing group-wise maps of statistically significant thickness change, but that regional statistics can vary between methods. We use a Support Vector Machine to classify patients against controls and did not find statistically significantly different results with voxel based methods compared to FreeSurfer. Finally we assessed longitudinal performance and concluded that currently FreeSurfer provides the most plausible measure of change over time, with further work required for voxel based methods.
Cortical thickness asymmetries and surgical outcome in neocortical epilepsy
Journal of the neurological sciences, 2016
We evaluated if cortical thickness measures were associated with surgical outcome in patients with non-lesional neocortical epilepsy. Twenty-one young patients (age: 2.4-19.7years) with epilepsy of neocortical origin and normal MRI underwent two-stage epilepsy surgery with subdural EEG monitoring. Cortical thickness was measured on presurgical volumetric MRI using the FreeSurfer software. The prognostic value of hemispheric and lobar/regional cortical thickness measures for 1-year and 2-year post-surgical seizure outcome has been analyzed. At one-year follow-up, 14 patients (67%) were seizure-free. Hemispheric and frontal lobe cortical thickness showed no/minimal asymmetry in seizure-free patients but thinner cortex ipsilateral to the seizure focus in those with recurrent seizures (p=0.02). More robust differences were found in patients≥6years of age (p=0.006 for frontal asymmetries), whose cortical thickness asymmetries remained prognostic for 2-year post-surgical outcome (p=0.007)...
Joint analysis of area and thickness as a replacement for the analysis of cortical volume
2016
Cortical surface area is an increasingly used brain morphology metric that is ontogenetically and phylogenetically distinct from cortical thickness and offers a separate index of neurodevelopment and disease. However, the various existing methods for assessment of cortical surface area from magnetic resonance images have never been systematically compared. We show that the surface area method implemented in FreeSurfer corresponds closely to the exact, but computationally more demanding, mass-conservative (pyc-nophylactic) method, provided that images are smoothed. Thus, the data produced by this method can be interpreted as estimates of cortical surface area, as opposed to areal expansion. In addition, focusing on the joint analysis of thickness and area, we compare an improved, analytic method for measuring cortical volume to a permutation based non-parametric combination (NPC) method. We use the methods to analyse area, thickness and volume in young adults born preterm with very l...
Cross-sectional analysis using voxel or surface based cortical thickness methods: A comparison study
2011 IEEE International Symposium on Biomedical Imaging: From Nano to Macro, 2011
Cortical thickness estimation performed in-vivo via magnetic resonance imaging is an important technique for the diagnosis and understanding of the progression of neurodegenerative diseases. Currently, two different computational paradigms exist, with methods generally classified as either surface or voxel-based. This paper provides a much needed comparison of the surface-based method FreeSurfer and two voxel-based methods using clinical data. We demonstrate that voxel-based methods can detect similar patterns of group-wise differences as well as FreeSurfer, where the lack of deformable model constraints may provide more sensitivity but with a resulting trade-off in reproducibility.
Cereb Cortex., 2017
Cortical surface area is an increasingly used brain morphology metric that is ontogenetically and phylogenetically distinct from cortical thickness and offers a separate index of neurodevelopment and disease. However, the various existing methods for assessment of cortical surface area from magnetic resonance images have never been systematically compared. We show that the surface area method implemented in FreeSurfer corresponds closely to the exact, but computationally more demanding, mass-conservative (pycnophylactic) method, provided that images are smoothed. Thus, the data produced by this method can be interpreted as estimates of cortical surface area, as opposed to areal expansion. In addition, focusing on the joint analysis of thickness and area, we compare an improved, analytic method for measuring cortical volume to a permutation-based nonparametric combination (NPC) method. We use the methods to analyze area, thickness and volume in young adults born preterm with very low birth weight, and show that NPC analysis is a more sensitive option for studying joint effects on area and thickness, giving equal weight to variation in both of these 2 morphological features.
Neuroimage, 2006
In vivo MRI-derived measurements of human cerebral cortex thickness are providing novel insights into normal and abnormal neuroanatomy, but little is known about their reliability. We investigated how the reliability of cortical thickness measurements is affected by MRI instrument-related factors, including scanner field strength, manufacturer, upgrade and pulse sequence. Several data processing factors were also studied. Two test -retest data sets were analyzed: 1) 15 healthy older subjects scanned four times at 2-week intervals on three scanners; 2) 5 subjects scanned before and after a major scanner upgrade. Within-scanner variability of global cortical thickness measurements was <0.03 mm, and the point-wise standard deviation of measurement error was approximately 0.12 mm. Variability was 0.15 mm and 0.17 mm in average, respectively, for cross-scanner (Siemens/GE) and cross-field strength (1.5 T/3 T) comparisons. Scanner upgrade did not increase variability nor introduce bias. Measurements across field strength, however, were slightly biased (thicker at 3 T). The number of (single vs. multiple averaged) acquisitions had a negligible effect on reliability, but the use of a different pulse sequence had a larger impact, as did different parameters employed in data processing. Sample size estimates indicate that regional cortical thickness difference of 0.2 mm between two different groups could be identified with as few as 7 subjects per group, and a difference of 0.1 mm could be detected with 26 subjects per group. These results demonstrate that MRI-derived cortical thickness measures are highly reliable when MRI instrument and data processing factors are controlled but that it is important to consider these factors in the design of multi-site or longitudinal studies, such as clinical drug trials. D
In vivo MRI-derived measurements of human cerebral cortex thickness are providing novel insights into normal and abnormal neuroanatomy, but little is known about their reliability. We investigated how the reliability of cortical thickness measurements is affected by MRI instrument-related factors, including scanner field strength, manufacturer, upgrade and pulse sequence. Several data processing factors were also studied. Two test -retest data sets were analyzed: 1) 15 healthy older subjects scanned four times at 2-week intervals on three scanners; 2) 5 subjects scanned before and after a major scanner upgrade. Within-scanner variability of global cortical thickness measurements was <0.03 mm, and the point-wise standard deviation of measurement error was approximately 0.12 mm. Variability was 0.15 mm and 0.17 mm in average, respectively, for cross-scanner (Siemens/GE) and cross-field strength (1.5 T/3 T) comparisons. Scanner upgrade did not increase variability nor introduce bias. Measurements across field strength, however, were slightly biased (thicker at 3 T). The number of (single vs. multiple averaged) acquisitions had a negligible effect on reliability, but the use of a different pulse sequence had a larger impact, as did different parameters employed in data processing. Sample size estimates indicate that regional cortical thickness difference of 0.2 mm between two different groups could be identified with as few as 7 subjects per group, and a difference of 0.1 mm could be detected with 26 subjects per group. These results demonstrate that MRI-derived cortical thickness measures are highly reliable when MRI instrument and data processing factors are controlled but that it is important to consider these factors in the design of multi-site or longitudinal studies, such as clinical drug trials. D
Basic and Clinical Neuroscience Journal, 2022
In this study, we intend to determine the correlation between the thickness of the cerebral cortex and the severity of the cognitive disorder in Alzheimer disease (AD). Methods: A total of 20 (14 women and 6 men) patients diagnosed with AD with a Mean age of 72.95 years, and 10 (7 women and 3 men) cognitively normal (CN) subjects with a Mean age of 70.50 years were included in the study. Of the AD patient and CN subjects, 70% were female, and 30% were male. All individuals underwent 1.5 T Magnetic resonance imaging (MRI). The MRI scanning protocol included 3D MPRAGE (3D-T1W) sequence. All images were analyzed using Freesurfer v5.3, and then the brain cortical thickness in 7 cortical areas (inferior temporal, middle temporal, superior temporal, parahippocampal, pars triangularis, rostral middle frontal, and superior frontal) was calculated. Results: The analysis of covariance (ANCOVA) was conducted to compare the mean thickness of each region between the patient and the control group. There was a significant difference in the mean cortical thickness in all regions. In all cases, the mean cortical thickness in CN subjects was greater than in AD patients. However, the mean thickness of pars triangularis left hand in CN subjects was not significantly greater than that in AD patients. The receiver operating characteristic system (ROC) was designed to evaluate the predictive power of the patients and the healthy people. We have selected a thousand cutoff points from 1.5 to 3.5 mm for cortical thickness. When the cutoff points were within 2.276878-2.299680 mm in the left hemisphere, Youden's index was maximum. The sensitivity and specificity, in this case, were 80%. Also, when the cutoff points were within the range of 2.263278-2.282278 mm in the right hemisphere, the sensitivity and specificity were 90% and 80%, respectively. Conclusion: This study demonstrates the importance of quantifying the cortical thickness changes in the early diagnosis of AD. In addition, examining the pattern of changes and quantifying the reduction in the thickness of the cortex is a crucial tool for displaying the local and global atrophy of the brain. Also, this pattern can be used as an alternative marker for the diagnosis of dementia. Finally, to the best of our knowledge, our study is the first to report finding on the cortical thickness that would help the clinician have a better differential diagnosis. Also, this study has checked the possibility of early diagnosis of the disease.