Reliability of MRI-derived measurements of human cerebral cortical thickness: The effects of field strength, scanner upgrade and manufacturer

Han, Xiao; Jovicich, Jorge; Salat, David H.; Kouwe, André van der; Quinn, Brian T.; Czanner, Silvester; Busa, Evelina; Pacheco, Jenni; Albert, Marilyn; Killiany, Ronald J.; Maguire, R. Paul; Rosas, Diana; Makris, Nikos; Dale, Anders M.; Dickerson, Bradford C.; Fischl, Bruce

doi:10.1016/j.neuroimage.2006.02.051

Cited by 1,371 publications

(1,259 citation statements)

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“…Although it would have been of interest to explore potential differences between syndromes, we could not test for differences between syndromes independent from the effect of scanner and imaging sequence, although there is evidence showing that measurements made on different scanners are reliable 19, 30. This was due to the practical and ethical constraints of the study, where children were scanned on a 1.5T scanner at a pediatric focused site and adults on a 3T scanner at a different site.…”

Section: Discussionmentioning

confidence: 99%

Thalamic volume reduction in drug‐naive patients with new‐onset genetic generalized epilepsy

et al. 2017

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SummaryObjectivePatients with genetic generalized epilepsy (GGE) have subtle morphologic abnormalities of the brain revealed with magnetic resonance imaging (MRI), particularly in the thalamus. However, it is unclear whether morphologic abnormalities of the brain in GGE are a consequence of repeated seizures over the duration of the disease, or are a consequence of treatment with antiepileptic drugs (AEDs), or are independent of these factors. Therefore, we measured brain morphometry in a cohort of AED‐naive patients with GGE at disease onset. We hypothesize that drug‐naive patients at disease onset have gray matter changes compared to age‐matched healthy controls.MethodsWe performed quantitative measures of gray matter volume in the thalamus, putamen, caudate, pallidum, hippocampus, precuneus, prefrontal cortex, precentral cortex, and cingulate in 29 AED‐naive patients with new‐onset GGE and compared them to 32 age‐matched healthy controls. We subsequently compared the shape of any brain structures found to differ in gray matter volume between the groups.ResultsThe thalamus was the only structure to show reduced gray matter volume in AED‐naive patients with new‐onset GGE compared to healthy controls. Shape analysis revealed that the thalamus showed deflation, which was not uniformly distributed, but particularly affected a circumferential strip involving anterior, superior, posterior, and inferior regions with sparing of medial and lateral regions.SignificanceStructural abnormalities in the thalamus are present at the initial onset of GGE in AED‐naive patients, suggesting that thalamic structural abnormality is an intrinsic feature of GGE and not a consequence of AEDs or disease duration.

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Section: Discussionmentioning

confidence: 99%

Thalamic volume reduction in drug‐naive patients with new‐onset genetic generalized epilepsy

et al. 2017

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“…Furthermore, procedures to measure cortical thickness using Freesurfer have been validated against histological analysis (Rosas et al., 2002) and manual measurements (Kuperberg et al., 2003; Salat et al., 2004). Lastly, Freesurfer morphometric procedures have been demonstrated to show good test–retest reliability across scanner manufacturers and field strengths (Han et al., 2006; Reuter, Schmansky, Rosas, & Fischl, 2012). …”

Section: Methodsmentioning

confidence: 99%

Strategy‐based reasoning training modulates cortical thickness and resting‐state functional connectivity in adults with chronic traumatic brain injury

et al. 2017

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IntroductionPrior studies have demonstrated training‐induced changes in the healthy adult brain. Yet, it remains unclear how the injured brain responds to cognitive training months‐to‐years after injury.MethodsSixty individuals with chronic traumatic brain injury (TBI) were randomized into either strategy‐based (N = 31) or knowledge‐based (N = 29) training for 8 weeks. We measured cortical thickness and resting‐state functional connectivity (rsFC) before training, immediately posttraining, and 3 months posttraining.ResultsRelative to the knowledge‐based training group, the cortical thickness of the strategy‐based training group showed diverse temporal patterns of changes over multiple brain regions (p vertex < .05, p cluster < .05): (1) increases followed by decreases, (2) monotonic increases, and (3) monotonic decreases. However, network‐based statistics (NBS) analysis of rsFC among these regions revealed that the strategy‐based training group induced only monotonic increases in connectivity, relative to the knowledge‐based training group (|Z| > 1.96, pNBS < 0.05). Complementing the rsFC results, the strategy‐based training group yielded monotonic improvement in scores for the trail‐making test (p < .05). Analyses of brain–behavior relationships revealed that improvement in trail‐making scores were associated with training‐induced changes in cortical thickness (p vertex < .05, p cluster < .05) and rsFC (p vertex < .05, p cluster < .005) within the strategy‐based training group.ConclusionsThese findings suggest that training‐induced brain plasticity continues through chronic phases of TBI and that brain connectivity and cortical thickness may serve as markers of plasticity.

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“…The model incorporates age, sex, estimated total intracranial volume, magnetic field strength and scanner vendor information to estimate subject‐specific regional cortical thickness averages. Age, but also extrinsic factors, such as field strength and scanner platform, may affect cortical thickness estimates and are, therefore, important to take into account (Govindarajan, Freeman, Cai, Rahbar, & Narayana, 2014; Han et al, 2006; Lusebrink, Wollrab, & Speck, 2013; Potvin et al, 2017). To quantify the accuracy, we computed the Euclidean distance for each region between the normative data and the average cortical thickness derived from either the original or corrected data across all subjects.…”

Section: Discussionmentioning

confidence: 99%

“…However, determination of cortical thickness based on MRI data has been criticized. The variation of myelin density across the cortical mantle, but also errors in T 1 quantification or MRI acquisition biases can result in reduced contrast between GM, WM, and CSF and, as a result, in inaccurate determination of cortical thickness (Han et al, 2006; Zilles & Amunts, 2015). Several software packages, for example, FreeSurfer (Dale, Fischl, & Sereno, 1999), FMRIB's software library (FSL; Smith et al, 2004), Statistical Parametric Mapping (SPM; Ashburner, 2009), and CBS High‐Res Brain Processing tools (Bazin et al, 2014), have been developed to automatically classify different tissue classes based on image‐specific criteria using varying segmentation algorithms, hereby putting a large emphasis on bias field removal.…”

Section: Introductionmentioning

confidence: 99%

The impact of correction on MP2RAGE cortical T₁ and apparent cortical thickness at 7T

Haast

Ivanov

Uludağ

2018

Human Brain Mapping

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Determination of cortical thickness using MRI has often been criticized due to the presence of various error sources. Specifically, anatomical MRI relying on T1 contrast may be unreliable due to spatially variable image contrast between gray matter (GM), white matter (WM) and cerebrospinal fluid (CSF). Especially at ultra‐high field (≥ 7T) MRI, transmit and receive B1‐related image inhomogeneities can hamper correct classification of tissue types. In the current paper, we demonstrate that residual normalB1+ (transmit) inhomogeneities in the T1‐weighted and quantitative T1 images using the MP2RAGE sequence at 7T lead to biases in cortical thickness measurements. As expected, post‐hoc correction for the spatially varying normalB1+ profile reduced the apparent T1 values across the cortex in regions with low normalB1+, and slightly increased apparent T1 in regions with high normalB1+. As a result, improved contrast‐to‐noise ratio both at the GM‐CSF and GM‐WM boundaries can be observed leading to more accurate surface reconstructions and cortical thickness estimates. Overall, the changes in cortical thickness ranged between a 5% decrease to a 70% increase after normalB1+ correction, reducing the variance of cortical thickness values across the brain dramatically and increasing the comparability with normative data. More specifically, the cortical thickness estimates increased in regions characterized by a strong decrease of apparent T1 after normalB1+ correction in regions with low normalB1+ due to improved detection of the pial surface. The current results suggest that cortical thickness can be more accurately determined using MP2RAGE data at 7T if normalB1+ inhomogeneities are accounted for.

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Reliability of MRI-derived measurements of human cerebral cortical thickness: The effects of field strength, scanner upgrade and manufacturer

Cited by 1,371 publications

References 41 publications

Thalamic volume reduction in drug‐naive patients with new‐onset genetic generalized epilepsy

Thalamic volume reduction in drug‐naive patients with new‐onset genetic generalized epilepsy

Strategy‐based reasoning training modulates cortical thickness and resting‐state functional connectivity in adults with chronic traumatic brain injury

The impact of correction on MP2RAGE cortical T₁ and apparent cortical thickness at 7T

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Reliability of MRI-derived measurements of human cerebral cortical thickness: The effects of field strength, scanner upgrade and manufacturer

Cited by 1,371 publications

References 41 publications

Thalamic volume reduction in drug‐naive patients with new‐onset genetic generalized epilepsy

Thalamic volume reduction in drug‐naive patients with new‐onset genetic generalized epilepsy

Strategy‐based reasoning training modulates cortical thickness and resting‐state functional connectivity in adults with chronic traumatic brain injury

The impact of correction on MP2RAGE cortical T1 and apparent cortical thickness at 7T

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The impact of correction on MP2RAGE cortical T₁ and apparent cortical thickness at 7T