Censoring Distances Based on Labeled Cortical Distance Maps in Cortical Morphometry

Ceyhan, Elvan; Nishino, Tomoyuki; Alexopolous, Dimitrios; Todd, Richard D.; Botteron, Kelly N.; Miller, Michael I.; Ratnanather, J. Tilak

doi:10.3389/fneur.2013.00155

Cited by 4 publications

(13 citation statements)

References 51 publications

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“…Also, the KS test will almost never be complementary for one-sided tests. Practical and theoretical aspects of pooled and censored LCDM analysis have been discussed extensively elsewhere (27, 28). In particular, Monte Carlo simulations suggest that these approaches are capable of capturing differences between diagnostic groups.…”

Section: Discussionmentioning

confidence: 99%

“…In particular, Monte Carlo simulations suggest that these approaches are capable of capturing differences between diagnostic groups. Furthermore, it is emphasized that censoring should be understood in a pointwise fashion, not as testing a whole range of LCDM distances (28). …”

Section: Discussionmentioning

confidence: 99%

“…Following Ceyhan et al (28), the pooled LCDM distances were tested at distances increasing by fixed increments of 0.01 mm. That is, for the first censoring step, pooled distances ≤0.01 mm were tested for group differences; at the second step, distances ≤0.02 mm were tested; and so forth until the maximum distance was reached (where at this last stage, censored distance analysis is equivalent to the pooled distance analysis).…”

Section: Methodsmentioning

confidence: 99%

“…In particular, the problem of within-sample dependence at each censoring step persists, but this was again shown to be negligible (28). On the other hand, censoring provides a powerful methodology that can identify at which distance values (with respect to the GM/WM surface) the potential differences start to occur.…”

Section: Methodsmentioning

confidence: 99%

“…For example, it is possible to pool the LCDM distances for each diagnostic group and perform statistical comparisons on the overall distance level for each group, rather than the individual level; further, it is possible to censor these distances to compare the diagnostic groups at specific distances from the GM/WM surface (27, 28). This is achieved by merging the distances for subjects from the same group to utilize more of the information provided in these distances.…”

Section: Introductionmentioning

confidence: 99%

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Morphometric Differences in Planum Temporale in Schizophrenia and Bipolar Disorder Revealed by Statistical Analysis of Labeled Cortical Depth Maps

et al. 2014

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Differences in cortical thickness in the lateral temporal lobe, including the planum temporale (PT), have been reported in MRI studies of schizophrenia (SCZ) and bipolar disorder (BPD) patients. Most of these studies have used a single-valued global or local measure for thickness. However, additional and complementary information can be obtained by generating labeled cortical distance maps (LCDMs), which are distances of labeled gray matter (GM) voxels from the nearest point on the GM/white matter (WM) (inner) cortical surface. Statistical analyses of pooled and censored LCDM distances reveal subtle differences in PT between SCZ and BPD groups from data generated by Ratnanather et al. (Schizophrenia Research, ). These results confirm that the left planum temporale (LPT) is more sensitive than the right PT in distinguishing between SCZ, BPD, and healthy controls. Also confirmed is a strong gender effect, with a thicker PT seen in males than in females. The differences between groups at smaller distances in the LPT revealed by pooled and censored LCDM analysis suggest that SCZ and BPD have different effects on the cortical mantle close to the GM/WM surface. This is consistent with reported subtle changes in the cortical mantle observed in post-mortem studies.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Morphometric Differences in Planum Temporale in Schizophrenia and Bipolar Disorder Revealed by Statistical Analysis of Labeled Cortical Depth Maps

et al. 2014

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Structural neuroimaging of the altered brain stemming from pediatric and adolescent hearing loss—Scientific and clinical challenges

Ratnanather

2019

WIREs Mechanisms of Disease

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There has been a spurt in structural neuroimaging studies of the effect of hearing loss on the brain. Specifically, magnetic resonance imaging (MRI) and diffusion tensor imaging (DTI) technologies provide an opportunity to quantify changes in gray and white matter structures at the macroscopic scale. To date, there have been 32 MRI and 23 DTI studies that have analyzed structural differences accruing from pre-or peri-lingual pediatric hearing loss with congenital or early onset etiology and postlingual hearing loss in pre-to-late adolescence. Additionally, there have been 15 prospective clinical structural neuroimaging studies of children and adolescents being evaluated for cochlear implants. The results of the 70 studies are summarized in two figures and three tables. Plastic changes in the brain are seen to be multifocal rather than diffuse, that is, differences are consistent across regions implicated in the hearing, speech and language networks regardless of modes of communication and amplification. Structures in that play an important role in cognition are affected to a lesser extent. A limitation of these studies is the emphasis on volumetric measures and on homogeneous groups of subjects with hearing loss.It is suggested that additional measures of morphometry and connectivity could contribute to a greater understanding of the effect of hearing loss on the brain. Then an interpretation of the observed macroscopic structural differences is given. This is followed by discussion of how structural imaging can be combined with functional imaging to provide biomarkers for longitudinal tracking of amplification.

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Analysis of cortical morphometric variability using labeled cortical distance maps

Ceyhan

Nishino

Botteron

et al. 2017

Statistics and Its Interface

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Morphometric (i.e., shape and size) differences in the anatomy of cortical structures are associated with neuro-developmental and neuropsychiatric disorders. Such differences can be quantized and detected by a powerful tool called Labeled Cortical Distance Map (LCDM). The LCDM method provides distances of labeled gray matter (GM) voxels from the GM/white matter (WM) surface for specific cortical structures (or tissues). Here we describe a method to analyze morphometric variability in the particular tissue using LCDM distances. To extract more of the information provided by LCDM distances, we perform pooling and censoring of LCDM distances. In particular, we employ Brown-Forsythe (BF) test of homogeneity of variance (HOV) on the LCDM distances. HOV analysis of pooled distances provides an overall analysis of morphometric variability of the LCDMs due to the disease in question, while the HOV analysis of censored distances suggests the location(s) of significant variation in these differences (i.e., at which distance from the GM/WM surface the morphometric variability starts to be significant). We also check for the influence of assumption violations on the HOV analysis of LCDM distances. In particular, we demonstrate that BF HOV test is robust to assumption violations such as the non-normality and within sample dependence of the residuals from the median for pooled and censored distances and are robust to data aggregation which occurs in analysis of censored distances. We recommend HOV analysis as a complementary tool to the analysis of distribution/location differences. We also apply the methodology on simulated normal and exponential data sets and assess the performance of the methods when more of the underlying assumptions are satisfied. We illustrate the methodology on a real data example, namely, LCDM distances of GM voxels in ventral medial prefrontal cortices (VMPFCs) to see the effects of depression or being of high risk to depression on the morphometry of VMPFCs. The methodology used here is also valid for morphometric analysis of other cortical structures.attention [27,28], Area 46 of the frontal cortex in fetal irradiated macaques [29] and ERC in normal aging controls and in subjects with mild cognitive impairment [30]. Finally, our observation of variable cortical thickness in the left PT in three groups of age-matched and gender-matched controls and patients with schizophrenia and bipolar disorder [31] is consistent with post-mortem analysis [32]. The approach has also been extended to deal with deeply buried sulci by modeling image intensity stochastically based on the normal distance where the model includes cortical thickness as one of the parameters [1]; others have similarly adapted LCDMs [33,34]. The LCDM approach is similar to the voxel-based cortical thickness method (VBCT) [35] where each voxel in the GM has a thickness value associated with it, but our analysis of these voxel-based thickness values is different. In VBCT cortical thickness values are compared on a voxel-by-voxel basis as in SP...

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Censoring Distances Based on Labeled Cortical Distance Maps in Cortical Morphometry

Cited by 4 publications

References 51 publications

Morphometric Differences in Planum Temporale in Schizophrenia and Bipolar Disorder Revealed by Statistical Analysis of Labeled Cortical Depth Maps

Morphometric Differences in Planum Temporale in Schizophrenia and Bipolar Disorder Revealed by Statistical Analysis of Labeled Cortical Depth Maps

Structural neuroimaging of the altered brain stemming from pediatric and adolescent hearing loss—Scientific and clinical challenges

Analysis of cortical morphometric variability using labeled cortical distance maps

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