scholarly journals Assumption-Free Assessment of Corpus Callosum Shape: Benchmarking and Application

2019 ◽  
Vol 2019 ◽  
pp. 1-10
Author(s):  
Erin I. Walsh ◽  
Marnie E. Shaw ◽  
Daniela A. Espinoza Oyarce ◽  
Mark Fraser ◽  
Nicolas Cherbuin
Keyword(s):  
Corpus Callosum ◽  
Shape Analysis ◽  
Principal Component ◽  
Predictive Performance ◽  
Shape Space ◽  
Great Promise ◽  
Mixed Effect ◽  
Global Shape ◽  
Dimensional Shape ◽  
Intuitive Method

Shape analysis provides a unique insight into biological processes. This paper evaluates the properties, performance, and utility of elliptical Fourier (eFourier) analysis to operationalise global shape, focussing on the human corpus callosum. 8000 simulated corpus callosum contours were generated, systematically varying in terms of global shape (midbody arch, splenium size), local complexity (surface smoothness), and nonshape characteristics (e.g., rotation). 2088 real corpus callosum contours were manually traced from the PATH study. Performance of eFourier was benchmarked in terms of its capacity to capture and then reconstruct shape and systematically operationalise that shape via principal components analysis. We also compared the predictive performance of corpus callosum volume, position in Procrustes-aligned Landmark tangent space, and position in eFourier n-dimensional shape space in relation to the Symbol Digit Modalities Test. Jaccard index for original vs. reconstructed from eFourier shapes was excellent (M=0.98). The combination of eFourier and PCA performed particularly well in reconstructing known n-dimensional shape space but was disrupted by the inclusion of local shape manipulations. For the case study, volume, eFourier, and landmark measures were all correlated. Mixed effect model results indicated all methods detected similar features, but eFourier estimates were most predictive, and of the two shape operationalization techniques had the least error and better model fit. Elliptical Fourier analysis, particularly in combination with principal component analysis, is a powerful, assumption-free and intuitive method of quantifying global shape of the corpus callosum and shows great promise for shape analysis in neuroimaging more broadly.

Deformation-based Statistical Shape Analysis of the Corpus Callosum in Mild Cognitive Impairment and Alzheimer’s Disease

2018 ◽  
Vol 15 (12) ◽  
pp. 1151-1160 ◽  
Author(s):  
Zihan Jiang ◽  
Huilin Yang ◽  
Xiaoying Tang
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Cognitive Impairment ◽  
Mild Cognitive Impairment ◽  
Corpus Callosum ◽  
Shape Analysis ◽  
Disease Assessment ◽  
Statistical Shape Analysis ◽  
Superior Part ◽  
Statistical Shape

Objective: In this study, we investigated the influence that the pathology of Alzheimer’s disease (AD) exerts upon the corpus callosum (CC) using a total of 325 mild cognitive impairment (MCI) subjects, 155 AD subjects, and 185 healthy control (HC) subjects. Method: Regionally-specific morphological CC abnormalities, as induced by AD, were quantified using a large deformation diffeomorphic metric curve mapping based statistical shape analysis pipeline. We also quantified the association between the CC shape phenotype and two cognitive measures; the Mini Mental State Examination (MMSE) and the Alzheimer’s Disease Assessment Scale-Cognitive Behavior Section (ADAS-cog). To identify AD-relevant areas, CC was sub-divided into three subregions; the genu, body, and splenium (gCC, bCC, and sCC). Results: We observed significant shape compressions in AD relative to that in HC, mainly concentrated on the superior part of CC, across all three sub-regions. The HC-vs-MCI shape abnormalities were also concentrated on the superior part, but mainly occurred on bCC and sCC. The significant MCI-vs-AD shape differences, however, were only detected in part of sCC. In the shape-cognition association, significant negative correlations to ADAS-cog were detected for shape deformations at regions belonging to gCC and sCC and significant positive correlations to MMSE at regions mainly belonging to sCC. Conclusion: Our results suggest that the callosal shape deformation patterns, especially those of sCC, linked tightly to the cognitive decline in AD, and are potentially a powerful biomarker for monitoring the progression of AD.

scholarly journals The earliest example of sexual dimorphism in bivalves—evidence from the astartid Nicaniella (Lower Jurassic, southern Germany)

2021 ◽  
pp. 1-10
Author(s):  
Baran Karapunar ◽  
Winfried Werner ◽  
Franz T. Fürsich ◽  
Alexander Nützel
Keyword(s):  
Principal Component Analysis ◽  
Life History ◽  
Shape Analysis ◽  
Principal Component ◽  
Sex Change ◽  
Lower Jurassic ◽  
Allocation Of Resources ◽  
Fourier Shape Analysis ◽  
Lower Height ◽  
Male To Female

Abstract Protandrous sex change (sex change from male to female) is one of the diverse sexual expressions exhibited by bivalves, but its expression in the shell is quite rare. Previous studies on living and fossil astartids suggest a relationship between protandrous sex change and the formation of crenulations on the ventral shell margin at later ontogenetic stages. Here we report the formation of such crenulations in the Early Jurassic astartid Nicaniella rakoveci (Kuhn, 1935) from the Amaltheenton Formation at Buttenheim, Franconia. This is the earliest known record of protandrous hermaphroditism in fossil bivalves, predating previous reports by at least 13 Myr. A principal component analysis of linear size measurements and Fourier shape analysis of the shell outlines revealed that the outline of Nicaniella rakoveci specimens varies from subquadrate to subcircular, but this variation is independent of the presence or absence of crenulations and therefore not associated with sex. Crenulated specimens exhibit a lower height/inflation ratio than non-crenulated ones, suggesting that the protandrous females have more inflated valves than the males. The formation of crenulations was probably related to allocation of resources for reproduction. The most likely function of the crenulations was to increase the internal shell volume in the female stage to accommodate more eggs rather than being an adaptation against predation as often assumed for other bivalves. The formation of crenulations is part of the protandrous life history and probably is controlled by a genetic mechanism that is also responsible for sex change.

Global Shape Analysis by k-Syntactic Similarity

1981 ◽  
Vol PAMI-3 (2) ◽  
pp. 144-155 ◽  
Author(s):  
Carolyn M. Bjorklund ◽  
Theodosios Pavlidis
Keyword(s):  
Shape Analysis ◽  
Global Shape ◽  
Syntactic Similarity

On the microstructural origin of brain white matter hydraulic permeability

2021 ◽  
Vol 118 (36) ◽  
pp. e2105328118
Author(s):  
Marco Vidotto ◽  
Andrea Bernardini ◽  
Marco Trovatelli ◽  
Elena De Momi ◽  
Daniele Dini
Keyword(s):  
White Matter ◽  
Corpus Callosum ◽  
Drug Transport ◽  
Three Dimensional ◽  
Principal Component ◽  
Hydraulic Permeability ◽  
Convection Enhanced Delivery ◽  
Brain White Matter ◽  
Significant Difference ◽  
The Brain

Brain microstructure plays a key role in driving the transport of drug molecules directly administered to the brain tissue, as in Convection-Enhanced Delivery procedures. The proposed research analyzes the hydraulic permeability of two white matter (WM) areas (corpus callosum and fornix) whose three-dimensional microstructure was reconstructed starting from the acquisition of electron microscopy images. We cut the two volumes with 20 equally spaced planes distributed along two perpendicular directions, and, on each plane, we computed the corresponding permeability vector. Then, we considered that the WM structure is mainly composed of elongated and parallel axons, and, using a principal component analysis, we defined two principal directions, parallel and perpendicular, with respect to the axons’ main direction. The latter were used to define a reference frame onto which the permeability vectors were projected to finally obtain the permeability along the parallel and perpendicular directions. The results show a statistically significant difference between parallel and perpendicular permeability, with a ratio of about two in both the WM structures analyzed, thus demonstrating their anisotropic behavior. Moreover, we find a significant difference between permeability in corpus callosum and fornix, which suggests that the WM heterogeneity should also be considered when modeling drug transport in the brain. Our findings, which demonstrate and quantify the anisotropic and heterogeneous character of the WM, represent a fundamental contribution not only for drug-delivery modeling, but also for shedding light on the interstitial transport mechanisms in the extracellular space.

Analysis of 3D Corpus Callosum Images in the Brains of Autistic Individuals

2016 ◽  
pp. 159-184
Author(s):  
Ahmed Elnakib ◽  
Manuel F. Casanova ◽  
Ahmed Soliman ◽  
Georgy Gimel'farb ◽  
Ayman El-Baz
Keyword(s):  
Autism Spectrum Disorder ◽  
Corpus Callosum ◽  
Human Brain ◽  
Shape Analysis ◽  
Neurodevelopmental Disorder ◽  
Autism Spectrum ◽  
Cerebral Hemispheres ◽  
Higher Cognitive Functions ◽  
The Right ◽  
Abnormal Anatomy

Autism spectrum disorder (ASD) is a complex neurodevelopmental disorder that is characterized by abnormalities in behavior and higher cognitive functions. The corpus callosum (CC) is the largest fiber bundle that connects the left and the right cerebral hemispheres of the human brain. Several studies have revealed an abnormal anatomy of the CC in the brains of autistic individuals that associates this neurodevelopmental condition with impaired communication between the hemispheres. In this chapter, we develop a framework to analyze the CC of autistic individuals in order to provide a diagnostic tool for autism. The key advantage of this approach is the development of a cylindrical mapping that offers simplified coordinates for comparing the brains of autistic individuals and neurotypicals. Experimental results showed significant differences (at the 95% confidence level) between 17 normal and 17 autistic subjects in four anatomical divisions, i.e. splenium, rostrum, genu, and body of their CCs. Moreover, the initial centerline-based shape analysis of the CC documented a promising supplement to the current techniques for diagnosing autism.

scholarly journals Improving data splitting for classification applications in spectrochemical analyses employing a random-mutation Kennard-Stone algorithm approach

2019 ◽  
Vol 35 (24) ◽  
pp. 5257-5263 ◽  
Author(s):  
Camilo L M Morais ◽  
Marfran C D Santos ◽  
Kássio M G Lima ◽  
Francis L Martin
Keyword(s):  
Biomedical Applications ◽  
Sample Selection ◽  
Principal Component ◽  
Predictive Performance ◽  
Model Construction ◽  
Classification Models ◽  
Data Splitting ◽  
Random Mutation ◽  
Linear Discriminant ◽  
Test Sets

Abstract Motivation Data splitting is a fundamental step for building classification models with spectral data, especially in biomedical applications. This approach is performed following pre-processing and prior to model construction, and consists of dividing the samples into at least training and test sets; herein, the training set is used for model construction and the test set for model validation. Some of the most-used methodologies for data splitting are the random selection (RS) and the Kennard-Stone (KS) algorithms; here, the former works based on a random splitting process and the latter is based on the calculation of the Euclidian distance between the samples. We propose an algorithm called the Morais-Lima-Martin (MLM) algorithm, as an alternative method to improve data splitting in classification models. MLM is a modification of KS algorithm by adding a random-mutation factor. Results RS, KS and MLM performance are compared in simulated and six real-world biospectroscopic applications using principal component analysis linear discriminant analysis (PCA-LDA). MLM generated a better predictive performance in comparison with RS and KS algorithms, in particular regarding sensitivity and specificity values. Classification is found to be more well-equilibrated using MLM. RS showed the poorest predictive response, followed by KS which showed good accuracy towards prediction, but relatively unbalanced sensitivities and specificities. These findings demonstrate the potential of this new MLM algorithm as a sample selection method for classification applications in comparison with other regular methods often applied in this type of data. Availability and implementation MLM algorithm is freely available for MATLAB at https://doi.org/10.6084/m9.figshare.7393517.v1.

How to look at objects in a five-dimensional shape space: looking at geodesics

1995 ◽  
Vol 27 (01) ◽  
pp. 35-43
Author(s):  
David G. Kendall
Keyword(s):  
Shape Space ◽  
The Third ◽  
Dimensional Shape

This paper is the third in a series with the general title ‘How to look at the five-dimensional shape space Σ4,3. Parts I and II were concerned with distributions and diffusions respectively. Here we ‘look at’ geodesics.

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