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Relating Cortical Atrophy in Temporal Lobe Epilepsy with Graph Diffusion-Based Network Models.

Abdelnour F, Mueller S, Raj A - PLoS Comput. Biol. (2015)

Bottom Line: We show that the network models closely reproduce the regional volumetric gray matter atrophy distribution of two epilepsy cohorts: 29 TLE subjects with medial temporal sclerosis (TLE-MTS), and 50 TLE subjects with normal appearance on MRI (TLE-no).We conclude that atrophy spread model out-performs the hyperactivity spread model.These results pave the way for future clinical application of the proposed model on individual patients, including estimating future spread of atrophy, identification of seizure onset zones and surgical planning.

View Article: PubMed Central - PubMed

Affiliation: Radiology, Weill Cornell Medical College, New York, New York, United States of America.

ABSTRACT
Mesial temporal lobe epilepsy (TLE) is characterized by stereotyped origination and spread pattern of epileptogenic activity, which is reflected in stereotyped topographic distribution of neuronal atrophy on magnetic resonance imaging (MRI). Both epileptogenic activity and atrophy spread appear to follow white matter connections. We model the networked spread of activity and atrophy in TLE from first principles via two simple first order network diffusion models. Atrophy distribution is modeled as a simple consequence of the propagation of epileptogenic activity in one model, and as a progressive degenerative process in the other. We show that the network models closely reproduce the regional volumetric gray matter atrophy distribution of two epilepsy cohorts: 29 TLE subjects with medial temporal sclerosis (TLE-MTS), and 50 TLE subjects with normal appearance on MRI (TLE-no). Statistical validation at the group level suggests high correlation with measured atrophy (R = 0.586 for TLE-MTS, R = 0.283 for TLE-no). We conclude that atrophy spread model out-performs the hyperactivity spread model. These results pave the way for future clinical application of the proposed model on individual patients, including estimating future spread of atrophy, identification of seizure onset zones and surgical planning.

No MeSH data available.


Related in: MedlinePlus

Histograms of R resulting from 1,000 instances of random permutations of the neuronal atrophy for each type of epilepsy and for both models.From the histograms, the estimated neuronal atrophy is likely to be specific to the atrophies obtained from both epilepsy groups, more so in the case of Model 2 where high R is obtained for both types of epilepsy. Histograms of R resulting from random permutation of neuronal atrophy, (a) TLE-MTS Model 1, (b) TLE-MTS, Model 2. Histogram of R resulting from TLE-no neuronal atrophy random permutation, (c) Model 1, and (d) Model 2.
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pcbi.1004564.g005: Histograms of R resulting from 1,000 instances of random permutations of the neuronal atrophy for each type of epilepsy and for both models.From the histograms, the estimated neuronal atrophy is likely to be specific to the atrophies obtained from both epilepsy groups, more so in the case of Model 2 where high R is obtained for both types of epilepsy. Histograms of R resulting from random permutation of neuronal atrophy, (a) TLE-MTS Model 1, (b) TLE-MTS, Model 2. Histogram of R resulting from TLE-no neuronal atrophy random permutation, (c) Model 1, and (d) Model 2.

Mentions: Fig 5 summarizes the findings. Fig 5(a) indicates the histogram resulting from the randomly shuffled measured atrophy in the case of Model 1 and TLE-MTS. None of the shuffled atrophies achieved a correlation exceeding that obtained from the empirical measured atrophy (R = 0.394). Similarly, measured atrophy randomization in Model 2 gives a histogram where the measured atrophy has the highest R, Fig 5(b). The TLE-no case does not perform as well. Fig 5(c) gives the histogram obtained in the case of Model 1. The measured atrophy has a correlation of R = 0.213, with 57 randomly shuffled instances of the atrophy yielding higher R, with a maximum R = 0.426. Nonetheless, only a small percentage of all iterations, 5.7% give R > 0.213. Model 2 gives improved results, with only 8 random atrophy patterns having R > 0.283 (0.8% of all iterations). The highest correlation obtained is R = 0.323. The fact that all reported R values are at the extreme end of the distribution conveys a strong suggestion that the network is indeed a relevant modulator or atrophy in TLE. The fact that the reported R statistic of Model 1, but not of Model 2, is only moderate in relation to the histogram further cements our conclusion that Model 2 (degenerative spread) is a superior network model than Model 1 (excitotoxicity spread).


Relating Cortical Atrophy in Temporal Lobe Epilepsy with Graph Diffusion-Based Network Models.

Abdelnour F, Mueller S, Raj A - PLoS Comput. Biol. (2015)

Histograms of R resulting from 1,000 instances of random permutations of the neuronal atrophy for each type of epilepsy and for both models.From the histograms, the estimated neuronal atrophy is likely to be specific to the atrophies obtained from both epilepsy groups, more so in the case of Model 2 where high R is obtained for both types of epilepsy. Histograms of R resulting from random permutation of neuronal atrophy, (a) TLE-MTS Model 1, (b) TLE-MTS, Model 2. Histogram of R resulting from TLE-no neuronal atrophy random permutation, (c) Model 1, and (d) Model 2.
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getmorefigures.php?uid=PMC4626097&req=5

pcbi.1004564.g005: Histograms of R resulting from 1,000 instances of random permutations of the neuronal atrophy for each type of epilepsy and for both models.From the histograms, the estimated neuronal atrophy is likely to be specific to the atrophies obtained from both epilepsy groups, more so in the case of Model 2 where high R is obtained for both types of epilepsy. Histograms of R resulting from random permutation of neuronal atrophy, (a) TLE-MTS Model 1, (b) TLE-MTS, Model 2. Histogram of R resulting from TLE-no neuronal atrophy random permutation, (c) Model 1, and (d) Model 2.
Mentions: Fig 5 summarizes the findings. Fig 5(a) indicates the histogram resulting from the randomly shuffled measured atrophy in the case of Model 1 and TLE-MTS. None of the shuffled atrophies achieved a correlation exceeding that obtained from the empirical measured atrophy (R = 0.394). Similarly, measured atrophy randomization in Model 2 gives a histogram where the measured atrophy has the highest R, Fig 5(b). The TLE-no case does not perform as well. Fig 5(c) gives the histogram obtained in the case of Model 1. The measured atrophy has a correlation of R = 0.213, with 57 randomly shuffled instances of the atrophy yielding higher R, with a maximum R = 0.426. Nonetheless, only a small percentage of all iterations, 5.7% give R > 0.213. Model 2 gives improved results, with only 8 random atrophy patterns having R > 0.283 (0.8% of all iterations). The highest correlation obtained is R = 0.323. The fact that all reported R values are at the extreme end of the distribution conveys a strong suggestion that the network is indeed a relevant modulator or atrophy in TLE. The fact that the reported R statistic of Model 1, but not of Model 2, is only moderate in relation to the histogram further cements our conclusion that Model 2 (degenerative spread) is a superior network model than Model 1 (excitotoxicity spread).

Bottom Line: We show that the network models closely reproduce the regional volumetric gray matter atrophy distribution of two epilepsy cohorts: 29 TLE subjects with medial temporal sclerosis (TLE-MTS), and 50 TLE subjects with normal appearance on MRI (TLE-no).We conclude that atrophy spread model out-performs the hyperactivity spread model.These results pave the way for future clinical application of the proposed model on individual patients, including estimating future spread of atrophy, identification of seizure onset zones and surgical planning.

View Article: PubMed Central - PubMed

Affiliation: Radiology, Weill Cornell Medical College, New York, New York, United States of America.

ABSTRACT
Mesial temporal lobe epilepsy (TLE) is characterized by stereotyped origination and spread pattern of epileptogenic activity, which is reflected in stereotyped topographic distribution of neuronal atrophy on magnetic resonance imaging (MRI). Both epileptogenic activity and atrophy spread appear to follow white matter connections. We model the networked spread of activity and atrophy in TLE from first principles via two simple first order network diffusion models. Atrophy distribution is modeled as a simple consequence of the propagation of epileptogenic activity in one model, and as a progressive degenerative process in the other. We show that the network models closely reproduce the regional volumetric gray matter atrophy distribution of two epilepsy cohorts: 29 TLE subjects with medial temporal sclerosis (TLE-MTS), and 50 TLE subjects with normal appearance on MRI (TLE-no). Statistical validation at the group level suggests high correlation with measured atrophy (R = 0.586 for TLE-MTS, R = 0.283 for TLE-no). We conclude that atrophy spread model out-performs the hyperactivity spread model. These results pave the way for future clinical application of the proposed model on individual patients, including estimating future spread of atrophy, identification of seizure onset zones and surgical planning.

No MeSH data available.


Related in: MedlinePlus