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High-throughput, automated quantification of white matter neurons in mild malformation of cortical development in epilepsy

High-throughput, automated quantification of white matter neurons in mild malformation of cortical development in epilepsy
High-throughput, automated quantification of white matter neurons in mild malformation of cortical development in epilepsy

INTRODUCTION: In epilepsy, the diagnosis of mild Malformation of Cortical Development type II (mMCD II) predominantly relies on the histopathological assessment of heterotopic neurons in the white matter. The exact diagnostic criteria for mMCD II are still ill-defined, mainly because findings from previous studies were contradictory due to small sample size, and the use of different stains and quantitative systems. Advance in technology leading to the development of whole slide imaging with high-throughput, automated quantitative analysis (WSA) may overcome these differences, and may provide objective, rapid, and reliable quantitation of white matter neurons in epilepsy. This study quantified the density of NeuN immunopositive neurons in the white matter of up to 142 epilepsy and control cases using WSA. Quantitative data from WSA was compared to two other systems, semi-automated quantitation, and the widely accepted method of stereology, to assess the reliability and quality of results from WSA.

RESULTS: All quantitative systems showed a higher density of white matter neurons in epilepsy cases compared to controls (P = 0.002). We found that, in particular, WSA with user-defined region of interest (manual) was superior in terms of larger sampled size, ease of use, time consumption, and accuracy in region selection and cell recognition compared to other methods. Using results from WSA manual, we proposed a threshold value for the classification of mMCD II, where 78% of patients now classified with mMCD II were seizure-free at the second post-operatively follow up.

CONCLUSION: This study confirms the potential role of WSA in future quantitative diagnostic histology, especially for the histopathological diagnosis of mMCD.

Adult, Cell Count, Electronic Data Processing, Epilepsy, Female, Humans, Male, Malformations of Cortical Development, Neurons, Phosphopyruvate Hydratase, Reproducibility of Results, Time Factors, White Matter, Journal Article, Research Support, Non-U.S. Gov't
2051-5960
1-10
Liu, Joan Y.W.
0e68a532-ba7f-451a-944c-461e1585c47e
Ellis, Matthew
afbca752-ced4-40dd-b0af-d9ecffbd5b63
Brooke-Ball, Hannah
35c584e1-cc7d-4337-87fb-d40af9fc293d
de Tisi, Jane
11ae411b-ca4b-4247-9356-afdd14d81176
Eriksson, Sofia H.
7db420e6-55b2-499c-b624-d9a1d4ed8082
Brandner, Sebastian
f64b2397-fa45-4378-bf5a-1c6bbb14f18e
Sisodiya, Sanjay M.
442600da-eda0-410b-97bb-cde8326d702d
Thom, Maria
a9f63dd8-ba68-4ea1-a945-e4bbd18525d2
Liu, Joan Y.W.
0e68a532-ba7f-451a-944c-461e1585c47e
Ellis, Matthew
afbca752-ced4-40dd-b0af-d9ecffbd5b63
Brooke-Ball, Hannah
35c584e1-cc7d-4337-87fb-d40af9fc293d
de Tisi, Jane
11ae411b-ca4b-4247-9356-afdd14d81176
Eriksson, Sofia H.
7db420e6-55b2-499c-b624-d9a1d4ed8082
Brandner, Sebastian
f64b2397-fa45-4378-bf5a-1c6bbb14f18e
Sisodiya, Sanjay M.
442600da-eda0-410b-97bb-cde8326d702d
Thom, Maria
a9f63dd8-ba68-4ea1-a945-e4bbd18525d2

Liu, Joan Y.W., Ellis, Matthew, Brooke-Ball, Hannah, de Tisi, Jane, Eriksson, Sofia H., Brandner, Sebastian, Sisodiya, Sanjay M. and Thom, Maria (2014) High-throughput, automated quantification of white matter neurons in mild malformation of cortical development in epilepsy. Acta Neuropathologica Communications, 2 (72), 1-10. (doi:10.1186/2051-5960-2-72).

Record type: Article

Abstract

INTRODUCTION: In epilepsy, the diagnosis of mild Malformation of Cortical Development type II (mMCD II) predominantly relies on the histopathological assessment of heterotopic neurons in the white matter. The exact diagnostic criteria for mMCD II are still ill-defined, mainly because findings from previous studies were contradictory due to small sample size, and the use of different stains and quantitative systems. Advance in technology leading to the development of whole slide imaging with high-throughput, automated quantitative analysis (WSA) may overcome these differences, and may provide objective, rapid, and reliable quantitation of white matter neurons in epilepsy. This study quantified the density of NeuN immunopositive neurons in the white matter of up to 142 epilepsy and control cases using WSA. Quantitative data from WSA was compared to two other systems, semi-automated quantitation, and the widely accepted method of stereology, to assess the reliability and quality of results from WSA.

RESULTS: All quantitative systems showed a higher density of white matter neurons in epilepsy cases compared to controls (P = 0.002). We found that, in particular, WSA with user-defined region of interest (manual) was superior in terms of larger sampled size, ease of use, time consumption, and accuracy in region selection and cell recognition compared to other methods. Using results from WSA manual, we proposed a threshold value for the classification of mMCD II, where 78% of patients now classified with mMCD II were seizure-free at the second post-operatively follow up.

CONCLUSION: This study confirms the potential role of WSA in future quantitative diagnostic histology, especially for the histopathological diagnosis of mMCD.

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2051-5960-2-72 - Version of Record
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Published date: 13 June 2014
Keywords: Adult, Cell Count, Electronic Data Processing, Epilepsy, Female, Humans, Male, Malformations of Cortical Development, Neurons, Phosphopyruvate Hydratase, Reproducibility of Results, Time Factors, White Matter, Journal Article, Research Support, Non-U.S. Gov't

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Local EPrints ID: 428178
URI: http://eprints.soton.ac.uk/id/eprint/428178
ISSN: 2051-5960
PURE UUID: dd747199-8d5a-4914-972f-e95625632394

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Date deposited: 13 Feb 2019 17:30
Last modified: 16 Mar 2024 00:08

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Contributors

Author: Joan Y.W. Liu
Author: Matthew Ellis
Author: Hannah Brooke-Ball
Author: Jane de Tisi
Author: Sofia H. Eriksson
Author: Sebastian Brandner
Author: Sanjay M. Sisodiya
Author: Maria Thom

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