Characterization of microcirculation in multiple sclerosis lesions by dynamic texture parameter analysis (DTPA).

<h4>Objective</h4>Texture analysis is an alternative method to quantitatively assess MR-images. In this study, we introduce dynamic texture parameter analysis (DTPA), a novel technique to investigate the temporal evolution of texture parameters using dynamic susceptibility contrast enhan...

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Autores principales:	Rajeev Kumar Verma, Johannes Slotboom, Mirjam Rachel Heldner, Frauke Kellner-Weldon, Raimund Kottke, Christoph Ozdoba, Christian Weisstanner, Christian Philipp Kamm, Roland Wiest
Formato:	article
Lenguaje:	EN
Publicado:	Public Library of Science (PLoS) 2013
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/d2e64339333b4a89ae4d6ad9ff09b258
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spelling	oai:doaj.org-article:d2e64339333b4a89ae4d6ad9ff09b2582021-11-18T07:37:36ZCharacterization of microcirculation in multiple sclerosis lesions by dynamic texture parameter analysis (DTPA).1932-620310.1371/journal.pone.0067610https://doaj.org/article/d2e64339333b4a89ae4d6ad9ff09b2582013-01-01T00:00:00Zhttps://www.ncbi.nlm.nih.gov/pmc/articles/pmid/23874432/?tool=EBIhttps://doaj.org/toc/1932-6203<h4>Objective</h4>Texture analysis is an alternative method to quantitatively assess MR-images. In this study, we introduce dynamic texture parameter analysis (DTPA), a novel technique to investigate the temporal evolution of texture parameters using dynamic susceptibility contrast enhanced (DSCE) imaging. Here, we aim to introduce the method and its application on enhancing lesions (EL), non-enhancing lesions (NEL) and normal appearing white matter (NAWM) in multiple sclerosis (MS).<h4>Methods</h4>We investigated 18 patients with MS and clinical isolated syndrome (CIS), according to the 2010 McDonald's criteria using DSCE imaging at different field strengths (1.5 and 3 Tesla). Tissues of interest (TOIs) were defined within 27 EL, 29 NEL and 37 NAWM areas after normalization and eight histogram-based texture parameter maps (TPMs) were computed. TPMs quantify the heterogeneity of the TOI. For every TOI, the average, variance, skewness, kurtosis and variance-of-the-variance statistical parameters were calculated. These TOI parameters were further analyzed using one-way ANOVA followed by multiple Wilcoxon sum rank testing corrected for multiple comparisons.<h4>Results</h4>Tissue- and time-dependent differences were observed in the dynamics of computed texture parameters. Sixteen parameters discriminated between EL, NEL and NAWM (pAVG = 0.0005). Significant differences in the DTPA texture maps were found during inflow (52 parameters), outflow (40 parameters) and reperfusion (62 parameters). The strongest discriminators among the TPMs were observed in the variance-related parameters, while skewness and kurtosis TPMs were in general less sensitive to detect differences between the tissues.<h4>Conclusion</h4>DTPA of DSCE image time series revealed characteristic time responses for ELs, NELs and NAWM. This may be further used for a refined quantitative grading of MS lesions during their evolution from acute to chronic state. DTPA discriminates lesions beyond features of enhancement or T2-hypersignal, on a numeric scale allowing for a more subtle grading of MS-lesions.Rajeev Kumar VermaJohannes SlotboomMirjam Rachel HeldnerFrauke Kellner-WeldonRaimund KottkeChristoph OzdobaChristian WeisstannerChristian Philipp KammRoland WiestPublic Library of Science (PLoS)articleMedicineRScienceQENPLoS ONE, Vol 8, Iss 7, p e67610 (2013)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Rajeev Kumar Verma Johannes Slotboom Mirjam Rachel Heldner Frauke Kellner-Weldon Raimund Kottke Christoph Ozdoba Christian Weisstanner Christian Philipp Kamm Roland Wiest Characterization of microcirculation in multiple sclerosis lesions by dynamic texture parameter analysis (DTPA).
description	<h4>Objective</h4>Texture analysis is an alternative method to quantitatively assess MR-images. In this study, we introduce dynamic texture parameter analysis (DTPA), a novel technique to investigate the temporal evolution of texture parameters using dynamic susceptibility contrast enhanced (DSCE) imaging. Here, we aim to introduce the method and its application on enhancing lesions (EL), non-enhancing lesions (NEL) and normal appearing white matter (NAWM) in multiple sclerosis (MS).<h4>Methods</h4>We investigated 18 patients with MS and clinical isolated syndrome (CIS), according to the 2010 McDonald's criteria using DSCE imaging at different field strengths (1.5 and 3 Tesla). Tissues of interest (TOIs) were defined within 27 EL, 29 NEL and 37 NAWM areas after normalization and eight histogram-based texture parameter maps (TPMs) were computed. TPMs quantify the heterogeneity of the TOI. For every TOI, the average, variance, skewness, kurtosis and variance-of-the-variance statistical parameters were calculated. These TOI parameters were further analyzed using one-way ANOVA followed by multiple Wilcoxon sum rank testing corrected for multiple comparisons.<h4>Results</h4>Tissue- and time-dependent differences were observed in the dynamics of computed texture parameters. Sixteen parameters discriminated between EL, NEL and NAWM (pAVG = 0.0005). Significant differences in the DTPA texture maps were found during inflow (52 parameters), outflow (40 parameters) and reperfusion (62 parameters). The strongest discriminators among the TPMs were observed in the variance-related parameters, while skewness and kurtosis TPMs were in general less sensitive to detect differences between the tissues.<h4>Conclusion</h4>DTPA of DSCE image time series revealed characteristic time responses for ELs, NELs and NAWM. This may be further used for a refined quantitative grading of MS lesions during their evolution from acute to chronic state. DTPA discriminates lesions beyond features of enhancement or T2-hypersignal, on a numeric scale allowing for a more subtle grading of MS-lesions.
format	article
author	Rajeev Kumar Verma Johannes Slotboom Mirjam Rachel Heldner Frauke Kellner-Weldon Raimund Kottke Christoph Ozdoba Christian Weisstanner Christian Philipp Kamm Roland Wiest
author_facet	Rajeev Kumar Verma Johannes Slotboom Mirjam Rachel Heldner Frauke Kellner-Weldon Raimund Kottke Christoph Ozdoba Christian Weisstanner Christian Philipp Kamm Roland Wiest
author_sort	Rajeev Kumar Verma
title	Characterization of microcirculation in multiple sclerosis lesions by dynamic texture parameter analysis (DTPA).
title_short	Characterization of microcirculation in multiple sclerosis lesions by dynamic texture parameter analysis (DTPA).
title_full	Characterization of microcirculation in multiple sclerosis lesions by dynamic texture parameter analysis (DTPA).
title_fullStr	Characterization of microcirculation in multiple sclerosis lesions by dynamic texture parameter analysis (DTPA).
title_full_unstemmed	Characterization of microcirculation in multiple sclerosis lesions by dynamic texture parameter analysis (DTPA).
title_sort	characterization of microcirculation in multiple sclerosis lesions by dynamic texture parameter analysis (dtpa).
publisher	Public Library of Science (PLoS)
publishDate	2013
url	https://doaj.org/article/d2e64339333b4a89ae4d6ad9ff09b258
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Characterization of microcirculation in multiple sclerosis lesions by dynamic texture parameter analysis (DTPA).

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