Institut Català de la Salut
[Marschallinger R] Department of Geoinformatics, University of Salzburg, Salzburg, Austria. Department of Neurology, Christian Doppler Medical Center, Paracelsus Medical University, Salzburg, Austria. [Tur C] Department of Neuroinflammation, Queen Square Multiple Sclerosis Centre, UCL Institute of Neurology, University College London, London, UK. Servei de Neurologia/Neuroimmunologia, Centre d'Esclerosi Múltiple de Catalunya (CEMCAT), Barcelona, Spain. [Marschallinger H] Marschallinger GeoInformatik, Seekirchen, Austria. [Sellner J] Department of Neurology, Christian Doppler Medical Center, Paracelsus Medical University, Salzburg, Austria. Department of Neurology, Landesklinikum Mistelbach-Gänserndorf, Liechtensteinstr, Mistelbach, Austria. Department of Neurology, Klinikum Rechts der Isar, Technische Universität München, München, Germany
Vall d'Hebron Barcelona Hospital Campus
2021-06-16T11:14:05Z
2021-06-16T11:14:05Z
2021-01-12
Càlcul estadístic R; Geoestadística; Esclerosi múltiple
Cálculo estadístico R; Geoestadística; Esclerosis múltiple
R statistical computing; Geostatistics; Multiple sclerosis
One significant characteristic of Multiple Sclerosis (MS), a chronic inflammatory demyelinating disease of the central nervous system, is the evolution of highly variable patterns of white matter lesions. Based on geostatistical metrics, the MS-Lesion Pattern Discrimination Plot reduces complex three- and four-dimensional configurations of MS-White Matter Lesions to a well-arranged and standardized two-dimensional plot that facilitates follow-up, cross-sectional and medication impact analysis. Here, we present a script that generates the MS-Lesion Pattern Discrimination Plot, using the widespread statistical computing environment R. Input data to the script are Nifti-1 or Analyze-7.5 files with individual MS-White Matter Lesion masks in Montreal Normal Brain geometry. The MS-Lesion Pattern Discrimination Plot, variogram plots and associated fitting statistics are output to the R console and exported to standard graphics and text files. Besides reviewing relevant geostatistical basics and commenting on implementation details for smooth customization and extension, the paper guides through generating MS-Lesion Pattern Discrimination Plots using publicly available synthetic MS-Lesion patterns. The paper is accompanied by the R script LDPgenerator.r, a small sample data set and associated graphics for comparison.
Artículo
Versión publicada
Inglés
Esclerosi múltiple; Imatgeria per ressonància magnètica; Patrons de programari; DISEASES::Nervous System Diseases::Nervous System Diseases::Demyelinating Diseases::Demyelinating Autoimmune Diseases, CNS::Multiple Sclerosis; INFORMATION SCIENCE::Information Science::Information Management::Pattern Recognition, Automated; ANALYTICAL, DIAGNOSTIC AND THERAPEUTIC TECHNIQUES, AND EQUIPMENT::Diagnosis::Diagnostic Techniques and Procedures::Diagnostic Imaging::Tomography::Magnetic Resonance Imaging; ENFERMEDADES::enfermedades del sistema nervioso::enfermedades del sistema nervioso::enfermedades desmielinizantes::enfermedades autoinmunes desmielinizantes del SNC::esclerosis múltiple; CIENCIA DE LA INFORMACIÓN::Ciencias de la información::gestión de la información::reconocimiento automatizado de patrones; TÉCNICAS Y EQUIPOS ANALÍTICOS, DIAGNÓSTICOS Y TERAPÉUTICOS::diagnóstico::técnicas y procedimientos diagnósticos::diagnóstico por imagen::tomografía::imagen por resonancia magnética
MDPI
Brain Sciences;11(1)
https://www.mdpi.com/2076-3425/11/1/90
Attribution 4.0 International
http://creativecommons.org/licenses/by/4.0/