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Agreement between different input image types in brain atrophy measurement in multiple sclerosis using SIENAX and SIENA
Author(s) -
Neacsu Veronica,
Jasperse Bas,
Korteweg Tijmen,
Knol Dirk L.,
Valsasina Paola,
Filippi Massimo,
Barkhof Frederik,
Rovaris Marco,
Vrenken Hugo
Publication year - 2008
Publication title -
journal of magnetic resonance imaging
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.563
H-Index - 160
eISSN - 1522-2586
pISSN - 1053-1807
DOI - 10.1002/jmri.21501
Subject(s) - contrast (vision) , atrophy , multiple sclerosis , magnetic resonance imaging , medicine , image contrast , brain size , nuclear medicine , computer science , artificial intelligence , radiology , pathology , psychiatry
Purpose To investigate whether multiple sclerosis (MS) atrophy can be assessed by SIENA and SIENAX software using other image types from MS research protocols than T1‐weighted images without contrast agent, which are not always available. Materials and Methods We selected 46 MS patients with identical magnetic resonance imaging (MRI) protocols at two timepoints. We calculated normalized brain volume (NBV) using SIENAX, and percentage brain volume change (PBVC) using SIENA, from T1‐weighted images with and without contrast agent, T2‐weighted images, and (calculated) pseudo‐T1‐weighted images. Relative agreement of the results was assessed using variance component estimation. Results Relative agreement with T1‐weighted images without contrast agent was good for T1‐weighted images with contrast agent (ICC = 0.86 for NBV, ICC = 0.77 for PBVC), and reasonably good for pseudo‐T1 and T2‐weighted images (T2: ICC = 0.72 for NBV, 0.58 for PBVC; pseudo‐T1: ICC = 0.68 for NBV, 0.83 for PBVC). Conclusion Brain atrophy can be studied using SIENA and SIENAX if T1‐weighted images without contrast agent are not available. T1‐weighted images with contrast agent should be used if available. Otherwise, pseudo‐T1 and T2‐weighted images seem acceptable and accessible alternatives. The use of these other images will greatly improve research possibilities, especially regarding older datasets. J. Magn. Reson. Imaging 2008;28:559–565. © 2008 Wiley‐Liss, Inc.