• Title of article

    Distinct patterns of active and non-active plaques using texture analysis on brain NMR images in multiple sclerosis patients: preliminary results

  • Author/Authors

    Yu، نويسنده , , O and Mauss، نويسنده , , Y and Zollner، نويسنده , , G and Namer، نويسنده , , I.J and Chambron، نويسنده , , J، نويسنده ,

  • Issue Information
    روزنامه با شماره پیاپی سال 1999
  • Pages
    7
  • From page
    1261
  • To page
    1267
  • Abstract
    The benefits of texture analysis of magnetic resonance images have been assessed in multiple sclerosis (MS) patients. Out of thirty-two lesions identified in eight MS patients, nine were considered active, judging from their gadolinium uptake. Texture analysis allowed to obtain forty-two characterizing parameters for each lesion. Using discriminant analysis as a statistical method allowed to classify the lesions into two groups: active or non-active. An attempt to classify their level of activity by using only co-occurrence matrices was unsuccessful. Alternately, the same type of analysis performed on runlength analysis criteria allowed the accurate classification of 88% of active lesions and 96% of non-active lesions. Using incremental discriminate analysis can reduce the number of useful parameters. This method showed that among the 42 parameters, 8 only were highly significant and permitted an accurate classification. Five of these parameters are runlength parameters, and three others are more directly related to the global distribution. The main interest of runlength parameters is that they allowed to demonstrate that the lesion structure was different in active and non-active plaques. This preliminary work suggests that using texture analysis could be of interest in the follow-up of MS patients because it provides an opportunity to identify active lesions without frequent gadolinium injections.
  • Keywords
    Demyelination , Gliosis , Runlength parameters , Blood–brain barrier , Multiple sclerosis , Texture analysis
  • Journal title
    Magnetic Resonance Imaging
  • Serial Year
    1999
  • Journal title
    Magnetic Resonance Imaging
  • Record number

    1830354