01649nas a2200133   4500008004100000020001400041245012400055210006900179260001200248300001400260490000800274520119200282856004101474       2001                        eng d  a0033-841900aBrain atrophy in relapsing-remitting multiple sclerosis: Fractional volumetric analysis of gray matter and white matter0 aBrain atrophy in relapsingremitting multiple sclerosis Fractiona  c2001///  a606 - 6100 v2203 aPURPOSE: To determine the fractional brain tissue volume changesin the gray matter and white matter of patients with relapsing-
remitting multiple sclerosis (MS) and to correlate these 
measurements with clinical disability and total lesion load. 
MATERIALS AND METHODS: Thirty patients with relapsing-remitting 
MS and 25 healthy control subjects underwent magnetic resonance 
imaging. Fractional brain tissue volumes (tissue volume relative 
to total intracranial volume) were obtained from the total 
segmented gray matter and white matter in each group and were 
analyzed. RESULTS: The fractional volume of white matter versus 
that of gray matter was significantly lower (-6.4%) in patients 
with MS (P <.0001) than in control subjects. Neither gray matter 
nor white matter fractional volume measurements correlated with 
clinical disability in the patients with MS. CONCLUSION: Loss of 
brain parenchymal volume in patients with relapsing-remitting MS 
is predominantly confined to white matter. Analysis of 
fractional brain tissue volumes provides additional information 
useful in characterizing MS and may have potential in evaluating 
treatment strategies.
  uhttps://www.inf.szte.hu/en/node/100402158nas a2200133   4500008004100000020001400041245009800055210006900153260001200222300001600234490000600250520172700256856004101983       2001                        eng d  a1076-633200aMultiprotocol MR image segmentation in multiple sclerosis: Experience with over 1,000 studies0 aMultiprotocol MR image segmentation in multiple sclerosis Experi  c2001///  a1116 - 11260 v83 aRATIONALE AND OBJECTIVES: Multiple sclerosis (MS) is an acquireddisease of the central nervous system. Several clinical measures 
are commonly used to express the severity of the disease, 
including the Expanded Disability Status Scale and the 
ambulation index. These measures are subjective and may be 
difficult to reproduce. The aim of this research is to 
investigate the possibility of developing more objective 
measures derived from MR imaging. MATERIALS AND METHODS: Various 
magnetic resonance (MR) imaging protocols are being investigated 
for the study of MS. Seeking to replace the Expanded Disability 
Status Scale and ambulation index with an objective means to 
assess the natural course of the disease and its response to 
therapy, the authors have developed multiprotocol MR image 
segmentation methods based on fuzzy connectedness to quantify 
both macrosopic features of the disease (lesions, gray matter, 
white matter, cerebrospinal fluid, and brain parenchyma) and the 
microscopic appearance of diseased white matter. Over 1,000 
studies have been processed to date. RESULTS: By far the 
strongest correlations with the clinical measures were 
demonstrated by the magnetization transfer ratio histogram 
parameters obtained for the various segmented tissue regions. 
These findings emphasize the importance of considering the 
microscopic and diffuse nature of the disease in the individual 
tissue regions. Brain parenchymal volume also demonstrated a 
strong correlation with clinical measures, which suggests that 
brain atrophy is an important disease indicator. CONCLUSION: 
Fuzzy connectedness is a viable, highly reproducible 
segmentation method for studying MS.
  uhttps://www.inf.szte.hu/en/node/100200375nas a2200085   4500008004100000245012600041210006900167260001200236856004100248       2000                        eng d00aBrain Atrophy in Relapsing-Remitting Multiple Sclerosis: A Fractional Volumetric Analysis of Gray Matter and White Matter0 aBrain Atrophy in RelapsingRemitting Multiple Sclerosis A Fractio  c2000///  uhttps://www.inf.szte.hu/en/node/107600356nas a2200085   4500008004100000245010700041210006900148260001200217856004100229       2000                        eng d00aMagnetization Transfer Ratio Histogram Analysis of Normal Appearing Gray Matter and White Matter in MS0 aMagnetization Transfer Ratio Histogram Analysis of Normal Appear  c2000///  uhttps://www.inf.szte.hu/en/node/107401836nas a2200109   4500008004100000245009700041210006900138260004200207300001600249520142000265856004101685       2000                        eng d00aMultiprotocol MR image segmentation in multiple sclerosis: experience with over 1000 studies0 aMultiprotocol MR image segmentation in multiple sclerosis experi  aBellingham; WashingtonbSPIEc2000///  a1017 - 10273 aMultiple Sclerosis (MS) is an acquired disease of the centralnervous system. Subjective cognitive and ambulatory test scores 
on a scale called EDSS are currently utilized to assess the 
disease severity. Various MRI protocols are being investigated 
to study the disease based on how it manifests itself in the 
images. In an attempt to eventually replace EDSS by an objective 
measure to assess the natural course of the disease and its 
response to therapy, we have developed image segmentation 
methods based on fuzzy connectedness to quantify various objects 
in multiprotocol MRI. These include the macroscopic objects such 
as lesions, the gray matter (GM), white matter (WM), 
cerebrospinal fluid (CSF), and brain parenchyma as well as the 
microscopic aspects of the diseased WM. Over 1000 studies have 
been processed to date. By far the strongest correlations with 
the clinical measures were demonstrated by the Magnetization 
Transfer Ratio (MTR) histogram parameters obtained for the 
various segmented tissue regions emphasizing the importance of 
considering the microscopic/diffused nature of the disease in 
the individual tissue regions. Brain parenchymal volume also 
demonstrated a strong correlation with the clinical measures 
indicating that brain atrophy is an important indicator of the 
disease. Fuzzy connectedness is a viable segmentation method for 
studying MS.
  uhttps://www.inf.szte.hu/en/node/101301615nas a2200133   4500008004100000020001400041245009600055210006900151260001200220300001400232490000700246520118700253856004101440       2000                        eng d  a1053-180700aNumerical tissue characterization in MS via standardization of the MR image intensity scale0 aNumerical tissue characterization in MS via standardization of t  c2000///  a715 - 7210 v123 aImage intensity standardization is a recently developedpostprocessing method that is capable of correcting the signal 
intensity variations in MR images. We evaluated signal intensity 
of healthy and diseased tissues in 10 multiple sclerosis (MS) 
patients based on standardized dual fast spin-echo MR images 
using a numerical postprocessing technique. The main idea of 
this technique is to deform the volume image histogram of each 
study to match a standard histogram and to utilize the resulting 
transformation to map the image intensities into standard scale. 
Upon standardization, the coefficients of variation of signal 
intensities for each segmented tissue (gray matter, white 
matter, lesion plaques, and diffuse abnormal white matter) in 
all patients were significantly smaller (2.3-9.2 times) than in 
the original images, and the same tissues from different 
patients looked alike, with similar intensity characteristics. 
Numerical tissue characterizability of different tissues in MS 
achieved by standardization offers a fixed tissue-specific 
meaning for the numerical values and can significantly 
facilitate image segmentation and analysis.
  uhttps://www.inf.szte.hu/en/node/100300376nas a2200097   4500008004100000245009600041210006900137260002300206300000800229856004100237       2000                        eng d00aNumerical Tissue Characterization in MS via Standardization of the MR Image Intensity Scale0 aNumerical Tissue Characterization in MS via Standardization of t  aBerkeleycApr 2000  a579  uhttps://www.inf.szte.hu/en/node/101900394nas a2200097   4500008004100000245011300041210006900154260002300223300000900246856004100255       2000                        eng d00aTissue Characterization in Relapsing-remitting and Secondary-progressive MS via Magnetization Transfer Ratio0 aTissue Characterization in Relapsingremitting and Secondaryprogr  aBerkeleycApr 2000  a1189  uhttps://www.inf.szte.hu/en/node/101800345nas a2200085   4500008004100000245009600041210006900137260001200206856004100218       1999                        eng d00aNumerical Tissue Characterization in MS via Standardization of the MR Image Intensity Scale0 aNumerical Tissue Characterization in MS via Standardization of t  c1999///  uhttps://www.inf.szte.hu/en/node/1073