PMID- 15780914
OWN - NLM
STAT- MEDLINE
DCOM- 20050601
LR  - 20061115
IS  - 1090-7807 (Print)
IS  - 1090-7807 (Linking)
VI  - 173
IP  - 2
DP  - 2005 Apr
TI  - The use of multivariate MR imaging intensities versus metabolic data from MR 
      spectroscopic imaging for brain tumour classification.
PG  - 218-28
AB  - This study investigated the value of information from both magnetic resonance 
      imaging and magnetic resonance spectroscopic imaging (MRSI) to automated 
      discrimination of brain tumours. The influence of imaging intensities and 
      metabolic data was tested by comparing the use of MR spectra from MRSI, MR 
      imaging intensities, peak integration values obtained from the MR spectra and a 
      combination of the latter two. Three classification techniques were objectively 
      compared: linear discriminant analysis, least squares support vector machines 
      (LS-SVM) with a linear kernel as linear techniques and LS-SVM with radial basis 
      function kernel as a nonlinear technique. Classifiers were evaluated over 100 
      stratified random splittings of the dataset into training and test sets. The area 
      under the receiver operating characteristic (ROC) curve (AUC) was used as a 
      global performance measure on test data. In general, all techniques obtained a 
      high performance when using peak integration values with or without MR imaging 
      intensities. For example for low- versus high-grade tumours, low- versus 
      high-grade gliomas and gliomas versus meningiomas, the mean test AUC was higher 
      than 0.91, 0.94, and 0.99, respectively, when both MR imaging intensities and 
      peak integration values were used. The use of metabolic data from MRSI 
      significantly improved automated classification of brain tumour types compared to 
      the use of MR imaging intensities solely.
FAU - Devos, A
AU  - Devos A
AD  - K.U. Leuven, ESAT-SCD (SISTA), Leuven, Belgium. adevos@esat.kuleuven.ac.be
FAU - Simonetti, A W
AU  - Simonetti AW
FAU - van der Graaf, M
AU  - van der Graaf M
FAU - Lukas, L
AU  - Lukas L
FAU - Suykens, J A K
AU  - Suykens JA
FAU - Vanhamme, L
AU  - Vanhamme L
FAU - Buydens, L M C
AU  - Buydens LM
FAU - Heerschap, A
AU  - Heerschap A
FAU - Van Huffel, S
AU  - Van Huffel S
LA  - eng
PT  - Comparative Study
PT  - Journal Article
PT  - Research Support, Non-U.S. Gov't
PL  - United States
TA  - J Magn Reson
JT  - Journal of magnetic resonance (San Diego, Calif. : 1997)
JID - 9707935
SB  - IM
MH  - Brain Chemistry
MH  - Brain Neoplasms/*diagnosis/*metabolism
MH  - Diagnosis, Computer-Assisted
MH  - Discriminant Analysis
MH  - Humans
MH  - Least-Squares Analysis
MH  - Magnetic Resonance Imaging/*methods
MH  - Magnetic Resonance Spectroscopy/*methods
MH  - Pattern Recognition, Automated
MH  - ROC Curve
EDAT- 2005/03/23 09:00
MHDA- 2005/06/02 09:00
CRDT- 2005/03/23 09:00
PHST- 2004/09/21 00:00 [received]
PHST- 2004/12/20 00:00 [revised]
PHST- 2005/03/23 09:00 [pubmed]
PHST- 2005/06/02 09:00 [medline]
PHST- 2005/03/23 09:00 [entrez]
AID - S1090-7807(04)00415-X [pii]
AID - 10.1016/j.jmr.2004.12.007 [doi]
PST - ppublish
SO  - J Magn Reson. 2005 Apr;173(2):218-28. doi: 10.1016/j.jmr.2004.12.007.