Abstract
Computer-based analysis of textures in magnetic resonance images provides a higher
sensitivity to textural changes that cannot be recognized by the naked human eye.
Thus, there is a better potential for identifying pathophysiological processes at
an earlier stage or of a different character than even a trained radiologist can find.
In the present study, the potential of texture analysis for in vivo identification
of the administering effect of an anti-inflammatory drug in cerebral stroke in rats
was evaluated.
Twenty-seven Wistar rats underwent middle cerebral artery occlusion resulting in local
ischemic brain infarct. One group of rats received alpha-melanocyte stimulating hormone
(α-MSH) and a control group received saline only. T2-weighted images, apparent diffusion
maps, and T2 maps were recorded by MR. Texture features were calculated in the T2-weighted
images and correlated to the apparent diffusion coefficient (ADC) and the T2 values.
From an array of tested texture features three independent features were tested further.
Two of which were found to provide a significant discriminative classification between
the control and the α-MSH groups. Furthermore, the same two texture features were
significantly correlated to the ADCs. Thus, quantification of texture features can
be helpful in detecting the effects of stroke therapy.
Keywords
To read this article in full you will need to make a payment
Purchase one-time access:
Academic & Personal: 24 hour online accessCorporate R&D Professionals: 24 hour online accessOne-time access price info
- For academic or personal research use, select 'Academic and Personal'
- For corporate R&D use, select 'Corporate R&D Professionals'
Subscribe:
Subscribe to Clinical ImagingAlready a print subscriber? Claim online access
Already an online subscriber? Sign in
Register: Create an account
Institutional Access: Sign in to ScienceDirect
References
- Evaluation of anti-vascular therapy with texture analysis.Anticancer Res. 2005; 25: 3399-3405
- Automated detection of focal cortical dysplasia lesions using computational models of their MRI characteristics and texture analysis.NeuroImage. 2003; 19: 1748-1759
- Multifractal analysis of deep white matter microstructural changes on MRI in relation to early-stage atherosclerosis.NeuroImage. 2006; 32: 1158-1166
- Texture analysis of medical images.Clin Radiol. 2004; 59: 1061-1069
- Texture analysis for image diagnostics.in: Wu HS Einstein AJ Image analysis in medical microscopy and pathology. Research Signpost, Kerala2007: 167-174
- Texture Analysis for Magnetic Resonance Imaging.Med4publishing, Prague2006
- Comparison of automated and visual texture analysis in MRI: characterization of normal and diseased skeletal muscle.Magn Reson Imaging. 1999; 17: 1393-1397
- Distinct patterns of active and non-active plaques using texture analysis on brain NMR images in multiple sclerosis patients: preliminary results.Magn Reson Imaging. 1999; 17: 1261-1267
- Existence of contralateral abnormalities revealed by texture analysis in unilateral intractable hippocampal epilepsy.Magn Reson Imaging. 2001; 19: 1305-1310
- Is magnetic resonance imaging texture analysis a useful tool for cell therapy in vivo monitoring?.Anticancer Res. 2001; 21: 3857-3860
- Remyelination assessment by MRI texture analysis in a cuprizone mouse model.Magn Reson Imaging. 2004; 22: 1139-1144
- Cerebellum segmentation employing texture properties and knowledge based image processing: applied to normal adult controls and patients.Magn Reson Imaging. 2002; 20: 425-429
- Segmentation of bone in clinical knee MRI using texture-based geodesic active contours.in: MICCAI, Lecture Notes in Computer Science. Cambridge, MA, USA1998
- Coupling texture analysis and physiological modeling for liver dynamic MRI interpretation.Conf Proc IEEE Eng Med Biol Soc. 2007; 1: 4223-4226
- Nuclear magnetic resonance (NMR) measurement of the apparent diffusion coefficient (ADC) of tissue water and its relationship to cell volume changes in pathological states.Neurochem Int. 2004; 45: 569-582
- Ischemic injury detected by diffusion imaging 11 minutes after stroke.Ann Neurol. 2005; 58: 462-465
- Imaging of acute stroke.Lancet Neurol. 2006; 5: 755-768
- Early changes in water diffusion, perfusion, T1, and T2 during focal cerebral ischemia in the rat studied at 8.5 T.Magn Reson Med. 1999; 41: 479-485
- Characterization of experimental ischemic brain edema utilizing proton nuclear magnetic resonance imaging.J Cereb Blood Flow Metab. 1986; 6: 212-221
- Comparison of diffusion- and T2-weighted MRI for the early detection of cerebral ischemia and reperfusion in rats.Magn Reson Med. 1991; 18: 39-50
- Edema and brain trauma.Neuroscience. 2004; 129: 1021-1029
- Experimental brain infarcts in cats: II. Ischemic brain edema.Stroke. 1980; 11: 593-601
- Inflammatory mediators and stroke: new opportunities for novel therapeutics.J Cereb Blood Flow Metab. 1999; 19: 819-834
- Mechanisms of antiinflammatory action of the neuroimmunomodulatory peptide alpha-MSH.Ann N Y Acad Sci. 1998; 840: 373-380
- Reduction of ischemic stroke in rat brain by alpha melanocyte stimulating hormone.Neuropeptides. 2008; 42: 331-338
- A comparison of seven techniques for choosing subsets of pattern recognition properties.IEEE Trans Comput. 1971; 20: 1023-1031
- Pattern Classification, A Unified View of Statistical and Neural Approaches.John Wiley & Sons, New York1996
- Introduction to Statistical Pattern Recognition.2nd ed. Academic Press, New York1990
- Artificial neural networks for feature extraction and multivariate data projection.IEEE Trans Neural Netw. 1995; 6: 296-316
- Statistical pattern recognition: A review.IEEE Trans Pattern Anal Mach Intell. 2000; 22: 4-37
Article info
Publication history
Published online: May 05, 2009
Accepted:
February 19,
2009
Received:
December 1,
2008
Footnotes
☆This work was supported by the Aarhus University Research Foundation and the Danish Helga and Peter Kornings Foundation. This research was partially supported by the MIC, Korea, under the IT Foreign Specialist Inviting Program supervised by the Institute of Information Technology Advancement (IITA).
Identification
Copyright
© 2010 Published by Elsevier Inc. All rights reserved.
