Texture Analysis of MR Images of Patients with Mild Traumatic Brain Injury

Overview

Journal BMC Med Imaging

Publisher Biomed Central

Specialty Radiology

Date 2010 May 14

PMID 20462439

Citations 21

Authors

Kirsi K Holli

Lara Harrison

Prasun Dastidar

Minna Waljas

Suvi Liimatainen

Tiina Luukkaala

Juha Ohman

Seppo Soimakallio

Hannu Eskola

Affiliations

Soon will be listed here.

Abstract

Background: Our objective was to study the effect of trauma on texture features in cerebral tissue in mild traumatic brain injury (MTBI). Our hypothesis was that a mild trauma may cause microstructural changes, which are not necessarily perceptible by visual inspection but could be detected with texture analysis (TA).

Methods: We imaged 42 MTBI patients by using 1.5 T MRI within three weeks of onset of trauma. TA was performed on the area of mesencephalon, cerebral white matter at the levels of mesencephalon, corona radiata and centrum semiovale and in different segments of corpus callosum (CC) which have been found to be sensitive to damage. The same procedure was carried out on a control group of ten healthy volunteers. Patients' TA data was compared with the TA results of the control group comparing the amount of statistically significantly differing TA parameters between the left and right sides of the cerebral tissue and comparing the most discriminative parameters.

Results: There were statistically significant differences especially in several co-occurrence and run-length matrix based parameters between left and right side in the area of mesencephalon, in cerebral white matter at the level of corona radiata and in the segments of CC in patients. Considerably less difference was observed in the healthy controls.

Conclusions: TA revealed significant changes in texture parameters of cerebral tissue between hemispheres and CC segments in TBI patients. TA may serve as a novel additional tool for detecting the conventionally invisible changes in cerebral tissue in MTBI and help the clinicians to make an early diagnosis.

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References

Schad L, Bluml S, Zuna I . MR tissue characterization of intracranial tumors by means of texture analysis. Magn Reson Imaging. 1993; 11(6):889-96. DOI: 10.1016/0730-725x(93)90206-s. View

Mahmoud-Ghoneim D, Toussaint G, Constans J, de Certaines J . Three dimensional texture analysis in MRI: a preliminary evaluation in gliomas. Magn Reson Imaging. 2003; 21(9):983-7. DOI: 10.1016/s0730-725x(03)00201-7. View

Levin H, Williams D, Eisenberg H, High Jr W, Guinto Jr F . Serial MRI and neurobehavioural findings after mild to moderate closed head injury. J Neurol Neurosurg Psychiatry. 1992; 55(4):255-62. PMC: 489036. DOI: 10.1136/jnnp.55.4.255. View

Kjaer L, Ring P, Thomsen C, Henriksen O . Texture analysis in quantitative MR imaging. Tissue characterisation of normal brain and intracranial tumours at 1.5 T. Acta Radiol. 1995; 36(2):127-35. View

Lerski R, Straughan K, Schad L, Boyce D, Bluml S, Zuna I . MR image texture analysis--an approach to tissue characterization. Magn Reson Imaging. 1993; 11(6):873-87. DOI: 10.1016/0730-725x(93)90205-r. View

Holli K, Laaperi A, Harrison L, Luukkaala T, Toivonen T, Ryymin P . Characterization of breast cancer types by texture analysis of magnetic resonance images. Acad Radiol. 2009; 17(2):135-41. DOI: 10.1016/j.acra.2009.08.012. View

Sinson G, Bagley L, Cecil K, Torchia M, McGOWAN J, Lenkinski R . Magnetization transfer imaging and proton MR spectroscopy in the evaluation of axonal injury: correlation with clinical outcome after traumatic brain injury. AJNR Am J Neuroradiol. 2001; 22(1):143-51. PMC: 7975548. View

Herlidou S, Rolland Y, Bansard J, Le Rumeur E, de Certaines J . Comparison of automated and visual texture analysis in MRI: characterization of normal and diseased skeletal muscle. Magn Reson Imaging. 1999; 17(9):1393-7. DOI: 10.1016/s0730-725x(99)00066-1. View

Hofman P, Stapert S, van Kroonenburgh M, Jolles J, de Kruijk J, Wilmink J . MR imaging, single-photon emission CT, and neurocognitive performance after mild traumatic brain injury. AJNR Am J Neuroradiol. 2001; 22(3):441-9. PMC: 7976823. View

10.

Kumar R, Husain M, Gupta R, Hasan K, Haris M, Agarwal A . Serial changes in the white matter diffusion tensor imaging metrics in moderate traumatic brain injury and correlation with neuro-cognitive function. J Neurotrauma. 2009; 26(4):481-95. DOI: 10.1089/neu.2008.0461. View

11.

Mahmoud-Ghoneim D, Cherel Y, Lemaire L, de Certaines J, Maniere A . Texture analysis of magnetic resonance images of rat muscles during atrophy and regeneration. Magn Reson Imaging. 2006; 24(2):167-71. DOI: 10.1016/j.mri.2005.10.002. View

12.

Freeborough P, Fox N . MR image texture analysis applied to the diagnosis and tracking of Alzheimer's disease. IEEE Trans Med Imaging. 1998; 17(3):475-9. DOI: 10.1109/42.712137. View

13.

Collewet G, Strzelecki M, Mariette F . Influence of MRI acquisition protocols and image intensity normalization methods on texture classification. Magn Reson Imaging. 2004; 22(1):81-91. DOI: 10.1016/j.mri.2003.09.001. View

14.

Bonilha L, Kobayashi E, Castellano G, Coelho G, Tinois E, Cendes F . Texture analysis of hippocampal sclerosis. Epilepsia. 2003; 44(12):1546-50. DOI: 10.1111/j.0013-9580.2003.27103.x. View

15.

Teasdale G, Jennett B . Assessment of coma and impaired consciousness. A practical scale. Lancet. 1974; 2(7872):81-4. DOI: 10.1016/s0140-6736(74)91639-0. View

16.

Castellano G, Bonilha L, Li L, Cendes F . Texture analysis of medical images. Clin Radiol. 2004; 59(12):1061-9. DOI: 10.1016/j.crad.2004.07.008. View

17.

Ganeshan B, Miles K, Young R, Chatwin C, Gurling H, Critchley H . Three-dimensional textural analysis of brain images reveals distributed grey-matter abnormalities in schizophrenia. Eur Radiol. 2009; 20(4):941-8. DOI: 10.1007/s00330-009-1605-1. View

18.

Frugier T, Morganti-Kossmann M, OReilly D, McLean C . In situ detection of inflammatory mediators in post mortem human brain tissue after traumatic injury. J Neurotrauma. 2009; 27(3):497-507. DOI: 10.1089/neu.2009.1120. View

19.

Jirak D, Dezortova M, Taimr P, Hajek M . Texture analysis of human liver. J Magn Reson Imaging. 2002; 15(1):68-74. DOI: 10.1002/jmri.10042. View

20.

Posse S, Tedeschi G, Risinger R, Ogg R, Le Bihan D . High speed 1H spectroscopic imaging in human brain by echo planar spatial-spectral encoding. Magn Reson Med. 1995; 33(1):34-40. DOI: 10.1002/mrm.1910330106. View