Quantification of Stretching in the Ventricular Wall and Corpus Callosum and Corticospinal Tracts in Hydrocephalus before and after Ventriculoperitoneal Shunt Operation

In this study, we establish a quantitative model to define the stretching of brain tissue, especially in ventricular walls, corpus callosum (CC) and corticospinal (CS) fiber tracts, and to investigate the correlation between stretching and regional cerebral blood flow (rCBF) before and after ventriculoperitoneal shunt operations. A nonlinear image registration method was used to calculate the degree of displacement and stretching of axonal fiber tracts based on the medical images of six hydrocephalus patients. Also, the rCBF data from the literature was analyzed and correlated with the strain level quantified in the present study. The results showed substantial increased displacement and strain levels in the ventricular walls as well as in the CC and CS fiber tracts on admission. Following shunt operations the displacement as well as the strain levels reduced substantially. A linear correlation was found to exist between strain level and the rCBF. The reduction in postoperative strain levels correlated with the improvement of rCBF. All patients improved clinically except for one patient due to existing dementia. These new quantitative data provide us with new insight into the mechanical cascade of events due to tissue stretching, thereby provide us with more knowledge into understanding of the role of brain tissue and axonal stretching in some of the hydrocephalus clinical symptoms.

[1]  P. V. van Zijl,et al.  Three‐dimensional tracking of axonal projections in the brain by magnetic resonance imaging , 1999, Annals of neurology.

[2]  Derek K. Jones,et al.  Diffusion‐tensor MRI: theory, experimental design and data analysis – a technical review , 2002 .

[3]  Gerhard A. Holzapfel,et al.  Nonlinear Solid Mechanics: A Continuum Approach for Engineering Science , 2000 .

[4]  Janet M. Miller,et al.  Reduction of astrogliosis and microgliosis by cerebrospinal fluid shunting in experimental hydrocephalus , 2007, Cerebrospinal Fluid Research.

[5]  J. Pickard,et al.  Normal pressure hydrocephalus and cerebral blood flow: a review , 2001, Acta neurologica Scandinavica.

[6]  C. W. Cummings,et al.  Cummings otolaryngology--head & neck surgery , 2010 .

[7]  Christian Woiciechowsky,et al.  Callosal and corticospinal tract function in patients with hydrocephalus: a morphometric and transcranial magnetic stimulation study , 1998, Journal of Neurology.

[8]  Douglas H. Smith,et al.  Mechanical breaking of microtubules in axons during dynamic stretch injury underlies delayed elasticity, microtubule disassembly, and axon degeneration , 2010, FASEB journal : official publication of the Federation of American Societies for Experimental Biology.

[9]  J. Pickard,et al.  Pattern of white matter regional cerebral blood flow and autoregulation in normal pressure hydrocephalus. , 2004, Brain : a journal of neurology.

[10]  P. Basser,et al.  In vivo fiber tractography using DT‐MRI data , 2000, Magnetic resonance in medicine.

[11]  N. Ayache,et al.  Fast Non Rigid Matching by Gradient Descent: Study and Improvements of the "Demons" Algorithm , 1999 .

[12]  T Yuasa,et al.  Altered Microstructure in Corticospinal Tract in Idiopathic Normal Pressure Hydrocephalus: Comparison with Alzheimer Disease and Parkinson Disease with Dementia , 2011, American Journal of Neuroradiology.

[13]  Arthur W. Toga,et al.  Stereotaxic white matter atlas based on diffusion tensor imaging in an ICBM template , 2008, NeuroImage.

[14]  P. Basser,et al.  MR diffusion tensor spectroscopy and imaging. , 1994, Biophysical journal.

[15]  H. Holst Organic bioelectrodes in clinical neurosurgery. , 2013 .

[16]  Thomas L. Chenevert Principles of Diffusion-Weighted Imaging (DW-MRI) as Applied to Body Imaging , 2010 .

[17]  B. Morrison,et al.  Experimental mild traumatic brain injury induces functional alteration of the developing hippocampus. , 2010, Journal of neurophysiology.

[18]  D. Le Bihan,et al.  Diffusion tensor imaging: Concepts and applications , 2001, Journal of magnetic resonance imaging : JMRI.

[19]  Nicholas Ayache,et al.  Iconic feature based nonrigid registration: the PASHA algorithm , 2003, Comput. Vis. Image Underst..

[20]  Hans von Holst,et al.  Increased strain levels and water content in brain tissue after decompressive craniotomy , 2012, Acta Neurochirurgica.

[21]  D. Meaney,et al.  Tissue-level thresholds for axonal damage in an experimental model of central nervous system white matter injury. , 2000, Journal of biomechanical engineering.

[22]  J. Gee,et al.  Characterization of regional pulmonary mechanics from serial magnetic resonance imaging data. , 2003, Academic radiology.

[23]  P. Basser,et al.  A simplified method to measure the diffusion tensor from seven MR images , 1998, Magnetic resonance in medicine.

[24]  P. Basser,et al.  Estimation of the effective self-diffusion tensor from the NMR spin echo. , 1994, Journal of magnetic resonance. Series B.

[25]  Nicholas Ayache,et al.  Insight into Efficient Image Registration Techniques and the Demons Algorithm , 2007, IPMI.

[26]  T. Neumann-Haefelin,et al.  Diffusion Tensor Imaging in Patients With Adult Chronic Idiopathic Hydrocephalus , 2010, Neurosurgery.

[27]  S. Mori,et al.  Principles of Diffusion Tensor Imaging and Its Applications to Basic Neuroscience Research , 2006, Neuron.

[28]  Juan Sahuquillo,et al.  Functional and magnetic resonance imaging correlates of corpus callosum in normal pressure hydrocephalus before and after shunting , 2006, Journal of Neurology, Neurosurgery & Psychiatry.

[29]  Xiaogai Li Finite Element and Neuroimaging Techniques toImprove Decision-Making in Clinical Neuroscience , 2012 .

[30]  Marvin Bergsneider,et al.  The Value of Supplemental Prognostic Tests for the Preoperative Assessment of Idiopathic Normal-pressure Hydrocephalus , 2005, Neurosurgery.

[31]  Jean-Philippe Thirion,et al.  Image matching as a diffusion process: an analogy with Maxwell's demons , 1998, Medical Image Anal..

[32]  P. Basser Inferring microstructural features and the physiological state of tissues from diffusion‐weighted images , 1995, NMR in biomedicine.

[33]  Tom Vercauteren,et al.  Diffeomorphic demons: Efficient non-parametric image registration , 2009, NeuroImage.