Magnetic Resonance Imaging 33 (2015) 531–536
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Diffusional kurtosis imaging in hydrocephalus Yafell Serulle ⁎, Rahul V. Pawar, Jan Eubig, Els Fieremans, Steven E. Kong, Ilena C. George, Christopher Morley, James S. Babb, Ajax E. George Center for Biomedical Imaging, Department of Radiology, NYU Langone Medical Center, 660 First Avenue, New York, NY 10016
a r t i c l e
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Article history: Received 5 June 2014 Accepted 10 February 2015 Keywords: Hydrocephalus Leukoaraiosis Diffusional kurtosis imaging Diffusion tensor imaging
a b s t r a c t Purpose: Diffusional kurtosis imaging is an advanced diffusion magnetic resonance imaging method that yields, in addition to conventional diffusion information, non-Gaussian diffusion effects, which may allow a more comprehensive characterization of tissue microstructure. The purpose of this study is to use diffusional kurtosis to assess white matter integrity in patients with hydrocephalus and to determine whether changes in kurtosis correlate with the severity of hydrocephalus and leukoaraiosis (LA), a commonly seen comorbidity in hydrocephalus. Methods: 26 patients with imaging evidence of hydrocephalus and 26 age- and sex- matched subjects with normal ventricular size were retrospectively analyzed. Standard diffusion tensor imaging and diffusional kurtosis metrics were compared between the two groups. Correlation between kurtosis and severity of hydrocephalus and presence and severity of LA was determined. Results: Hydrocephalus patients relative to controls demonstrated statistically significant decrease in all kurtosis metrics in most brain regions studied. The severity of hydrocephalus was associated with greater decrease in kurtosis in the corpus callosum. There was more LA in the hydrocephalus group, and severity of LA was associated with decrease in kurtosis. After controlling for the degree of LA, kurtosis was still decreased in hydrocephalus relative to the controls. Conclusion: Diffusional kurtosis imaging detects microstructural changes in the white matter of patients with hydrocephalus. Our results suggest that hydrocephalus plays a role in altering white matter integrity. © 2015 Elsevier Inc. All rights reserved.
1. Introduction Hydrocephalus is a common condition present in both the adult and pediatric population. In communicating hydrocephalus, the ventricular system is enlarged without the presence of obstruction. In the adult population, chronic communicating hydrocephalus can develop as a consequence of prior central nervous system pathology such as subarachnoid hemorrhage, meningitis or traumatic brain injury. More commonly, idiopathic normal pressure hydrocephalus (NPH), a disorder characterized by the triad of motor deficits, cognitive impairment and urinary incontinence, can develop in older adults [1]. Neuropathologic studies of chronic hydrocephalus have suggested the presence of white matter damage [2–4], presumably resulting from mechanical pressure due to ventricular enlargement and metabolic derangement. Diffusion tensor imaging (DTI) has been used to detect microstructural changes in the periventricular white matter of patients with hydrocephalus [5]. Diffusional kurtosis imaging ⁎ Corresponding author at: Department of Radiology, University of Maryland Medical Center, 22 S. Greene St., Baltimore, MD 21201. Tel.: +1 410 328 5112. E-mail address: [email protected] (Y. Serulle). http://dx.doi.org/10.1016/j.mri.2015.02.009 0730-725X/© 2015 Elsevier Inc. All rights reserved.
(DKI), an extension of DTI, is a recently developed technique sensitive to non-Gaussian diffusion effects and therefore to microstructural changes in the brain [6]. The non-Gaussian diffusion effects in the brain are believed to arise from diffusion restriction by barriers, such as cell membranes and organelles, as well as the presence of distinct water compartments with differing diffusivities. The term ‘leukoaraiosis’ (LA) [7] refers to patchy or diffuse areas of hypodensity on computed tomography or hyperintensity on T2-weighted magnetic resonance imaging (MRI), with most evidence suggesting that these lesions may be the result of ischemic injury to the brain secondary to microvascular disease [8]. These macroscopic cerebral white matter changes are usually associated with aging and are present with high prevalence in patients with chronic hydrocephalus [9]. It is uncertain whether these white matter lesions correlate with microstructural changes measured with diffusion MRI techniques. In the current study, we used DKI to evaluate the white matter microstructural integrity in a group of adult patients with communicating hydrocephalus and compare them to subjects with normal ventricular size. Our primary objective was to determine if there are alterations of white matter kurtosis in patients with enlarged ventricles, and if there is correlation between kurtosis and the
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Y. Serulle et al. / Magnetic Resonance Imaging 33 (2015) 531–536
severity of ventriculomegaly. Additionally, we determined whether the severity of LA, which is commonly seen in this patient population, correlates with changes in kurtosis. 2. Materials & methods 2.1. Subjects This retrospective, anonymized, single-center, Health Insurance Portability and Accountability Act-compliant study was exempt from institutional review board approval. We reviewed MRI scans from 26 patients with hydrocephalus (14 females, 12 males) and 26 patients with normal ventricle size (15 females, 11 males). Patients were matched for sex and age. Patients were selected from a database of potential candidates generated by a computer search for patients who had undergone MRI scans that included DKI imaging, and in addition, had received a radiologic diagnosis of hydrocephalus, communicating hydrocephalus, NPH or normal. All resulting MRI scans were then reviewed. Subjects were excluded that demonstrated additional pathologies such as tumor, infarction, or hematoma. The selected hydrocephalus patients fulfilled radiological diagnostic criteria including moderate or greater ventriculomegaly, enlargement of the third ventricle and temporal horns, upward bowing and stretching of the corpus callosum, flattening of the roof of the third ventricle, compression of the interpeduncular cistern and either compression, or variable dilatation of cortical sulci and fissures. The control group had normal brain MRI scans. Two neuroradiologists, with 5 and 40 years of academic experience, respectively, agreed upon the radiologic findings. 2.2. Imaging techniques and post-processing All patients were scanned on a Siemens © 1.5 T magnet (Avanto ©). Diffusion-weighted data were obtained using an axial single-shot echo-planar sequence with the following imaging parameters: repetition time/echo time = 4500/96 ms; matrix size = 82 × 82; 32 slices; voxel size = 2.7 × 2.7 × 5 mm 3. B values of 0, 1000 and 2000 mm −2 s were applied over 30 directions corresponding to the vertices of a truncated icosahedron.
The post-processing of the data was performed using in-house software programmed in Matlab (The MathWorks, Inc., Natick, MA, USA) based on methods previously described [10]. Briefly, the software generates the parametric maps of mean diffusivity (MD), radial diffusivity (RD), axial diffusivity (AD), fractional anisotropy (FA), mean kurtosis (MK), radial kurtosis (RK) and axial kurtosis (AK) (Fig. 1). All of these maps are estimated from the diffusion and kurtosis tensors. MK is defined as the average of the kurtosis over all possible diffusion directions. AK is defined, in analogy with AD, as the kurtosis in the direction of the diffusion tensor eigenvector with the largest diffusion eigenvalue, and RK is defined as the average of the kurtosis over all directions perpendicular to the diffusion eigenvector with the largest eigenvalue. In white matter, the axial direction is typically aligned with the axon bundles [11]. Parameters were measured in manually drawn regions of interest (ROIs) matching the size of the anatomical ROI. ROIs were placed symmetrically within the subcortical white matter of the frontal and parietal lobes, and genu and splenium of the corpus callosum. At the level of the third ventricle, ROIs were symmetrically placed within the posterior limbs of the internal capsules. All ROIs were placed by a neuroradiology fellow. Additionally, the ROIs were also independently drawn in all the same subjects by a trained medical student and reviewed by a neuroradiology attending. There were no statistical differences in the measures obtained by the two different readers. Ventricular volume was generated in three steps using FireVoxel [12]: (a) Bridge Burner algorithm was used to segment the whole brain excluding cerebrospinal fluid [12]; (b) morphologic closure of the brain mask was performed to include the ventricular spaces; (c) 3D set difference between (b) and (a) was taken as ventricular volume. Ventricular volumes were normalized to brain size. The severity of LA was graded on fluid-attenuation inversion recovery and T2-weighted images as either none = no lesions; mild = multiple focal periventricular lesions; moderate = multiple focal periventricular and subcortical lesions; severe = multiple diffuse confluent lesions. Grading was performed by two different neuroradiologists, who were blinded to the diffusion metrics of the patients. 2.3. Statistical analysis An unequal variance t-test was used to compare the hydrocephalus group and controls with respect to metric values
Fig. 1. Representative transaxial B0 images (left column) and MK maps (right column) from normal controls (a) and hydrocephalus (b).
Y. Serulle et al. / Magnetic Resonance Imaging 33 (2015) 531–536
acquired within every ROI. Pearson correlation test was used to determine whether severity of hydrocephalus and LA correlated with changes in diffusivity and kurtosis metrics.
3. Results There were no significant differences in age (hydrocephalus group: 76.2 ± 1.5; control group: 74.1 ± 1.4; p = 0.3) and gender distribution between the hydrocephalus and normal control groups. Fig. 2 shows the means of the diffusivity metrics for the two groups for each ROI; it also indicates the indices that were found to be statistically significant after t-test comparison. Relative to the control group, hydrocephalus patients showed significant mean and radial diffusivity increases in all brain regions examined except for the bilateral internal capsule. Axial diffusivity was significantly increased in all brain regions except for the bilateral internal capsule and splenium of the corpus callosum. FA in hydrocephalus was decreased in all brain regions except for the bilateral internal capsule when compared to the control group. Fig. 3 shows the means of the kurtosis metrics for the two groups with the indices that were found to be statistically significant after t-test. Relative to the control group, hydrocephalus patients showed significant decrease in mean kurtosis in all brain regions. Radial kurtosis was decreased in all brain regions except for the bilateral internal capsule. Axial kurtosis was decreased in all regions except
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for the genu and splenium of the corpus callosum and the right internal capsule. Ventricular size was quantified in the hydrocephalus group and ventricular volume was correlated with the different diffusivity and kurtosis metrics (Tables 1 and 2). There was a significant inverse correlation between ventricular volume and both mean (r = − 0.4, p b 0.05) and radial kurtosis (r = − 0.41, p b 0.05) in the genu of the corpus callosum. There was a significant direct correlation between ventricular volume and mean (r = 0.44, p b 0.04) and radial (r = 0.45, p b 0.05) diffusivity at the genu of the corpus callosum. Additionally, both mean (r = 0.5, p b 0.05) and radial (r = 0.52, p b 0.05) diffusivities were also directly correlated with ventricular volumes. FA was inversely related to ventricular volumes in both the genu (r = − 0.46, p b 0.05) and splenium (r = − 0.43, p b 0.05). Table 3 demonstrates a higher prevalence of white matter lesions in the hydrocephalus group (21/26) compared to controls (14/26). There was a significant correlation between severity of LA and decreased kurtosis in both the hydrocephalus and control group across all brain regions (Fig. 4) with more severe LA associated with lower kurtosis. To determine whether the difference in kurtosis between controls and hydrocephalus patients depended on the more severe LA seen in the hydrocephalus group, we controlled for the degree of LA and compared the kurtosis metrics between groups with similar severity of white matter disease (i.e. hydrocephalus patients with no evidence for LA vs controls with no evidence for LA). Hydrocephalus patients without evidence of LA demonstrated
Fig. 2. Comparison of mean diffusivity, radial diffusion, axial diffusion and fractional anisotropy between hydrocephalus and normal controls for the different brain regions. RF = right frontal, LF = left frontal, RP = right parietal, LP = left parietal, Ge = genu, Sp = splenium, RIC = right internal capsule, LIC = left internal capsule. * = p b 0.05; ** = p b 0.005; *** = p b 0.001.
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Y. Serulle et al. / Magnetic Resonance Imaging 33 (2015) 531–536 Table 1 Correlation of kurtosis measures with ventricular volume in patients with hydrocephalus. Measure
Region
R
P
AK AK AK AK AK AK AK AK MK MK MK MK MK MK MK MK RK RK RK RK RK RK RK RK
Ge LF LIC LP RF RIC RP Sp Ge LF LIC LP RF RIC RP Sp Ge LF LIC LP RF RIC RP Sp
0.02 0.06 −0.19 −0.23 0.03 0.06 −0.22 0.31 −0.40 −0.21 0.12 −0.08 −0.06 0.25 −0.19 −0.14 −0.41 −0.23 0.24 −0.20 −0.02 0.03 −0.30 −0.21
NS NS NS NS NS NS NS NS p b 0.05 NS NS NS NS NS NS NS p b 0.05 NS NS NS NS NS NS NS
AK = axial kurtosis, MK = mean kurtosis, RK = radial kurtosis, Ge = genu, LF = left frontal, LIC = left internal capsule, LP = left parietal, RF = right frontal, RIC = right internal capsule, RP = right parietal, Sp = splenium.
finding of this study is a significant difference of DKI parameters between patients with hydrocephalus relative to controls. DTI is a conventional diffusion weighted imaging method which uses sensitizing gradients along numerous spatial directions that Table 2 Correlation between diffusivity measures and ventricular volume in patients with hydrocephalus.
Fig. 3. Comparison of mean kurtosis, radial kurtosis and axial kurtosis between hydrocephalus and normal controls for the different brain regions. RF = right frontal, LF = left frontal, RP = right parietal, LP = left parietal, Ge = genu, Sp = splenium, RIC = right internal capsule, LIC = left internal capsule. * = p b 0.05; ** = p b 0.005; *** = p b 0.001.
decreased kurtosis in most brain regions relative to the control group (Fig. 5). Similar results were obtained for patients with mild, moderate and severe LA (data not shown). 4. Discussion Evidence suggests that brain damage in hydrocephalus occurs primarily on the periventricular white matter [13]. Up to a certain time point, the white matter changes are believed to be reversible. However, permanent atrophy, first of the white matter and then of the cortex, can develop [14]. The purpose of the current study was to assess the integrity of the white matter in patients with hydrocephalus using a recently-developed diffusion technique, DKI. The major
Measure
Region
R
P
AD AD AD AD AD AD AD AD MD MD MD MD MD MD MD MD RD RD RD RD RD RD RD RD FA FA FA FA FA FA FA FA
Ge LF LIC LP RF RIC RP Sp Ge LF LIC LP RF RIC RP Sp Ge LF LIC LP RF RIC RP Sp Ge LF LIC LP RF RIC RP Sp
0.24 0.09 0.03 −0.08 −0.02 0.18 0.00 0.39 0.44 0.00 −0.01 0.03 0.09 0.18 0.09 0.50 0.45 −0.05 −0.05 0.05 0.14 0.03 0.12 0.52 −0.46 0.16 0.04 −0.12 −0.27 0.04 −0.22 −0.43
NS NS NS NS NS NS NS NS pb NS NS NS NS NS NS pb pb NS NS NS NS NS NS pb pb NS NS NS NS NS NS pb
0.05
0.05 0.05
0.05 0.05
0.05
AD = axial diffusivity, MD = mean diffusivity, RD = radial diffusivity, FA = fractional anisotropy.
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Table 3 Degree of leukoariaosis in patients with hydrocephalus and controls.
None Mild Moderate Severe
Control
Hydrocephalus
12 8 4 2
5 14 5 2
yield the diffusion tensor [15], providing directional information on the neuroarchitectural orientation of the white matter tracts. DTI metrics include the MD, and FA, which are used to quantify and characterize the inherent anisotropy of white matter [16]. The underlying assumption in DTI is that water diffusion occurs in a free and unrestricted environment, thereby obeying a Gaussian probability distribution function. In recent literature, DTI has been shown to be relatively effective in characterizing hydrocephalus. Kanno et al. [17], demonstrated that on average, MD and FA of supratentorial white matter were increased and decreased, respectively, in patients with idiopathic NPH. Our data yielded similar results, confirming a generalized increase in diffusivity and reduction of FA. In biologic tissues, complex intra- and extracellular structures exist that hinder and restrict water diffusion, technically making water diffusivity an inherently non-Gaussian process [6]. Since kurtosis is a measure of deviation, or convexity, from a Gaussian probability profile, DKI allows, in addition to the diffusion tensor, formulation of a fourth-order kurtosis tensor that allows for more accurate description of the diffusion MRI signal in biological tissue. The non-Gaussian diffusion metrics (kurtosis) can be theoretically linked to restricted diffusion and diffusional heterogeneity [18] and may provide more information about tissue compartments and tissue heterogeneity, compared with conventional DTI metrics. Additionally, by quantifying diffusional non-Gaussianity, DKI is suitable for evaluating both anisotropic and non-anisotropic (isotropic) structures, such as gray matter [19]. Ultimately, kurtosis is believed to reflect neural tissue microstructural complexity. Preliminary application of DKI to ischemic stroke, aging, Alzheimer’s disease, schizophrenia and attention deficit hyperactivity disorder has been promising [20–22]. In this study, we show that there are statistically significant alterations of white matter kurtosis in patients with hydrocephalus. All kurtosis metrics were significantly reduced in most ROIs, which included the corpus callosum and periventricular white matter. Mean kurtosis was decreased in all ROIs measured, whereas radial kurtosis measured in the genu of the corpus callosum showed the
Fig. 4. Correlation of DKI with severity of LA. Scatterplot shows correlation between severity of LA and mean kurtosis in the frontal region (taken as a representative result) of hydrocephalus patients. R = −0.74, p b 0.001. Note that similar results were obtained in multiple other brain regions (see Table 4).
Fig. 5. Comparison of mean kurtosis between hydrocephalus and normal controls with no evidence for LA. RF = right frontal, LF = left frontal, RP = right parietal, LP = left parietal, Ge = genu, Sp = splenium, RIC = right internal capsule, LIC = left internal capsule. * = p b 0.05; ** = p b 0.005; *** = p b 0.001.
largest individual difference between controls and hydrocephalus. Additionally, we found an association between larger ventricular volumes and decreased mean and radial kurtosis in the genu of the corpus callosum, but not in the remaining brain regions queried, suggesting that fibers at the genu may be particularly sensitive to the degree of ventricular enlargement. RK has been shown to correlate with intra-axonal water fraction [23], therefore our observation of decreased RK in hydrocephalus may be related to an increased extra-axonal water fraction (edema) or possibly demyelination and/or axonal loss. It seems to follow that diminished white matter kurtosis in hydrocephalus reflects a decrease in the microstructural complexity of functionally relevant white matter. A white matter model based upon DKI metrics has
Table 4 Correlation between kurtosis measures and degree of leukoariaosis in patients with hydrocephalus. Measure
Region
R
P
AK AK AK AK AK AK AK AK MK MK MK MK MK MK MK MK RK RK RK RK RK RK RK RK
Ge LF LIC LP RF RIC RP Sp Ge LF LIC LP RF RIC RP Sp Ge LF LIC LP RF RIC RP Sp
−0.25 −0.41 −0.33 −0.58 −0.48 −0.25 −0.73 −0.14 −0.28 −0.62 −0.4 −0.72 −0.74 −0.46 −0.72 −0.05 −0.26 −0.48 −0.2 −0.62 −0.64 −0.61 −0.54 −0.27
NS pb NS pb pb NS pb NS NS pb pb pb pb pb pb NS NS pb NS pb pb pb pb NS
0.05 0.05 0.05 0.05
0.05 0.05 0.05 0.05 0.05 0.05
0.05 0.05 0.05 0.05 0.05
AK = axial kurtosis, MK = mean kurtosis, RK = radial kurtosis, Ge = genu, LF = left frontal, LIC = left internal capsule, LP = left parietal, RF = right frontal, RIC = right internal capsule, RP = right parietal, Sp = splenium.
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been devised that may help explain the role myelin dysfunction plays in neurodegenerative disorders and hydrocephalus [23]. Recent research demonstrates similar changes in diffusivity, kurtosis, and FA in the plaques of multiple sclerosis suggesting the white matter alterations in hydrocephalus may at least in part be due to loss of myelin [24]. LA is considered a macroscopic manifestation of white matter damage due to microvascular disease, and is seen as increased signal in the white matter in T2-weighted and fluid-attenuation inversion recovery images. It is well documented that there is increased incidence of LA in patients with larger ventricles [25,26], as also demonstrated in our cohort. Previous studies have shown increased MD and reduced FA in patients with LA [27,28]. In the current study, we also found a strong correlation between LA and kurtosis metrics. More importantly, we found that while LA is associated with decreased kurtosis, the effect of hydrocephalus on kurtosis is independent of the effects LA. Our study has several limitations. We did not evaluate the relation between patients’ clinical status and DKI metrics or degree of hydrocephalus, as our initial objective was to first establish a relation between enlarged ventricles and white matter integrity. Thus, we selected patients based only on imaging features and not on clinical presentation. It is known that enlarged ventricles can be a manifestation of a variety of neurodegenerative diseases; therefore it is possible that our hydrocephalus group may represent a heterogeneous group in regards to the underlying etiology of the hydrocephalus. Moreover, some of these patients may be asymptomatic. Correlation between DKI metrics and clinical symptoms would be very important to further understand the value of DKI in the different pathologies responsible for hydrocephalus. 5. Conclusions Statistically significant deficits of white matter kurtosis are demonstrated in patients with hydrocephalus. All kurtosis metrics were significantly reduced in hydrocephalus relative to the control group. References [1] Hebb AO, Cusimano MD. Idiopathic normal pressure hydrocephalus: a systematic review of diagnosis and outcome. Neurosurgery 2001;49(5):1166–84 [discussion 1184–6]. [2] Akai K, Uchiqasaki S, Tanaka U, Komatsu A. Normal pressure hydrocephalus. Neuropathological study. Acta Pathol Jpn 1987;37(1):97–110. [3] Ding Y, McAllister JP, Yao B, Yan N, Canady Al. Axonal damage associated with enlargement of ventricles during hydrocephalus: a silver impregnation study. Neurol Res 2001;23(6):581–7. [4] Del Bigio MR, Wilson MJ, Enno T. Chronic hydrocephalus in rats and humans: white matter loss and behavior changes. Ann Neurol 2003;53(3):337–46. [5] Hattingen E, Jurcoane A, Melber J, Blasel S, Zanella FE, Neumann-Haefelin T, et al. Diffusion tensor imaging in patients with adult chronic idiopathic hydrocephalus. Neurosurgery 2010;66(5):917–24.
[6] Wu EX, Cheung MM. MR diffusion kurtosis imaging for neural tissue characterization. NMR Biomed 2010;23(7):836–48. [7] Hachinski VC, Potter P, Merskey H. Leuko-araiosis. Arch Neurol 1987;44(1): 21–3. [8] Pantoni L, Garcia JH. The significance of cerebral white matter abnormalities 100 years after Binswanger's report. A review. Stroke 1995;26(7):1293–301. [9] Pantoni L, Garcia JH. Pathogenesis of leukoaraiosis: a review. Stroke 1997;28(3): 652–9. [10] Tabesh A, Jensen JH, Ardekani BA, Helpern JA. Estimation of tensors and tensorderived measures in diffusional kurtosis imaging. Magn Reson Med 2011;65(3): 823–36. [11] Jensen JH, Falangola MF, Hu C, Tabesh A, Rapalino O, Lo C, et al. Preliminary observations of increased diffusional kurtosis in human brain following recent cerebral infarction. NMR Biomed 2011;24(5):452–7. [12] Mikheev A, Nevsky G, Govindan S, Grossman R, Rusinek H. Fully automatic segmentation of the brain from T1-weighted MRI using Bridge Burner algorithm. J Magn Reson Imaging 2008;27(6):1235–41. [13] Del Bigio MR. Neuropathological changes caused by hydrocephalus. Acta Neuropathol 1993;85(6):573–85. [14] Del Bigio MR. Cellular damage and prevention in childhood hydrocephalus. Brain Pathol 2004;14(3):317–24. [15] Basser PJ. Inferring microstructural features and the physiological state of tissues from diffusion-weighted images. NMR Biomed 1995;8(7–8):333–44. [16] Mascalchi M, Filippi M, Floris R, FOnda C, Gasparotti R, Villari N. Diffusionweighted MR of the brain: methodology and clinical application. Radiol Med 2005;109(3):155–97. [17] Kanno S, Abe N, Saito M, Takaqi M, Nishio Y, Hayashi A, et al. White matter involvement in idiopathic normal pressure hydrocephalus: a voxel-based diffusion tensor imaging study. J Neurol 2011;258(11):1949–57. [18] Jensen HH, Helpern JA, Ramani A, Lu H, Kaczynski K. Diffusional kurtosis imaging: the quantification of non-Gaussian water diffusion by means of magnetic resonance imaging. Magn Reson Med 2005;53(6):1432–40. [19] Jensen JH, Helpern JA. MRI quantification of non-Gaussian water diffusion by kurtosis analysis. NMR Biomed 2010;23(7):698–710. [20] Falangola MF, Jensen JH, Babb JS, Hu C, Castellanos FX, Di Martino A, et al. Agerelated non-Gaussian diffusion patterns in the prefrontal brain. J Magn Reson Imaging 2008;28(6):1345–50. [21] Fieremans E, Benitez A, Jensen JH, Falangola MF, Tabesh A, Deardorff RL, et al. Novel white matter tract integrity metrics sensitive to Alzheimer disease progression. AJNR Am J Neuroradiol 2013;34:2105–12. [22] Helpern JA, Adisetiyo V, Falangola MF, Hu C, Di Martino A, Williams K, et al. Preliminary evidence of altered gray and white matter microstructural development in the frontal lobe of adolescents with attention-deficit hyperactivity disorder: a diffusional kurtosis imaging study. J Magn Reson Imaging 2011; 33(1):17–23. [23] Fieremans E, Jensen JH, Helpern JA. White matter characterization with diffusional kurtosis imaging. Neuroimage 2011;58(1):177–88. [24] Raz E, Bester M, Sigmund EE, Tabesh A, Babb JS, Jaggi H, et al. A better characterization of spinal cord damage in multiple sclerosis: a diffusional kurtosis imaging study. AJNR Am J Neuroradiol 2013;34(9):1846–52. [25] Bradley WG, Whittemore AR, Watanabe AS, Davis SJ, Teresi LM, Homyak M. Association of deep white matter infarction with chronic communicating hydrocephalus: implications regarding the possible origin of normal-pressure hydrocephalus. AJNR Am J Neuroradiol 1991;12(1):31–9. [26] Tullberg M, Jensen C, Ekholm S, Wikkelsø C. Normal pressure hydrocephalus: vascular white matter changes on MR images must not exclude patients from shunt surgery. AJNR Am J Neuroradiol 2001;22(9):1665–73. [27] O'Sullivan M, Morris RG, Huckstep B, Jones DK, Williams SC, Markus HS. Diffusion tensor MRI correlates with executive dysfunction in patients with ischaemic leukoaraiosis. J Neurol Neurosurg Psychiatry 2004;75(3):441–7. [28] O'Sullivan M, Summers PE, Jones DK, Jarosz JM, Williams SC, Markus HS. Normalappearing white matter in ischemic leukoaraiosis: a diffusion tensor MRI study. Neurology 2001;57(12):2307–10.
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Diffusional kurtosis imaging in hydrocephalus Yafell Serulle ⁎, Rahul V. Pawar, Jan Eubig, Els Fieremans, Steven E. Kong, Ilena C. George, Christopher Morley, James S. Babb, Ajax E. George Center for Biomedical Imaging, Department of Radiology, NYU Langone Medical Center, 660 First Avenue, New York, NY 10016
a r t i c l e
i n f o
Article history: Received 5 June 2014 Accepted 10 February 2015 Keywords: Hydrocephalus Leukoaraiosis Diffusional kurtosis imaging Diffusion tensor imaging
a b s t r a c t Purpose: Diffusional kurtosis imaging is an advanced diffusion magnetic resonance imaging method that yields, in addition to conventional diffusion information, non-Gaussian diffusion effects, which may allow a more comprehensive characterization of tissue microstructure. The purpose of this study is to use diffusional kurtosis to assess white matter integrity in patients with hydrocephalus and to determine whether changes in kurtosis correlate with the severity of hydrocephalus and leukoaraiosis (LA), a commonly seen comorbidity in hydrocephalus. Methods: 26 patients with imaging evidence of hydrocephalus and 26 age- and sex- matched subjects with normal ventricular size were retrospectively analyzed. Standard diffusion tensor imaging and diffusional kurtosis metrics were compared between the two groups. Correlation between kurtosis and severity of hydrocephalus and presence and severity of LA was determined. Results: Hydrocephalus patients relative to controls demonstrated statistically significant decrease in all kurtosis metrics in most brain regions studied. The severity of hydrocephalus was associated with greater decrease in kurtosis in the corpus callosum. There was more LA in the hydrocephalus group, and severity of LA was associated with decrease in kurtosis. After controlling for the degree of LA, kurtosis was still decreased in hydrocephalus relative to the controls. Conclusion: Diffusional kurtosis imaging detects microstructural changes in the white matter of patients with hydrocephalus. Our results suggest that hydrocephalus plays a role in altering white matter integrity. © 2015 Elsevier Inc. All rights reserved.
1. Introduction Hydrocephalus is a common condition present in both the adult and pediatric population. In communicating hydrocephalus, the ventricular system is enlarged without the presence of obstruction. In the adult population, chronic communicating hydrocephalus can develop as a consequence of prior central nervous system pathology such as subarachnoid hemorrhage, meningitis or traumatic brain injury. More commonly, idiopathic normal pressure hydrocephalus (NPH), a disorder characterized by the triad of motor deficits, cognitive impairment and urinary incontinence, can develop in older adults [1]. Neuropathologic studies of chronic hydrocephalus have suggested the presence of white matter damage [2–4], presumably resulting from mechanical pressure due to ventricular enlargement and metabolic derangement. Diffusion tensor imaging (DTI) has been used to detect microstructural changes in the periventricular white matter of patients with hydrocephalus [5]. Diffusional kurtosis imaging ⁎ Corresponding author at: Department of Radiology, University of Maryland Medical Center, 22 S. Greene St., Baltimore, MD 21201. Tel.: +1 410 328 5112. E-mail address: [email protected] (Y. Serulle). http://dx.doi.org/10.1016/j.mri.2015.02.009 0730-725X/© 2015 Elsevier Inc. All rights reserved.
(DKI), an extension of DTI, is a recently developed technique sensitive to non-Gaussian diffusion effects and therefore to microstructural changes in the brain [6]. The non-Gaussian diffusion effects in the brain are believed to arise from diffusion restriction by barriers, such as cell membranes and organelles, as well as the presence of distinct water compartments with differing diffusivities. The term ‘leukoaraiosis’ (LA) [7] refers to patchy or diffuse areas of hypodensity on computed tomography or hyperintensity on T2-weighted magnetic resonance imaging (MRI), with most evidence suggesting that these lesions may be the result of ischemic injury to the brain secondary to microvascular disease [8]. These macroscopic cerebral white matter changes are usually associated with aging and are present with high prevalence in patients with chronic hydrocephalus [9]. It is uncertain whether these white matter lesions correlate with microstructural changes measured with diffusion MRI techniques. In the current study, we used DKI to evaluate the white matter microstructural integrity in a group of adult patients with communicating hydrocephalus and compare them to subjects with normal ventricular size. Our primary objective was to determine if there are alterations of white matter kurtosis in patients with enlarged ventricles, and if there is correlation between kurtosis and the
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Y. Serulle et al. / Magnetic Resonance Imaging 33 (2015) 531–536
severity of ventriculomegaly. Additionally, we determined whether the severity of LA, which is commonly seen in this patient population, correlates with changes in kurtosis. 2. Materials & methods 2.1. Subjects This retrospective, anonymized, single-center, Health Insurance Portability and Accountability Act-compliant study was exempt from institutional review board approval. We reviewed MRI scans from 26 patients with hydrocephalus (14 females, 12 males) and 26 patients with normal ventricle size (15 females, 11 males). Patients were matched for sex and age. Patients were selected from a database of potential candidates generated by a computer search for patients who had undergone MRI scans that included DKI imaging, and in addition, had received a radiologic diagnosis of hydrocephalus, communicating hydrocephalus, NPH or normal. All resulting MRI scans were then reviewed. Subjects were excluded that demonstrated additional pathologies such as tumor, infarction, or hematoma. The selected hydrocephalus patients fulfilled radiological diagnostic criteria including moderate or greater ventriculomegaly, enlargement of the third ventricle and temporal horns, upward bowing and stretching of the corpus callosum, flattening of the roof of the third ventricle, compression of the interpeduncular cistern and either compression, or variable dilatation of cortical sulci and fissures. The control group had normal brain MRI scans. Two neuroradiologists, with 5 and 40 years of academic experience, respectively, agreed upon the radiologic findings. 2.2. Imaging techniques and post-processing All patients were scanned on a Siemens © 1.5 T magnet (Avanto ©). Diffusion-weighted data were obtained using an axial single-shot echo-planar sequence with the following imaging parameters: repetition time/echo time = 4500/96 ms; matrix size = 82 × 82; 32 slices; voxel size = 2.7 × 2.7 × 5 mm 3. B values of 0, 1000 and 2000 mm −2 s were applied over 30 directions corresponding to the vertices of a truncated icosahedron.
The post-processing of the data was performed using in-house software programmed in Matlab (The MathWorks, Inc., Natick, MA, USA) based on methods previously described [10]. Briefly, the software generates the parametric maps of mean diffusivity (MD), radial diffusivity (RD), axial diffusivity (AD), fractional anisotropy (FA), mean kurtosis (MK), radial kurtosis (RK) and axial kurtosis (AK) (Fig. 1). All of these maps are estimated from the diffusion and kurtosis tensors. MK is defined as the average of the kurtosis over all possible diffusion directions. AK is defined, in analogy with AD, as the kurtosis in the direction of the diffusion tensor eigenvector with the largest diffusion eigenvalue, and RK is defined as the average of the kurtosis over all directions perpendicular to the diffusion eigenvector with the largest eigenvalue. In white matter, the axial direction is typically aligned with the axon bundles [11]. Parameters were measured in manually drawn regions of interest (ROIs) matching the size of the anatomical ROI. ROIs were placed symmetrically within the subcortical white matter of the frontal and parietal lobes, and genu and splenium of the corpus callosum. At the level of the third ventricle, ROIs were symmetrically placed within the posterior limbs of the internal capsules. All ROIs were placed by a neuroradiology fellow. Additionally, the ROIs were also independently drawn in all the same subjects by a trained medical student and reviewed by a neuroradiology attending. There were no statistical differences in the measures obtained by the two different readers. Ventricular volume was generated in three steps using FireVoxel [12]: (a) Bridge Burner algorithm was used to segment the whole brain excluding cerebrospinal fluid [12]; (b) morphologic closure of the brain mask was performed to include the ventricular spaces; (c) 3D set difference between (b) and (a) was taken as ventricular volume. Ventricular volumes were normalized to brain size. The severity of LA was graded on fluid-attenuation inversion recovery and T2-weighted images as either none = no lesions; mild = multiple focal periventricular lesions; moderate = multiple focal periventricular and subcortical lesions; severe = multiple diffuse confluent lesions. Grading was performed by two different neuroradiologists, who were blinded to the diffusion metrics of the patients. 2.3. Statistical analysis An unequal variance t-test was used to compare the hydrocephalus group and controls with respect to metric values
Fig. 1. Representative transaxial B0 images (left column) and MK maps (right column) from normal controls (a) and hydrocephalus (b).
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acquired within every ROI. Pearson correlation test was used to determine whether severity of hydrocephalus and LA correlated with changes in diffusivity and kurtosis metrics.
3. Results There were no significant differences in age (hydrocephalus group: 76.2 ± 1.5; control group: 74.1 ± 1.4; p = 0.3) and gender distribution between the hydrocephalus and normal control groups. Fig. 2 shows the means of the diffusivity metrics for the two groups for each ROI; it also indicates the indices that were found to be statistically significant after t-test comparison. Relative to the control group, hydrocephalus patients showed significant mean and radial diffusivity increases in all brain regions examined except for the bilateral internal capsule. Axial diffusivity was significantly increased in all brain regions except for the bilateral internal capsule and splenium of the corpus callosum. FA in hydrocephalus was decreased in all brain regions except for the bilateral internal capsule when compared to the control group. Fig. 3 shows the means of the kurtosis metrics for the two groups with the indices that were found to be statistically significant after t-test. Relative to the control group, hydrocephalus patients showed significant decrease in mean kurtosis in all brain regions. Radial kurtosis was decreased in all brain regions except for the bilateral internal capsule. Axial kurtosis was decreased in all regions except
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for the genu and splenium of the corpus callosum and the right internal capsule. Ventricular size was quantified in the hydrocephalus group and ventricular volume was correlated with the different diffusivity and kurtosis metrics (Tables 1 and 2). There was a significant inverse correlation between ventricular volume and both mean (r = − 0.4, p b 0.05) and radial kurtosis (r = − 0.41, p b 0.05) in the genu of the corpus callosum. There was a significant direct correlation between ventricular volume and mean (r = 0.44, p b 0.04) and radial (r = 0.45, p b 0.05) diffusivity at the genu of the corpus callosum. Additionally, both mean (r = 0.5, p b 0.05) and radial (r = 0.52, p b 0.05) diffusivities were also directly correlated with ventricular volumes. FA was inversely related to ventricular volumes in both the genu (r = − 0.46, p b 0.05) and splenium (r = − 0.43, p b 0.05). Table 3 demonstrates a higher prevalence of white matter lesions in the hydrocephalus group (21/26) compared to controls (14/26). There was a significant correlation between severity of LA and decreased kurtosis in both the hydrocephalus and control group across all brain regions (Fig. 4) with more severe LA associated with lower kurtosis. To determine whether the difference in kurtosis between controls and hydrocephalus patients depended on the more severe LA seen in the hydrocephalus group, we controlled for the degree of LA and compared the kurtosis metrics between groups with similar severity of white matter disease (i.e. hydrocephalus patients with no evidence for LA vs controls with no evidence for LA). Hydrocephalus patients without evidence of LA demonstrated
Fig. 2. Comparison of mean diffusivity, radial diffusion, axial diffusion and fractional anisotropy between hydrocephalus and normal controls for the different brain regions. RF = right frontal, LF = left frontal, RP = right parietal, LP = left parietal, Ge = genu, Sp = splenium, RIC = right internal capsule, LIC = left internal capsule. * = p b 0.05; ** = p b 0.005; *** = p b 0.001.
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Y. Serulle et al. / Magnetic Resonance Imaging 33 (2015) 531–536 Table 1 Correlation of kurtosis measures with ventricular volume in patients with hydrocephalus. Measure
Region
R
P
AK AK AK AK AK AK AK AK MK MK MK MK MK MK MK MK RK RK RK RK RK RK RK RK
Ge LF LIC LP RF RIC RP Sp Ge LF LIC LP RF RIC RP Sp Ge LF LIC LP RF RIC RP Sp
0.02 0.06 −0.19 −0.23 0.03 0.06 −0.22 0.31 −0.40 −0.21 0.12 −0.08 −0.06 0.25 −0.19 −0.14 −0.41 −0.23 0.24 −0.20 −0.02 0.03 −0.30 −0.21
NS NS NS NS NS NS NS NS p b 0.05 NS NS NS NS NS NS NS p b 0.05 NS NS NS NS NS NS NS
AK = axial kurtosis, MK = mean kurtosis, RK = radial kurtosis, Ge = genu, LF = left frontal, LIC = left internal capsule, LP = left parietal, RF = right frontal, RIC = right internal capsule, RP = right parietal, Sp = splenium.
finding of this study is a significant difference of DKI parameters between patients with hydrocephalus relative to controls. DTI is a conventional diffusion weighted imaging method which uses sensitizing gradients along numerous spatial directions that Table 2 Correlation between diffusivity measures and ventricular volume in patients with hydrocephalus.
Fig. 3. Comparison of mean kurtosis, radial kurtosis and axial kurtosis between hydrocephalus and normal controls for the different brain regions. RF = right frontal, LF = left frontal, RP = right parietal, LP = left parietal, Ge = genu, Sp = splenium, RIC = right internal capsule, LIC = left internal capsule. * = p b 0.05; ** = p b 0.005; *** = p b 0.001.
decreased kurtosis in most brain regions relative to the control group (Fig. 5). Similar results were obtained for patients with mild, moderate and severe LA (data not shown). 4. Discussion Evidence suggests that brain damage in hydrocephalus occurs primarily on the periventricular white matter [13]. Up to a certain time point, the white matter changes are believed to be reversible. However, permanent atrophy, first of the white matter and then of the cortex, can develop [14]. The purpose of the current study was to assess the integrity of the white matter in patients with hydrocephalus using a recently-developed diffusion technique, DKI. The major
Measure
Region
R
P
AD AD AD AD AD AD AD AD MD MD MD MD MD MD MD MD RD RD RD RD RD RD RD RD FA FA FA FA FA FA FA FA
Ge LF LIC LP RF RIC RP Sp Ge LF LIC LP RF RIC RP Sp Ge LF LIC LP RF RIC RP Sp Ge LF LIC LP RF RIC RP Sp
0.24 0.09 0.03 −0.08 −0.02 0.18 0.00 0.39 0.44 0.00 −0.01 0.03 0.09 0.18 0.09 0.50 0.45 −0.05 −0.05 0.05 0.14 0.03 0.12 0.52 −0.46 0.16 0.04 −0.12 −0.27 0.04 −0.22 −0.43
NS NS NS NS NS NS NS NS pb NS NS NS NS NS NS pb pb NS NS NS NS NS NS pb pb NS NS NS NS NS NS pb
0.05
0.05 0.05
0.05 0.05
0.05
AD = axial diffusivity, MD = mean diffusivity, RD = radial diffusivity, FA = fractional anisotropy.
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Table 3 Degree of leukoariaosis in patients with hydrocephalus and controls.
None Mild Moderate Severe
Control
Hydrocephalus
12 8 4 2
5 14 5 2
yield the diffusion tensor [15], providing directional information on the neuroarchitectural orientation of the white matter tracts. DTI metrics include the MD, and FA, which are used to quantify and characterize the inherent anisotropy of white matter [16]. The underlying assumption in DTI is that water diffusion occurs in a free and unrestricted environment, thereby obeying a Gaussian probability distribution function. In recent literature, DTI has been shown to be relatively effective in characterizing hydrocephalus. Kanno et al. [17], demonstrated that on average, MD and FA of supratentorial white matter were increased and decreased, respectively, in patients with idiopathic NPH. Our data yielded similar results, confirming a generalized increase in diffusivity and reduction of FA. In biologic tissues, complex intra- and extracellular structures exist that hinder and restrict water diffusion, technically making water diffusivity an inherently non-Gaussian process [6]. Since kurtosis is a measure of deviation, or convexity, from a Gaussian probability profile, DKI allows, in addition to the diffusion tensor, formulation of a fourth-order kurtosis tensor that allows for more accurate description of the diffusion MRI signal in biological tissue. The non-Gaussian diffusion metrics (kurtosis) can be theoretically linked to restricted diffusion and diffusional heterogeneity [18] and may provide more information about tissue compartments and tissue heterogeneity, compared with conventional DTI metrics. Additionally, by quantifying diffusional non-Gaussianity, DKI is suitable for evaluating both anisotropic and non-anisotropic (isotropic) structures, such as gray matter [19]. Ultimately, kurtosis is believed to reflect neural tissue microstructural complexity. Preliminary application of DKI to ischemic stroke, aging, Alzheimer’s disease, schizophrenia and attention deficit hyperactivity disorder has been promising [20–22]. In this study, we show that there are statistically significant alterations of white matter kurtosis in patients with hydrocephalus. All kurtosis metrics were significantly reduced in most ROIs, which included the corpus callosum and periventricular white matter. Mean kurtosis was decreased in all ROIs measured, whereas radial kurtosis measured in the genu of the corpus callosum showed the
Fig. 4. Correlation of DKI with severity of LA. Scatterplot shows correlation between severity of LA and mean kurtosis in the frontal region (taken as a representative result) of hydrocephalus patients. R = −0.74, p b 0.001. Note that similar results were obtained in multiple other brain regions (see Table 4).
Fig. 5. Comparison of mean kurtosis between hydrocephalus and normal controls with no evidence for LA. RF = right frontal, LF = left frontal, RP = right parietal, LP = left parietal, Ge = genu, Sp = splenium, RIC = right internal capsule, LIC = left internal capsule. * = p b 0.05; ** = p b 0.005; *** = p b 0.001.
largest individual difference between controls and hydrocephalus. Additionally, we found an association between larger ventricular volumes and decreased mean and radial kurtosis in the genu of the corpus callosum, but not in the remaining brain regions queried, suggesting that fibers at the genu may be particularly sensitive to the degree of ventricular enlargement. RK has been shown to correlate with intra-axonal water fraction [23], therefore our observation of decreased RK in hydrocephalus may be related to an increased extra-axonal water fraction (edema) or possibly demyelination and/or axonal loss. It seems to follow that diminished white matter kurtosis in hydrocephalus reflects a decrease in the microstructural complexity of functionally relevant white matter. A white matter model based upon DKI metrics has
Table 4 Correlation between kurtosis measures and degree of leukoariaosis in patients with hydrocephalus. Measure
Region
R
P
AK AK AK AK AK AK AK AK MK MK MK MK MK MK MK MK RK RK RK RK RK RK RK RK
Ge LF LIC LP RF RIC RP Sp Ge LF LIC LP RF RIC RP Sp Ge LF LIC LP RF RIC RP Sp
−0.25 −0.41 −0.33 −0.58 −0.48 −0.25 −0.73 −0.14 −0.28 −0.62 −0.4 −0.72 −0.74 −0.46 −0.72 −0.05 −0.26 −0.48 −0.2 −0.62 −0.64 −0.61 −0.54 −0.27
NS pb NS pb pb NS pb NS NS pb pb pb pb pb pb NS NS pb NS pb pb pb pb NS
0.05 0.05 0.05 0.05
0.05 0.05 0.05 0.05 0.05 0.05
0.05 0.05 0.05 0.05 0.05
AK = axial kurtosis, MK = mean kurtosis, RK = radial kurtosis, Ge = genu, LF = left frontal, LIC = left internal capsule, LP = left parietal, RF = right frontal, RIC = right internal capsule, RP = right parietal, Sp = splenium.
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been devised that may help explain the role myelin dysfunction plays in neurodegenerative disorders and hydrocephalus [23]. Recent research demonstrates similar changes in diffusivity, kurtosis, and FA in the plaques of multiple sclerosis suggesting the white matter alterations in hydrocephalus may at least in part be due to loss of myelin [24]. LA is considered a macroscopic manifestation of white matter damage due to microvascular disease, and is seen as increased signal in the white matter in T2-weighted and fluid-attenuation inversion recovery images. It is well documented that there is increased incidence of LA in patients with larger ventricles [25,26], as also demonstrated in our cohort. Previous studies have shown increased MD and reduced FA in patients with LA [27,28]. In the current study, we also found a strong correlation between LA and kurtosis metrics. More importantly, we found that while LA is associated with decreased kurtosis, the effect of hydrocephalus on kurtosis is independent of the effects LA. Our study has several limitations. We did not evaluate the relation between patients’ clinical status and DKI metrics or degree of hydrocephalus, as our initial objective was to first establish a relation between enlarged ventricles and white matter integrity. Thus, we selected patients based only on imaging features and not on clinical presentation. It is known that enlarged ventricles can be a manifestation of a variety of neurodegenerative diseases; therefore it is possible that our hydrocephalus group may represent a heterogeneous group in regards to the underlying etiology of the hydrocephalus. Moreover, some of these patients may be asymptomatic. Correlation between DKI metrics and clinical symptoms would be very important to further understand the value of DKI in the different pathologies responsible for hydrocephalus. 5. Conclusions Statistically significant deficits of white matter kurtosis are demonstrated in patients with hydrocephalus. All kurtosis metrics were significantly reduced in hydrocephalus relative to the control group. References [1] Hebb AO, Cusimano MD. Idiopathic normal pressure hydrocephalus: a systematic review of diagnosis and outcome. Neurosurgery 2001;49(5):1166–84 [discussion 1184–6]. [2] Akai K, Uchiqasaki S, Tanaka U, Komatsu A. Normal pressure hydrocephalus. Neuropathological study. Acta Pathol Jpn 1987;37(1):97–110. [3] Ding Y, McAllister JP, Yao B, Yan N, Canady Al. Axonal damage associated with enlargement of ventricles during hydrocephalus: a silver impregnation study. Neurol Res 2001;23(6):581–7. [4] Del Bigio MR, Wilson MJ, Enno T. Chronic hydrocephalus in rats and humans: white matter loss and behavior changes. Ann Neurol 2003;53(3):337–46. [5] Hattingen E, Jurcoane A, Melber J, Blasel S, Zanella FE, Neumann-Haefelin T, et al. Diffusion tensor imaging in patients with adult chronic idiopathic hydrocephalus. Neurosurgery 2010;66(5):917–24.
[6] Wu EX, Cheung MM. MR diffusion kurtosis imaging for neural tissue characterization. NMR Biomed 2010;23(7):836–48. [7] Hachinski VC, Potter P, Merskey H. Leuko-araiosis. Arch Neurol 1987;44(1): 21–3. [8] Pantoni L, Garcia JH. The significance of cerebral white matter abnormalities 100 years after Binswanger's report. A review. Stroke 1995;26(7):1293–301. [9] Pantoni L, Garcia JH. Pathogenesis of leukoaraiosis: a review. Stroke 1997;28(3): 652–9. [10] Tabesh A, Jensen JH, Ardekani BA, Helpern JA. Estimation of tensors and tensorderived measures in diffusional kurtosis imaging. Magn Reson Med 2011;65(3): 823–36. [11] Jensen JH, Falangola MF, Hu C, Tabesh A, Rapalino O, Lo C, et al. Preliminary observations of increased diffusional kurtosis in human brain following recent cerebral infarction. NMR Biomed 2011;24(5):452–7. [12] Mikheev A, Nevsky G, Govindan S, Grossman R, Rusinek H. Fully automatic segmentation of the brain from T1-weighted MRI using Bridge Burner algorithm. J Magn Reson Imaging 2008;27(6):1235–41. [13] Del Bigio MR. Neuropathological changes caused by hydrocephalus. Acta Neuropathol 1993;85(6):573–85. [14] Del Bigio MR. Cellular damage and prevention in childhood hydrocephalus. Brain Pathol 2004;14(3):317–24. [15] Basser PJ. Inferring microstructural features and the physiological state of tissues from diffusion-weighted images. NMR Biomed 1995;8(7–8):333–44. [16] Mascalchi M, Filippi M, Floris R, FOnda C, Gasparotti R, Villari N. Diffusionweighted MR of the brain: methodology and clinical application. Radiol Med 2005;109(3):155–97. [17] Kanno S, Abe N, Saito M, Takaqi M, Nishio Y, Hayashi A, et al. White matter involvement in idiopathic normal pressure hydrocephalus: a voxel-based diffusion tensor imaging study. J Neurol 2011;258(11):1949–57. [18] Jensen HH, Helpern JA, Ramani A, Lu H, Kaczynski K. Diffusional kurtosis imaging: the quantification of non-Gaussian water diffusion by means of magnetic resonance imaging. Magn Reson Med 2005;53(6):1432–40. [19] Jensen JH, Helpern JA. MRI quantification of non-Gaussian water diffusion by kurtosis analysis. NMR Biomed 2010;23(7):698–710. [20] Falangola MF, Jensen JH, Babb JS, Hu C, Castellanos FX, Di Martino A, et al. Agerelated non-Gaussian diffusion patterns in the prefrontal brain. J Magn Reson Imaging 2008;28(6):1345–50. [21] Fieremans E, Benitez A, Jensen JH, Falangola MF, Tabesh A, Deardorff RL, et al. Novel white matter tract integrity metrics sensitive to Alzheimer disease progression. AJNR Am J Neuroradiol 2013;34:2105–12. [22] Helpern JA, Adisetiyo V, Falangola MF, Hu C, Di Martino A, Williams K, et al. Preliminary evidence of altered gray and white matter microstructural development in the frontal lobe of adolescents with attention-deficit hyperactivity disorder: a diffusional kurtosis imaging study. J Magn Reson Imaging 2011; 33(1):17–23. [23] Fieremans E, Jensen JH, Helpern JA. White matter characterization with diffusional kurtosis imaging. Neuroimage 2011;58(1):177–88. [24] Raz E, Bester M, Sigmund EE, Tabesh A, Babb JS, Jaggi H, et al. A better characterization of spinal cord damage in multiple sclerosis: a diffusional kurtosis imaging study. AJNR Am J Neuroradiol 2013;34(9):1846–52. [25] Bradley WG, Whittemore AR, Watanabe AS, Davis SJ, Teresi LM, Homyak M. Association of deep white matter infarction with chronic communicating hydrocephalus: implications regarding the possible origin of normal-pressure hydrocephalus. AJNR Am J Neuroradiol 1991;12(1):31–9. [26] Tullberg M, Jensen C, Ekholm S, Wikkelsø C. Normal pressure hydrocephalus: vascular white matter changes on MR images must not exclude patients from shunt surgery. AJNR Am J Neuroradiol 2001;22(9):1665–73. [27] O'Sullivan M, Morris RG, Huckstep B, Jones DK, Williams SC, Markus HS. Diffusion tensor MRI correlates with executive dysfunction in patients with ischaemic leukoaraiosis. J Neurol Neurosurg Psychiatry 2004;75(3):441–7. [28] O'Sullivan M, Summers PE, Jones DK, Jarosz JM, Williams SC, Markus HS. Normalappearing white matter in ischemic leukoaraiosis: a diffusion tensor MRI study. Neurology 2001;57(12):2307–10.
