November 2014
Volume 55, Issue 11
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Glaucoma  |   November 2014
Cerebral Microinfarcts in Primary Open-Angle Glaucoma Correlated With DTI-Derived Integrity of Optic Radiation
Author Affiliations & Notes
  • Johannes Schoemann
    Friedrich-Alexander-University Erlangen-Nürnberg (FAU), Erlangen, Germany
  • Tobias Engelhorn
    Department of Neuroradiology, Friedrich-Alexander-University Erlangen-Nürnberg (FAU), Erlangen, Germany
  • Simone Waerntges
    Department of Ophthalmology, Friedrich-Alexander-University Erlangen-Nürnberg (FAU), Erlangen, Germany
  • Arnd Doerfler
    Department of Neuroradiology, Friedrich-Alexander-University Erlangen-Nürnberg (FAU), Erlangen, Germany
  • Ahmed El-Rafei
    Department of Computer Science, Friedrich-Alexander-University Erlangen-Nürnberg (FAU), Erlangen, Germany
  • Georg Michelson
    Department of Ophthalmology, School of Advanced Optical Technologies (SOAT), Interdisciplinary Center of Ophthalmic Preventive Medicine and Imaging (IZPI), Friedrich-Alexander-University Erlangen-Nürnberg (FAU), Erlangen, Germany
  • Footnotes
     Current affiliation: *Center for Thrombosis and Hemostasis (CTH), University Medical Center Mainz, Germany.
  • Footnotes
     Engineering Physics and Mathematics Department, Ain Shams University, Cairo, Egypt.
  • Correspondence: Johannes Schoemann and Georg Michelson, Department of Ophthalmology, Friedrich-Alexander-Universität Erlangen-Nürnberg, Schwabachanlage 6, 91054 Erlangen, Germany; johannes.schoemann@fau.de
Investigative Ophthalmology & Visual Science November 2014, Vol.55, 7241-7247. doi:10.1167/iovs.14-14919
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      Johannes Schoemann, Tobias Engelhorn, Simone Waerntges, Arnd Doerfler, Ahmed El-Rafei, Georg Michelson; Cerebral Microinfarcts in Primary Open-Angle Glaucoma Correlated With DTI-Derived Integrity of Optic Radiation. Invest. Ophthalmol. Vis. Sci. 2014;55(11):7241-7247. doi: 10.1167/iovs.14-14919.

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Abstract

Purpose.: To evaluate the correlation between the extent of cerebral white matter lesions (WMLs) and the integrity of the visual pathway represented by fractional anisotropy (FA) in patients with primary open-angle glaucoma (POAG).

Methods.: This case-control study included a total of 61 German patients (39 POAG patients, 22 controls) matched for age and sex. Fractional anisotropy of the optic radiation was determined by 3-Tesla diffusion tensor imaging. White matter lesions and brain volumes were manually measured by using a T2-weighted, 3-D fluid-attenuated inversion recovery sequence.

Results.: In POAG patients WML volumes were significantly (P = 0.04) increased in the subcortical area. This applied for both absolute and relative units to the specific patient's brain volume, compared to controls. The WML volumes were significantly (P = 0.003) greater in middle-aged (40–59 years) POAG patients than control patients. In controls there was a significant age correlation of WML volumes in the total brain, subcortical, and optic radiation regions of interest. There was a significant correlation between FA and WML in POAG regarding the total brain, the periventricular region, and the optic radiation in both hemispheres. In POAG, FA left and right optic radiation correlated significantly with age (P = 0.002).

Conclusions.: We were able to demonstrate that (1) POAG patients aged 40 to 60 years had higher volumes of cerebral microinfarcts and (2) POAG patients showed a significant correlation between cerebral microinfarcts and degeneration of the optic radiation. This indicates that cerebral microinfarcts might be an intracerebral risk factor for glaucomatous optic nerve atrophy.

Introduction
Glaucoma will increase rapidly in the next few decades worldwide and is the second most common cause of blindness with 8.4 million bilaterally blind people.1 
It is a group of disorders with multifactorial etiology resulting in chronic, progressive, and intraocular pressure (IOP)–associated optic neuropathy, associated with loss of axons and astrocytes, followed by visual field defects.2 Recent articles3,4 suggest that glaucoma is associated with alterations of the lateral geniculate nucleus (LGN) and the visual cortex. 
Primary open-angle glaucoma (POAG), the most common type of glaucoma, has a prevalence of 2% in populations of Europe and Africa.57 Because of slow progression and sometimes late detection of visual field loss, an accurate diagnosis is often made late.8 Several prognostic risk factors for the progression of POAG are known, such as abnormalities in the visual field, individual increased IOP, and advancing age.912 
The appearance of white matter lesions (WMLs) is proposed as an independent risk factor for visual field progression in POAG.13 White matter lesions are a subcategory of silent cerebral infarct (SCI). In contrast to SCI, WMLs do not accrue in the gray matter or in the brainstem.14 These are patchy subcortical areas of increased signals on T2 fluid-attenuated inversion recovery (FLAIR)–weighted magnetic resonance images within the cortical white matter, mostly discovered coincidently by computed tomography (CT) or magnetic resonance imaging (MRI).15,16 White matter lesions are a signal of ischemic damage to the white matter, with subsequent degeneration of axons and glial cells.17,18 
There is evidence that in glaucoma there is reduced integrity of the axons in the optic tract.19 
Axonal integrity can be measured by fractional anisotropy (FA), based on MRI. Fractional anisotropy hereby characterizes the structure of brain tissue, based on underlying water diffusivity.20 The risk factors for a decreased integrity of the optic radiation are unknown. 
To date it is not known whether there is an association between cerebral microangiopathy and axonal degeneration in the optic radiation. 
Hence the purpose of this case-control study was to evaluate the correlation between the extent of cerebral WMLs and the integrity of the visual pathway, determined by 3-Tesla diffusion tensor imaging (DTI) in patients with POAG, compared to sex and aged-matched controls. 
Methods
The study was approved by the institutional Clinical Investigation Ethics Committee, and informed written consent was obtained from all subjects before the study, following explanation of the nature and possible consequences of the study. All tenets of the Declaration of Helsinki were complied with. 
Study Population and Baseline Clinical Characteristics
Baseline clinical characteristics for all participants are listed in Table 1. A total of 61 Caucasian German patients, aged 46 to 84 years, from the Department of Ophthalmology at the University Hospital Erlangen were included in this study. Twenty-two controls and 39 glaucoma patients underwent a complete ophthalmologic examination including optic coherence tomography (OCT), white-on-white perimetry, ophthalmoscopy, and 3T MRI scanning. The controls consisted of 9 male and 13 female patients with an average age of 63.27 ± 11.85 years (mean and standard deviation [SD]), while the glaucoma group included 39 persons aged 63.90 ± 9.25 years (26 female and 13 male). To avoid confusion due to age effects, the control group was age matched to the POAG group. There was no significant difference in age between both groups (P = 0.165). The age of both control patients and POAG patients followed a normal distribution. The ophthalmologic examination revealed no eye diseases in all 22 controls, or any other diseases (e.g., cardiovascular) that would affect the prevalence of WMLs; nor were significant differences found in age, sex, visual acuity, or IOP when compared to the POAG patients. All patients with other diseases affecting the integrity of the central nervous system (e.g., multiple sclerosis, Parkinson's disease, Alzheimer's disease, diabetes, or migraine) or with cardiac diseases were excluded. We included those with self-reported absence of these diseases. Mean defect (MD), age, and retinal nerve fiber thickness, measured by OCT, followed a normal distribution. The glaucoma patients and the controls differed significantly (P > 0.05) in the retinal nerve fiber thickness and MD. 
Table 1
 
Baseline Clinical Characteristics
Table 1
 
Baseline Clinical Characteristics
Characteristics POAG n = 39, 64% Controls n = 22, 36% Value
Age, y* 63.9 ± 9.3 63.3 ± 11.9 0.165
Sex, male/female 13/26 9/13 0.296
Visual acuity, decimal
 Right eye 0.80 ± 0.22 0.72 ± 0.29 0.392
 Left eye 0.77 ± 0.26 0.71 ± 0.31 0.614
IOP, mm Hg
 Right eye 14.67 ± 5.2 14.10 ± 2.8 0.981
 Left eye 15.10 ± 5.7 14.33 ± 2.7 1.000
Mean defect, dB
 Right eye* 7.36 ± 6.56 0.20 ± 0.28 0.037†
 Left eye* 8.70 ± 6.80 0.50 ± 1.13 0.075
Retinal nerve fiber thickness, μm
 Right eye* 71.03 ± 15.70 104.00 ± 13.38 <0.0001†
 Left eye* 66.55 ± 16.16 101.29 ± 12.24 <0.0001†
Ophthalmic Examination
The identification of POAG was performed by experienced ophthalmologists. The inclusion criteria for POAG was a bilateral open anterior chamber angle, thinned retinal nerve fiber layer, cupping of the optic disc, and visual field defects worse than +2 dB. Controls were age matched to POAG patients. The controls and POAG patients were recruited from the outpatient clinic of the Department of Ophthalmology at the University Erlangen-Nuremberg. The controls were examined in the same manner as the POAG patients. 
MRI Data Acquisition
An MRI of the brain was performed on a 3T high-field scanner (Magnetom Tim Trio; Siemens Healthcare AG, Erlangen, Germany) with gradient field strength of up to 45 mT/m (72 mT/m effective). For DTI the anatomic data were obtained in a T1-weighted, 3-D magnetization–prepared rapid gradient echo (MPRAGE) sequence (repetition time [TR] = 900 ms, echo time [TE] = 3 ms, field of view (FoV) = 23 × 23 cm, acquisition matrix size = 512 × 256 reconstructed to 512 × 512, reconstructed axial planes with 1.2-mm slice thickness). Diffusion tensor imaging was performed in the axial plane with 4-mm slice thickness by using a single-shot, spin echo, echo planar imaging diffusion tensor sequence, thus covering the whole visual pathway (TR = 3400 ms, TE = 93 ms, FoV = 23 × 23 cm, acquisition matrix size = 256 × 256 reconstructed to 512 × 512, number of signal averages = 7, partial Fourier acquisition = 60%) (Fig. 1A). Diffusion weighting with a maximal b-factor of 1000 s/mm2 was carried out along 15 icosahedral directions complemented by one scan with b = 0. Data sets were automatically corrected for imaging distortions and coregistered in reference to T1-weighted MPRAGE images. To analyze WML, a T2-weighted 3-D FLAIR sequence was used with sagittal acquisition. One-mm-thick slices were reconstructed (TR = 5000 ms, TE = 388 ms, FoV = 25 × 25 cm, resolution = 512 × 512).19 
Figure 1
 
Region of interest identified on the optic radiation demonstrated on a fractional anisotropy image (A). White matter lesions in the optic radiation shown on a T2-weighted FLAIR image (B). The picture was not from the same patient.
Figure 1
 
Region of interest identified on the optic radiation demonstrated on a fractional anisotropy image (A). White matter lesions in the optic radiation shown on a T2-weighted FLAIR image (B). The picture was not from the same patient.
Image Processing
To assess WMLs and whole brain volumes, reconstructed axial planes from a 3-D FLAIR sequence with 5-mm slice thickness were used. Volumetry of WML was done with Siemens built-in software. There were no overlaps or gaps between the slices. To guarantee high accuracy, volumetric measurement was performed manually while blinded to the patient's clinical conditions.21,22 To obtain the whole brain volume, the cross-sectional area of the whole supratentorial brain of each reconstructed slice was measured by circling the cross-sectional area by hand. The surface area was calculated by the Siemens Syngo Software. White matter lesions, occurring as bright signals in FLAIR, were circled by hand and categorized to one of three regions of interest (ROIs), that is, “subcortical,” “periventricular,” and within the “optic radiation” (Fig. 1B). Every bright lesion in the white matter less than 1 cm away from the cortical surface was regarded as subcortical. 
In addition, FA of the optic radiation was calculated by DTI, and reconstruction of the optic radiation was used to classify the location of WMLs as lesions within the optic radiation.23 Diffusion tensor imaging provides valuable information describing the fiber microstructure of axons.20,24,25 It was therefore used for the identification of different fiber structures including the entire visual system and its subsets, such as the optic radiation.26,27 The tensor was calculated from a set of diffusion-weighted images at each voxel location. 
Diffusion anisotropy measurements, such as FA, can be calculated from the diffusion tensor. It is a valid measurement for determining the integrity of axons in the optic tract and giving a quantitative evaluation of the optic radiation.19,20,28,29 Fractional anisotropy is used to describe the proportional part of the main diffusion directions of molecules. In normal white matter this diffusion is limited by neurons, glial cells, or axons.30 Evidence has shown that the FA value decreases in axons with decreased neuronal integrity.31 Fractional anisotropy extends from zero for an isotropic diffusion, representing a lot of damage to the optic tract, to one for a perfect anisotropic diffusion, where there is no neuronal alteration. 
The DTI data were interpolated in the Log-Euclidean framework to avoid the swelling effect. The data were further processed and the estimated segmented optic radiation was checked for concordance with anatomic knowledge. The slice, which included the LGN, was chosen for further procedures and calculations. Analysis of the segmentation errors additionally showed that anatomic structures that are not part of the optic radiation were segmented. These structures were removed manually. This predominantly included parts of the optic tract, the forceps major of the corpus callosum, which proceeds medially to the optic radiations, and all tracts that do not connect to the visual cortex. The DTI data were used to detect WMLs of the optic radiation in conjunction with FLAIR images. 
Data Analysis
Statistical analysis was performed by using SPSS (Version 21.0; IBM-SPAA, Chicago, IL, USA). All P values < 0.05 were considered statistically significant. Normal distribution assumption was tested with the Kolmogorov-Smirnov test. Continuous variables were expressed as mean ± standard deviation. 
The measured surface area of the sectional plane of the brain was multiplied by 0.5 cm to determine the volumes in cubic centimeters. The measured WML volumes (hereinafter “absolute WML volumes”) were calculated analogously. 
The percentage of WML volumes (hereinafter “relative WML volumes”) compared to whole brain volumes was subsequently calculated by dividing the absolute WML volumes by the volumes of the whole brain. In this way the extent of WMLs could be compared between different patients, thus avoiding a bias for age, sex, or other factors affecting the brain volume. 
Four aspects were analyzed. We examined whether there were differences in relative WML volumes between POAG patients and the controls. Furthermore, WML and FA were correlated with age. Finally, a correlation between WML and FA of the optic radiation was performed. 
A Mann-Whitney U test (a nonparametric test) was performed, comparing the WML volumes in different ROIs (total brain, subcortical, periventricular, and within the optic radiation) in POAG patients and controls. As a null hypothesis it was assumed that there was no difference in the relative WML volumes between both groups. 
U-tests examined whether there was a difference in relative WML volumes or FA in age groups in both POAG patients and controls. For these tests, the patient cohort was distributed in age groups by decades. For FA as a null hypothesis, it was assumed that there was no difference in FA between the age groups. For WML as a null hypothesis, it was assumed that there were no differences in relative WML volumes in respective decades between POAG patients and the controls. Three tests for correlation were conducted: the Pearson coefficient was determined for the correlation between WML and age, FA and volumes of WML, and between FA and age. 
Results
Relative WML Volumes in POAG Patients and Controls
White matter lesions were found in 97% of POAG patients and in 77% of controls. In POAG patients the volumes of WML in the subcortical area were significantly (P = 0.04) increased in both absolute and relative units of the specific patient's brain volume, compared to controls. 
In the “total brain,” “periventricular area,” and “optic radiation” ROIs there were increased volumes of microinfarcts in POAG patients, without reaching the level of significance. For the total brain ROI, POAG patients showed a volume of cerebral microinfarcts that was approximately 2.1 times greater than that of age-matched controls (Table 2). The WML volumes residua followed an approximately normal distribution. 
Table 2
 
Relative and Absolute Volumes of WMLs in cm3 in Different Areas of the Brain, P Value of U-Test
Table 2
 
Relative and Absolute Volumes of WMLs in cm3 in Different Areas of the Brain, P Value of U-Test
Structure POAG Controls Factor Value
Absolute WML volumes, cm3
Total brain 2.7 ± 4.4 1.2 ± 1.7 2.15 0.087
Subcortical 1.1 ± 2.1 0.5 ± 0.9 1.99 0.040*
Periventricular 1.0 ± 2.2 0.4 ± 0.7 2.83 0.215
Optic radiation 0.6 ± 1.1 0.4 ± 0.5 1.75 0.355
Relative WML volumes
Total brain × 10E-3 2.57 ± 4.2 1.22 ± 1.6 2.11 0.083
Subcortical × 10E-3 1.03 ± 1.9 0.54 ± 0.9 1.90 0.039*
Periventricular × 10E-3 0.95 ± 2.2 0.34 ± 0.6 2.80 0.210
Optic radiation × 10E-3 0.59 ± 1.1 0.34 ± 0.4 1.73 0.347
There were significantly (P = 0.003) greater WML volumes in middle-aged (40–59 years) POAG patients than age-matched control patients. In POAG patients aged 60 to 79 years there were increased volumes of WML, but these did not reach the level of significance (P = 0.300) (Fig. 2). 
Figure 2
 
White matter lesion volumes in different decades. *Significant difference, P = 0.003.
Figure 2
 
White matter lesion volumes in different decades. *Significant difference, P = 0.003.
Furthermore, a correlation between mean retinal nerve fiber layer (RNFL) thickness of both eyes and WML volumes of the subcortical region was found. This trend did not reach the level of significance (POAG patients: 0.713, P = 0.072; controls: 0.050; P = 0.790). 
Correlation Between Age and Relative WML Volumes
There was a significant relationship between relative WML volumes and age (0.584, P = 0.004) in the controls. The correlation was significant for the total brain, subcortical, and optic radiation ROIs (Table 3). The older the controls, the greater were the volumes of the lesion area. In the glaucoma group there was no significant linear age correlation (0.246, P = 0.131). 
Table 3
 
Correlation Between WML Volumes and Age
Table 3
 
Correlation Between WML Volumes and Age
Structure Age in POAG Age in Controls
Location of WML Value Value
Total brain WML 0.248 0.131 0.584 0.004*
Subcortical WML 0.080 0.628 0.617 0.002*
Periventricular WML 0.301 0.063 0.357 0.103
Optic radiation WML 0.210 0.199 0.425 0.049*
Correlation of Age and Fractional Anisotropy
In POAG patients, FA values correlated inversely with age. There was a strong and significant coherence between age and FA in each hemisphere with a P value of 0.002. In controls the correlation did not reach the level of significance (Table 4). 
Table 4
 
Correlation Between Axonal Integrity of the Optic Radiation and Age
Table 4
 
Correlation Between Axonal Integrity of the Optic Radiation and Age
Structure Age in POAG Age in Controls
Axonal Integrity Value Value
Right visual pathway −0.481 0.002* −0.345 0.116
Left visual pathway −0.489 0.002* −0.230 0.303
In older POAG patients the integrity of the optic radiation (FA) was significantly decreased (P = 0.009) as compared to younger POAG patients. Fractional anisotropy followed a normal distribution for both sides. 
Figure 3 depicts mean FA values of both hemispheres in POAG and controls. 
Figure 3
 
Mean fractional anisotropy for both hemispheres. *Significant difference, P = 0.001. **Significant difference, P = 0.011.
Figure 3
 
Mean fractional anisotropy for both hemispheres. *Significant difference, P = 0.001. **Significant difference, P = 0.011.
Correlation of WML Volumes and Fractional Anisotropy
In POAG patients, but not in controls, increasing volumes of WML were significantly associated with a decrease in FA. Significant correlations of relative WML volumes and FA were found in the optic radiation, total brain, and periventricular ROIs, but not in the subcortical ROI. 
Table 5 depicts the correlation of both hemispheres in both groups. 
Table 5
 
Correlation Between Fractional Anisotropy of the Optic Radiation and WML Volumes
Table 5
 
Correlation Between Fractional Anisotropy of the Optic Radiation and WML Volumes
FA in POAG FA in Controls
Right Optic Radiation Left Optic Radiation Right Optic Radiation Left Optic Radiation
WML Volumes Value Value Value Value
Total brain −0.420 0.008* −0.393 0.013* −0.187 0.404 −0.096 0.672
Subcortical −0.930 0.571 −0.143 0.384 −0.146 0.517 0.026 0.909
Periventricular −0.432 0.006* −0.504 0.001* −0.093 0.681 −0.127 0.572
Optic radiation −0.453 0.004* −0.409 0.010* −0.267 0.229 −0.219 0.328
Discussion
As far as we know, our study is the first to be performed with simultaneous measurement of microinfarcts in the optic radiation and neuronal integrity of the optic radiation. Relative WML volumes in the optic radiation were correlated with FA of the optic radiation. 
Recent studies1618,32 have demonstrated that WMLs are regions of ischemic microinfarcts caused by vascular changes. Evidence has shown that in the general population there is a direct correlation between age and WML: the older the patients, the more WML volumes are detected.17,33 The present study supported this finding. A significant correlation between age and relative WML volumes in controls for middle-aged (40–59 years) patients was found. 
Furthermore, it is known that higher WML volumes are found in POAG patients than controls.13,3437 Our study was able to confirm this. We demonstrated significantly increased WML volumes in the subcortical region of the brain in POAG. Particularly in POAG patients aged 40 to 60 years there were significantly increased relative WML volumes. 
In recent studies19,38 we have demonstrated that in POAG the neuronal integrity of the optic radiation, indexed by FA, is significantly reduced. This finding is consistent with other study results.3941 In this study we were not able to demonstrate a significant reduction of FA in POAG patients compared to control patients of the same age group. This may have been caused by the small sample size. But we were able to show that there is a significant reduction of FA values in older POAG patients compared to younger POAG patients. 
The present study showed that there was a significant correlation between increased volumes of WML and reduced integrity of the optic radiation in POAG patients. This correlation was found for the optic radiation and for the whole brain. 
This result suggests that there is a close association between the number of microinfarcts in the optic radiation and the degree of neuronal disintegration of the optic radiation in POAG patients, indicating that cerebral microinfarcts might be an intracerebral risk factor for glaucomatous optic nerve atrophy. 
This hypothesis is supported by previous findings: Stroman36 has found more WMLs in POAG (there: normal tension glaucoma), suggesting a vascular disease component. Others have found that POAG is related not only to microvascular changes of the cortex but also to a macrovascular insufficiency of the posterior cerebral artery, leading to decreased cerebral blood flow in the primary visual cortex and to other conditions associated with vessel disease.4245 Prins46 has described an intracranial degeneration of the optic radiation in POAG. He assumed that WML, especially periventricularly located WML, may cause damage to the fiber tracts. 
Gupta3 has shown that in glaucoma there is a histologic degeneration of axons in the visual pathway and in the whole visual cortex, and Hernowo47 has shown evidence of radiologically detectable degeneration. In an MRI and magnetization transfer imaging–based study, Kitsos et al.37 demonstrate optic nerve atrophy in POAG. Lu et al.40 have shown that the occipital white matter in POAG patients, compared with nonglaucoma subjects, has significantly lower FA values, also indicating neuronal degeneration. Gupta and Yücel39 and Weinreb and Khaw5 have thus assumed that POAG might have a neuronally based pathogenesis. 
The association discovered between relative WML volumes and structural damage to the fiber tract of the optic radiation matches the functional correlation between WML and enhanced progression of visual field loss in POAG patients, which Leung et al.13 have demonstrated. These findings are supported by the correlation we demonstrated between mean RNFL thickness of both eyes and WML volumes of the subcortical region. This study indicates a trend, as levels of significance were not reached (POAG patients: 0.713, P = 0.072; controls: 0.050; P = 0.790). Further studies with a larger sample size might confirm this. 
Our data lead to the assumption that WMLs might act as an intracerebral risk factor for the pathogenesis of POAG. It is important to note that they may also be a consequence of neuronal degeneration, which is evidenced in POAG by reduced FA values.40,41 Ultimately, WMLs may be related to cardiovascular diseases, which have also been proposed as a risk factor for POAG.5 
The strength of our study was the simultaneous measurement of WMLs and integrity of the optic radiation in controls and POAG patients. The manual outlining of WMLs guaranteed high accuracy of volume measurement. Furthermore, any subjects with cerebral diseases causing WMLs were excluded. Both groups were similar by age and sex to avoid any bias concerning the brain volume. The use of sensitive MRI sequences in contrast to CT scans increased the reliability of our results with respect to relative WML volumes. 
Limitations of our study included in particular the small sample size, such that some results did not reach the level of significance although they were highly correlated (e.g., correlation between FA values and relative subcortical WML volume in POAG patients, Table 5). Furthermore, the number of controls as compared to POAG patients was small. To verify our observations or to correct some inconsistencies in our data, a larger, longitudinal study will be required to account for unilateral brain changes, which are a common finding in volumetric investigations with small sample size.48 
In conclusion, this study was able to demonstrate that (1) POAG patients, aged 40 to 60 years, had higher volumes of cerebral microinfarcts and (2) POAG patients showed a significant correlation between cerebral microinfarcts and degeneration of the optic radiation. 
Acknowledgments
The present work was performed in (partial) fulfillment of the requirements for obtaining the degree “Dr. med.” 
Disclosure: J. Schoemann, None; T. Engelhorn, None; S. Waerntges, None; A. Doerfler, None; A. El-Rafei, None; G. Michelson, None 
References
Quigley HA. The number of people with glaucoma worldwide in 2010 and 2020. Br J Ophthalmol. 2006; 90: 262–267. [CrossRef] [PubMed]
Casson RJ Chidlow G Wood JPM Crowston JG Goldberg I. Definition of glaucoma: clinical and experimental concepts. Clin Exp Ophthalmol. 2012; 40: 341–349. [CrossRef]
Gupta N. Human glaucoma and neural degeneration in intracranial optic nerve, lateral geniculate nucleus, and visual cortex. Br J Ophthalmol. 2006; 90: 674–678. [CrossRef] [PubMed]
Kanjee R Yücel Y Steinbach MJ González EG Gupta N. Delayed saccadic eye movements in glaucoma. Eye Brain. 2012; 4: 63–68.
Weinreb RN Khaw PT. Primary open-angle glaucoma. Lancet. 2004; 363: 1711–1720. [CrossRef] [PubMed]
Rahmani B Tielsch JM Katz J The cause-specific prevalence of visual impairment in an urban population: The Baltimore Eye Survey. Ophthalmology. 1996; 103: 1721–1726. [CrossRef] [PubMed]
Quigley HA Vitale S. Models of open-angle glaucoma prevalence and incidence in the United States. Invest Ophthalmol Vis Sci. 1997; 38: 83–91. [PubMed]
Heijl A Bengtsson B Hyman L Leske MC. Natural history of open-angle glaucoma. Ophthalmology. 2009; 116: 2271–2276. [CrossRef] [PubMed]
Kass MA Heuer DK Higginbotham EJ The Ocular Hypertension Treatment Study: a randomized trial determines that topical ocular hypotensive medication delays or prevents the onset of primary open-angle glaucoma. Arch Ophthalmol. 2002; 120: 701–713; discussion 829–830. [CrossRef] [PubMed]
Gordon MO Beiser JA Brandt JD The Ocular Hypertension Treatment Study: baseline factors that predict the onset of primary open-angle glaucoma. Arch Ophthalmol. 2002; 120: 714–720; discussion 829–830. [CrossRef] [PubMed]
Sommer A Tielsch JM Katz J Relationship between intraocular pressure and primary open angle glaucoma among white and black Americans: The Baltimore Eye Survey. Arch Ophthalmol. 1991; 109: 1090–1095. [CrossRef] [PubMed]
Mitchell P Smith W Attebo K Healey PR. Prevalence of open-angle glaucoma in Australia: The Blue Mountains Eye Study. Ophthalmology. 1996; 103: 1661–1669. [CrossRef] [PubMed]
Leung DY Tham CC Li FC Kwong YY Chi SC Lam DS. Silent cerebral infarct and visual field progression in newly diagnosed normal-tension glaucoma. Ophthalmology. 2009; 116: 1250–1256. [CrossRef] [PubMed]
Mok V Wong A Tang WK Determinants of prestroke cognitive impairment in stroke associated with small vessel disease. Dement Geriatr Cogn Disord. 2005; 20: 225–230. [CrossRef] [PubMed]
Zijdenbos AP Dawant BM Margolin RA Palmer AC. Morphometric analysis of white matter lesions in MR images: method and validation. IEEE Trans Med Imaging. 1994; 13: 716–724. [CrossRef] [PubMed]
Vermeer SE Hollander M van Dijk EJ Hofman A Koudstaal PJ Breteler MM. Silent brain infarcts and white matter lesions increase stroke risk in the general population: the Rotterdam Scan Study. Stroke. 2003; 34: 1126–1129. [CrossRef] [PubMed]
Pantoni L Garcia JH. Pathogenesis of leukoaraiosis: a review. Stroke. 1997; 28: 652–659. [CrossRef] [PubMed]
Baleanu D Michelson G. Diagnostik und Therapie des Normaldruckglaukoms. Klin Monatsbl Augenheilkd. 2005; 222: 760–771. [CrossRef] [PubMed]
Engelhorn T Michelson G Waerntges S Changes of radial diffusivity and fractional anisotopy in the optic nerve and optic radiation of glaucoma patients. ScientificWorldJournal. 2012; 2012: 1–5. [CrossRef]
Basser PJ Mattiello J LeBihan D. MR diffusion tensor spectroscopy and imaging. Biophys J. 1994; 66: 259–267. [CrossRef] [PubMed]
Steen RG Hamer RM Lieberman JA. Measuring brain volume by MR imaging: impact of measurement precision and natural variation on sample size requirements. AJNR Am J Neuroradiol. 2007; 28: 1119–1125. [CrossRef] [PubMed]
Ambarki K Wåhlin A Birgander R Eklund A Malm J. MR imaging of brain volumes: evaluation of a fully automatic software. AJNR Am J Neuroradiol. 2011; 32: 408–412. [CrossRef] [PubMed]
Basser PJ Pierpaoli C. Microstructural and physiological features of tissues elucidated by quantitative-diffusion-tensor MRI. J Magn Reson B. 1996; 111: 209–219. [CrossRef] [PubMed]
Mori S Barker PB. Diffusion magnetic resonance imaging: its principle and applications. Anat Rec. 1999; 257: 102–109. [CrossRef] [PubMed]
Le Bihan D Mangin JF Poupon C Diffusion tensor imaging: concepts and applications. J Magn Reson Imaging. 2001; 13: 534–546. [CrossRef] [PubMed]
Staempfli P Rienmueller A Reischauer C Valavanis A Boesiger P Kollias S. Reconstruction of the human visual system based on DTI fiber tracking. J Magn Reson Imaging. 2007; 26: 886–893. [CrossRef] [PubMed]
Sherbondy AJ Dougherty RF Napel S Wandell BA. Identifying the human optic radiation using diffusion imaging and fiber tractography. J Vis. 2008; 8 (10): 1–11.
Sullivan EV Rohlfing T Pfefferbaum A. Quantitative fiber tracking of lateral and interhemispheric white matter systems in normal aging: relations to timed performance. Neurobiol Aging. 2010; 31: 464–481. [CrossRef] [PubMed]
Engelhorn T Michelson G Waerntges S Struffert T Haider S Doerfler A. Diffusion tensor imaging detects rarefaction of optic radiation in glaucoma patients. Acad Radiol. 2011; 18: 764–769. [CrossRef] [PubMed]
Beaulieu C. The basis of anisotropic water diffusion in the nervous system: a technical review. NMR Biomed. 2002; 15: 435–455. [CrossRef] [PubMed]
Engelhorn T Michelson G Waerntges S A new approach to assess intracranial white matter abnormalities in glaucoma patients: changes of fractional anisotropy detected by 3T diffusion tensor imaging. Acad Radiol. 2012; 19: 485–488. [CrossRef] [PubMed]
Smith EE Schneider JA Wardlaw JM Greenberg SM. Cerebral microinfarcts: the invisible lesions. Lancet Neurol. 2012; 11: 272–282. [CrossRef] [PubMed]
Breteler M van Swieten JC Bots ML Cerebral white matter lesions, vascular risk factors, and cognitive function in a population-based study: The Rotterdam Study. Neurology. 1994; 44: 1246. [CrossRef] [PubMed]
Ong K Farinelli A Billson F Houang M Stern M. Comparative study of brain magnetic resonance imaging findings in patients with low-tension glaucoma and control subjects. Ophthalmology. 1995; 102: 1632–1638. [CrossRef] [PubMed]
Suzuki J Tomidokoro A Araie M Visual field damage in normal-tension glaucoma patients with or without ischemic changes in cerebral magnetic resonance imaging. Jpn J Ophthalmol. 2004; 48: 340–344.
Stroman GA. Magnetic resonance imaging in patients with low-tension glaucoma. Arch Ophthalmol. 1995; 113: 168. [CrossRef] [PubMed]
Kitsos G Zikou AK Bagli E Kosta P Argyropoulou MI. Conventional MRI and magnetisation transfer imaging of the brain and optic pathway in primary open-angle glaucoma. Br J Radiol. 2009; 82: 896–900. [CrossRef] [PubMed]
Michelson G Engelhorn T Wärntges S El Rafei A Hornegger J Doerfler A. DTI parameters of axonal integrity and demyelination of the optic radiation correlate with glaucoma indices. Graefes Arch Clin Exp Ophthalmol. 2013; 251: 243–253. [CrossRef] [PubMed]
Gupta N Yücel YH. What changes can we expect in the brain of glaucoma patients? Sur Ophthalmol. 2007; 52: S122. [CrossRef]
Lu P Shi L Du H Reduced white matter integrity in primary open-angle glaucoma: a DTI study using tract-based spatial statistics. J Neuroradiol. 2013; 40: 89–93. [CrossRef] [PubMed]
Garaci FG Bolacchi F Cerulli A Optic nerve and optic radiation neurodegeneration in patients with glaucoma: in vivo analysis with 3-T diffusion-tensor MR imaging. Radiology. 2009; 252: 496–501. [CrossRef] [PubMed]
Shinkawa A Ueda K Kiyohara Y Silent cerebral infarction in a community-based autopsy series in Japan: The Hisayama Study. Stroke. 1995; 26: 380–385. [CrossRef] [PubMed]
Longstreth WT Jr Diehr P Beauchamp NJ Manolio TA. Patterns on cranial magnetic resonance imaging in elderly people and vascular disease outcomes. Arch Neurol. 2001; 58: 2074. [CrossRef] [PubMed]
Wong TY Klein R Sharrett AR Cerebral white matter lesions, retinopathy, and incident clinical stroke. JAMA. 2002; 288: 67–74. [CrossRef] [PubMed]
Zhang S Xie Y Yang J Reduced cerebrovascular reactivity in posterior cerebral arteries in patients with primary open-angle glaucoma. Ophthalmology. 2013; 120: 2501–2507. [CrossRef] [PubMed]
Prins ND. Cerebral white matter lesions and the risk of dementia. Arch Neurol. 2004; 61: 1531. [CrossRef] [PubMed]
Hernowo AT Boucard CC Jansonius NM Hooymans JM Cornelissen FW. Automated morphometry of the visual pathway in primary open-angle glaucoma. Invest Ophthalmol Vis Sci. 2011; 52: 2758–2766. [CrossRef] [PubMed]
Williams AL Lackey J Wizov SS Evidence for widespread structural brain changes in glaucoma: a preliminary voxel-based MRI study. Invest Ophthalmol Vis Sci. 2013; 54: 5880–5887. [CrossRef] [PubMed]
Figure 1
 
Region of interest identified on the optic radiation demonstrated on a fractional anisotropy image (A). White matter lesions in the optic radiation shown on a T2-weighted FLAIR image (B). The picture was not from the same patient.
Figure 1
 
Region of interest identified on the optic radiation demonstrated on a fractional anisotropy image (A). White matter lesions in the optic radiation shown on a T2-weighted FLAIR image (B). The picture was not from the same patient.
Figure 2
 
White matter lesion volumes in different decades. *Significant difference, P = 0.003.
Figure 2
 
White matter lesion volumes in different decades. *Significant difference, P = 0.003.
Figure 3
 
Mean fractional anisotropy for both hemispheres. *Significant difference, P = 0.001. **Significant difference, P = 0.011.
Figure 3
 
Mean fractional anisotropy for both hemispheres. *Significant difference, P = 0.001. **Significant difference, P = 0.011.
Table 1
 
Baseline Clinical Characteristics
Table 1
 
Baseline Clinical Characteristics
Characteristics POAG n = 39, 64% Controls n = 22, 36% Value
Age, y* 63.9 ± 9.3 63.3 ± 11.9 0.165
Sex, male/female 13/26 9/13 0.296
Visual acuity, decimal
 Right eye 0.80 ± 0.22 0.72 ± 0.29 0.392
 Left eye 0.77 ± 0.26 0.71 ± 0.31 0.614
IOP, mm Hg
 Right eye 14.67 ± 5.2 14.10 ± 2.8 0.981
 Left eye 15.10 ± 5.7 14.33 ± 2.7 1.000
Mean defect, dB
 Right eye* 7.36 ± 6.56 0.20 ± 0.28 0.037†
 Left eye* 8.70 ± 6.80 0.50 ± 1.13 0.075
Retinal nerve fiber thickness, μm
 Right eye* 71.03 ± 15.70 104.00 ± 13.38 <0.0001†
 Left eye* 66.55 ± 16.16 101.29 ± 12.24 <0.0001†
Table 2
 
Relative and Absolute Volumes of WMLs in cm3 in Different Areas of the Brain, P Value of U-Test
Table 2
 
Relative and Absolute Volumes of WMLs in cm3 in Different Areas of the Brain, P Value of U-Test
Structure POAG Controls Factor Value
Absolute WML volumes, cm3
Total brain 2.7 ± 4.4 1.2 ± 1.7 2.15 0.087
Subcortical 1.1 ± 2.1 0.5 ± 0.9 1.99 0.040*
Periventricular 1.0 ± 2.2 0.4 ± 0.7 2.83 0.215
Optic radiation 0.6 ± 1.1 0.4 ± 0.5 1.75 0.355
Relative WML volumes
Total brain × 10E-3 2.57 ± 4.2 1.22 ± 1.6 2.11 0.083
Subcortical × 10E-3 1.03 ± 1.9 0.54 ± 0.9 1.90 0.039*
Periventricular × 10E-3 0.95 ± 2.2 0.34 ± 0.6 2.80 0.210
Optic radiation × 10E-3 0.59 ± 1.1 0.34 ± 0.4 1.73 0.347
Table 3
 
Correlation Between WML Volumes and Age
Table 3
 
Correlation Between WML Volumes and Age
Structure Age in POAG Age in Controls
Location of WML Value Value
Total brain WML 0.248 0.131 0.584 0.004*
Subcortical WML 0.080 0.628 0.617 0.002*
Periventricular WML 0.301 0.063 0.357 0.103
Optic radiation WML 0.210 0.199 0.425 0.049*
Table 4
 
Correlation Between Axonal Integrity of the Optic Radiation and Age
Table 4
 
Correlation Between Axonal Integrity of the Optic Radiation and Age
Structure Age in POAG Age in Controls
Axonal Integrity Value Value
Right visual pathway −0.481 0.002* −0.345 0.116
Left visual pathway −0.489 0.002* −0.230 0.303
Table 5
 
Correlation Between Fractional Anisotropy of the Optic Radiation and WML Volumes
Table 5
 
Correlation Between Fractional Anisotropy of the Optic Radiation and WML Volumes
FA in POAG FA in Controls
Right Optic Radiation Left Optic Radiation Right Optic Radiation Left Optic Radiation
WML Volumes Value Value Value Value
Total brain −0.420 0.008* −0.393 0.013* −0.187 0.404 −0.096 0.672
Subcortical −0.930 0.571 −0.143 0.384 −0.146 0.517 0.026 0.909
Periventricular −0.432 0.006* −0.504 0.001* −0.093 0.681 −0.127 0.572
Optic radiation −0.453 0.004* −0.409 0.010* −0.267 0.229 −0.219 0.328
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