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Evidence of Subcortical and Cortical Aging of the Acoustic Pathway: A Diffusion Tensor Imaging (DTI) Study
Evidence of Subcortical and Cortical Aging of the Acoustic Pathway: A Diffusion Tensor Imaging (DTI) Study1 Juergen Lutz, MD, Felix Hemminger, MD, Robert Stahl, MD, Olaf Dietrich, MD, Martin Hempel, MD Maximilian Reiser, MD, Lorenz Jäger, MD
Rationale and Objectives. During aging, there is evidence of microstructural changes in certain cortical and subcortical brain regions. Diffusion tensor imaging (DTI) is used to study age related microstructural changes in the acoustic pathway. Materials and Methods. Twenty healthy volunteers (mean age 28.5 years) and 15 healthy volunteers (mean age 61.3 years) were examined using a 1.5-T MR system with a high-resolution T1-weighted sequence and an integrated parallel imaging technique DTI Echo-planar-imaging (EPI) sequence. For reliability, 10 subjects underwent a second examination 2 days later. The fractional anisotropy (FA) and the apparent diffusion coefficient (ADC) were measured in six brain regions of the auditory pathway. Results. We found no left/right asymmetry in the selected brain structures. There were no significant differences (P ⬍ .05) in the ADC and FA in the lateral lemniscus and medial geniculate body of young and elderly subjects. However, FA was significantly increased (P ⬍ .05) in the inferior colliculus and decreased in the auditory radiation, the superficial temporal gyrus, and the transverse temporal gyrus in the elder subjects than in the younger ones. There were no significant differences in anisotropy in subsequent examinations in the younger individuals. Conclusions. These findings suggest evidence of age-related changes in the acoustic pathway. These changes are associated with a decrease in anisotropy mainly in the cortical grey and white matter rather than in the subcortical regions. Our DTI measurements were reproducible. Key Words. Diffusion tensor imaging; reproducibility; aging, auditory pathway; fractional anisotropy; apparent diffusion coefficient. ©
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The aging brain shows a variety of micro- and macroscopic changes, which can result in some degree of functional decline. During aging, the auditory system undergoes numerous changes in its structure, function, and neuro-
Acad Radiol 2007; 14:692–700 1
From the Department of Clinical Radiology (J.L., F.H., R.S., O.D., M.R., L.J.) and Department of Otolaryngology (M.H.), University of Munich, Grosshadern, Marchioninistr. 15, 81377 Munich, Germany. Received August 24, 2006; accepted February 13, 2007. Address correspondence to J.L. e-mail: [email protected]
© AUR, 2007 doi:10.1016/j.acra.2007.02.014
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chemistry (1,2). Age-related hearing changes have usually been attributed to changes in the cochlea, inducing a loss of sensory cells, atrophy of stria vascularis, and a loss of spiral ganglion cells (4). However, there is strong evidence that changes in the ability of hearing is also due to changes in the central auditory system (5,6). The anatomic structure of the acoustic pathway is organized as follows: The anatomic organization of the auditory system consists of a large ensemble of subcortical nuclei, connected with each other and with the auditory cortex through ascending and descending white matter fiber pathways, processing both serial and parallel information
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within the auditory system. The cochlear nerve connects the cochlear with the anterior and posterior cochlear nucleus in the brainstem. Then, the majority of fibres cross to the contralateral side (90%) and approximately 10% run ipsilaterally to connect the auditory nuclei with the superior olivary complex. The fibers of the pathway reach the medial geniculate body, which is the thalamic auditory relay station and are there transmitted bilateral toward the primary auditory cortices. The gyri directly involved in the auditory perception are the transverse temporal gyri (of Heschl) and the superior temporal gyrus. Diffusion tensor imaging (DTI), a recently emerged, exciting variation of magnetic resonance imaging (MRI), provides a unique opportunity to visualize the integrity of tissue microstructure and quantify the diffusion of water in various tissues noninvasively (7,8). Tissues, which have a random microstructure, such as cerebrospinal fluid, show isotropic diffusion properties (9). This means diffusion is equal in all directions. In contrast, in tissues that have a regularly ordered microstructure, such as brain white matter, water molecules behave in a sorted fashion, with a predominant motion direction and a given orientation, indicating a marked anisotropy in the diffusion properties (10). The microstructural tissue changes can be expressed as FA (fractional anisotropy), which has no dimension and as mean diffusitivity (apparent diffusion coefficient, ADC) with ⫻10⫺3 mm2/s (11). These indices can be seen as complementary for the evaluation of brain tissue. Whereas ADC is a measure of the directionally averaged magnitude of diffusional motion of water molecules (⫽ related to integrity of membranes), FA describes the degree of anisotropy the process of molecular diffusion (⫽ degree of structural alignment) (11). Previous DTI studies have shown white matter declines in normal aging and various neuropsychiatric disorders (9,12–14). Two earlier studies investigating the acoustic pathway by the means of DTI were focused on patients with sensineuronal hearing loss (15) and the FA value of Heschl’s gyrus in a normal population (16). However, to the best of our knowledge, there is no previous study, investigating the aging of the acoustic pathway. The major goal of this study was to evaluate the aging of structures of the acoustic pathway by means of measuring the mean diffusivity and anisotropy values in young healthy adults in comparison to elderly healthy adults. Therefore, we designed a DTI acquisition protocol, using integrated parallel imaging technique (iPAT) to investigate the anisotropy of the acoustic pathway. To analyze the reliability of anisotropy measurements, we
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investigated the reproducibility of our DTI measurements, using a second follow-up examination of our younger study group in the same experimental settings.
MATERIAL AND METHODS Subjects Twenty young healthy adults (11 males and 9 females; mean age 28.5 years; age range 23–29 years) and 15 elderly healthy adults (8 males and 7 females; mean age 61.3 years; age range 46 – 66 years) volunteered to participate in this study after a written informed consent form was signed. For the reproducibility evaluation, the same 10 young individuals were examined in the identical setting 2 days later. The study was approved by the institutional review board. All subjects completed a detailed questionnaire about current and past medical and psychiatric conditions, medications, and substance use. Additionally, special emphasis was put on previous otologic surgery, systemic ototoxic drugs, and any anatomic abnormalities concerning the auditory system. Subjects were included only if they had no more than three subcortical white matter intensities as examined on the T2-weighted images exceeding 10 mm in diameter. A qualified radiologist (LJ) with 13 years’ experience in head and neck radiology read all MRIs for structural abnormalities. To assess the hearing abilities of both volunteer groups, pure tone audiometry was performed by an experienced ENT specialist (MH) using a clinical audiometer (Auritec AT 330, Dorn, Hamburg, Germany). Image Acquisition The study was performed on a 1.5-T MR System (Magnetom Sonata Maestro Class, Siemens Medical Solution, Erlangen, Germany) with a maximum gradient strength of 40 mT/m using an eight-channel phased-array head coil for signal reception and capable of iPAT. DTI images were acquired with parallel imaging using the generalized autocalibrating partially parallel acquisition algorithm with an acceleration factor of two. During a single examination, the following MRIs were obtained: 1) For structural data, a high-resolution three-dimensional inversion-recovery gradient-echo T1-weighted magnetization prepared rapidly acquired gradient echo sequence (MPRAGE) with a resolution of 1.1 ⫻ 1.1 ⫻ 1.1 mm3 and echo time/inversion time (TI)/repetition time of 3.9 milliseconds/800 milliseconds/1,570 milliseconds, respec-
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tively. We acquired 160 sagittal slices with a matrix size of 256 ⫻ 256 and a field of view of 270 ⫻ 270 mm2. Examination time was 6:42 minutes. 2) An iPAT spinecho single-shot EPI-sequence (echo time 71 milliseconds, repetition time 6,000 milliseconds) with a matrix size of 128 ⫻ 128, field of view of 230 ⫻ 230 mm2 and a resulting voxel size of 1.8 ⫻ 1.8 ⫻ 3.6 mm3 spatial resolution. Thirty-six slices with axial orientation were acquired and 10 measurements were selected and averaged. The minimum b value was 0 seconds/mm2 and the maximum was 1,000 seconds/mm2. Diffusion gradients in six different spatial directions were applied. The use of six gradient directions adequately characterizes the full diffusion tensor (17). Examination time was 7:44 minutes. Image Analysis Calculation of the diffusion tensor was based on the method of Bassser et al (18). All analysis of the diffusion tensor was performed on an offline workstation using inhouse software running on Matlab 5.3 (The Math Works Inc, Novi, MI). From the diffusion-weighted sequences, the values for FA and ADC in each voxel were calculated using an in-house developed software under IDL (Interactive Data Language, version 5.4, Research of System Inc., Fort Collins, CO). One set, the T2-weighted images, from the EPI sequence with a b value of 0, as well as the diffusion-weighted (six sets) and the MPRAGE images, were converted separately into a three-dimensional volume dataset of the analyze format. Motion correction was performed using a spatial realignment algorithm under SPM 99 with the six diffusion direction-encoded datasets and the one, non– diffusion weighted (b ⫽ 0) dataset. The T2-weighted data records were subsequently coregistered to the corresponding MPRAGE data records using the coregistration algorithms offered by the SPM 99-software package (Statistical Parametric Mapping, Wellcome Department of Cognitive Neurology, University College London, London, UK; extension of the MATLAB programming language, version 5.3, The Math Works Inc). These received transformation parameters were applied to the FA and mean diffusitivity (MD) datasets. To apply a set of regions of interest (ROI) and compare the data between the examined subjects, interferences from individual brain forms had to be excluded. This was done by normalizing the MPRAGE data by using the SPM 99 program and wrapping them into the standardized Talairach space (19). The normalized and wrapped datasets were again applied to the coregistered DTI datasets beginning with the b ⫽ 0 images and then to the six diffusion-
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Figure 1. Representative fractional anisotropy (FA) maps of four transverse slices of a 25-year-old male volunteer and a 65-yearold volunteer.
weighted datasets using the affine transformation of SPM 99 for the calculation of the different ROIs of FA and ADC values. Representative FA maps of the younger and older adults are shown in Fig 1.
Region of Interest MD and FA values were collected from regions of interest (ROIs), in six different gray and white matter brain regions. All ROIs were marked by the same person (LJ), blind to participant’s age and date of examination. Rectangular ROIs of variable size (range ⫽ 11.4 – 46.7 mm2), depending on the anatomic region studied, were placed bilaterally in the white and gray matter of the selected areas. The ROIs were drawn on the corresponding slice of the MPRAGE image, where the structures were visualized to be at their thickest. Using the visualization software MRIcro (Version 1.40 build 1), the structure in question was outlined following its boundaries. However, the lateral lemniscus, the inferior colliculus, and the medial geniculate body had very small ROIs placed, owing to their anatomic distinct localization. The inferior colliculus and medial geniculate body were measured on two adjacent slices, on which they were fully contained. The lateral lemniscus, acoustic radiation, and Heschl’s gyrus (transverse temporal gyrus) were identified and measured on three slices. All regional definitions included only voxels with minimal partial voluming with cerebrospinal fluid. These ROIs were transferred to the ADC and FA datasets of each subject and the appropriate mean values of each ROI were calculated. Here appropriate left and right measurements were taken separately. Representative ROIs are shown in Fig 2.
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Figure 2. Positioning of the regions of interest (ROIs) on the normalized axial T1-weighted MPRAGE images. From upper right to lower left: inferior colliculus (IC), medial geniculate body (CGM), lateral lemniscus (LL), acoustic radiation (RA), Heschl’s gyrus (TTG), and superior temporal gyrus (STG).
Statistical Analysis The FA values of the study group are reported as the mean ⫾ standard deviation. The calculated mean values of the ADC and FA were tested for normal distribution using the KolmogorovSmirnov test. The mean values for the left and right hemispheres of each individual were compared using the two-tailed paired Student t-test (significant with P ⬍ .05). If there is no significant left-right difference detectable, the values are averaged for all further analysis. The twotailed unpaired Student t-tests were performed to compare the mean ADC and FA values in the ROIs individually across the younger and elderly study group. For the follow-up examination, the two-tailed unpaired Student t-test was used. A P value of less than .05 was considered to indicate a statistically significant difference. All evaluations were done using the software package SPSS (Statistical software for the Social Sciences, version 10, SPSS Inc., Chicago, IL).
RESULTS The coregistration and normalization procedures were applied to all datasets without any difficulties. Comparing the left and right side in both study groups, there were no significant differences (P ⬎ .05) in the FA and ADC values for all brain regions (Tables 1 and 2). Hence, for fur-
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ther analysis, the FA and ADC values of the right and left were averaged. The ADC values in all selected brain regions showed no significant difference for the younger or elderly study group. The comparison between younger and elderly subjects did not reveal significant differences (P ⬎ .05) in FA in the lateral lemniscus and medial geniculate body. We found a significant reduction (P ⬍ .05) of FA values in the acoustic radiation, Heschl’s gyrus, and the superior temporal gyrus in the elderly subjects in comparison to the younger subjects (Table 3). In contrast, there was a significant increase (P ⬍ .05) in the anisotropy indices FA in the inferior colliculus. The summary of the different P values is shown in Table 3 and Fig 3. For evaluating the reproducibility, the follow-up examinations in the same younger subject population showed no significant differences (P ⬍ .05) in MD and FA measurements. The summary of the different P values is presented in Table 4 and Fig 4.
DISCUSSION Diagnostic imaging of the acoustic pathway is mainly based on MRI. Gross pathologies, such as acoustic schwannomas or encephalitis, are readily detected. Using MRI, the changes of cerebral structures associated with aging have been extensively investigated. Volume loss of the brain tissue, enlargement of the lateral ventricles, patchy areas of abnormal signal intensity within the white matter and basal ganglia, as well as progressive hypointensity in the globus pallidus and putamen were described as typical signs of aging (20). In contrast to cortical gray matter, white matter shows little age-related volume alteration in conventional MRI (21). Histopathology studies detected substantial age-related changes also in the white matter of the brain, such as decrease or disturbances in the microstructure of white matter, proven as demyelination, deterioration, and axonal loss (22). Because of this, we used DTI to study the morphologic changes in the microstructural environment of the auditory pathway during aging and examined the reliability of our results. This new imaging technique has been applied successfully to detect functional changes in several neurologic and psychiatric conditions—for example, multiple sclerosis (23–25), ischemia (26), and schizophrenia (27). However, there is little knowledge about the reproducibility of DTI indices for longitudinal studies.
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Table 1 Comparison of the ADC and FA Values for the Different Brain Regions of the Left and Right Hemisphere in the Younger Study Group Comparison of Right and Left Hemisphere: Younger Subjects ADC (⫻ 10⫺3 mm2/s)
FA
Region
Right
Left
P Value
Right
Left
P Value
Lateral lemniscus Inferior colliculus Medial geniculate body Acoustic radiation Heschl’s gyrus Superior temp gyrus
0.805 (⫾ 0.01) 0.537 (⫾ 0.02) 0.644 (⫾ 0.02) 0.708 (⫾ 0.07) 0.779 (⫾ 0.01) 0.762 (⫾ 0.05)
0.801 (⫾ 0.01) 0.534 (⫾ 0.03) 0.653 (⫾ 0.06) 0.700 (⫾ 0.05) 0.755 (⫾ 0.04) 0.743 (⫾ 0.05)
.198 .272 .758 .317 .262 .174
0.32 (⫾ 0.05) 0.17 (⫾ 0.03) 0.21 (⫾ 0.02) 0.71 (⫾ 0.03) 0.37 (⫾ 0.03) 0.37 (⫾ 0.03)
0.32 (⫾ 0.04) 0.16 (⫾ 0.02) 0.21 (⫾ 0.02) 0.72 (⫾ 0.02) 0.37 (⫾ 0.03) 0.37 (⫾ 0.02)
.979 .084 .758 .149 .463 0.943
ADC: apparent diffusion coefficient; FA: fractional anisotropy. Mean values with standard deviation in parentheses. P values ⬍ .05 indicate significant difference.
Table 2 Comparison of the ADC and FA Values for the Different Brain Regions of the Left and Right Hemisphere in the Elderly Study Group Comparison of Right and Left Hemisphere: Elder Subjects ADC (⫻ 10⫺3mm2/s)
FA
Region
Right
Left
P Value
Right
Left
P Value
Lateral lemniscus Inferior colliculus Medial geniculate body Acoustic radiation Heschl’s gyrus Superior temp gyrus
0.802 (⫾ 0.02) 0.552 (⫾ 0.05) 0.644 (⫾ 0.02) 0.737 (⫾ 0.05) 0.755 (⫾ 0.04) 0.775 (⫾ 0.04)
0.810 (⫾ 0.02) 0.543 (⫾ 0.03) 0.643 (⫾ 0.02) 0.725 (⫾ 0.06) 0.751 (⫾ 0.06) 0.759 (⫾ 0.06)
.087 .258 .563 .463 .681 .059
0.30 (⫾ 0.01) 0.18 (⫾ 0.08) 0.22 (⫾ 0.02) 0.64 (⫾ 0.03) 0.30 (⫾ 0.03) 0.35 (⫾ 0.01)
0.30 (⫾ 0.02) 0.18 (⫾ 0.09) 0.22 (⫾ 0.02) 0.65 (⫾ 0.04) 0.31 (⫾ 0.03) 0.35 (⫾ 0.01)
.569 .277 .918 .277 .196 .717
ADC: apparent diffusion coefficient; FA: fractional anisotropy. Mean values with standard deviation in parentheses. P values ⬍ .05 indicate significant difference.
Therefore, we have examined the morphologic changes in the microstructural environment of the acoustic pathway during aging and the reproducibility of the DTI results. For the evaluation of reproducibility, we did follow-up examinations in our younger study collective with a second scan on the same scanner system 2 days later. The FA and ADC values of the regions of the acoustic pathway of our younger study group showed no significant difference in both examinations. Our results confirm the previously published reproducibility of DTI results of supratentorial brain areas (28). Additionally, we were able to show that FA and ADC values are also reproducible in infratentorial brain regions, as with the inferior colliculus. Our results argue for the use of DTI indices to quantify changes of neuronal microarchitecture from aging or neurologic dysfunction.
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DTI has also been used in the investigation of normal aging to detect age-related degeneration (12,13,29). Significant age-related declines in median FA have been demonstrated in densely packed white matter fiber areas, particularly in the genu of the corpus callosum and the centrum semiovale (29). However, the aging of the acoustic pathway has not yet been studied. A prior DTI study published by Sullivan et al demonstrated no substantial gender dependent differences in anisotropy in aging men and women (30). According to the previous DTI study, we did not attempt to investigate the effect of gender in our study group because of the relatively small number of subjects. Age-related changes in the structures of the auditory circuit and accompanying hearing impairment are one of the most common age-related health problems afflicting
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Table 3 Average ADC and FA Values for the Different Brain Regions of the Younger and the Elder Subjects Comparison of Younger vs Elder Subjects ADC (⫻ 10⫺3 mm2/s)
FA
Region
Younger
Older
P Value
Younger
Older
P Value
Lateral lemniscus Inferior colliculus Medial geniculate body Acoustic radiation Heschl’s gyrus Superior temp gyrus
0.801 (⫾ 0.02) 0.540 (⫾ 0.04) 0.650 (⫾ 0.05) 0.700 (⫾ 0.04) 0.821 (⫾ 0.01) 0.764 (⫾ 0.01)
0.805 (⫾ 0.03) 0.547 (⫾ 0.02) 0.645 (⫾ 0.02) 0.732 (⫾ 0.02) 0.830 (⫾ 0.03) 0.810 (⫾ 0.06)
.658 .112 .323 .067 .441 .356
0.31 (⫾ 0.04) 0.17 (⫾ 0.02) 0.21 (⫾ 0.02) 0.71 (⫾ 0.05) 0.36 (⫾ 0.04) 0.37 (⫾ 0.02)
0.31 (⫾ 0.01) 0.18 (⫾ 0.06) 0,21 (⫾ 0.01) 0.64 (⫾ 0.02) 0.31 (⫾ 0.05) 0.35 (⫾ 0.03)
.691 .0006 .686 ⬍.0001 ⬍.0001 ⬍.0001
ADC: apparent diffusion coefficient; FA: fractional anisotropy. Mean values with standard deviation in parentheses. P values ⬍ .05 indicate significant difference.
Figure 3. The mean values of the fractional anisotropy index for the right (a) and the left (b) hemisphere in younger and elder group at six locations of the auditory pathway are shown. There was no difference to the correspondent measured acoustic radiation indices.
the elderly population. Typically, there is a loss of hair cells of the cochlea. Concomitantly with the loss of hair cells, reduction of hearing ability is accompanied by a loss of spiral ganglion cells, which usually comprises the loss of peripheral dendrites as well as central projections (ie, auditory nerve fibers) (31). Although changes in the hearing function are predominantly the result of cochlear pathology, the results of several studies indicate that changes in the function of the central auditory system may also play an important role (2). Because of the divergent findings published, we compared the FA and ADC values of the acoustic pathway between younger and elderly subjects. We found a significant increase of FA values in the inferior colliculus of the elderly population as compared with the group of young individuals. These findings could argue for a change in the molecular structure and the integrity of white matter fibers in the inferior
colliculus that result in an increase in measured anisotropy. An increase in anisotropy was found previously in maturation studies during childhood and was regarded as increasing myelination in children ⬍5 years or as a higher degree of fiber tract organization (32). This higher degree of fiber tract organization has been shown before to result in an increase in fractional anisotropy during nerve development, which is brought about by an increase in longitudinal diffusion without a concurrent decrease in transverse diffusion. Cellular components and membranes, such as tissue hydration, myelination, fiber diameter, and cell-packing density, influence fiber tract organization. This increased dense and ordered packing of fiber tracks leads to directionally more restricted extracellular, rather than intracellular space. Therefore, it may be speculated, that an increase of overall anisotropy in the inferior colliculus may be the result of an increased density of tightly
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Table 4 The P Values of the Follow-Up Examination of the Younger Study Group, Indicating Excellent Reproducibility (P > .05) for the FA value (a) and the ADC (b) a. FA P Values (P ⬍ .05) Reproducibility: Younger Subjects Right
Left
Region
1. Scan
2. Scan
P Value
1. Scan
2. Scan
P Value
Lateral lemniscus Inferior colliculus Medial geniculate body Acoustic radiation Heschl’s gyrus Superior temp gyrus
0.32 (⫾ 0.05) 0.17 (⫾ 0.03) 0.21 (⫾ 0.02) 0.71 (⫾ 0.03) 0.37 (⫾ 0.03) 0.37 (⫾ 0.03)
0.28 (⫾ 0.02) 0.18 (⫾ 0.04) 0.19 (⫾ 0.03) 0.70 (⫾ 0.01) 0.35 (⫾ 0.02) 0.38 (⫾ 0.06)
.176 .310 .091 .147 .35 .466
0.32 (⫾ 0.04) 0.16 (⫾ 0.02) 0.21 (⫾ 0.02) 0.72 (⫾ 0.02) 0.37 (⫾ 0.03) 0.37 (⫾ 0.02)
0.30 (⫾ 0.01) 0.19 (⫾ 0.03) 0.19 (⫾ 0.03) 0.70 (⫾ 0.02) 0.35 (⫾ 0.01) 0.37 (⫾ 0.02)
.240 .058 0.128 .063 .553 .695
b. ADC (⫻ 10–3mm2/s) P Values (P ⬍ .05) Reproducibility: Younger Subjects Right
Left
Region
1. Scan
2. Scan
P Value
1. Scan
2. Scan
P Value
Lateral lemniscus Inferior colliculus Medial geniculate body Acoustic radiation Heschl’s gyrus Superior temp gyrus
0.805 (⫾ 0.01) 0.537 (⫾ 0.02) 0.644 (⫾ 0.02) 0.708 (⫾ 0.07) 0.779 (⫾ 0.01) 0.762 (⫾ 0.05)
0.811 (⫾ 0.06) 0.540 (⫾ 0.02) 0.671 (⫾ 0.04) 0.691 (⫾ 0.02) 0.775 (⫾ 0.05) 0.739 (⫾ 0.03)
.352 .753 .061 .485 .977 .078
0.801 (⫾ 0.01) 0.534 (⫾ 0.03) 0.653 (⫾ 0.06) 0.700 (⫾ 0.05) 0.755 (⫾ 0.04) 0.743 (⫾ 0.05)
0.820 (⫾ 0.06) 0.552 (⫾ 0.04) 0.667 (⫾ 0.04) 0.718 (⫾ 0.05) 0.768 (⫾ 0.01) 0.753 (⫾ 0.02)
.080 .053 .500 .159 .798 .187
ADC: apparent diffusion coefficient (ADC); FA: fractional anisotropy (FA). Mean values with standard deviation in parentheses.
Figure 4. For reproducibility evaluation, the mean values of the fractional anisotropy index for the right (a) and the left (b) hemisphere in the younger group are depicted. No statistically significant differences were present between the follow-up examinations at all six locations.
packed axonal components in this highly organized gateway of ascending and descending tracts in the central auditory pathway, leading to the hypothesis that these microstructural changes are due to a compensatory midbrain modulation as a response to a decreased cortical cellular organization and reduction in cortical activity. Furthermore, in animal studies, the inferior colliculus proved to show capability of plastic transformation on the
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microstructural and functional level during the aging process (5,33). These hypotheses are supported by our findings. In contrast to the significant increase in anisotropy in the inferior colliculus, the FA and ADC values in the lateral lemniscus and medial geniculate body showed no significant difference between the two age groups. These results indicate that the integrity of the ascending path-
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ways to the inferior colliculus and particularly the intrathalamic structures of the auditory pathway seem to be not affected by the aging process. In the acoustic radiation and Heschl’s gyrus, we found significantly decreased FA values. These changes of a reduction in anisotropy in these cortical regions argue for a possible disruption of axonal constitution, loss of dendrites, astrogliosis, demyelination, and possible breakdown of white matter fiber tracts and are consistent with previous DTI studies addressing age related brain changes (28,34) and postmortem findings in different other brain regions (35,36). So far, there is not much experience in studying the anisotropy of the acoustic pathway. To the best of our knowledge, a systematic evaluation of the aging of the acoustic pathway has not yet been done. In one of the recent DTI studies concerning regions of the auditory cortex, Hiwatashi et al (16) studied the difference in FA of the Heschl’s and the superior temporal gyrus in six normal subjects (mean age 32 years). In their study, they found higher mean FA values of the subcortical white matter of the Heschl’s gyrus than of the superior temporal gyrus. In their study, the effect of the FA differences was studied using subjects from a wide age range (26 – 41 years). In our study, studying two different age groups, we found slightly lower mean FA values in the Heschl’s gyrus than in the superior temporal gyrus of both age groups. However, the evaluation of the difference between Heschl’s gyrus and the superior temporal gyrus was not the main goal of this study. Because of the difference in age range, both results may not be directly compared. In any case, both regions show a concomitant significant decrease of anisotropy (FA) during aging. Concerning the infratentorial regions of the acoustic pathway, there is some indication that microstructural neuronal organization of the inferior colliculus in subjects with sensorineural hearing loss (15) takes place. To conclude, the results of our study support the hypothesis that aging of the acoustic pathway results not only from deteriorated function of the inner ear, but also from processes of central origin. However, it is difficult to determine to what extent the different subcortical and cortical regions of the central pathway contribute to the declining efficiency in the ability of processing different sound information (eg, frequency changes). All these findings in the aging brain argue for the further use of DTI to evaluate the plasticity of the associated cortical and subcortical regions and in subjects with sensorineural hearing loss (3).
REFERENCES 1. Rauschecker JP. Auditory cortical plasticity: a comparison with other sensory systems. Trends Neurosci 1999; 22:74 – 80. 2. Syka F. Plastic changes in the central auditory system after hearing loss, restoration of function, and during learning. Physiol Rev 2002; 82: 601– 636. 3. Ponton CW, Vasama JP, Tremblay K, et al. Plasticity in the adult human central auditory system: evidence from late-onset profound unilateral deafness. Hear Res 2001; 154:32– 44. 4. Soucek S, Michaels L. Hearing loss in the elderly. London: Springer Verlag, 1990. 5. Mendelson JR, Lui B. The effects of aging in the medial geniculate nucleus: a comparison with the inferior colliculus and auditory cortex. Hear Res 2004; 191:21–33. 6. Moore JK, Niparko JK, Miller MR, et al. Effect of profound hearing loss on a central auditory nucleus. Am J Otol 1994; 15:588 –595. 7. Sotak CH. Nuclear magnetic resonance (NMR) measurement of the apparent diffusion coefficient (ADC) of tissue water and its relationship to cell volume changes in pathological states. Neurochem Int 2004; 45: 569 –582. 8. Moseley ME, Cohen Y, Mintorovitch J, et al. Early detection of ischemic injury: comparison of spectroscopy, diffusion-, T2-, and magnetic susceptibility-weighted MRI in cats. Acta Neurochir 1990; 51:207–209. 9. Le Bihan D, Mangin JF, Poupon C, et al. Diffusion tensor imaging: concepts and applications. J Magn Reson Imaging 2001; 13:534 –546. 10. Beaulieu C. The basis of anisotropic water diffusion in the nervous system—a technical review. NMR Biomed 2002; 15:435– 455. 11. Pierpaoli C, Jezzard P, Basser PJ, et al. Diffusion tensor MR imaging of the human brain. Radiology 1996; 201:637– 648. 12. Moseley M. Diffusion tensor imaging and aging-a review. NMR Biomed 2002; 15:553–560. 13. Sullivan EV, Pfefferbaum A. Diffusion tensor imaging in normal aging and neuropsychiatric disorders. Eur J Radiol 2003; 45:244 –255. 14. Taylor WD, Hsu E, Ranga Rama Krishnan K, et al. Diffusion tensor imaging: background, potential, and utility in psychiatric research. Biol Psychiatry 2004; 55:201–207. 15. Chang Y, Lee SH, Lee YJ, et al. Auditory neural pathway evaluation on sensorineural hearing loss using diffusion tensor imaging. NeuroReport 2004; 15:1699 –1703. 16. Hiwatashi A, Zhong J, Ekholm SE, et al. Fractional anisotropy is higher in Heschl’s gyrus than in superior temporal gyrus in normal subjects. Acad Radiol 2006; 13:73–76. 17. Basser PJ, Pierpaoli C. A simplified method to measure the diffusion tensor from seven MR images. Magn Reson Med 1998; 39:928 –934. 18. Basser PJ. Cable equation for a myelinated axon derived from its microstructure. Med Biol Eng Comput 1993; 31:87–92. 19. Talairach J, Tournoux P. Co-planar stereotaxic atlas of the human brain. New York: Thieme, 1988. 20. Drayer BP. Imaging of the aging brain, I: normal findings. Radiology 1988; 166:785–796. 21. Pfefferbaum A, Mathalon DH, Sullivan EV, et al. A quantitative magnetic resonance imaging study of changes in brain morphology from infancy to late adulthood. Arch Neurol 1994; 51:874 – 887. 22. Aboititz F, Rodriguez E, Olivares R, et al. Age-related changes in fibre composition of the human corpus callosum: sex differences. NeuroReport 1996; 7:1761–1764. 23. Ciccarelli O, Werring DJ, Barker GJ, et al. A study of the mechanisms of normal-appearing white matter damage in multiple sclerosis using diffusion tensor imaging-evidence of Wallerian degeneration. J Neurol 2003; 250:287–292. 24. Guo AC, Jewells VL, Provenzale JM. Analysis of normal-appearing white matter in multiple sclerosis: comparison of diffusion tensor MR imaging and magnetization transfer imaging. AJNR Am J Neuroradiol 2001; 22:1893–1900. 25. Werring DJ, Clark CA, Barker GJ, et al. Diffusion tensor imaging of lesions and normal-appearing white matter in multiple sclerosis. Neurology 1999; 52:1626 –1632.
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26. Sorensen AG, Copen WA, Ostergaard L, et al. Hyperacute stroke: simultaneous measurement of relative cerebral blood volume, relative cerebral flow, and mean tissue transit time. Radiology 1999; 210:519 –527. 27. Lim KO, Hedeus M, Moseley M, et al. Compromised white matter tract integrity in schizophrenia inferred from diffusion tensor imaging. Arch Gen Psychiatry 1999; 56:367–374. 28. Pfefferbaum A, Adalsteinsson E, Sullivan EV. Replicability of diffusion tensor imaging measurements of fractional anisotropy and trace in brain. J Magn Reson Imaging 2003; 18:427– 433. 29. Pfefferbaum A, Sullivan EV, Hedehus M, et al. Age-related decline in brain white matter anisotropy measured with spatially corrected echo-planar diffusion tensor imaging. Magn Reson Med 2000; 44: 259 –268. 30. Sullivan EV, Adalsteinsson E, Hedehus M, et al. Equivalent disruption of regional white matter microstructure in ageing healthy men and women. NeuroReport 2001; 12:99 –104.
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31. Willott JF. Aging and the auditory system: anatomy, physiology, and psychophysics. San Diego, Ca: Singular, 1991. 32. Schmithorst VJ, Wilke M, Dardziinski BJ, et al. Correlation of white matter diffusivity and anisotropy with age during childhood and adolescence: a cross-sectional diffusion-tensor MR imaging study. Radiology 2002; 222:212–218. 33. Palombi PS, Caspary DM. Physiology of the aged Fischer rat 344 inferior colliculus: responses to contralateral stimuli. J Neurophysiol 1996; 76:3114 –3125. 34. Caspary DM, Milbrandt JC, Helfert RH. Central auditory aging: GABA changes in the inferior colliculus. Exp Gerontol 1995; 30:349 –360. 35. Bronge L, Bogdanovic N, Wahlund LO. Postmortem MRI and histopathology of white matter changes in Alzheimer brains. A quantitative, comparative study. Dement Geriatr Cogn Disord 2002; 13:205–212. 36. Meier-Ruge W, Ulrich J, Bruhlamnn, M, et al. Age-related white matter atrophy in the human brain. Ann N Y Acad Sci 1992; 673:260 –269.
Rationale and Objectives. During aging, there is evidence of microstructural changes in certain cortical and subcortical brain regions. Diffusion tensor imaging (DTI) is used to study age related microstructural changes in the acoustic pathway. Materials and Methods. Twenty healthy volunteers (mean age 28.5 years) and 15 healthy volunteers (mean age 61.3 years) were examined using a 1.5-T MR system with a high-resolution T1-weighted sequence and an integrated parallel imaging technique DTI Echo-planar-imaging (EPI) sequence. For reliability, 10 subjects underwent a second examination 2 days later. The fractional anisotropy (FA) and the apparent diffusion coefficient (ADC) were measured in six brain regions of the auditory pathway. Results. We found no left/right asymmetry in the selected brain structures. There were no significant differences (P ⬍ .05) in the ADC and FA in the lateral lemniscus and medial geniculate body of young and elderly subjects. However, FA was significantly increased (P ⬍ .05) in the inferior colliculus and decreased in the auditory radiation, the superficial temporal gyrus, and the transverse temporal gyrus in the elder subjects than in the younger ones. There were no significant differences in anisotropy in subsequent examinations in the younger individuals. Conclusions. These findings suggest evidence of age-related changes in the acoustic pathway. These changes are associated with a decrease in anisotropy mainly in the cortical grey and white matter rather than in the subcortical regions. Our DTI measurements were reproducible. Key Words. Diffusion tensor imaging; reproducibility; aging, auditory pathway; fractional anisotropy; apparent diffusion coefficient. ©
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The aging brain shows a variety of micro- and macroscopic changes, which can result in some degree of functional decline. During aging, the auditory system undergoes numerous changes in its structure, function, and neuro-
Acad Radiol 2007; 14:692–700 1
From the Department of Clinical Radiology (J.L., F.H., R.S., O.D., M.R., L.J.) and Department of Otolaryngology (M.H.), University of Munich, Grosshadern, Marchioninistr. 15, 81377 Munich, Germany. Received August 24, 2006; accepted February 13, 2007. Address correspondence to J.L. e-mail: [email protected]
© AUR, 2007 doi:10.1016/j.acra.2007.02.014
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chemistry (1,2). Age-related hearing changes have usually been attributed to changes in the cochlea, inducing a loss of sensory cells, atrophy of stria vascularis, and a loss of spiral ganglion cells (4). However, there is strong evidence that changes in the ability of hearing is also due to changes in the central auditory system (5,6). The anatomic structure of the acoustic pathway is organized as follows: The anatomic organization of the auditory system consists of a large ensemble of subcortical nuclei, connected with each other and with the auditory cortex through ascending and descending white matter fiber pathways, processing both serial and parallel information
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within the auditory system. The cochlear nerve connects the cochlear with the anterior and posterior cochlear nucleus in the brainstem. Then, the majority of fibres cross to the contralateral side (90%) and approximately 10% run ipsilaterally to connect the auditory nuclei with the superior olivary complex. The fibers of the pathway reach the medial geniculate body, which is the thalamic auditory relay station and are there transmitted bilateral toward the primary auditory cortices. The gyri directly involved in the auditory perception are the transverse temporal gyri (of Heschl) and the superior temporal gyrus. Diffusion tensor imaging (DTI), a recently emerged, exciting variation of magnetic resonance imaging (MRI), provides a unique opportunity to visualize the integrity of tissue microstructure and quantify the diffusion of water in various tissues noninvasively (7,8). Tissues, which have a random microstructure, such as cerebrospinal fluid, show isotropic diffusion properties (9). This means diffusion is equal in all directions. In contrast, in tissues that have a regularly ordered microstructure, such as brain white matter, water molecules behave in a sorted fashion, with a predominant motion direction and a given orientation, indicating a marked anisotropy in the diffusion properties (10). The microstructural tissue changes can be expressed as FA (fractional anisotropy), which has no dimension and as mean diffusitivity (apparent diffusion coefficient, ADC) with ⫻10⫺3 mm2/s (11). These indices can be seen as complementary for the evaluation of brain tissue. Whereas ADC is a measure of the directionally averaged magnitude of diffusional motion of water molecules (⫽ related to integrity of membranes), FA describes the degree of anisotropy the process of molecular diffusion (⫽ degree of structural alignment) (11). Previous DTI studies have shown white matter declines in normal aging and various neuropsychiatric disorders (9,12–14). Two earlier studies investigating the acoustic pathway by the means of DTI were focused on patients with sensineuronal hearing loss (15) and the FA value of Heschl’s gyrus in a normal population (16). However, to the best of our knowledge, there is no previous study, investigating the aging of the acoustic pathway. The major goal of this study was to evaluate the aging of structures of the acoustic pathway by means of measuring the mean diffusivity and anisotropy values in young healthy adults in comparison to elderly healthy adults. Therefore, we designed a DTI acquisition protocol, using integrated parallel imaging technique (iPAT) to investigate the anisotropy of the acoustic pathway. To analyze the reliability of anisotropy measurements, we
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investigated the reproducibility of our DTI measurements, using a second follow-up examination of our younger study group in the same experimental settings.
MATERIAL AND METHODS Subjects Twenty young healthy adults (11 males and 9 females; mean age 28.5 years; age range 23–29 years) and 15 elderly healthy adults (8 males and 7 females; mean age 61.3 years; age range 46 – 66 years) volunteered to participate in this study after a written informed consent form was signed. For the reproducibility evaluation, the same 10 young individuals were examined in the identical setting 2 days later. The study was approved by the institutional review board. All subjects completed a detailed questionnaire about current and past medical and psychiatric conditions, medications, and substance use. Additionally, special emphasis was put on previous otologic surgery, systemic ototoxic drugs, and any anatomic abnormalities concerning the auditory system. Subjects were included only if they had no more than three subcortical white matter intensities as examined on the T2-weighted images exceeding 10 mm in diameter. A qualified radiologist (LJ) with 13 years’ experience in head and neck radiology read all MRIs for structural abnormalities. To assess the hearing abilities of both volunteer groups, pure tone audiometry was performed by an experienced ENT specialist (MH) using a clinical audiometer (Auritec AT 330, Dorn, Hamburg, Germany). Image Acquisition The study was performed on a 1.5-T MR System (Magnetom Sonata Maestro Class, Siemens Medical Solution, Erlangen, Germany) with a maximum gradient strength of 40 mT/m using an eight-channel phased-array head coil for signal reception and capable of iPAT. DTI images were acquired with parallel imaging using the generalized autocalibrating partially parallel acquisition algorithm with an acceleration factor of two. During a single examination, the following MRIs were obtained: 1) For structural data, a high-resolution three-dimensional inversion-recovery gradient-echo T1-weighted magnetization prepared rapidly acquired gradient echo sequence (MPRAGE) with a resolution of 1.1 ⫻ 1.1 ⫻ 1.1 mm3 and echo time/inversion time (TI)/repetition time of 3.9 milliseconds/800 milliseconds/1,570 milliseconds, respec-
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tively. We acquired 160 sagittal slices with a matrix size of 256 ⫻ 256 and a field of view of 270 ⫻ 270 mm2. Examination time was 6:42 minutes. 2) An iPAT spinecho single-shot EPI-sequence (echo time 71 milliseconds, repetition time 6,000 milliseconds) with a matrix size of 128 ⫻ 128, field of view of 230 ⫻ 230 mm2 and a resulting voxel size of 1.8 ⫻ 1.8 ⫻ 3.6 mm3 spatial resolution. Thirty-six slices with axial orientation were acquired and 10 measurements were selected and averaged. The minimum b value was 0 seconds/mm2 and the maximum was 1,000 seconds/mm2. Diffusion gradients in six different spatial directions were applied. The use of six gradient directions adequately characterizes the full diffusion tensor (17). Examination time was 7:44 minutes. Image Analysis Calculation of the diffusion tensor was based on the method of Bassser et al (18). All analysis of the diffusion tensor was performed on an offline workstation using inhouse software running on Matlab 5.3 (The Math Works Inc, Novi, MI). From the diffusion-weighted sequences, the values for FA and ADC in each voxel were calculated using an in-house developed software under IDL (Interactive Data Language, version 5.4, Research of System Inc., Fort Collins, CO). One set, the T2-weighted images, from the EPI sequence with a b value of 0, as well as the diffusion-weighted (six sets) and the MPRAGE images, were converted separately into a three-dimensional volume dataset of the analyze format. Motion correction was performed using a spatial realignment algorithm under SPM 99 with the six diffusion direction-encoded datasets and the one, non– diffusion weighted (b ⫽ 0) dataset. The T2-weighted data records were subsequently coregistered to the corresponding MPRAGE data records using the coregistration algorithms offered by the SPM 99-software package (Statistical Parametric Mapping, Wellcome Department of Cognitive Neurology, University College London, London, UK; extension of the MATLAB programming language, version 5.3, The Math Works Inc). These received transformation parameters were applied to the FA and mean diffusitivity (MD) datasets. To apply a set of regions of interest (ROI) and compare the data between the examined subjects, interferences from individual brain forms had to be excluded. This was done by normalizing the MPRAGE data by using the SPM 99 program and wrapping them into the standardized Talairach space (19). The normalized and wrapped datasets were again applied to the coregistered DTI datasets beginning with the b ⫽ 0 images and then to the six diffusion-
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Figure 1. Representative fractional anisotropy (FA) maps of four transverse slices of a 25-year-old male volunteer and a 65-yearold volunteer.
weighted datasets using the affine transformation of SPM 99 for the calculation of the different ROIs of FA and ADC values. Representative FA maps of the younger and older adults are shown in Fig 1.
Region of Interest MD and FA values were collected from regions of interest (ROIs), in six different gray and white matter brain regions. All ROIs were marked by the same person (LJ), blind to participant’s age and date of examination. Rectangular ROIs of variable size (range ⫽ 11.4 – 46.7 mm2), depending on the anatomic region studied, were placed bilaterally in the white and gray matter of the selected areas. The ROIs were drawn on the corresponding slice of the MPRAGE image, where the structures were visualized to be at their thickest. Using the visualization software MRIcro (Version 1.40 build 1), the structure in question was outlined following its boundaries. However, the lateral lemniscus, the inferior colliculus, and the medial geniculate body had very small ROIs placed, owing to their anatomic distinct localization. The inferior colliculus and medial geniculate body were measured on two adjacent slices, on which they were fully contained. The lateral lemniscus, acoustic radiation, and Heschl’s gyrus (transverse temporal gyrus) were identified and measured on three slices. All regional definitions included only voxels with minimal partial voluming with cerebrospinal fluid. These ROIs were transferred to the ADC and FA datasets of each subject and the appropriate mean values of each ROI were calculated. Here appropriate left and right measurements were taken separately. Representative ROIs are shown in Fig 2.
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Figure 2. Positioning of the regions of interest (ROIs) on the normalized axial T1-weighted MPRAGE images. From upper right to lower left: inferior colliculus (IC), medial geniculate body (CGM), lateral lemniscus (LL), acoustic radiation (RA), Heschl’s gyrus (TTG), and superior temporal gyrus (STG).
Statistical Analysis The FA values of the study group are reported as the mean ⫾ standard deviation. The calculated mean values of the ADC and FA were tested for normal distribution using the KolmogorovSmirnov test. The mean values for the left and right hemispheres of each individual were compared using the two-tailed paired Student t-test (significant with P ⬍ .05). If there is no significant left-right difference detectable, the values are averaged for all further analysis. The twotailed unpaired Student t-tests were performed to compare the mean ADC and FA values in the ROIs individually across the younger and elderly study group. For the follow-up examination, the two-tailed unpaired Student t-test was used. A P value of less than .05 was considered to indicate a statistically significant difference. All evaluations were done using the software package SPSS (Statistical software for the Social Sciences, version 10, SPSS Inc., Chicago, IL).
RESULTS The coregistration and normalization procedures were applied to all datasets without any difficulties. Comparing the left and right side in both study groups, there were no significant differences (P ⬎ .05) in the FA and ADC values for all brain regions (Tables 1 and 2). Hence, for fur-
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ther analysis, the FA and ADC values of the right and left were averaged. The ADC values in all selected brain regions showed no significant difference for the younger or elderly study group. The comparison between younger and elderly subjects did not reveal significant differences (P ⬎ .05) in FA in the lateral lemniscus and medial geniculate body. We found a significant reduction (P ⬍ .05) of FA values in the acoustic radiation, Heschl’s gyrus, and the superior temporal gyrus in the elderly subjects in comparison to the younger subjects (Table 3). In contrast, there was a significant increase (P ⬍ .05) in the anisotropy indices FA in the inferior colliculus. The summary of the different P values is shown in Table 3 and Fig 3. For evaluating the reproducibility, the follow-up examinations in the same younger subject population showed no significant differences (P ⬍ .05) in MD and FA measurements. The summary of the different P values is presented in Table 4 and Fig 4.
DISCUSSION Diagnostic imaging of the acoustic pathway is mainly based on MRI. Gross pathologies, such as acoustic schwannomas or encephalitis, are readily detected. Using MRI, the changes of cerebral structures associated with aging have been extensively investigated. Volume loss of the brain tissue, enlargement of the lateral ventricles, patchy areas of abnormal signal intensity within the white matter and basal ganglia, as well as progressive hypointensity in the globus pallidus and putamen were described as typical signs of aging (20). In contrast to cortical gray matter, white matter shows little age-related volume alteration in conventional MRI (21). Histopathology studies detected substantial age-related changes also in the white matter of the brain, such as decrease or disturbances in the microstructure of white matter, proven as demyelination, deterioration, and axonal loss (22). Because of this, we used DTI to study the morphologic changes in the microstructural environment of the auditory pathway during aging and examined the reliability of our results. This new imaging technique has been applied successfully to detect functional changes in several neurologic and psychiatric conditions—for example, multiple sclerosis (23–25), ischemia (26), and schizophrenia (27). However, there is little knowledge about the reproducibility of DTI indices for longitudinal studies.
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Table 1 Comparison of the ADC and FA Values for the Different Brain Regions of the Left and Right Hemisphere in the Younger Study Group Comparison of Right and Left Hemisphere: Younger Subjects ADC (⫻ 10⫺3 mm2/s)
FA
Region
Right
Left
P Value
Right
Left
P Value
Lateral lemniscus Inferior colliculus Medial geniculate body Acoustic radiation Heschl’s gyrus Superior temp gyrus
0.805 (⫾ 0.01) 0.537 (⫾ 0.02) 0.644 (⫾ 0.02) 0.708 (⫾ 0.07) 0.779 (⫾ 0.01) 0.762 (⫾ 0.05)
0.801 (⫾ 0.01) 0.534 (⫾ 0.03) 0.653 (⫾ 0.06) 0.700 (⫾ 0.05) 0.755 (⫾ 0.04) 0.743 (⫾ 0.05)
.198 .272 .758 .317 .262 .174
0.32 (⫾ 0.05) 0.17 (⫾ 0.03) 0.21 (⫾ 0.02) 0.71 (⫾ 0.03) 0.37 (⫾ 0.03) 0.37 (⫾ 0.03)
0.32 (⫾ 0.04) 0.16 (⫾ 0.02) 0.21 (⫾ 0.02) 0.72 (⫾ 0.02) 0.37 (⫾ 0.03) 0.37 (⫾ 0.02)
.979 .084 .758 .149 .463 0.943
ADC: apparent diffusion coefficient; FA: fractional anisotropy. Mean values with standard deviation in parentheses. P values ⬍ .05 indicate significant difference.
Table 2 Comparison of the ADC and FA Values for the Different Brain Regions of the Left and Right Hemisphere in the Elderly Study Group Comparison of Right and Left Hemisphere: Elder Subjects ADC (⫻ 10⫺3mm2/s)
FA
Region
Right
Left
P Value
Right
Left
P Value
Lateral lemniscus Inferior colliculus Medial geniculate body Acoustic radiation Heschl’s gyrus Superior temp gyrus
0.802 (⫾ 0.02) 0.552 (⫾ 0.05) 0.644 (⫾ 0.02) 0.737 (⫾ 0.05) 0.755 (⫾ 0.04) 0.775 (⫾ 0.04)
0.810 (⫾ 0.02) 0.543 (⫾ 0.03) 0.643 (⫾ 0.02) 0.725 (⫾ 0.06) 0.751 (⫾ 0.06) 0.759 (⫾ 0.06)
.087 .258 .563 .463 .681 .059
0.30 (⫾ 0.01) 0.18 (⫾ 0.08) 0.22 (⫾ 0.02) 0.64 (⫾ 0.03) 0.30 (⫾ 0.03) 0.35 (⫾ 0.01)
0.30 (⫾ 0.02) 0.18 (⫾ 0.09) 0.22 (⫾ 0.02) 0.65 (⫾ 0.04) 0.31 (⫾ 0.03) 0.35 (⫾ 0.01)
.569 .277 .918 .277 .196 .717
ADC: apparent diffusion coefficient; FA: fractional anisotropy. Mean values with standard deviation in parentheses. P values ⬍ .05 indicate significant difference.
Therefore, we have examined the morphologic changes in the microstructural environment of the acoustic pathway during aging and the reproducibility of the DTI results. For the evaluation of reproducibility, we did follow-up examinations in our younger study collective with a second scan on the same scanner system 2 days later. The FA and ADC values of the regions of the acoustic pathway of our younger study group showed no significant difference in both examinations. Our results confirm the previously published reproducibility of DTI results of supratentorial brain areas (28). Additionally, we were able to show that FA and ADC values are also reproducible in infratentorial brain regions, as with the inferior colliculus. Our results argue for the use of DTI indices to quantify changes of neuronal microarchitecture from aging or neurologic dysfunction.
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DTI has also been used in the investigation of normal aging to detect age-related degeneration (12,13,29). Significant age-related declines in median FA have been demonstrated in densely packed white matter fiber areas, particularly in the genu of the corpus callosum and the centrum semiovale (29). However, the aging of the acoustic pathway has not yet been studied. A prior DTI study published by Sullivan et al demonstrated no substantial gender dependent differences in anisotropy in aging men and women (30). According to the previous DTI study, we did not attempt to investigate the effect of gender in our study group because of the relatively small number of subjects. Age-related changes in the structures of the auditory circuit and accompanying hearing impairment are one of the most common age-related health problems afflicting
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Table 3 Average ADC and FA Values for the Different Brain Regions of the Younger and the Elder Subjects Comparison of Younger vs Elder Subjects ADC (⫻ 10⫺3 mm2/s)
FA
Region
Younger
Older
P Value
Younger
Older
P Value
Lateral lemniscus Inferior colliculus Medial geniculate body Acoustic radiation Heschl’s gyrus Superior temp gyrus
0.801 (⫾ 0.02) 0.540 (⫾ 0.04) 0.650 (⫾ 0.05) 0.700 (⫾ 0.04) 0.821 (⫾ 0.01) 0.764 (⫾ 0.01)
0.805 (⫾ 0.03) 0.547 (⫾ 0.02) 0.645 (⫾ 0.02) 0.732 (⫾ 0.02) 0.830 (⫾ 0.03) 0.810 (⫾ 0.06)
.658 .112 .323 .067 .441 .356
0.31 (⫾ 0.04) 0.17 (⫾ 0.02) 0.21 (⫾ 0.02) 0.71 (⫾ 0.05) 0.36 (⫾ 0.04) 0.37 (⫾ 0.02)
0.31 (⫾ 0.01) 0.18 (⫾ 0.06) 0,21 (⫾ 0.01) 0.64 (⫾ 0.02) 0.31 (⫾ 0.05) 0.35 (⫾ 0.03)
.691 .0006 .686 ⬍.0001 ⬍.0001 ⬍.0001
ADC: apparent diffusion coefficient; FA: fractional anisotropy. Mean values with standard deviation in parentheses. P values ⬍ .05 indicate significant difference.
Figure 3. The mean values of the fractional anisotropy index for the right (a) and the left (b) hemisphere in younger and elder group at six locations of the auditory pathway are shown. There was no difference to the correspondent measured acoustic radiation indices.
the elderly population. Typically, there is a loss of hair cells of the cochlea. Concomitantly with the loss of hair cells, reduction of hearing ability is accompanied by a loss of spiral ganglion cells, which usually comprises the loss of peripheral dendrites as well as central projections (ie, auditory nerve fibers) (31). Although changes in the hearing function are predominantly the result of cochlear pathology, the results of several studies indicate that changes in the function of the central auditory system may also play an important role (2). Because of the divergent findings published, we compared the FA and ADC values of the acoustic pathway between younger and elderly subjects. We found a significant increase of FA values in the inferior colliculus of the elderly population as compared with the group of young individuals. These findings could argue for a change in the molecular structure and the integrity of white matter fibers in the inferior
colliculus that result in an increase in measured anisotropy. An increase in anisotropy was found previously in maturation studies during childhood and was regarded as increasing myelination in children ⬍5 years or as a higher degree of fiber tract organization (32). This higher degree of fiber tract organization has been shown before to result in an increase in fractional anisotropy during nerve development, which is brought about by an increase in longitudinal diffusion without a concurrent decrease in transverse diffusion. Cellular components and membranes, such as tissue hydration, myelination, fiber diameter, and cell-packing density, influence fiber tract organization. This increased dense and ordered packing of fiber tracks leads to directionally more restricted extracellular, rather than intracellular space. Therefore, it may be speculated, that an increase of overall anisotropy in the inferior colliculus may be the result of an increased density of tightly
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Table 4 The P Values of the Follow-Up Examination of the Younger Study Group, Indicating Excellent Reproducibility (P > .05) for the FA value (a) and the ADC (b) a. FA P Values (P ⬍ .05) Reproducibility: Younger Subjects Right
Left
Region
1. Scan
2. Scan
P Value
1. Scan
2. Scan
P Value
Lateral lemniscus Inferior colliculus Medial geniculate body Acoustic radiation Heschl’s gyrus Superior temp gyrus
0.32 (⫾ 0.05) 0.17 (⫾ 0.03) 0.21 (⫾ 0.02) 0.71 (⫾ 0.03) 0.37 (⫾ 0.03) 0.37 (⫾ 0.03)
0.28 (⫾ 0.02) 0.18 (⫾ 0.04) 0.19 (⫾ 0.03) 0.70 (⫾ 0.01) 0.35 (⫾ 0.02) 0.38 (⫾ 0.06)
.176 .310 .091 .147 .35 .466
0.32 (⫾ 0.04) 0.16 (⫾ 0.02) 0.21 (⫾ 0.02) 0.72 (⫾ 0.02) 0.37 (⫾ 0.03) 0.37 (⫾ 0.02)
0.30 (⫾ 0.01) 0.19 (⫾ 0.03) 0.19 (⫾ 0.03) 0.70 (⫾ 0.02) 0.35 (⫾ 0.01) 0.37 (⫾ 0.02)
.240 .058 0.128 .063 .553 .695
b. ADC (⫻ 10–3mm2/s) P Values (P ⬍ .05) Reproducibility: Younger Subjects Right
Left
Region
1. Scan
2. Scan
P Value
1. Scan
2. Scan
P Value
Lateral lemniscus Inferior colliculus Medial geniculate body Acoustic radiation Heschl’s gyrus Superior temp gyrus
0.805 (⫾ 0.01) 0.537 (⫾ 0.02) 0.644 (⫾ 0.02) 0.708 (⫾ 0.07) 0.779 (⫾ 0.01) 0.762 (⫾ 0.05)
0.811 (⫾ 0.06) 0.540 (⫾ 0.02) 0.671 (⫾ 0.04) 0.691 (⫾ 0.02) 0.775 (⫾ 0.05) 0.739 (⫾ 0.03)
.352 .753 .061 .485 .977 .078
0.801 (⫾ 0.01) 0.534 (⫾ 0.03) 0.653 (⫾ 0.06) 0.700 (⫾ 0.05) 0.755 (⫾ 0.04) 0.743 (⫾ 0.05)
0.820 (⫾ 0.06) 0.552 (⫾ 0.04) 0.667 (⫾ 0.04) 0.718 (⫾ 0.05) 0.768 (⫾ 0.01) 0.753 (⫾ 0.02)
.080 .053 .500 .159 .798 .187
ADC: apparent diffusion coefficient (ADC); FA: fractional anisotropy (FA). Mean values with standard deviation in parentheses.
Figure 4. For reproducibility evaluation, the mean values of the fractional anisotropy index for the right (a) and the left (b) hemisphere in the younger group are depicted. No statistically significant differences were present between the follow-up examinations at all six locations.
packed axonal components in this highly organized gateway of ascending and descending tracts in the central auditory pathway, leading to the hypothesis that these microstructural changes are due to a compensatory midbrain modulation as a response to a decreased cortical cellular organization and reduction in cortical activity. Furthermore, in animal studies, the inferior colliculus proved to show capability of plastic transformation on the
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microstructural and functional level during the aging process (5,33). These hypotheses are supported by our findings. In contrast to the significant increase in anisotropy in the inferior colliculus, the FA and ADC values in the lateral lemniscus and medial geniculate body showed no significant difference between the two age groups. These results indicate that the integrity of the ascending path-
A DIFFUSION TENSOR IMAGING STUDY
Academic Radiology, Vol 14, No 6, June 2007
ways to the inferior colliculus and particularly the intrathalamic structures of the auditory pathway seem to be not affected by the aging process. In the acoustic radiation and Heschl’s gyrus, we found significantly decreased FA values. These changes of a reduction in anisotropy in these cortical regions argue for a possible disruption of axonal constitution, loss of dendrites, astrogliosis, demyelination, and possible breakdown of white matter fiber tracts and are consistent with previous DTI studies addressing age related brain changes (28,34) and postmortem findings in different other brain regions (35,36). So far, there is not much experience in studying the anisotropy of the acoustic pathway. To the best of our knowledge, a systematic evaluation of the aging of the acoustic pathway has not yet been done. In one of the recent DTI studies concerning regions of the auditory cortex, Hiwatashi et al (16) studied the difference in FA of the Heschl’s and the superior temporal gyrus in six normal subjects (mean age 32 years). In their study, they found higher mean FA values of the subcortical white matter of the Heschl’s gyrus than of the superior temporal gyrus. In their study, the effect of the FA differences was studied using subjects from a wide age range (26 – 41 years). In our study, studying two different age groups, we found slightly lower mean FA values in the Heschl’s gyrus than in the superior temporal gyrus of both age groups. However, the evaluation of the difference between Heschl’s gyrus and the superior temporal gyrus was not the main goal of this study. Because of the difference in age range, both results may not be directly compared. In any case, both regions show a concomitant significant decrease of anisotropy (FA) during aging. Concerning the infratentorial regions of the acoustic pathway, there is some indication that microstructural neuronal organization of the inferior colliculus in subjects with sensorineural hearing loss (15) takes place. To conclude, the results of our study support the hypothesis that aging of the acoustic pathway results not only from deteriorated function of the inner ear, but also from processes of central origin. However, it is difficult to determine to what extent the different subcortical and cortical regions of the central pathway contribute to the declining efficiency in the ability of processing different sound information (eg, frequency changes). All these findings in the aging brain argue for the further use of DTI to evaluate the plasticity of the associated cortical and subcortical regions and in subjects with sensorineural hearing loss (3).
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