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MRI acquisition and post-processing
MRI data were acquired on a 1.5 T Signa Excite (GE Medical Systems, Milwaukee, WI) using a high-resolution 8-channel head coil. The diffusion weighted imaging was performed by using single shot spin-echo echo-planar imaging with the following parameters: TR/TE = 9600/72ms, NEX 1. Following the literature recommendations [20], we used diffusion gradients in 25 spatial directions. The b values used were 0s/mm2 and 1000 s/mm2. Images were acquired with a 128 × 128 matrix, which were reconstructed to 256×256 over a FOV of 240mm. The resulting voxel size was 0.94mm×0.94mm×5mm (number of slices=24, with no gap). The imaging sections were parallel to the anterior commissure–posterior commissure line (AC–PC). Head motions were minimized by the use of tightly padded clamps attached to the head coil.
Tractography data were analysed using TrackVis, an interactive environment for fiber tracking reconstruction, display and analysis developed at the Harvard Medical School Martinos Center for Biomedical Imaging at Massachusetts General Hospital (www. trackvis.org) [21].
Diffusion-registration tool was used for motion and eddy current corrections. FA was calculated according to the scheme proposed by Basser and collaborators [22]. Directionally encoded coloured maps were created from the FA values and the three vector elements [23]. The vector maps were assigned to red (x element, left–right), green (y, antero-posterior), and blue (z, supero-inferior) with a proportional intensity scale according to the FA (Fig. 2). ROIs were placed on these coloured maps.
Anatomical landmarks and ROIs
One trained observer, with knowledge of the fiber pathways and with help of an experienced neuroanatomist and an atlas of white matter [24], placed the ROIs on the color maps, according to anatomical landmarks described below. To ensure a reproducibility of placement from subject to subject, precise anatomical landmarks easily to define on DTI colour maps whatever the subjects considered and located at proximity from the point of measure were used.
The size of each ROI was adjusted so as to cover the whole fasciculus. FA was measured for each ROI. Fiber tracking was performed with the fiber assignment by continuous tracking (FACT) algorithm [25] in TrackVis, to ensure the correct ROIs position. Tracking was done on all voxels included in the ROI, with a FA threshold of 0.1 and a threshold of prohibited angle of 0.85 (38◦). Five ROIs were defined: right and left anterior cingulum (on coronal section to mid-genu of the corpus callosum, Fig. 3A and B), right and left frontal part of the arcuate fasciculus (axial section through the intersection between the long segment and the anterior segment, Fig. 4 A and B), and mid-splenium (Fig. 5).
Fractional anisotropy of the anterior cingulum
Mean FA values in Gyoung were of 0.46 ± 0.03 for the right cingulum and of 0.51± 0.02 for the left cingulum, and respectively of 0.39 ± 0.03 and 0.44 ± 0.03 in Gold (Table 2). These values are in the range expected for the cingulum, which presents a less coherent microstructure than the corpus callosum [4].
Wilcoxon non parametric test with hemisphere as within subjects factor demonstrated a significant difference in both Gyoung and Gold in mean FA values of the right hemisphere compared to the mean FA values of the left hemisphere for the anterior cingulum ROI (p < 0.004 in Gyoung and p < 0.001 in Gold).
Concerning the anterior cingulum, the analysis revealed that means FA values of Gold (0.39 ± 0.03 and 0.44 ± 0.03 respectively for right and left anterior cingulum ROIs) were significantly decreased compared to the mean FA value of Gyoung (p < 0.001 for both right and left) (Fig. 6).
Fractional anisotropy of the splenium of the corpus callosum
According to previous studies [4, 5, 27], mean FA value of the corpus callosum is around 0.9, because of its composition of large and heavily myelinisated commissural fibers.
The analysis revealed that mean FA value of Gold (0.9 ± 0.05) was statistically stable compared to mean FA value of Gyoung (0.91 ± 0.04), p = 0.345. These results are in the range expected for the splenium. [4-6]
Fractional anisotropy of the frontal part of the arcuate fasciculus
To our knowledge, no study analysed the FA of the anterior part of the arcuate fasciculus. The previous studies placed the ROIs on the mid-part of the arcuate fasciculus but the mean values of the right (0.58 ± 0.03) and left (0.61 ± 0.01) in Gyoung are quite similar of those of the literature [4] (Table 2).
Wilcoxon test, with hemisphere as within subjects factor, demonstrated a significant difference in Gyoung in mean FA values of the right hemisphere compared to the mean FA values of the left hemisphere for the arcuate fasciculus ROI (p < 0.004). The same differences were observed in Gold (p < 0.001).
Considering FA values between groups, it only indicated a difference among groups for the right arcuate fasciculus ROI (p = 0.048, <0.05). Inversely, mean FA values of the left arcuate fasciculus were not statistically different in the two groups (p = 0.209) (Fig. 6). This demonstrates that the left arcuate fasciculus, one of the major white matter structures involved in language comprehension and production, is not affected in its microstructural composition during aging.
Effects of aging on the anterior cingulum and the splenium of the corpus callosum.
A significant decrease of FA values in the anterior part of the cingulum bundle in elderly subjects compared to young subjects was observed, while no significative difference was shown in the splenium of the corpus callosum. This result confirms previous studies showing a selective vulnerability of frontal white matter systems to normal aging, including the genu of the corpus callosum [4] [5, 6, 27]. Even if FA provides limited useful information for determining specific pathological processes at the cellular level, our results may reflect demyelination processes, which have been described in histological studies [34]. From a functional point of view, the frontal white matter damages, and specifically the cingulum bundle injuries, closely follow the frontal grey matter atrophy observed during aging [1, 3, 35]. It may probably represent part of the anatomical support of the cognitive decline in elderly people, characterized by executive function impairments [36-38].
Effects of aging on the arcuate fasciculus.
The main result of the present study reveals that the left arcuate fasciculus, one of the principal white matter structures involved in language comprehension and production, is not affected in its microstructural composition during aging. No significant decrease of FA values in the frontal part of the arcuate fasciculus in elderly compared to young subjects was observed. These results corroborate the clinical observations, and explain why spoken language comprehension typically does not show age-related declines [15, 16].
In functional magnetic resonance imaging (fMRI) studies, it has been demonstrated that syntax is preserved in aging because of the functional recruitment of other brain regions, which successfully compensate for neural atrophy. This preservation was related to an increased activity in right hemisphere frontotemporal regions, associated with age-related atrophy in the left hemisphere frontotemporal network activated in the young [39, 40]. It has been argued that preserved syntactic processing across the life span is due to the shift from a primarily left hemisphere frontotemporal system to a bilateral functional language network.
But, to our knowledge, all studies fail to explain if this right-hempisphere compensation is only due to the age-associated cognitive impairment (i.e functions-problem solving, working memory and dual tasking issues as undesirable effects of advancing age), or secondary to age-related decline of the arcuate fasciculus.
From our observation and the previous fMRI studies, we claim that right-hemisphere participation in language production and comprehension in elderly people is due to compensate the age-related cognitive impairment.
The second interesting observation of this study is that we observed a significant difference among groups for the right arcuate fasciculus, reflecting the aging effects of this bundle. This result is not so surprising, knowing that studies found a significant FA increase in the right hemisphere with age, with a significant, but less pronounced, effect for left hemisphere [41].
But some questions still remain unanswered: what is the clinical function of the right arcuate fasciculus, and what are the clinical manifestations of the age-related effects of this bundle? Many studies showed the role of the right arcuate fasciculus on left-damages secondary aphasia [42-44], but there is poor knowledge about its physiological function. It has been proposed on fMRI studies that the right arcuate fasciculus is involved in processing of affective prosody [45, 46]. In spoken language, information about the emotional state of the speaker can be expressed via propositional cues at the verbal level and via non-verbal means of communication by modulation of the speech melody (affective prosody). Affective prosody is characterized by variations of suprasegmental language features, such as pitch, syllable duration, and voice quality [47]. Evidence obtained from lesion studies indicates a right-hemispheric superiority in processing of these features [45, 48]. This function seems to be impaired with aging.
So it might be interesting on future studies to evaluate the evolution of prosody with age, and to correlate it with imaging techniques, using more specific cognitive tests.
Table of contents :
Préface
1. Introduction
2. Methods
2.1. Subjects
2.2. MRI acquisition and post-processing
2.3. Anatomical landmarks and ROIs
2.4. Statistical analyses
3. Results
3.1. Fractional anisotropy of the anterior cingulum
3.2. Fractional anisotropy of the splenium of the corpus callosum
3.3. Fractional anisotropy of the frontal part of the arcuate fasciculus
4. Discussion
4.1. Lateralization
4.2. Effects of aging on the anterior cingulum and the splenium of the corpus callosum.
4.3 Effects of aging on the arcuate fasciculus.
4.4 Methodological considerations
Conclusion
Conflict of interest
Acknowledgments
Bibliography
