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Neuroradiology |
1 From the Department of Clinical Radiology, University Hospitals–Grosshadern (R.S., O.D., M.F.R., S.O.S.); and Department of Psychiatry (S.J.T., H.H.), Ludwig Maximilians University of Munich, Marchioninistrasse 15, 81377 Munich, Germany. From the 2004 RSNA Annual Meeting. Received October 20, 2005; revision requested December 15; revision received June 8, 2006; accepted July 7; final version accepted September 1. Address correspondence to R.S. (e-mail: Robert.Stahl{at}med.uni-muenchen.de).
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ABSTRACT |
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 TOP ABSTRACT INTRODUCTIONMATERIALS AND METHODSRESULTSDISCUSSIONADVANCE IN KNOWLEDGEReferences |
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Materials and Methods: Institutional review board approval and informed consent were obtained. Fifteen patients with AD (seven men, eight women; mean age; 68.8 years), 16 patients with MCI (nine men, seven women; mean age, 68.9 years) and 19 healthy control subjects (eight men, 11 women; mean age, 63.9 years) underwent diffusion-tensor imaging performed with a 1.5-T magnetic resonance system. An echo-planar imaging diffusion sequence was used with an integrated parallel acquisition technique (PAT) and an eight-element head coil. The mean apparent diffusion coefficient (ADC), fractional anisotropy (FA), and relative anisotropy (RA) values of several white matter (WM) regions were determined. The Kruskal-Wallis test was used initially to test for overall equality of median values in each data group. Single posttest comparisons were performed with the Mann-Whitney U test, with an overall statistical significance level of .05.
Results: FA and RA values were significantly (P < .05) decreased, whereas ADC values in the splenium of the corpus callosum were higher in patients with AD than in patients with MCI. Evidence of higher ADC values in the WM of the temporal lobe was observed in patients with AD compared with the ADC values in patients with MCI and in control subjects. ADC values in the parietal WM were significantly (P < .05) elevated in patients with MCI compared with those in control subjects. The images obtained with integrated PAT showed fewer susceptibility artifacts and were less distorted than images acquired without parallel imaging techniques.
Conclusion: Reduced FA and RA values in patients with AD suggest that diffusion-tensor imaging of the brain can be used to confirm clinical manifestation of AD but is less applicable in the detection of MCI.
© RSNA, 2007
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INTRODUCTION |
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TOPABSTRACTINTRODUCTIONMATERIALS AND METHODSRESULTSDISCUSSIONADVANCE IN KNOWLEDGEReferences |
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Anisotropy of water diffusion yields important information about fiber tract systems. The diffusion of water molecules is more restricted in directions perpendicular rather than parallel to the longitudinal axis of the fibers, resulting in high diffusion anisotropy in the WM.
Diffusion-tensor imaging is a further development of diffusion-weighted imaging. Whereas an averaged apparent diffusion coefficient (ADC) is calculated with diffusion-weighted imaging, the effective diffusion tensor in diffusion-tensor imaging allows computation of principal diffusivity and diffusion anisotropy. In several disease processes the cellular integrity of nerve fibers is reduced or destroyed, resulting in less constrained motion of the water molecules and leading to higher ADC values and lower anisotropy values. Thus, the role of diffusion-tensor imaging in the evaluation of WM damage is currently being established, and diffusion-tensor imaging has been successfully applied in the early diagnosis of several neurologic diseases (9). Following the hypothesized spread of neurologic disease from the neuronal periphery to the neuronal soma in AD, diffusion-tensor imaging might be able to depict neurofibrillary degeneration in patients with early stages of AD (10–12).
A major disadvantage of the single-shot echo-planar imaging procedures typically used with diffusion-tensor imaging are the substantial susceptibility artifacts that result from the long echo times (>50 msec). These artifacts arise particularly in the skull base region (especially the frontal base) and negatively affect the image quality and accuracy of further postprocessing steps, such as calculation of ADC maps or fiber tracking (13). These single-shot sequences enable the echo time to be shortened by reducing the number of phase-encoding steps; however, this leads to a reduction in spatial resolution. Parallel imaging is a relatively new procedure that permits the number of phase-encoding steps to be reduced, and thus leads to shorter echo times without loss of spatial resolution. However, special receiving coils are necessary to simultaneously record the MR signal with several different spatially arranged coil elements.
The aim of our study was to prospectively determine regional differences in fiber tract integrity between elderly patients with AD, those with MCI, and healthy elderly subjects by using diffusion-tensor imaging with parallel imaging techniques and a new eight-element receiving coil.
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MATERIALS AND METHODS |
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TOPABSTRACTINTRODUCTIONMATERIALS AND METHODSRESULTSDISCUSSIONADVANCE IN KNOWLEDGEReferences |
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We examined 15 patients with AD (seven men, eight women; age range, 45–82 years; mean age, 68.8 years ± 10.8 [standard deviation]) and 16 patients with MCI (nine men, seven women; age range, 52–84 years; mean age, 68.9 years ± 9.3). Patients with AD fulfilled the clinical criteria for clinically probable AD set forth by the National Institute of Neurologic and Communicative Disorders (14). Subjects with MCI fulfilled the criteria set forth by Petersen et al (15,16) (ie, subjective memory complaints, delayed verbal recall at least 1.5 standard deviations below the respective age standard, normal general cognitive function, and capability to perform normal activities of daily living). Dementia severity was assessed with the Minimal Mental State Examination (MMSE) (17). The MMSE scores of patients with AD ranged from 15 to 29, with a median score of 25 (25th percentile, 17; 75th percentile, 25); the MMSE scores of patients with MCI ranged from 23 to 29, with a median score of 27 (25th percentile, 25; 75th percentile, 28).
In addition, 19 healthy control subjects were examined (eight men, 11 women; age range, 37–78 years; mean age, 63.9 years ± 10.3). Control subjects did not have subjective cognitive impairment: Their MMSE scores ranged from 27 to 30, with a median score of 30 (25th percentile, 28; 75th percentile, 30). All subject scores were within 1 standard deviation of the age-adjusted mean value in all subtests of the Consortium to Establish a Registry for Alzheimer's Disease cognitive battery (18).
The MMSE score of patients with AD was significantly lower than that of patients with MCI (Mann-Whitney U test, P < .005) and control subjects (Mann-Whitney U test, P < .001). The MMSE score of patients with MCI was significantly lower than that of control subjects (Mann-Whitney U test, P < .001). Mean age did not differ significantly (analysis of variance, P = .637) between the examined groups. The sex distribution did not differ between groups.
Subjects were recruited from the Department of Psychiatry, Alzheimer Memorial Center, Ludwig Maximilians University of Munich, Germany. Medical comorbidity in patients and control subjects was excluded by means of history taking, physical and neurologic examinations, psychiatric evaluation, chest radiography, electrocardiography, electroencephalography, brain MR imaging, and laboratory tests (complete blood count; assessment of sedimentation rate; evaluation of levels of serum B12 and folate, electrolytes, glucose, blood urea nitrogen, creatinine, liver-associated enzymes, cholesterol, high-density lipoprotein cholesterol, triglycerides, and antinuclear antibodies; rheumatoid factor analysis; Venereal Disease Research Laboratories test; human immunodeficiency virus screening; thyroid function tests; and urine analysis). Participants were included in our study only after they provided written informed consent. The study was approved by the institutional review board.
MR Imaging and Preliminary Testing
The basic principle of parallel imaging is that image acquisition can be accelerated by decreasing the number of phase-encoding steps without reducing the spatial resolution of the image. For these methods, the simultaneous acquisition of data with two or more receiving coils that have different spatial sensitivities is fundamental.
We performed MR imaging of the brain with a 1.5-T MR imager (Magnetom Sonata Maestro Class; Siemens Medical Solutions, Erlangen, Germany). We used an eight-element phased-array head coil and integrated hardware and software solutions (iPAT; Siemens Medical Solutions) for the parallel acquisition technique (PAT).
The following sequences were used: For acquisition of structural data, a high-spatial-resolution T1-weighted magnetization-prepared rapidly acquired gradient-echo sequence was applied. This was a three-dimensional inversion-recovery gradient-echo sequence with a spatial resolution of 1.1 x 1.1 x 1.1 mm and a repetition time msec/echo time msec/inversion time msec of 1570/3.9/800. A total of 160 sagittal sections were acquired with a 256 x 256 matrix and a 270 x 270-mm field of view. The examination lasted 6 minutes 42 seconds. To identify WM lesions, 36 T2-weighted transverse sections were acquired by using a conventional fast spin-echo sequence (repetition time msec/echo time msec, 7450/93) with a 256 x 208 matrix and a 230 x 187-mm field of view, which resulted in a voxel size of 0.9 x 0.9 x 3.6 mm.
Diffusion-weighted data were collected with a spin-echo single-shot echo-planar imaging sequence (6000/71). Diffusion gradients were applied in six spatial directions, as described by Basser and Pierpaoli (19). The b values used were 0 sec/mm2 and 1000 sec/mm2. Images were acquired with a 128 x 128 matrix and a 230 x 230-mm field of view. The resulting voxel size was 1.8 x 1.8 x 3.6 mm. Thirty-six transverse sections were acquired. Ten measurements were obtained and averaged. The examination time was 7 minutes 44 seconds. During each course of imaging, each subject was examined in the same position in the imager.
Previous measurements were obtained in a phantom and in vivo to compare the quality of images obtained with the eight-element head coil with the quality of images obtained with a conventional quadrature head coil, which had a slightly larger inside diameter (head coil diameter, 24 cm vs 26 cm). For phantom measurements, a cylindrically shaped 120-mm-diameter water phantom (Siemens Medical Solutions) was placed in each head coil. The spin-echo diffusion-tensor echo-planar imaging sequence was applied without integrated PAT in both coils and with integrated PAT in the eight-element head coil by using a b value of 1000 sec/mm2 and diffusion weighting in the section direction. Diffusion-weighted imaging parallel to the section gradient axis increased the echo time to 101 msec with integrated PAT and to 144 msec without integrated PAT. These measurements were obtained 20 times to enable calculation of image noise from the subtraction image of two subsequent acquisitions. Two regions of interest (ROIs), one in a central position (size, 35 pixels) and the other in a peripheral position (size, 130 pixels) with respect to the coil, were selected within the phantom and the brain by a radiologist (R.S.). Ten signal-to-noise ratio (SNR) measurements were calculated as the ratio of the mean signal intensity of two subsequent repetitions and the variance of the signal intensity in the difference image (scaled with a factor of 1/
2) (20).
To receive an impression of the image distortions, six healthy control subjects were examined with the eight-element head coil by using the spin-echo diffusion-tensor echo-planar imaging sequence with and without integrated PAT. A radiologist (S.O.S.) with 8 years of experience with head MR imaging compared these images with those obtained with the T1-weighted magnetization-prepared rapidly acquired gradient-echo sequence described previously.
The MR imaging unit supported the use of modified sensitivity encoding (21) and generalized autocalibrating partially parallel acquisition (GRAPPA) (22) reconstruction algorithms. Test measurements were obtained in healthy control subjects to assess image quality, SNR, and imaging artifacts for the modified sensitivity encoding and GRAPPA algorithms. The GRAPPA algorithm revealed fewer ghosting artifacts (N/2-ghost) and a better SNR, which resulted in a better image quality. With use of an acceleration factor of three, considerable ghosting artifacts degraded the image quality. Thus, for all of the remaining examinations, we used an acceleration factor of two with the GRAPPA reconstruction algorithm.
Postprocessing and Image Analysis
The ADC (
) represents the mean diffusivity and is the mean value of the three eigenvalues, as shown in Equation (1):
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The following anisotropy indexes could be developed from the full diffusion tensor and are invariant to the head position of the examined subjects. Relative anisotropy (RA) is the ratio of the standard deviation of the eigenvalues to their mean value. The values range between 0 (isotropy) and 2 (complete anisotropy), as shown in Equation (2):
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Fractional anisotropy (FA) can be interpreted as the fraction of the magnitude of the diffusion tensor that can be ascribed to anisotropic diffusion. The values range between 0 (isotropy) and 1 (complete anisotropy), as shown in Equation (3):
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From the diffusion-weighted sequence, the ADC, FA, and RA values in each voxel were calculated with software developed in house with Interactive Data Language (version 5.4; Research Systems, Boulder, Colo). The resulting maps and the diffusion-tensor echo-planar T2-weighted images (those obtained with the diffusion-tensor echo-planar sequence and a b value of 0 sec/mm2), the magnetization-prepared rapidly acquired gradient-echo images, and the conventional T2-weighted images were converted separately into three-dimensional data sets.
The ADC, FA, and RA values were examined in different WM areas. First, a radiologist (S.O.S.) who was blinded to the clinical diagnosis identified WM lesions on all images to guarantee that these areas were not included in the evaluation. Subjects had no more than three subcortical WM hyperintense areas, and none of the areas exceeded 10 mm in diameter.
Thereafter, an observer (R.S., 4 years of experience in brain MR image interpretation) carefully placed several ROIs (12–30 pixels, the number of pixels depended on the anatomic region) bilaterally directly in the WM (Fig 1) on T2-weighted diffusion-tensor echo-planar images (those with a b value of 0 sec/mm2) in agreement with previous studies (11). The correct ROI position was confirmed by means of simultaneous visual comparison with the corresponding layers of the magnetization-prepared rapidly acquired gradient-echo and conventional T2-weighted data sets (a) at the genu and splenium of the corpus callosum in three consecutive sections on which these structures were completely shown; (b) laterally in the pericallosal WM; (c) in two consecutive sections at the genu of the corpus callosum and the posterior limb of the internal capsule, located between the head of the caudate nucleus and the pallidum, as well as between the pallidum and the thalamus; (d) in the WM of the frontal lobes on three consecutive sections starting at the most cranial section where at least one lateral ventricle was completely contained; (e) in the parietal lobe posterior to the central sulcus on the most caudal section where it could be identified and on the contiguous section above this section; (f) in the temporal lobe posterolateral to the lateral fissure, beginning at the most caudal section where it could be identified and continuing to the two contiguous sections above this section; and (g) in the occipital lobe within the optic radiations in two consecutive sections, beginning at the most caudal section where the occipital horn of the lateral ventricle was fully contained. These ROIs were transferred to the ADC, FA, and RA data sets of each subject, and the appropriate mean values of each ROI were calculated.
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RESULTS |
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TOPABSTRACTINTRODUCTIONMATERIALS AND METHODSRESULTSDISCUSSIONADVANCE IN KNOWLEDGEReferences |
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2, particularly in the peripherally positioned ROIs.
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Comparison of data obtained with and without integrated PAT in six control subjects revealed there were fewer distortion artifacts on images obtained with integrated PAT, particularly in the area of the eyeballs and the frontal base. For example, the right eyeball appeared circular with the magnetization-prepared rapidly acquired gradient-echo sequence (which served as the reference standard); however, it was distorted and took on an elliptical shape when echo-planar imaging sequences were used (Fig 2). The ratio of the major and minor axes of this ellipse served as an indicator of the extent of distortion. Without integrated PAT, the average ratio was 1.54 ± 0.15 (standard deviation), whereas use of integrated PAT yielded an average ratio of 1.24 ± 0.08 and resulted in a significant improvement of 19% (paired t test, P < .001). At the frontal base (at the level of the frontal sinus), the semicircular frontal parts of the brain appeared to be displaced backward and the frontal dural edge was irregularly impressed when echo-planar sequences were used (Fig 2). The sagittal distance between the rostral and posterior brain frontiers at a right paramedian line obtained with the magnetization-prepared rapidly acquired gradient-echo sequence was used as the reference standard, with an arbitrarily defined length of 1. This average distance amounted to 0.93 ± 0.03 without integrated PAT and to 0.97 ± 0.02 with integrated PAT. The use of integrated PAT resulted in a significant improvement of 4% (paired t test, P < .005).
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No significant correlation between age (AD group, P > .123; MCI group, P > .155; control group, P > .214) or MMSE score (AD group, P > .104; MCI group, P > .215; control group, P > .106) and the diffusion and anisotropy parameters was observed in any group.
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DISCUSSION |
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TOPABSTRACTINTRODUCTIONMATERIALS AND METHODSRESULTSDISCUSSIONADVANCE IN KNOWLEDGEReferences |
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2 compared with the SNR obtained with nonintegrated PAT. However, measurements obtained in vivo show an increase in SNR that can be explained by the shorter T2 in combination with the reduced echo time. (Echo time was reduced from 144 msec without integrated PAT to 101 msec with integrated PAT.) Additionally, use of the eight-element head coil yielded an improved SNR in comparison with the SNR yielded by the conventional quadrature head coil, at least in eccentrically positioned regions, because of the better sensitivity of surface coil elements in the short range. This effect was enhanced by the smaller inside diameter of the eight-element head coil, resulting in a better filling factor. In our study, the ranges of ADC and anisotropy values in patients and control subjects were comparable with values reported by other authors. For example, Basser and Pierpaoli (19) and Kantarci et al (24) obtained values that ranged from (0.692 to 0.915) x 10–3 mm2/sec in the WM of healthy subjects. In our study, control subjects had ADC values between (0.724 and 0.828) x 10–3 mm2/sec. Thus, we concluded that our results, which we obtained with integrated PAT technology, were realistic and that our method was valid.
Diffusion-Tensor Imaging in Patients with AD and in Those with MCI
AD can be regarded as a cortical disconnection syndrome that affects not only the cortical neuronal soma but also the axons and dendrites in the cerebral WM. According to this model, a pattern of WM disease that encompassed the temporal-parietal-frontal association cortex was found with diffusion-weighted imaging and diffusion-tensor imaging in several studies (Table 5). However, different mechanisms beyond primary fiber degeneration contribute to WM changes in patients with AD. First, Wallerian degeneration leads to secondary neurofibrillary degeneration. Second, vascular or ischemic alterations cause axonal damage and gliosis, which lead to WM rarefaction (25). In addition, myelin breakdown—especially in late-myelinating association areas—has been suggested (26,27). In diffusion-tensor imaging, elevated ADC values are related to neurodegeneration, whereas decreased FA values indicate disturbed WM homogeneity.
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Our findings contradict some findings reported in the literature (Table 5). This contradiction might be due to methodologic issues: Some authors (24,28–30) used only diffusion-weighted imaging, which, when compared with DTI (11,12,31,32), does not develop a full tensor; therefore, data obtained in these studies were susceptible to different head positions of the examined subjects. The parallel imaging technique was not used in any of these studies. The heterogeneity of the examined subjects may also play a role: Bozzali et al (11) reported significantly increased ADC values, reduced FA values, or both in pericallosal areas and frontal and parietal lobes, whereas we found no significant differences in these values between patients with AD and control subjects. This might partly be explained by the fact that MMSE scores of patients in our study were slightly higher than MMSE scores of patients in the Bozzali et al study. This disparity indicated that patients in our study exhibited a somewhat milder form of AD than did patients in the Bozzali et al study. Also, Bozalli et al reported FA values that were only about half of the values obtained in our study. A reason for this disparity might be that Bozalli et al examined large ROIs; thus, the FA values may apply to not only WM but also cerebrospinal fluid.
In regard to patients with MCI, we observed only elevated ADC values in the parietal WM and no differences in the anisotropy indexes compared with measurements in the control subjects. Since structural imaging studies have revealed temporal and particularly hippocampal atrophy in patients with early AD (33), we expected at least some difference in this area. In agreement with our findings, Fellgiebel et al (12) demonstrated FA values in patients with MCI that did not differ from those in control subjects. In the study of Fellgiebel et al, FA values had a comparable order of magnitude as in our study, and the patients with MCI had a mean MMSE score and mean age similar to those of our patient group. In contrast to our findings, Fellgiebel et al observed elevated ADC values in the temporal WM. In a conventional diffusion-weighted imaging study involving patients with MCI, Kantarci et al (24) observed reduced anisotropy values only in the occipital WM, whereas no differences occurred in frontal, parietal, temporal, or anterior WM.
Study Limitations
The variability of our findings in comparison with previous results may be caused by other factors, such as the number of participants and the stage of disease, the differential size and placement of ROIs across studies, and the fact that changes in diffusion and anisotropy indexes do not necessarily reflect WM damage but could also be a result of partial volume effects in atrophic brains. However, to avoid this last point, we used a manual approach in the present study to place ROIs on individual images. We took care to place ROIs consistently in only WM areas to avoid partial volume effects through cerebrospinal fluid spaces. This is also the reason we used relatively small ROIs. In addition, in the studies performed with diffusion-weighted imaging, a position-invariant tensor also was not developed; thus, their results are influenced by different head positions of the examined subjects.
Diffusion-tensor imaging with integrated PAT yields images with fewer distortions because the echo time is shorter; however, more reconstruction artifacts occurred. In addition, in comparison with a conventional head coil, the new eight-element head coil leads to an improved SNR so that better quality of measured data can be assumed.
In conclusion, we found reduced FA and RA values only in patients with AD, whereas patients with MCI had only elevated ADC values in the parietal WM in comparison with control subjects; therefore, we conclude that diffusion-tensor imaging of the brain is less applicable for early detection of AD-related abnormal changes in patients with MCI than for confirmation of clinical manifestations of AD. As a result of heterogeneous findings in the literature, possible correlations between diffusion-tensor imaging data and clinical parameters should be examined in further studies.
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ADVANCE IN KNOWLEDGE |
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TOPABSTRACTINTRODUCTIONMATERIALS AND METHODSRESULTSDISCUSSIONADVANCE IN KNOWLEDGEReferences |
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ACKNOWLEDGMENTS |
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FOOTNOTES |
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Abbreviations: AD = Alzheimer disease • ADC = apparent diffusion coefficient • FA = fractional anisotropy • MCI = mild cognitive impairment • MMSE = Minimal Mental State Examination • PAT = parallel acquisition technique • RA = relative anisotropy • ROI = region of interest • SNR = signal-to-noise ratio • WM = white matter
Authors stated no financial relationship to disclose.
Author contributions: Guarantors of integrity of entire study, O.D., S.J.T., M.F.R., S.O.S.; study concepts/study design or data acquisition or data analysis/interpretation, all authors; manuscript drafting or manuscript revision for important intellectual content, all authors; manuscript final version approval, all authors; literature research, R.S., O.D., S.J.T., S.O.S.; clinical studies, R.S., O.D., S.J.T.; experimental studies, R.S., O.D.; statistical analysis, R.S.; and manuscript editing, all authors
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References |
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