Methylmalonic acidemia (MMA), caused by deficient L-methylmalonyl-CoA mutase (McKusick 251000, EC 188.8.131.52), is an inborn error of branched-chain amino acid metabolism. Neurological abnormalities often include lethargy, acute encephalopathy, seizures and delayed psychomotor development.1 The incidence is estimated to be between 1 in 48 000 to 1 in 250 000 live births.2 Prevalence is increased in regions with consanguineous marriage owing to the autosomal recessive nature of the disorder.3 CT scan and MRI of the brain can detect extensive abnormalities in basal ganglia, cerebral atrophy, as well as delayed myelination.4 It has been suggested that neurological damage in MMA has been the result of acute metabolic decompensation episodes characterized by severe acidosis and hyperammonaemia.
Diffusion tensor imaging (DTI) measures the random translational motion of water molecules. In structured tissues such as myelin fibers, this motion is restricted. It is superior to T1-W and T2-W imaging in detecting unmyelinated or premyelinated fiber tracts,5 as well as in assessing the microstructural organization of the developing white matter. The relative preference of the diffusion in fiber direction is called anisotropy. The degree of anisotropy is given as fractional anisotropy (FA) and can be calculated from the eigenvalues of the diffusion tensor, which is used as a measure for white matter integrity. Several studies showed the potential of this new structural imaging technique to quantify functionally relevant alterations of white matter integrity in different neurological and psychiatric syndromes and diseases.5,6
There is evidence that DTI is a more sensitive technique for detecting structural alterations of brain tissue than conventional MRI,7 and DTI parameters ensure a more exact quantification of structural changes. The aim of the study was to detect and to quantify structural brain tissue alterations and white matter tract injury in patients with MMA. We notice that there have been only three prior reports of cases of diffusion-weighted imaging in patients with MMA8-10 and there have been no prior reports of using DTI FA references value in patients with MMA.
Patients and control subjects
We retrospectively analyzed DTI images of 12 patients (7 males, 5 females, age range 7-12 months, mean age 9.25±1.70 months) with MMA confirmed by urine analysis with negative MRI findings. The diagnosis was established by the continuing profound increase in urinary methylmalonate and methylcitrate and raised methylmalonate in the blood, with normal plasma vitamin B-12 concentrations and no detectable plasma homocystine. All the patients showed different degrees of neurological symptoms within 6 weeks after birth, such as abnormal posturing and movements, generalized hypotonia, lethargy, etc.
And another 12 age-matched and gender-matched healthy infants (7 males, 5 females, age range 7-12 months, mean age 9.50±1.67 months) that were recruited from the local community were physically healthy and had no history of neurological diseases, head injury, or psychiatric disorders as control subjects. The DTI FA value of different white matter tracts of the brain were measured in both groups.
The study was done in accordance with the ethical standards of the Helsinki Declaration of 1975, as revised in 1983. The Ethics Committee of Shanghai Xinhua Hospital approved all aspects of the study. Written informed consent was obtained from the parents of all the patients and control subjects.
All subjects underwent examinations with a 1.5-T Signa Horizon LX MRI system (GE Medical Systems, Milwaukee, WI, U.S.A.). A circularly polarized head coil was used for both ratio frequency (RF) transmission and reception of the nuclear magnetic resonance (NMR) signal. Transaxial T1-, proton-density-, and T2-weighted images were acquired using a spin echo (SE) or turbo SE sequence (repetition time (TR)/echo time (TE) =540/12, 3500/15, 3500/96 mseconds, respectively). Multislice planes in longitudinal studies were positioned the same distance from the anterior commissure-posterior commissure (AC-PC) line. We used single-shot spin-echo echo-planar sequences (TR/TE= 5000/102 mseconds, 5 mm slice thickness and 1.5 mm gap, field of view (FOV)=21×21 cm2, number of excitation (NEX)=4, 128×128 pixel matrix) for diffusion tensor analysis. Diffusion gradients (b-value of 1000 s/mm2/axis; the duration, separation and amplitude of the diffusion gradients was 31.3, 25.3 ms and 21.858 mT/m) were always applied on two axes simultaneously around the 180° pulse. Diffusion properties were measured along 6 noncollinear directions. The diffusion-weighted MR images acquired were transferred to the workstation supplied by the manufacturer (Advantage Workstation, GE Medical Systems) for data processing. The six elements of the diffusion tensor were estimated in each voxel assuming a mono-exponential relationship between signal intensity and the b-matrix. Using multivariate regression, the eigenvectors and eigenvalues of the diffusion tensor were determined. A DTI FA map was generated on a voxel-by-voxel basis.11
Chloral hydrate (0.5 ml/kg) was administered to all the subjects as a sedative to ensure minimal head movement.
Analysis of the regions of interest (ROI)
DTI FA value was determined in regions of frontal white matter, temporal white matter, Genu of corpus callosum, anterior limb of the internal capsule, posterior limb of the internal capsule, splenium of corpus callosum, occipital white matter, superior corona radiata and centrum semiovale. Because there is a likelihood of partial volume contamination of CSF, we did not measure values in cerebral cortical gray matter. We chose to examine diffusion properties using the ROI method in this study with much attention to minimize intersubject variability in the directionality and spread of fiber tracts. The elliptical ROIs that appeared on FA maps were drawn bilaterally in a mirrored fashion in the above-mentioned areas. Each ROI should contain at least 15 pixels (Figure). A certain anatomical area of the brain may be manifested in different slices of the DTI FA map. In that case, we chose the ROI of that area with the highest FA value. Because signal characteristics derived from DTI are dependent on the size of the ROI, especially in the small anatomic structures, such as the posterior limb of the internal capsule, we determined to locate ROIs in a similar size specific to each anatomic structure and recorded the measured area. The ROIs of cerebral white matter were selected at areas of maximal distance from cortical gray matter and the ventricle to avoid partial volume averaging. Two experienced researchers in infant DTI achieved consensus on ROI placement and measurements using homemade programs based on Image Processing Toolbox of MATLAB R2007b (The Mathworks Inc., USA).
The non-parametric Wilcoxon signed-rank test12 was used to determine whether statistically significant differences existed between the corresponding left-sided and right-sided ROI FA values in the two groups (control and patients). Subsequently, an independent two-sample t-test was performed to evaluate for statistically significant differences between ROI in patients and control subjects using SPSS15.0 (Chicago, Illinois, USA)
There were no significant intra-individual hemispheric differences in white matter FA. Therefore, FA value was averaged across hemispheres for all the white matter ROI regions. The Table shows the result of a comparison between patients with MMA and control subjects. Significant reductions in white matter FA values were found in widespread regions of the frontal, temporal and occipital lobes of the MMA patients compared with those of the control subjects. White matter FA values of the genu of corpus callosum, anterior limb of the internal capsule, posterior limb of the internal capsule, splenium of corpus callosum, superior corona radiata, as well as centrum semiovale in the MMA patients did not show statistically significance from the normal controls.
The primary result of our study is for MMA patients with negative MRI findings was that abnormal white matter anisotropy in widespread regions of the frontal, temporal and occipital lobes were still observed. There was some evidence to suggest that there is a relationship between lowered white matter FA values of the inferior frontal brain region and neurological symptoms in MMA patients.
Previous studies of DTI alterations in neurological symptoms, such as late-life depression, have focused on the white matter of the frontal brain regions.13-14 Taylor et al14 reported that microstructural changes in the white matter of the right superior frontal gyrus were associated with late-life depression. Lee et al15 concluded that white matter microstructure in autism is abnormal in temporal lobe regions. Alexopoulos et al13 showed that microstructural white matter abnormalities lateral to the anterior cingulate may be associated with a low rate of remission.
The different parts of the frontal lobes have afferent and efferent connections with other neocortical, limbic, and subcortical regions and participate in the limbic-cortico-striatal-pallidal-thalamic circuits.16 These neuroanatomical circuits play an important role in the regulation and modulation of affection and emotion, and contribute to the pathogenesis of non-specific neurological symptoms in patients with MMA. The reduction of white matter anisotropy, observed in our DTI study, is suggestive of possible loss of integrity within frontal, temporal and occipital white matter fiber tracts, and supports the hypothesis that neuron-anatomical circuit abnormalities are a key factor in the functional anatomy of cognitive disorders in patients with neurological symptoms such as late-life depression17 and Alzheimer's disease.18 Although white matter anisotropy could be influenced by many factors such as the dense packing of axons, relative membrane permeability to water, internal axonal structure, tissue water content, or degree of myelination, the pathophysiology underlying reduced white matter FA values in widespread regions of the frontal, temporal, and occipital lobes in patients with MMA has not been confirmed. More than one process may be responsible for FA reduction.
Also we observed that anisotropy values are normally lower in the central white matter than in the posterior limb of the internal capsule. This is a consequence of the orientation of the white matter fiber tracts. In the centrum semiovale, the fibers in the central cerebral white matter have a multidirectional orientation as opposed to the tightly packed, unidirectional, and roughly parallel orientation of the white matter fibers in the posterior limb of the internal capsule.19,20 Thus, in children, the macroscopic organization of white matter fiber tracts influences anisotropy; this phenomenon has been previously reported to occur in adults.21,22 Further study is needed to determine whether MMA patients have more extensive and quantitative abnormalities in diffusion-tensor MR imaging. Better understanding of normal preterm white matter development is essential to encourage the use of DTI for evaluation and treatment of white-matter injury. Early diagnosis of white-matter abnormalities means that early intervention may be possible. We are exploring the possibility of brain repair, and new MR imaging techniques such as DTI will enable us to improve our understanding of how the developing brain responds to our interventions.
Studying DTI parameters of the infants, like MMA patients, is challenging for many reasons. One of these challenges is to determine a standard for the size and shape of the ROIs. An ROI is a controlled identification of a given area of an image for numerical analysis and the area of anatomy being scanned that is of particular importance in the image. Different authors have used different ways to set their ROIs.14,15,23 We believe that automatic verification will become common practice in the future. A possible solution for ROI comparisons between researchers is the use of a neonatal brain atlas coordinate system.23 Individual brain images could then be transformed into a common coordinate space and the ROIs could be placed at specific topographic coordinates. However, there's something else that we should not neglect.
An important non-biological factor that we should also focus on is the effect of changes in image resolution with respect to the brain size.24 To obtain the same amount of anatomical information from brains of different sizes, ideally, the number of pixels within the brain should be kept constant. This could be especially important for DTI, for which partial volume effects may occur easily due to the convoluted white matter structures. Low anisotropy in younger brains, therefore, could be in part due to larger partial volume effects. On the other hand, reduction of the voxel size is limited by the necessity to maintain an adequate signal to noise ratio. Because it has been reported that lower Signal to Noise Ratio (SNR) leads to higher FA,25 this alternative approach may also lead to bias in the measurement. In addition, a number of studies evaluated the impact of scan parameter on FA measurements.26 These issues exemplify the difficulty in absolute quantification studies of developing brains.
In conclusion, DTI has a wide range of potential applications in the brain of children, both in the normal and in disease states. Further technical refinements are needed to improve the spatial resolution of DTI and to increase its sensitivity to crossing fibers without making it too time consuming for clinical use. As a research tool, DTI has potential applications in determining the connectivity of abnormal white matter tracts in congenital malformation and potential white matter abnormalities in acquired disease states, just like the MMA disease in our study.
The main limitation of our study is the combination of a small sample size and narrow age range in the choice of MMA patients. And we did not analyze the correlations between the degree of macrostructural abnormalities of white matter and clinical symptom severity, as quantification of clinical symptom severity has not been easy. Also, we were unable to examine potential effects of successful treatments on DTI FA values. Future studies will attempt to analyze the exact mechanism of metabolic diseases, including MMA, on the central nervous system and its corresponding clinical symptoms.
In addition to conventional T1-W and T2-W MRI, Brain DTI presents a useful, sensitive and complementary tool for the assessment of white matter injury in patients with MMA who have neurological symptoms. We suggest that brain DTI should be recommended for children with neurological disorders with/without negative MRI findings.
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