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Pediatric Neuro-Oncology |
Brain and Behavior Program, Research Institute (D.J.M., C.R.), Paediatric Brain Tumor Program, Haematology/Oncology (D.J.M., E.B.), and Department of Diagnostic Imaging, Division of Neuroradiology (S.L.), The Hospital for Sick Children, Toronto, ON M5G 1X8; Departments of Paediatrics (D.J.M., E.B.) and Medical Imaging (M.D.N., S.L.), University of Toronto, Toronto, ON M5S 3J3; and Brain-Body Institute, St. Joseph's Healthcare, and Departments of Radiology and Medical Physics, McMaster University (M.D.N.), Hamilton, ON L8S 4M4; Canada
2 Address correspondence to Donald J. Mabbott, Brain and Behavior Program, The Hospital for Sick Children, 555 University Avenue, Toronto, ON M5G 1X8, Canada (donald.mabbott{at}sickkids.ca).
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Key Words: cranial radiation • diffusion tensor imaging • intelligence • white matter
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CSR can be associated with injury to the developing brain. The most salient effects are diffuse and multifocal white matter abnormalities, observed as increased signal intensity on T2-weighted images (Edwards-Brown and Jakacki, 1999; Mulhern et al., 2001). The extent of abnormality varies from scattered, small white matter lesions to larger confluent lesions (Edwards-Brown and Jakacki, 1999). Cerebral atrophy can also be observed (Edwards-Brown and Jakacki, 1999; Fouladi et al., 2000). Further, decline in brain volume not evident on clinical scans has been identified, including volume loss in normal-appearing white matter (Mulhern et al., 2001; Reddick et al., 2000), the corpus callosum (Palmer et al., 2002), and the hippocampus (Nagel et al., 2004). The loss of normal-appearing white matter volume predicts lower cognitive outcome (Mulhern et al., 2001; Reddick et al., 2003). Possible mechanisms of radiation injury are alterations of the microvasculature within the brain, damage to the oligodendrocytes that produce myelin, and possibly glial (both microglial and astrocytic) death (Habrand and De Crevoisier, 2001; Schultheiss et al., 1995), resulting in an increase in brain water with the loss of brain tissue (Edwards-Brown and Jakacki, 1999).
Although volumetric MRI techniques have provided important information regarding decline in normal-appearing white matter volume following radiation, they provide little information regarding the potential microstructural changes within this brain tissue. Understanding these changes is important both for early identification of radiation injury and for understanding the complex relationships between mechanisms of radiation injury brain and intellectual outcome. Diffusion tensor magnetic resonance imaging (DTI) is particularly useful for examining changes in white matter microstructure and relating those changes to cognitive outcome (Paus et al., 2001) because of the rotationally invariant ability of DTI to quantify three-dimensional measures of water diffusion. First, DTI is sensitive to developmental changes in white matter: A decrease in mean diffusivity and an increase in anisotropy have been associated with increasing age in newborns and children (Huppi et al., 1998; Li and Noseworthy, 2002; Mukherjee et al., 2001; Neil et al., 1998; Suzuki et al., 2003). These changes have been attributed to the impact of premyelination, reduction in brain water, myelination, increases in fiber diameter, greater cohesiveness, compactness of the fiber tracts, and reduced extra-axonal spaces (i.e., greater packing) as white matter matures over time (Beaulieu, 2002; Huppi et al., 1998; Klingberg et al., 1999; Neil et al., 1998; Suzuki et al., 2003). Second, DTI measures have been used to document tissue breakdown in disorders known to influence white matter microstructure, including multiple sclerosis, brain injury, perinatal cerebral white matter injury, and adrenoleukodystrophy (Huppi et al., 2001; Ito et al., 2001; Jones et al., 2000; Wieshmann et al., 1999). Finally, lower anisotropy values have been found in the posterior fossa (cerebellar hemispheres, pons, and medulla oblongata) and cerebral white matter (corpus callosum, frontal periventricular, parietal periventricular, and corona radiata) for children treated with CSR for medulloblastoma relative to control children (Khong et al., 2003; Leung et al., 2004), and lower values have been related to younger age at diagnosis and larger radiation dose (Khong et al., 2005). Because of the sensitivity to white matter changes with development and/or injury, DTI is an excellent means for evaluating potential damage following treatment with radiation and relations with intellectual outcome.
We evaluated diffusivity by determining apparent diffusion coefficient (ADC) and directionality by determining fractional anisotropy (FA) in normal-appearing white matter in children treated with CSR for medulloblastoma and in normal children. No evaluation of the relationships between DTI measures and intellectual outcome exists in the literature. Examining these relationships is essential for understanding and potentially mediating the mechanism of cognitive decline following cranial-spinal radiation. Our first goal was to examine whether DTI measures are related to adverse intellectual outcome in children treated with CSR. We expected that increased diffusion and decreased anisotropy should be associated with lower intellectual outcome in patients treated with CSR. Second, we compared ADC and FA values of the two samples. We expected increased diffusivity and decreased directionality in patients treated with radiation relative to controls. Other unique contributions of the present study include comprehensive coverage of regions within cerebral white matter, an area where significant loss of volume has been identified (Mulhern et al., 2001; Reddick et al., 2000), and the inclusion of deep gray matter to compare measures in white matter and gray matter structures.
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MR Imaging and Postprocessing
The MRI measurements were performed with a GE LX 1.5T MRI scanner (GE Healthcare, Milwaukee, Wis.) and a single-channel quadrature head coil. Following a routine clinical brain tumor imaging protocol, DTI measurements were acquired for each subject by using a single-shot, spin-echo DTI sequence with an EPI (echo-planar imaging) readout (imaging parameters as follows: TE/TR [echo time/repetition time] = 100/6000 ms, 128 x 128 matrix, number of excitations = 1, field of view = 24 cm, receive bandwidth = 125 kHz, beta (b) = 1000 s/mm2, 25 directions, one b = 0 image). The number of slices and thickness varied across subjects as clinically required: 21 to 42 contiguous axial slices were acquired, and slice thickness ranged from 3 to 5.5 mm across subjects. Total additional scanning time for patients was approximately 5 min.
Postprocessing, including eddy current correction, was conducted with a commercial software program (FUNCTOOL 3.1.10; GE Medical Systems, GE Healthcare). ADC and FA were calculated by acquiring the traces and eigenvalues from matrices of diffusion gradients on a pixel-by-pixel basis. ADC and FA were evaluated by using a region of interest (ROI) approach. ROI analysis was conducted using the b = 0 images: ROIs were identified from this image rather than the ADC or FA maps, which avoids the problem of using the dependant variable (i.e., ADC or FA) to define the anatomic regions (Pfefferbaum et al., 2000). As these images were acquired in the same space as the diffusion gradients, image registration was not necessary. ROIs were placed on three successive axial slices to provide comprehensive coverage and were chosen by referring to existing literature documenting radiation-related changes in the regions (Khong et al., 2003; Leung et al., 2004) as well as to provide comprehensive coverage of larger fiber tracts and hemispheric white matter. Specific ROIs for white matter included the genu of the corpus callosum, the anterior and posterior limbs of the internal capsule, inferior frontal white matter, high frontal white matter, and parietal white matter. ROIs were also placed in the thalamus and the putamen to enable comparison of deep gray matter and white matter structures (Fig. 1). All ROIs were reviewed by a neuroradiologist (S.L.) to ensure accuracy of placement: The clinical scans were also reviewed to identify any areas of white matter abnormality. Any areas of white matter hyperintensity on T2 were not included in the ROIs so that the diffusion tensor measures were calculated for normal-appearing white matter only. To conduct qualitative comparisons between the patient and control groups, fiber tractography was performed using the DTIStudio program developed at Johns Hopkins Medical Institute in Baltimore, Md. (http://cmrm.med.jhmi.edu). In this algorithm, the fiber tracts are reconstructed along the eigenvector corresponding to the preferred (largest) diffusion in each voxel. The arrangement of eigenvectors in space forms the so-called diffusion vector field. From this discrete three-dimensional vector field, the fiber tracts within the imaged volume were obtained (Bammer et al., 2003; Mori at al., 1999). Two ROIs were placed within the corpus callosum (in the middle of the genu and splenium): Tractography was started with any voxels with FA greater than 0.60 and discontinued at voxels with FA less than 0.40.
Intellectual Functioning
Intellectual functioning was assessed for all subjects by using a short-form estimate of the Full Scale IQ from the Wechsler Intelligence Scales for Children (WISC; either the 3rd or 4th edition), comprising the block design, coding, vocabulary, and information subtests (Wechsler, 1991, 2003). Although estimates of full-scale IQ from WISC-III and WISC-IV obtained within the same test group are highly related (r = 0.89) (Wechsler, 2003), we acknowledge that standard scores for these tests are based on different normative samples. Individual test scores were converted to standard scores (based on age-related means and standard deviations from test standardization norms) with a mean of 100 and a standard deviation of 15. Mean time and median time from diagnosis to the follow-up assessment for the patients were 2.38 and 2.07 years, respectively (range, 1.25-5.22 years). Because data for the patient groups were acquired as part of ongoing clinical follow-up, IQ and MRI data were obtained on different occasions. The mean and median times from the study MRI scan to follow-up intellectual testing were 0.63 and 0.54 years, respectively (range, 0.25-1.42 years). For the control sample, IQ data were collected on the same day as the MRI scan. Finally, all of the patients also had an initial assessment of IQ prior to the follow-up assessment: Mean and median times from diagnosis to this initial assessment were 0.78 and 0.50 years, respectively (range, 0.10-3.30 years).
Statistical Analysis
First, differences in intellectual functioning were examined with t tests to provide the context within which to examine the brain behavior relations. IQ at the initial assessment for the patient group was compared to IQ for controls to determine whether any group differences existed at a relatively early point in treatment for the patients. Further, initial and follow-up IQs were compared within the patient group to determine whether intellectual function declined over time, as this is a known effect of cranial radiation (Copeland et al., 1999; Palmer et al., 2001, 2003; Ris et al., 2001; Spiegler et al., 2004).
For imaging analyses, mean ADC and FA across voxels and slices within each ROI were calculated and used in subsequent analyses. First, correlation analyses were used to examine the correlation among IQ, FA, and ADC. Second, mean IQ was examined between the patient group (follow-up assessment) and control group by using one-way analysis of variance. To determine whether potential differences in white matter integrity as measured by ADC and FA were associated with differences in intellectual functioning, these measures were included as covariates in subsequent analyses of covariance comparing IQ of the two groups. Third, a 2 (group) x 8 (ROI) analysis of variance with repeated measures for the ROIs was conducted to compare overall ADC and FA for patients treated with CSR relative to the control sample across the eight ROIs. Further, multiple one-way analyses of variance were conducted for each ROI to evaluate differences between the two groups. To correct for multiple comparisons, all results were considered significant at the P < 0.01 level only.
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Neurocognitive Functioning and DTI Measures
To examine the correlation between intellectual functioning and white matter integrity, FA and ADC values were averaged across all ROIs. For FA, only the ROIs including white matter were used to calculate the composite, as these regions were significantly different in the control and the CSR groups (details below). All ROIs were used to calculate the overall mean ADC. Across the entire sample, decreased IQ at the time of scanning was associated with increased ADC (r = -0.60, P < 0.01). The relation between IQ and FA was weak (r = 0.32, P > 0.10). When the scatter plot for FA and IQ was examined, an outlier existed: A single patient demonstrated low IQ and high FA, whereas for all other subjects, both patients and controls, low IQ corresponded with low FA. The correlation analysis was conducted with the outlier removed, and a significant relation was identified between decreased IQ and decreased FA (r = 0.65, P < 0.01).
Mean IQ for the CSR group at the time of scanning was almost 1 SD below the normative mean, and it was significantly lower than that of the control sample (87.50 vs. 112.75; F = 9.53; P < 0.01). This effect was not significant when controlling for overall mean FA (with the outlier removed) or ADC (Fs > 1.42; Ps > 0.10). Hence, FA and ADC appear to be associated with the effect of radiation treatment on intellectual outcome.
Fractional Anisotropy
The FA for the total sample was significantly higher in the corpus callosum and the posterior limb internal capsule relative to all other structures (Table 1): FA for the corpus callosum and FA for the posterior limb internal capsule did not differ. Mean FA for the anterior limb internal capsule was higher than for the inferior frontal white matter, high frontal white matter, thalamus, and putamen, but not different from parietal white matter. Mean FA did not differ among inferior frontal white matter, high frontal white matter, and parietal white matter, but was higher in these areas relative to the thalamus and putamen. Mean FA was not different in the thalamus and putamen. Finally, mean FA across all ROIs was lower in the CSR group relative to controls (0.28 vs. 0.44; P < 0.01; Fig. 2).
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Univariate comparisons (Table 2) showed that mean FA was significantly lower in the corpus callosum, posterior limb internal capsule, anterior limb internal capsule, inferior frontal white matter, and high frontal white matter for patients treated with CSR relative to controls. Tractography was conducted within the corpus callosum to provide qualitative/visual evidence of the differences in FA. Specifically, tractography was conducted for a patient with enlarged ventricles, a patient without enlarged ventricles, and two age-matched controls (Fig. 3). The resulting fiber tracts for the controls were thicker and had greater complexity in connections relative to those of the patients. The significant difference in mean FA for the corpus callosum of the two groups likely reflects differences in axonal/white matter integrity, yielding the impoverishment of tract connections in the patients. No differences in FA were evident between the groups for the parietal white matter, thalamus, and putamen.
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Apparent Diffusion Coefficient
Few differences existed in mean ADC values across ROIs (Table 1). Mean ADC was higher for the corpus callosum than for the posterior limb internal capsule and was higher for parietal white matter than for high frontal white matter or anterior limb internal capsule. Mean ADC across all ROIs was higher for the CSR group relative to controls (826 vs. 498; P < 0.01). Univariate comparisons (Table 2) showed mean ADC was significantly higher within each ROI, including the thalamus and putamen, for patients treated with CSR relative to controls (P < 0.01).
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Discussion |
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According to our findings, both FA and ADC appear to be sensitive measures of brain tissue damage following CSR for pediatric brain tumors. FA values across ROIs were consistent with expected anatomical microstructure: For example, the highest FA was observed in the corpus callosum, a structure with substantial directionality in fiber orientation, and the lowest FA was observed in the subcortical nuclei, where little directionality in water diffusion would be expected. Consistent with previous work (Khong et al., 2003, 2005; Leung et al., 2004), our findings showed that FA was reduced in multiple hemispheric sites in patients treated with radiation for medulloblastoma relative to age-matched controls. Specifically, we observed decreased directionality in water diffusion in five of the six regions of white matter, with the largest differences being observed for the large fiber tracts (i.e., genu of the corpus callosum and internal capsule). Demyelination is often a common pathological expression of white matter injury, irrespective of the etiology, as demonstrated in clinical studies of advanced spinal cord injury and animal studies (Schultheiss et al., 1995) and thus must be considered a plausible mechanism accounting for observed FA differences. However, myelin's role as the primary influence on FA is doubtful: Myelination is not necessary for significant anisotropy to be observed (Beaulieu, 2002). FA likely reflects the primary influence of axonal membranes, including axonal density and fiber packing, which is then attenuated by myelin (Beaulieu, 2002). Hence, mechanisms other than myelin loss should also be considered in accounting for differences in FA between normal and clinical populations treated with radiation. Another potential mechanism in accounting for differences in FA may be the loss of glial progenitor cells that develop into and replenish myelin, as loss of these cells has been implicated in radiation injury (Schultheiss et al., 1995). Thus, differences in FA may reflect a failure of myelin development in addition to actual demyelination. Developing white matter may be vulnerable to the adverse effects of radiation because it results in cell-cycle disruption in growing tissue (Fouladi et al., 2000; Mulhern et al., 2001; Steen et al., 2001). Finally, radiation may also have an impact on astrocytes (Schultheiss et al., 1995). Astrocytes are often characterized as the glue that holds neural tissue together, making various contacts with neurons, synapses, ependyma, and meninges, as well as being one of the structural components of the blood-brain barrier (Schultheiss et al., 1995). Damage to these cells could result in volume loss as well as lead to decreased packing of fibers or fiber density, yielding decreased FA without any direct effects on existing myelin. Current evidence cannot differentiate between these mechanisms. Regardless, our findings regarding FA are consistent with compromised white matter microstructure and/or fiber integrity that is not evident on standard clinical MR imaging sequences or volumetric analyses. This compromise is evident in the very thin and unelaborated fiber tracts of a patient's corpus callosum following tractography.
Higher ADC values were observed across ROIs, including the thalamus and putamen, in children treated with CSR as compared to controls. This is generally consistent with the findings of Khong et al. (2003), who noted that mean diffusivity was increased in most ROIs for their CSR group relative to the controls, although their differences did not reach statistical significance. Consistent with the FA data in our study, the greatest differences in the Kong et al. (2003) study were observed for the large fiber tracts, including the corpus callosum and internal capsule. An increase in ADC, and presumably increased free water content, is consistent with loss of tissue across both white matter and gray matter nuclei, though this loss is greatest in white matter. The putamen is a component of the lentiform nuclei, and the thalamus has some white matter within it (internal medullary lamina), so the ADC increase may reflect white matter injury as noted previously. Further, this loss may reflect death of glial support cells, as differences are evident in white matter and subcortical nuclei.
Finally, some limitations due to the use of a small and clinically acquired patient sample are relevant for interpreting our findings. First, because of the relatively small sample of patients, we were unable to address important clinical questions, including the influence of age at diagnosis, time since diagnosis, and radiation dose on brain microstructure. Further, we were unable to determine whether severity of intellectual impairment was related to DTI measures. These variables will need to be evaluated in studies with greater power in order to examine the relative risks associated with each. Second, the distribution between males (n = 7) and females (n = 1) in the patient sample is not desirable for accounting for the effects of gender when considering brain behavior correlation following radiation. There is evidence that female cancer patients display greater neurocognitive impairment than males (Brown et al., 1998). As our sample included primarily males, our findings may reflect an underestimate of what might be seen for females when considering DTI measures of white matter and IQ. Third, mean IQ for the control sample was higher than the baseline IQ for a patient sample and was almost 1 SD above the normative mean. Hence, the differences between the control and the patient groups are likely greater than would be expected if a more representative control sample were available, such as a sample comprising siblings of the brain tumor patients. It is notable that despite this potentially exacerbated difference in IQ, controlling for FA and ADC nullified the significant group effect in IQ. It would be expected that an increased difference in IQ between the groups would make it less likely that a covariate would account for any differences. Hence, our findings are robust. Fourth, our study was limited to data for a single scanning time. To evaluate the time course of changes in ADC and FA, we plan to collect longitudinal DTI data in future studies. Finally, to gain greater understanding of the correlation between radiation-related changes in the brain and behavior, more specific measures of cognitive function may be necessary. Intelligence tests have been useful in monitoring the global neurotoxic effects of disease and treatment. However, the mechanism by which damage to white matter may result in adverse intellectual outcome is not well understood. Delineating this mechanism is essential because global intelligence measures are not sufficient for explaining functional outcomes such as academic attainment and vocational success, nor are they suited for determining the basic brain-behavior correlations that are directly affected by treatment (Neisser et al., 1996). There is evidence that attentional difficulties are related to reduced white matter volume (Mulhern et al., 2004) and may mediate the correlation between white matter volume and poor intellectual outcome (Reddick et al., 2000). Quantitative DTI measures are well suited for examining the correlation between brain integrity and specific cognitive functions such as attention, because these measures provide quantitative information regarding tissue microstructure within the normal-appearing white matter that is often examined in volumetric studies, providing a more detailed level of analysis.
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Note added in proof: While this paper was in production, Khong et al. (2006) identified a correlation between FA and IQ in childhood cancer survivors.
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3 Abbreviations used are as follows: ADC, apparent diffusion coefficient; CSR, cranial-spinal radiation; DTI, diffusion tensor magnetic resonance imaging; FA, fractional anisotropy; PF, posterior fossa; ROI, region of interest; WISC, Wechsler Intelligence Scales for Children.
Received for publication September 30, 2005. Accepted for publication January 6, 2006.
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