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Published online before print December 13, 2001, 10.1148/radiol.2222010179
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(Radiology 2002;222:405-409.)
© RSNA, 2002

Pediatric Imaging

Changes in Brain Water Diffusion during the 1st Year of Life1

Kirsten P. N. Forbes, MD, FRCR, James G. Pipe, PhD and C. Roger Bird, MD

1 From the Division of Neuroradiology, Barrow Neurological Institute, St Joseph’s Hospital and Medical Center, 350 W Thomas Rd, Phoenix, AZ 85013. From the 2000 RSNA scientific assembly. Received December 22, 2000; revision requested February 6, 2001; revision received May 21; accepted June 20. Address correspondence to K.P.N.F. (e-mail: kforbes@chw.edu).


   ABSTRACT
TOP
 ABSTRACT
INTRODUCTION
 MATERIALS AND METHODS
RESULTS
DISCUSSION
 REFERENCES
 
PURPOSE: To evaluate the normal water diffusion changes that occur during the 1st year of life.

MATERIALS AND METHODS: Diffusion-weighted imaging was performed in 40 subjects (age range, birth to 1 year) in whom both magnetic resonance imaging and neurologic assessment results were normal at the time of imaging and, where available, at follow-up. Apparent diffusion coefficient (ADC) was calculated in four areas of white matter (anterior and posterior subcortical and internal capsule) and four of gray matter (cortex, thalamus, head of the caudate nucleus, and lentiform nucleus). Linear regression was used to examine the effect of age on ADC, and analysis of variance was used to compare ADC within different brain regions.

RESULTS: ADC decreased with age in all regions (P < .01). Data best fit with a logarithmic decline (r2 = 0.20–0.63). ADC was significantly higher in white (113 x 10-5 mm2/sec) than in gray matter (102 x 10-5 mm2/sec; P < .001). Significant differences were seen among three white matter regions (subcortical, 188 x 10-5 mm2/sec at birth; anterior limb of internal capsule, 130 x 10-5 mm2/sec; posterior limb of internal capsule, 109 x 10-5 mm2/sec) and three gray matter regions (cortex, 134 x 10-5 mm2/sec at birth; head of caudate nucleus, 134 x 10-5 mm2/sec at birth; and thalamus and lentiform nucleus, 120 x 10-5 mm2/sec; P < .01).

CONCLUSION: Results suggest that in neonates and infants, water diffusion is highly dependent on both subject age and brain location.

Index terms: Brain, diffusion, 10.139 • Brain, MR, 10.12144


   INTRODUCTION
TOP
 ABSTRACT
 INTRODUCTION
MATERIALS AND METHODS
RESULTS
DISCUSSION
 REFERENCES
 
The apparent diffusion coefficient (ADC) provides a measure of random water diffusion within tissue and varies with both overall water content and cellular location. The normal neonatal brain shows much higher ADC values than does the adult brain, which is thought to reflect both higher water content and structural differences in brain composition (1). Although the decrease in ADC during childhood likely reflects normal brain maturation, the timing and extent of change remains unclear (2). If diffusion-weighted (DW) imaging is to be used as an accurate means of detecting ischemic brain damage in the pediatric population, knowledge of normal ADC values is paramount (3–5).

DW imaging is highly sensitive to acute cerebral infarction in adults and allows confirmation of ischemic damage before other imaging modalities can (6). Severe ischemia causes a decrease in ADC, thought to be due in part to development of cytotoxic edema (7). When focal, this ischemia normally can be detected easily as a region of hyperintensity, as compared with that of normal brain, on DW images (6). In neonates and infants, however, ischemia is commonly global, with widespread damage preventing comparison with normal brain. This may underlie the lower sensitivity of DW imaging to global, as compared with focal, ischemic damage in childhood (4,5). Interpretation of pediatric DW images may be assisted with knowledge of normal age-corrected ADC values; however, these are currently unavailable. If normal adult ADC values were used in interpretation of neonatal DW images, false-negative findings would likely be commonplace. The purpose of our study was to evaluate the normal water diffusion changes that occur during the 1st year of life.


   MATERIALS AND METHODS
TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
RESULTS
DISCUSSION
 REFERENCES
 
Subjects
As magnetic resonance (MR) examination in the 1st year of life commonly requires sedation, ethical considerations precluded us from recruiting healthy volunteers for this study. In place of this, we retrospectively studied 40 sequential subjects (19 male, 21 female), referred for MR imaging during a 3-year period from 1997 to 2000, who fulfilled predefined criteria. All were in the 1st year of life and had a gestational age greater than or equal to 37 weeks: 0–1 month, 16 subjects; 1–2 months, six; 2–3 months, one; 3–4 months, four; 4–5 months, two; 5–6 months, four; 6–7 months, one; 7–8 months, zero; 8–9 months, one; 9–10 months, one; 10–11 months, two; 11–12 months, two. Ages were corrected to a gestational age of 40 weeks.

Subjects had been referred for MR imaging, the results of which were deemed normal for a variety of clinical reasons, as shown in the Table. In addition, subjects fulfilled various clinical criteria with (a) normal neurologic assessment by a pediatrician both before MR imaging and at the time of discharge, with no evidence of developmental delay; (b) no clinical, radiologic, or laboratory evidence of neurologic damage; and (c) normal neurologic follow-up results, where available.


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  		Clinical Findings and Reason for Brain Imaging

 
All attempts were made to obtain clinical or radiologic follow-up results in this group of patients to ensure there was no evidence of delayed onset of neurologic damage or developmental delay. For each child, pediatric inpatient, outpatient, emergency room, surgical, and radiology records were examined. Clinical follow-up results (median, 11 months; range, 1–36 months) were obtained in 14 subjects, and neurologic assessment results were normal in all. One of these subjects also underwent computed tomography of the brain to evaluate the skull, which was deemed normal. The remainder of the subjects had not presented again to the medical services listed earlier. Our institutional review board did not require its approval or patient informed consent, as identifying patient data were not used.

Imaging Parameters
MR imaging performed at 1.5 T (N/Vi, or Echospeed; GE Medical Systems, Milwaukee, Wis) was our routine examination with both conventional and DW sequences. DW imaging was performed with a maximum diffusion-sensitizing gradient of a b value of 1,000 sec/mm2 applied to three orthogonal planes. By using an echo-planar technique, transverse images were obtained, both with and without the diffusion gradient: 6,500/101 (repetition time msec/echo time msec); section thickness, 5 mm; intersection gap, 2.5 mm; field of view, 20 cm; matrix size, 128 x 128; one signal acquired. Data were used to derive both isotropic and anisotropic ADC maps by using the Stejskal and Tanner equation (7): S = S0e-bADC, where S = signal intensity at a b value of 1,000 sec/mm2 and S0 = signal intensity at a b value of 0 sec/mm2. Conventional MR sequences comprised transverse (480/16) and sagittal (450/8) T1-weighted sequences and transverse T2-weighted sequences (3,000/30-90).

Image Analysis
The average ADC was calculated in four areas of gray matter (cortex, thalamus, head of the caudate nucleus, and lentiform nucleus) and four areas of white matter (anterior and posterior subcortical and internal capsule) that were chosen for their propensity to ischemic damage with a hypoxic insult (Fig 1). Regions of interest of six pixels were outlined manually (K.P.N.F.) in these areas by using a combination of the image with a b value of 0 and the isotropic and anisotropic DW images to help identify relevant anatomy.



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  		Figure 1. Transverse diffusion-weighted MR image (b = 1,000 sec/mm2) shows the regions of interest used to calculate ADC in gray and white matter: 1 = anterior subcortical white matter, 2 = anterior limb of the internal capsule, 3 = posterior limb of the internal capsule, 4 = posterior subcortical white matter, 5 = head of the caudate nucleus, 6 = lentiform nucleus, 7 = thalamus, 8 = cortex.

 
Statistical Analysis
Statistical analysis was performed (STATISTICAL ANALYSIS SYSTEM; SAS, Cary, NC). A general linear regression model, the Student-Newman-Keuls test, was used to examine the relationship between ADC and both subject age and logarithm of subject age (9). Analysis of variance, or ANOVA, was used to compare ADCs in different brain regions (9).


   RESULTS
TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
RESULTS
DISCUSSION
 REFERENCES
 
Relationship of ADC to Subject Age
In each of the eight areas of the brain examined, ADC showed the highest values at birth and decreased with age, as shown in Figure 2 (P < .01). Data best fit with a logarithmic decline.



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  		Figure 2. Graphs show the reduction in ADC in different brain regions with increasing age. Raw data have been plotted that illustrate a logarithmic decline (ie, early rapid decrease) that plateaus. Subject age has been adjusted for gestational length, with resultant negative values for subjects born before 40 weeks of gestation. Each point represents the average ADC value for an individual subject. The middle continuous line represents the best fit regression line for all data points, with the dashed lines on either side the 95% CIs, such that 95% of data points are within these bounds.

 
The strongest relationship with age, the largest r2 value, was observed in the subcortical white matter, where ADC decreased from 188 x 10-5 mm2/sec at birth to 105 x 10-5 mm2/sec at 1 year, with ADC of 188 minus 14ln(age) (r2 = 0.63). The internal capsule and the head of the caudate nucleus also showed a strong effect of age on ADC. Within the anterior limb of the internal capsule, ADC was 130 minus 7ln(age) with r2 of 0.50, and in the posterior limb ADC was 109 minus 5ln(age) with r2 of 0.40. Within the head of the caudate nucleus, ADC was 134 minus 8ln(age) with r2 of 0.48. A weaker relationship of ADC with time was demonstrated in the lentiform nucleus and thalamus, with ADC of 120 minus 6ln(age) and r2 of 0.39, and cortex, with ADC of 134 minus 5 ln(age) with r2 of 0.20.

Differences in ADC among Brain Regions
Overall, ADC was significantly higher in white matter (113 x 10-5 mm2/sec) than in gray matter (102 x 10-5 mm2/sec; P < .001) (Fig 3). Within white matter, subcortical white matter showed the highest ADC value of 188 x 10-5 mm2/sec at birth. No significant difference was observed between anterior and posterior subcortical white matter. The anterior limb of the internal capsule showed a significantly lower ADC value at birth (130 x 10-5 mm2/sec; P < .01), and the ADC within the posterior limb was even lower (109 x 10-5 mm2/sec at birth), again significantly different from the other white matter regions (P < .01).



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  		Figure 3. Bar graph shows ADC values in different brain regions. Both the average ADC value within the 1st month of life (black bars) and within 9-12 months of age (white bars) are shown for each region to allow temporal changes to be observed. ANT IC = anterior limb of the internal capsule, ANT WM = anterior subcortical white matter, CAUDATE = head of the caudate nucleus, GP/PUTAMEN = globus pallidus/putamen (lentiform nucleus), POST IC = posterior limb of the internal capsule, POST WM = posterior subcortical white matter. Error bars represent SD of ADC.

 
Significant differences were also observed among different gray matter regions. At birth, the highest ADC values were observed in the cortex and head of the caudate nucleus (both, 134 x 10-5 mm2/sec). These regions were, however, significantly different from each other because of the more rapid decrease in ADC in the head of the caudate nucleus. Lower ADC values were seen in the thalamus and lentiform nucleus (both, 120 x 10-5 mm2/sec at birth), which were similar to each other but different from those of other gray matter areas (P < .01).


   DISCUSSION
TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
RESULTS
DISCUSSION
REFERENCES
 
Our results suggest that in neonates and infants, water diffusion is highly dependent on subject age and decreases by approximately one-third to one-half during the 1st year of life. Unlike ADC in adults, ADC in neonates and infants also varies markedly with brain location, with differences observed both between gray and white matter and within each of these categories.

Although it would be optimal for normal ADC values to be determined in entirely healthy subjects not seeking medical attention, the requirement for sedation or general anesthesia in children of this age precludes this study for ethical reasons (10). We therefore chose to examine ADC values in a group of subjects who were already undergoing brain MR imaging in whom both imaging and neurologic assessment results were normal.

Our study was limited both by the small number of subjects and by the lack of follow-up data in many of the subjects, who have not presented to our clinical services again during the 1–36 months elapsed since their initial presentation. Although this may reflect the healthy nature of the subjects in our study, we cannot exclude the possibility that some subjects have presented with neurologic symptoms to another hospital or will present with symptoms in the future. It should be noted that if we have inadvertently included any subject with cerebral ischemic damage, then this would decrease rather than exaggerate the difference between adult and child. Although our results provide an indication of the trend of ADC changes that occur during the 1st year of life, we do not suggest our data should be used as normal reference values for application in clinical practice.

The importance of using age-specific values in interpretation of pediatric DW images is clear, however, when one considers the much lower normal adult values of 76 x 10-5 mm2/sec in the subcortical white matter, as compared with 188 x 10-5 x 10-5 mm2/sec in the term neonate at birth, and 75 x 10-5 mm2/sec in the thalamus, as compared with 120 x 10-5 mm2/sec at birth (2,11). Failure to appreciate normal differences between adult and pediatric ADC may result in erroneous reporting of DW imaging results in neonates and infants. For example, at our institution we have observed that within subcortical white matter, ADC decreases by approximately 45% in neonates with global hypoxic-ischemic damage, giving values of around 85 x 10-5 mm2/sec at birth (4). If this value were compared with the normal adult ADC of 76 x 10-5 mm2/sec, the hypoxic insult would be overlooked, and a false-negative result would ensue.

The highest ADC values in the brain were seen at birth, with a gestational age of less than 40 weeks further increasing ADC. The reduction in ADC observed with age was most marked during the 1st few months of life, thereafter becoming more gradual, in keeping with a logarithmic decline. These temporal ADC changes likely reflect a combination of factors (12), including a reduction in overall water content (13), cellular maturation (14), and white matter myelination (1,8,15). The growth of neuronal and glial cells observed with MR spectroscopy is likely to play an important role in reducing ADC (14). Small increases in the radius of the cell lead to much larger increases in cellular volume, with subsequent decreases in the extracellular space. As the majority of water diffusion occurs within the extracellular space, even small changes in volume could substantially alter ADC and may explain the exponential nature of the ADC decline.

The correlation of ADC to age was stronger in white than in gray matter, likely reflecting the effect of progressive white matter myelination on ADC. White matter myelination limits water diffusion across axons while still allowing diffusion alongside axons, a phenomenon termed "diffusion anisotropy" (1,8, 15). Overall, this effect decreases ADC.

We found that ADC varies widely with brain location during the 1st year of life. The most marked differences were found among different regions of white matter, with subcortical areas showing ADC values nearly double those in the posterior limb of the internal capsule. Such marked differences among white matter regions are likely due to differences in the degree of myelination (1,8,15). The differences in ADC we detected in white matter conform to those that might be predicted from the sequential pattern of myelination observed in conventional MR studies (16). Myelination of cerebral white matter follows a standard pattern, with myelination of deep tracts occurring before myelination of subcortical regions, and that of posterior before that of anterior white matter. Correspondingly, we found the lowest ADC values in the posterior limb of the internal capsule, which is myelinated at birth, and sequentially higher values in tracts that undergo myelination later—the anterior limb of the internal capsule and then subcortical white matter.

Although there was less variation among different gray matter regions, significantly higher values were seen in the head of the caudate nucleus and the cortex than in other areas. The reason for this variation is unclear and may represent reduced cellularity or increased water content, as compared with that in the deep gray nuclei of the thalamus and lentiform nuclei.

In the 1st year of life, both brain location and age are important in determining normal ADC. The difference in maturation between infant and adult brain has marked effects on normal ADC, with each age group demonstrating values that would be pathologic in the other group. Appreciation of the normal changes in brain ADC that occur with age is important when interpreting DW images, particularly in the case of global ischemia, when normal brain may not be available for comparison.


   FOOTNOTES
 
See also the editorial by Medina (pp 316–318 ) in this issue.

Abbreviations: ADC = apparent diffusion coefficient, DW = diffusion-weighted

Author contributions: Guarantor of integrity of entire study, K.P.N.F.; study concepts, K.P.N.F., C.R.B.; study design, K.P.N.F., C.R.B., J.G.P.; literature research, K.P.N.F.; clinical studies, K.P.N.F.; data acquisition, K.P.N.F.; data analysis/interpretation, K.P.N.F.; statistical analysis, K.P.N.F.; manuscript preparation, K.P.N.F., C.R.B., J.G.P.; manuscript definition of intellectual content and editing, C.R.B., J.G.P.; manuscript revision/review and final version approval, K.P.N.F., C.R.B., J.G.P.


   REFERENCES
TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
RESULTS
DISCUSSION
 REFERENCES
 

  1. Sakuma H, Nomura Y, Takeda K, et al. Adult and neonatal human brain: diffusional anisotropy and myelination with diffusion-weighted MR imaging. Radiology 1991; 180:229-233.
  2. Tanner SF, Ramenghi LA, Ridgway JP, et al. Quantitative comparison of intrabrain diffusion in adults and preterm and term neonates and infants. AJR Am J Roentgenol 2000; 174:1643-1649.
  3. Gadian DG, Calamante F, Kirkham FJ, et al. Diffusion and perfusion magnetic resonance imaging in childhood stroke. J Child Neurol 2000; 15:279-283.
  4. Forbes KP, Pipe JG, Bird R. Neonatal hypoxic-ischemic encephalopathy: detection with diffusion-weighted MR imaging. AJNR Am J Neuroradiol 2000; 21:1490-1496.
  5. Robertson RL, Ben-Sira L, Barnes PD, et al. MR line-scan diffusion-weighted imaging of term neonates with perinatal brain ischemia. AJNR Am J Neuroradiol 1999; 20:1658-1670.
  6. van Everdingen KJ, van der Grond J, Kappelle LJ, Ramos LM, Mali WP. Diffusion-weighted magnetic resonance imaging in acute stroke. Stroke 1998; 29:1783-1790.
  7. Moseley ME, Kucharczyk J, Mintorovitch J, et al. Diffusion-weighted MR imaging of acute stroke: correlation with T2-weighted and magnetic susceptibility-enhanced MR imaging in cats. AJNR Am J Neuroradiol 1990; 11:423-429.
  8. Nomura Y, Sakuma H, Takeda K, Tagami T, Okuda Y, Nakagawa T. Diffusional anisotropy of the human brain assessed with diffusion-weighted MR: relation with normal brain development and aging. AJNR Am J Neuroradiol 1994; 15:231-238.
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