Published online October 2, 2006
PEDIATRICS Vol. 118 No. 4 October 2006, pp. 1467-1477 (doi:10.1542/peds.2005-2976)
This Article
Right arrow Abstract Freely available
Right arrow Full Text (PDF)
Right arrow P3Rs: Submit a response
Right arrow Alert me when this article is cited
Right arrow Alert me when P3Rs are posted
Right arrow Alert me if a correction is posted
Right arrow Citation Map
Services
Right arrow E-mail this article to a friend
Right arrow Similar articles in this journal
Right arrow Similar articles in PubMed
Right arrow Alert me to new issues of the journal
Right arrow Add to My File Cabinet
Right arrow Download to citation manager
Right arrow reprints & permissions
Citing Articles
Right arrow Citing Articles via HighWire
Right arrow Citing Articles via CrossRef
Right arrow Citing Articles via ISI Web of Science (1)
Right arrow Citing Articles via Google Scholar
Google Scholar
Right arrow Articles by Shanmugalingam, S.
Right arrow Articles by Robertson, N. J.
Right arrow Search for Related Content
PubMed
Right arrow PubMed Citation
Right arrow Articles by Shanmugalingam, S.
Right arrow Articles by Robertson, N. J.
Related Collections
Right arrow Premature & Newborn

ARTICLE

Comparative Prognostic Utilities of Early Quantitative Magnetic Resonance Imaging Spin-Spin Relaxometry and Proton Magnetic Resonance Spectroscopy in Neonatal Encephalopathy

Shanthi Shanmugalingam, MRCPCHa, John S. Thornton, PhDb,c, Osuke Iwata, MDa, Alan Bainbridge, PhDd, Frances E. O'Brien, MRCPCHa, Andrew N. Priest, DPhild, Roger J. Ordidge, PhDb, Ernest B. Cady, BScb,d, John S. Wyatt, FRCPCHa and Nicola J. Robertson, FRCPCH, PhDa

a Centre for Perinatal Brain Research, Institute for Women's Health
b Department of Medical Physics and Bioengineering, University College London, London, United Kingdom
c Lysholm Department of Neuroradiology, National Hospital for Neurology and Neurosurgery
d Department of Medical Physics and Bioengineering, University College London Hospitals National Health Service Foundation Trust, London, United Kingdom


   ABSTRACT
TOP
 ABSTRACT
METHODS
 RESULTS
 DISCUSSION
 CONCLUSIONS
 REFERENCES
 
OBJECTIVE. We sought to compare the prognostic utilities of early MRI spin-spin relaxometry and proton magnetic resonance spectroscopy in neonatal encephalopathy.

METHODS. Twenty-one term infants with neonatal encephalopathy were studied at a mean age of 3.1 days (range: 1–5). Basal ganglia, thalamic and frontal, parietal, and occipital white matter spin-spin relaxation times were determined from images with echo times of 25 and 200 milliseconds. Metabolite ratios were determined from an 8-mL thalamic-region magnetic resonance spectroscopy voxel (1H point-resolved spectroscopy; echo time 270 milliseconds). Outcomes were assigned at age 1 year as follows: (1) normal, (2) moderate (neuromotor signs or Griffiths developmental quotient of 75–84), (3) severe (functional neuromotor deficit or developmental quotient <75 or died). Predictive efficacies for differentiation between normal and adverse (combined moderate and severe) outcomes were compared by receiver operating characteristic curve analysis and logistic regression.

RESULTS. Thalamic and basal ganglia spin-spin relaxation times correlated positively with outcome and predicted adversity. Although thalamic and basal ganglia spin-spin relaxation times were prognostic of adversity, magnetic resonance spectroscopy metabolite ratios were better predictors, and, of these, lactate/N-acetylaspartate was most accurate.

CONCLUSIONS. Deep gray matter spin-spin relaxation time was increased in the first few days after birth in infants with an adverse outcome. Proton magnetic resonance spectroscopy was more prognostic than spin-spin relaxation time, with lactate/N-acetylaspartate the best measure. Nevertheless, both techniques were useful for early prognosis, and the potential superior spatial resolution of spin-spin relaxometry may define better the precise anatomic pattern of injury in the early days after birth.

Key Words: neonatal • encephalopathy • MRI • T2 relaxometry • magnetic resonance spectroscopy

Abbreviations: NE—neonatal encephalopathy • HI—hypoxia-ischemia • T2—spin-spin relaxation time • DWI—diffusion-weighted imaging • 1H MRS—proton magnetic resonance spectroscopy • Cr—creatine plus phosphocreatine • NAA—N-acetylaspartate • TE—echo time • TR—recovery time • ROI—region of interest • DQ—developmental quotient

Twenty-three percent of the 4 million annual worldwide neonatal deaths are caused by perinatal asphyxia.1 In the United Kingdom, hypoxic-ischemic injury leads to death or severe neurologic disability in 1 to 2 per 1000 term infants.2 As routine use of effective neuroprotective agents becomes increasingly likely in neonatal encephalopathy (NE) secondary to perinatal hypoxia-ischemia (HI), methods are needed to assess the pattern and the severity of cerebral injury shortly after birth. Such information may be useful for patient-specific neuroprotective strategies.

Abnormalities on conventional spin-spin relaxation time (T2)-weighted MRI, in which tissue contrast depends on the T2, may be subtle in the early postnatal course and take several days to become obvious.3–10 This represents a period when therapeutic interventions may provide maximal benefit. Diffusion-weighted imaging (DWI) reveals early abnormalities; however, there may be false-negative results in the first 24 hours after birth, and the brain regions that exhibit abnormal diffusivity may change with time.11–13 Proton magnetic resonance spectroscopy (1H MRS) also demonstrates early abnormalities; cerebral metabolite ratios such as lactate/total creatine (including phosphocreatine; Cr) and lactate/N-acetylaspartate (NAA) that are measured between the first day and the end of the second week after birth provide accurate markers of injury severity and subsequent neurodevelopmental outcome.14–24

Quantitative MRI brain-water T2 measurements provide another opportunity for early in vivo investigation.25 T2 is influenced by tissue properties, including water content and its compartmental distribution, cerebral blood flow or volume,25 and tissue protein content.26 In many adult pathologies, quantification of brain-water T2 has identified objectively areas of signal abnormality, including regions that appeared normal on conventional T2-weighted imaging.27,28 Similarly, neonatal brain-water T2 may provide a more sensitive and objective assessment of early and subtle cerebral pathologies when conventional imaging is unreliable. The aim of this study was to assess whether regional brain-water T2 in the first week of life was prognostic in infants with NE and to make an objective comparison with 1H MRS.


   METHODS
TOP
 ABSTRACT
 METHODS
RESULTS
 DISCUSSION
 CONCLUSIONS
 REFERENCES
 
Patients
The Committee on the Ethics of Human Research at University College London Hospitals National Health Service Foundation Trust approved this study, and informed parental consent was obtained. We studied 21 infants who were born at a mean gestational age of 40.2 weeks (SD: 1.5) and had a birth weight of 2.62 kg (SD: 1.42). Infants fulfilled the following criteria: (1) gestational age at scan 36 to 42 completed weeks; (2) acute NE as defined by detailed structured neurologic assessment29; and (3) a clinical history consistent with perinatal HI as primary cause of NE (late decelerations on cardiotocography, meconium-stained liquor, acidemia [pH <7.0 and/or base deficit >12 mmol/L] in umbilical cord blood or arterial blood <1 hour of birth).

Infants with major congenital malformations and those who were enrolled in therapeutic hypothermia trials were excluded. Table 1 gives clinical details. No infant showed intraventricular hemorrhage on cranial ultrasound or MRI.


View this table:
[in this window]
[in a new window]
  		TABLE 1 Clinical Details of Infants With NE

 
Patient Handling
MRI and MRS were clinically indicated and performed after sedation with oral chloral hydrate for self-ventilating infants or with intravenous morphine for those who were mechanically ventilated. T2 relaxometry was additional to the clinical scans. Infants were examined within a transparent plastic pod attached to an MRI-compatible incubator that provided environmental temperature control. Gentle head restraint was provided by a bag of polystyrene beads that was evacuated of air (PRA Plastics Ltd, London, United Kingdom). Neonatal intensive care was continued throughout, and monitoring included electrocardiogram, pulse oximetry, skin temperature, and apnea alarm. A pediatrician was always present.

MRI/MRS System
Studies used a 2.35-T Bruker Avance system (Bruker Medizintechnik, Ettlingen, Germany) with actively shielded gradients (Bruker S-260) and a Bruker birdcage coil (internal diameter: 19.5 cm; 7 studies) or a custom-made Helmholtz coil (internal diameter: 15 cm; 14 studies). Both coils were used in transmit/receive mode.

MRI T2 Relaxometry
Conventional spin-echo images (slice thickness and interslice gap: 5 mm; field of view: 15 cm; 128 x 256 matrix zero-filled to 256 x 256) were acquired from 7 axial slices positioned using a sagittal image such that the central axial slice intersected the genu and splenium of the corpus callosum. Two separate images (with the same receiver gain and transmitter power) were acquired: proton density weighted with echo time (TE) of 25 milliseconds followed by T2-weighted with TE of 200 milliseconds (TEs were optimized using previous data30). Magnetization recovery time (TR) was 4500 milliseconds to allow substantial spin-lattice relaxation. The total acquisition time was 19.2 minutes. Pixel-by-pixel T2 maps were generated assuming that signal intensity was proportional to exp(–TE/T2).

Data were anonymized before blind region of interest (ROI) analysis by a single observer (S.S.). ROIs of ~100 pixels (tissue volume ~0.2 mL) were defined on specific subcortical gray and white matter locations in each cerebral hemisphere (Fig 1). Basal ganglia ROIs were centered on the head of the caudate nucleus. Corresponding left- and right-hemisphere T2s were averaged for each region in each patient.


Figure 1
View larger version (107K):
[in this window]
[in a new window]
  		FIGURE 1 A representative T2 map. The filled rectangles show the ROIs from which brain-water T2 was obtained. T, thalamic; BG, basal ganglia; FWM, frontal white matter; PWM, parietal white matter; OWM, occipital white matter. Mean T2 was calculated for each ROI, and results from left and right hemispheres were averaged. The open rectangle indicates the position of the 1H-MRS voxel.

 
1H MRS
1H point-resolved spectroscopy (TE: 270 milliseconds; TR: 1730 milliseconds; 256 summed echoes) data were acquired from a single 8-mL cubic voxel centered on the thalami using a sagittal image coplanar with the midline (see Fig 1 for position on an axial image). Metabolite signal ratios were determined by using LCModel software.31

Neurodevelopmental Assessments
All surviving infants were examined at 1 year of age (mean: 12 months, 17 days; SD: 24 days). This included a standard neurologic assessment by a pediatrician29 and a Griffiths developmental assessment32 by a psychologist who was blind to the clinical history and magnetic resonance findings. Infants were classified according to outcome: normal (normal neurologic assessment and a Griffiths developmental quotient [DQ] of ≥85), moderate (neuromotor signs but no functional difficulties or Griffiths DQ of 75–84 on at least 1 subscale), or severe (functional motor or sensory deficits, or Griffiths DQ <75 on at least 1 subscale). Infants who died earlier as a result of NE were classified as severe.

Statistical Methods
Statistical calculations used Sigma Stat 2.03 (Aspire Software International, Ashburn, VA) and SPSS 12.01 (SPSS, Inc, Chicago, IL). Regional T2s were summarized as mean (SD) for each group, and intergroup comparisons for co-hemispheric regions used 1-way analysis of variance and Dunnett's multiple comparison test. 1H MRS metabolite ratios generally were not normally distributed; they therefore were expressed as medians with interquartile ranges, and intergroup comparisons used the nonparametric Kruskal-Wallis test with the Dunn multiple comparison test. Pearson product-moment correlation was used to investigate both the degree of association between metabolite ratios and brain-water T2 and the relationships between T2 or metabolite ratios and outcome score. Binary logistic regression was performed to examine the predictive values of brain-water T2 and metabolite ratios for differentiating normal from adverse (moderate and severe combined) outcome. Prognostic accuracies were assessed further by calculation of the area under the receiver operating characteristic curves for each measure.


   RESULTS
TOP
 ABSTRACT
 METHODS
 RESULTS
DISCUSSION
 CONCLUSIONS
 REFERENCES
 
A representative T2 map is shown in Fig 1. Representative 1H spectra from an infant with normal outcome and from 1 with severe outcome are shown in Fig 2.


Figure 2
View larger version (12K):
[in this window]
[in a new window]
  		FIGURE 2 Representative 1H spectra from an infant with normal outcome (A) and an infant with severely abnormal outcome (B). Lac indicates lactate; Cho, choline.

 
Neurodevelopmental Outcome
Of the 21 infants in the study, 8 had normal outcomes, 5 had moderate, and 8 had severe including 6 who died as a direct consequence of NE within 1 year of birth.

Age at Study
The overall mean postnatal age at scan was 3.1 days (range: 1–5), normal outcome was 3.3 days (range: 1–5), moderate outcome was 4.0 days (range: 3–5), and severe outcome was 2.4 days (range: 1–5). Infants with severe outcome were scanned earlier than those with moderate outcome (P = .030; Dunnett's test).

Brain-Water T2 Relaxometry
Co-hemispheric regional brain-water T2s in each infant arranged according to outcome are shown in Figs 3 A and B, and outcome-group means are given in Table 2. There were positive correlations between both thalamic and basal ganglia T2 and outcome (r = 0.571, P = .007; and r = 0.511, P = .018, respectively). Compared with normal outcome, thalamic and basal ganglia T2s were increased for severe outcome (both P < .05). SD comparison (Table 2) revealed that T2s generally varied more in white than in gray matter. There was no significant correlation between white matter T2 and outcome, and there were no significant white matter T2 inter-regional differences.


Figure 3
View larger version (9K):
[in this window]
[in a new window]
  		FIGURE 3 T2s in gray matter (A) and white matter (B) ROIs by neurodevelopmental outcome at age 1 year, and metabolite peak-area ratios (C) in the thalmic region by neurodevelopmental outcome at 1 year. aP < .05, analysis of variance and Dunnett test versus normal-outcome group. bP < .05, Dunn test compared with normal-outcome group. •, normal; {square}, moderate; {triangleup}, severe.

 

View this table:
[in this window]
[in a new window]
  		TABLE 2 Brain-Water T2 According to Neurodevelopmental-Outcome Group for Each ROI

 
1H MRS
Metabolite ratios according to outcome for each infant are shown in Fig 3C, and medians (interquartile ranges) are given in Table 3. Both lactate/Cr and lactate/NAA demonstrated significant positive associations with outcome (r = 0.648, P = .002; and r = 0.718, P < .001, respectively). NAA/Cr decreased with worsening outcome (r = –0.720, P < .001). Compared with normal outcome, lactate/Cr and lactate/NAA were higher and NAA/Cr was lower for severe outcome (all P < .05).


View this table:
[in this window]
[in a new window]
  		TABLE 3 Metabolite Peak-Area Ratios According to Neurodevelopmental-Outcome Group

 
Gray Matter T2 and Metabolite Ratios
Pearson correlation revealed positive associations between both lactate/Cr and lactate/NAA and thalamic T2 (r = 0.605, P = .004; and r = 0.657, P = .001, respectively) and a negative correlation between NAA/Cr and thalamic T2 (r = –0.538, P = .012). There were similar correlations between these ratios and basal ganglia T2 (r = 0.638, P = .002; r = 0.610, P = .003; and r = –0.462, P = .035, respectively).

Prediction of Adverse Outcome
For comparison of the prognostic abilities of regional brain-water T2 and metabolite ratios, infants with moderate and severe outcome were incorporated into a single-adverse-outcome group. Univariate binary logistic regression was used to model the probability of adverse relative to normal outcome as a function of brain-water T2 or metabolite ratio. The likelihood-ratio test was used to determine significance (Table 4).


View this table:
[in this window]
[in a new window]
  		TABLE 4 Logistic-Regression Analysis

 
Both thalamic and basal ganglia T2 were significant predictors of adverse outcome (P = .002 and .005, respectively). Despite the lack of linear correlation with outcome in our study (r = 0.338, P = .134), parietal white matter T2 was increased for adverse outcome (P = .049). The likelihood-ratio test was nonsignificant for both frontal and occipital white matter T2. Lactate/Cr, lactate/NAA, and NAA/Cr were significant predictors of outcome (all P ≤ .001). Likelihood-ratio test statistics of 10.5, 12.3, and 17.7 for NAA/Cr, lactate/Cr, and lactate/NAA, respectively, exceeded those for all regional T2s, suggesting that metabolite ratios were better predictors of adversity, with lactate/NAA the most useful. These findings were tested by calculation of the sensitivity, specificity, and percentage of cases that were assigned correctly to their actual outcome using a threshold for positive classification corresponding to a predicted probability of .5 (Table 4). Of all of the measures, lactate/NAA and NAA/Cr demonstrated the highest sensitivity (84% and 85%, respectively), and lactate/NAA and lactate/Cr demonstrated the highest specificity (both 88%). Of the MRI relaxometry measures, thalamic T2 gave the highest sensitivity and specificity (85% and 63%, respectively). The probabilities of adverse outcome predicted by logistic regression against lactate/NAA and thalamic T2 are shown in Figs 4 A and B, respectively. Receiver operating characteristic curve analysis results also are shown in Table 4. Lactate/NAA demonstrated the greatest accuracy in predicting neurodevelopmental outcome (area under curve: 0.96; P = .001). Lactate/Cr, NAA/Cr, and thalamic and basal ganglia T2 also demonstrated good prognostic utility.


Figure 4
View larger version (18K):
[in this window]
[in a new window]
  		FIGURE 4 Predicted probability of an adverse outcome versus Lac/NAA (likelihood-ratio test statistic = 17.1, 1 degree of freedom, P < .001; A) and thalamic T2 (likelihood-ratio test statistic = 9.5, 1 degree of freedom, P = .002; B). For comparison, the actual data grouped according to normal and adverse outcome are superimposed. (Lac/NAA is reported on a logarithmic axis for clarity; all data analyses were performed on nontransformed data.)

 

   DISCUSSION
TOP
 ABSTRACT
 METHODS
 RESULTS
 DISCUSSION
CONCLUSIONS
 REFERENCES
 
In this study, we observed positive correlations between elevated thalamic and basal ganglia brain-water T2 and neurodevelopmental outcome severity in infants who had NE and were studied within the first 5 days after birth (mean: 3.1 days). There were positive associations between basal ganglia and thalamic T2 and both lactate/Cr and lactate/NAA; there were negative correlations between basal ganglia and thalamic T2 and NAA/Cr. NAA/Cr, lactate/Cr, and lactate/NAA were better predictors of adversity than all regional T2s; lactate/NAA demonstrated the greatest accuracy in predicting outcome. However, both 1H MRS and T2 were useful for assigning early prognosis, and, in the future, the superior spatial resolution that is afforded by T2 might define the pattern as well as the severity of injury.

Conventional T2-weighted MRI contrast depends on factors such as (1) T2, (2) proton density, (3) spin-lattice relaxation, and (4) parameters such as TE and TR. In conventional MRI, absolute image intensities are scaled arbitrarily and therefore are not comparable between patients. T2 relaxometry uses multiple TEs to yield T2 maps, independent of intensity scaling and uncontaminated by other contrast mechanisms, which are interstudy comparable. Hence, T2 relaxometry may reveal tissue abnormalities that are not apparent on conventional T2-weighted imaging.

Methodologic Considerations and Potential Limitations
Because of time constraints, it was impossible to assess T2 reproducibility by repeated scans during each examination. However, relaxometry methods similar to ours have provided reproducible T2s in adults33,34 (using a briefer second TE [120 milliseconds] appropriate to the shorter mature-brain T2) and in healthy term infants.30 Owing to software limitations and time constraints, we approximated that MRI signal T2 decay was monoexponential and used only 2 TEs. In fact, cerebral T2 relaxation in the adult commonly is multiexponential35 and is likely to be similarly so in the neonate. The values that are reported herein therefore should be considered effective T2s. Nevertheless, our results demonstrate the prognostic utility of T2 relaxometry in NE and suggest that multi-TE measurements, providing more detailed characterization of T2 relaxation, may be worthwhile.

It is likely that the prognostic accuracies of T2 relaxometry and 1H MRS will depend on the delay since perinatal HI. In our study, we aimed to scan on postnatal day 3 and at the latest by day 5. This was achieved, despite the challenges of studying sick infants in a busy tertiary referral hospital. Day 3 was chosen because experimental studies have shown that the best correlation between brain lesion size on T2-weighted MRI and the histologic extent of injury occurs by 72 hours after HI.36–38 1H MRS metabolite concentrations, in particular that of lactate, also are likely to be most abnormal at this stage20; whether lactate signal remains elevated19 or then normalizes may depend on the severity of the initial injury.

We assumed that HI occurred perinatally; however, it is possible that HI may have been prenatal in some patients. It also is possible that patterns of brain injury were patient specific39 with different temporal evolutions. This also would influence T2 prognostic accuracy. Serial scans in a larger cohort of patients will be necessary to determine the effect of such modulatory factors on basal ganglia and thalamic T2. Conventional brain MRI during the second week provides reliable prognostic information about the pattern of subsequent neurodevelopmental impairment in NE10 and is a recommended standard of care.40 Comparison of our early regional T2 results with conventional imaging in the second week and serial MRI may help to clarify the temporal dependence of T2. This information would enable greater interpretational precision from early T2 relaxometry and facilitate accurate definition of injury pattern and severity.

We used 2 MRI coils: a Bruker birdcage and a custom-made Helmholtz coil. Our spin-echo relaxometry method used 2 separate acquisitions for which all parameters except TE were identical. For both coils, we anticipated some flip-angle ({theta}) nonuniformity. In regions where flip angles deviate from 90 degrees and 180 degrees, a spin-echo sequence generates a refocused component and others that are unrefocused.41 In our method, the 90-degree pulse was phase-cycled, and spoiler gradients were used before and after the 180-degree pulse; these sophistications eliminate unrefocused components, leaving only the wanted refocused component for acquisition. The latter component is proportional to sin3{theta} exp(–TE/T2); with the same transmitter power for each TE (hence, spatially matching {theta}), sin3{theta} cancels when calculating T2. For this reason, our relaxometry method gave coil-invariant results. Furthermore, inter-coil comparison of regional T2s for the infants with normal outcome (4 studied with each coil) suggested consistent results; for example, thalamic T2 was a mean of 133.1 milliseconds (SD: 12.4) for the Helmholtz and a mean of 139.2 milliseconds (SD: 12.9) for the birdcage coil. These results also were similar to a neonatal thalamic mean value of 135.5 milliseconds (SD: 12.9) that we obtained previously using another birdcage coil.30

Pathophysiologic and Clinical Implications of Cerebral T2 Relaxometry
T2 depends on brain-water concentration and its extra- and intracellular distribution and interactions with the microstructural environment.25,26 The relatively higher water and lower myelin content in the perinatal period engenders markedly longer neonatal brain T2s compared with adult values. Brain T2s decrease with maturation, reflecting the falling brain-water content and increasing myelin-associated lipid and protein.30,42–44

T2 prolongation has been observed in adult brain in several pathologic conditions, including edema, demyelination, neuronal loss, extracellular space expansion, infarction, and gliosis and in the hippocampus in temporal lobe epilepsy.33,34 The precise cause of elevated T2 in NE is unknown; histologic studies in experimental models of adult stroke and neonatal HI have suggested that T2 prolongation reflects vasogenic edema associated with blood-brain barrier disruption and loss of tissue integrity.36–38,45,46 Given the considerable neuronal and glial apoptosis in developing brain after HI, the increased extracellular water as a result of cell shrinkage and loss of plasma-membrane integrity may also contribute to T2 prolongation. If necrosis is dominant after HI, then T2 prolongation may occur sooner and T2 increase faster as cellular architecture disruption starts earlier compared with apoptosis.47

The inherent biological variability of perinatal HI and the consequent different patterns and severities of cerebral injury may explain regional T2 heterogeneity. T2 evolution after HI has been studied in animal models.48 After a latent period of 6 to 12 hours,49,50 T2 begins to rise in injured tissue. Both experimental36 and clinical studies51 have suggested that T2 continues to rise as tissue integrity is lost. However, transitory T2 normalization ("MRI fogging") has been observed toward the end of the first week by some groups. Rodent studies have suggested that the best correlation between brain lesion size on T2-weighted MRI and the histologic extent of injury occurs 72 hours after HI.36–38 Indeed, T2-weighted MRI on days 537 and 750 showed smaller lesions than contemporary histology. MRI fogging has been described in both adult stroke patients52,53 and neonatal HI models.36,50,54 Possible mechanisms include partial normalization of cerebral water content54 and invasion of inflammatory cells into the injured tissue and activation of gliosis.55 Such factors could explain the T2 spread in our severe-outcome group.

There has been much interest in the last decade in applying DWI to NE. Although DWI shows abnormalities early, its prognostic role in NE is not yet clear.12,16,56 In a large series of infants who had NE and in whom DWI was measured contemporaneously with conventional MRI, false-negative results were frequent, in particular with moderate basal ganglia or white matter injury.11 In another serial study, the regions of brain with abnormal diffusivity were prone to change with time.13 The precise relationships among diffusion, T2, and metabolite ratio changes after HI are of considerable interest, and we are exploring these in a newborn piglet model.57

We found no relationship between white matter T2s and neurodevelopmental outcome. On both conventional MRI58 and T2 relaxometry,30 white matter T2s vary markedly with anatomic location and age even in healthy infants, particularly in the frontal region.42 This, combined with partial volume contamination from adjacent gray matter or cerebrospinal fluid and difficulties in positioning ROIs reproducibly, may have caused the higher white matter T2 SDs, thereby reducing prognostic sensitivity. Furthermore, susceptibility to HI injury, mode of cell death, or the time course of pathologic T2 changes may be different in white matter.59,60 Metabolic features render deep gray matter selectively vulnerable to perinatal HI, for example, (1) a higher metabolic rate for glucose and oxygen consumption61,62 and (2) overexpression of glutamate receptors and nitric oxide synthase.63,64

Cerebral T2 and Metabolite Ratios
Lactate/Cr, lactate/NAA, and NAA/Cr correlated with neurodevelopmental outcome severity, consistent with previous studies.14,15,17–19,21–23 Elevated brain lactate and diminished NAA have been documented in patients as early as 18 hours after HI.16,23 Increased brain lactate is thought to reflect increased anaerobic glycolysis secondary to disruption of the mitochondrial electron transport chain and oxidative phosphorylation; macrophage infiltration or an altered redox state also may contribute.19,24,55 NAA is found exclusively in the central nervous system, predominantly in neurons; a fall in NAA may represent reduced neuronal and axonal density as cell death proceeds. In the thalamic region, lactate/NAA and lactate/Cr were correlated more strongly with T2 than with NAA/Cr.

Prognostic Efficacies of Deep Gray Matter T2 and 1H MRS
Of the regional MRI measures, thalamic and basal ganglia T2 were the best predictors of adversity. Although lactate/NAA overall was the most accurate predictor of unfavorable outcome, deep gray matter T2 also provided predictive information.

It is possible that T2 relaxometry combined with MRS may enhance the early prognostic evaluation of NE. To this end, future studies need to concentrate on combining magnetic resonance measures at particular time points. Because of low patient numbers and only a single scan session per patient, this was not achievable in our study. In addition, more sophisticated 3-dimensional methods, such as voxel-based T2 relaxometry, may improve further the prognostic utility and the definition of the early pattern of injury.65


   CONCLUSIONS
TOP
 ABSTRACT
 METHODS
 RESULTS
 DISCUSSION
 CONCLUSIONS
REFERENCES
 
We demonstrated positive correlations between elevated thalamic and basal ganglia water T2 and neurodevelopmental outcome severity in infants who had NE and were studied ~3 days after birth. T2 gave prognostic information at a time when conventional MRI of is little benefit. Basal ganglia and thalamic T2 were associated positively with both lactate/Cr and lactate/NAA and negatively with NAA/Cr. These metabolite ratios were better predictors of adversity than all regional T2s; lactate/NAA demonstrated the greatest prognostic accuracy. However, both T2 relaxometry and MRS were useful for early prognosis assignment, and, in the future, the superior spatial resolution that is afforded by T2 relaxometry might define the pattern as well as the severity of injury. Early knowledge of the anatomic pattern and the severity of brain injury is important because therapeutic interventions may have maximal benefit if initiated at this time.


   ACKNOWLEDGMENTS
 
This study was supported by the Wellcome Trust Action Medical Research, Sport Aiding Medical Research for Kids, United Kingdom Engineering and Physical Sciences Research Council, and United Kingdom Medical Research Council.


   FOOTNOTES
 
Accepted Jun 1, 2006.

Address correspondence to Nicola J. Robertson, PhD, Department of Obstetrics and Gynaecology, University College London, 86-96, Chenies Mews WC1E 6HX, United Kingdom. E-mail: n.robertson{at}ucl.ac.uk

The authors have indicated they have no financial relationships relevant to this article to disclose.


   REFERENCES
TOP
 ABSTRACT
 METHODS
 RESULTS
 DISCUSSION
 CONCLUSIONS
 REFERENCES
 

  1. Lawn JE, Cousens S, Zupan J. 4 million neonatal deaths: when? Where? Why? Lancet. 2005;365 :891 –900[CrossRef][ISI][Medline]
  2. Levene MI, Evans DJ, Mason S, Brown J. An international network for evaluating neuroprotective therapy after severe birth asphyxia. Semin Perinatol. 1999;23 :226 –233[CrossRef][ISI][Medline]
  3. Jouvet P, Cowan FM, Cox P, et al. Reproducibility and accuracy of MR imaging of the brain after severe birth asphyxia. AJNR Am J Neuroradiol. 1999;20 :1343 –1348[Abstract/Free Full Text]
  4. Rutherford MA, Pennock JM, Counsell SJ, et al. Abnormal magnetic resonance signal in the internal capsule predicts neurodevelopmental outcome in infants with hypoxic-ischemic encephalopathy. Pediatrics. 1998;102 :323 –328[Abstract/Free Full Text]
  5. Aida N, Nishimura G, Hachiya Y, Matsui K, Takeuchi M, Itani Y. MR imaging of perinatal brain damage: comparison of clinical outcome with initial and follow-up MR findings. AJNR Am J Neuroradiol. 1998;19 :1909 –1921[Abstract]
  6. Kuenzle C, Baenziger O, Martin E, et al. Prognostic value of early MR imaging in term infants with severe perinatal asphyxia. Neuropediatrics. 1994;25 :191 –200[ISI][Medline]
  7. Barkovich AJ, Westmark K, Partridge C, Sola A, Ferriero DM. Perinatal asphyxia: MR findings in the first 10 days. AJNR Am J Neuroradiol. 1995;16 :427 –438[Abstract]
  8. Rutherford MA, Pennock JM, Schwieso JE, Cowan FM, Dubowitz LMS. Hypoxic ischaemic encephalopathy: early magnetic resonance imaging findings and their evolution. Neuropediatrics. 1995;26 :183 –191[ISI][Medline]
  9. Barkovich AJ, Hajlal BL, Vigneron D, et al. Prediction of neuromotor outcome in perinatal asphyxia: evaluation of MR scoring systems. AJNR Am J Neuroradiol. 1998;19 :143 –149[Abstract]
  10. Cowan F. Outcome after intrapartum asphyxia in term infants. Semin Neonatol. 2000;5 :127 –140[CrossRef][Medline]
  11. Rutherford M, Counsell S, Allsop J, et al. Diffusion-weighted magnetic resonance imaging in term perinatal brain injury: a comparison with site of lesion and time from birth. Pediatrics. 2004;114 :1004 –1014[Abstract/Free Full Text]
  12. Zarifi MK, Astrakas LG, Poussaint TY, du Plessis A, Zurakowski D, Tzika AA. Prediction of adverse outcome with cerebral lactate level and apparent diffusion coefficient in infants with perinatal asphyxia. Radiology. 2002;225 :859 –870[Abstract/Free Full Text]
  13. Barkovich AJ. MR imaging of neonatal brain. Neuroimaging Clin N Am. 2006;16 :117 –135
  14. Amess PN, Penrice J, Wylezinska M, et al. Early brain proton magnetic resonance spectroscopy and neonatal neurology related to neurodevelopmental outcome a 1 year in term infants after presumed hypoxic-ischaemic brain injury. Dev Med Child Neurol. 1999;41 :436 –445[CrossRef][ISI][Medline]
  15. Penrice J, Cady EB, Lorek A, et al. Proton magnetic resonance spectroscopy of the brain in preterm and term infants, and early changes after perinatal hypoxia-ischemia. Pediatr Res. 1996;40 :6 –14[ISI][Medline]
  16. Barkovich AJ, Westmark KD, Bedi HS, Partridge C, Ferriero DM, Vigneron DB. Proton spectroscopy and diffusion imaging on the first day of life after perinatal asphyxia: preliminary report. AJNR Am J Neuroradiol. 2001;22 :1786 –1794[Abstract/Free Full Text]
  17. Groenendaal F, Veenhoven RH, van der Grond J, Jansen GH, Witkamp TD, de Vries LS. Cerebral lactate and N-acetyl-aspartate/choline ratios in asphyxiated full-term neonates demonstrated in vivo using proton magnetic resonance spectroscopy. Pediatr Res. 1994;35 :148 –151[ISI][Medline]
  18. Hanrahan JD, Cox IJ, Azzopardi D, et al. Relation between proton magnetic resonance spectroscopy within 18 hours of birth asphyxia and neurodevelopment at 1 year of age. Dev Med Child Neurol. 1999;41 :76 –82[CrossRef][ISI][Medline]
  19. Robertson NJ, Cox JI, Cowan FM, Counsell SJ, Azzopardi D, Edwards EA. Cerebral intracellular lactic alkalosis persisting months after neonatal encephalopathy measured by magnetic resonance spectroscopy. Pediatr Res. 1999;46 :287 –296[ISI][Medline]
  20. Barkovich AJ, Miller SP, Bartha A, et al. MR imaging, MR spectroscopy, and diffusion tensor imaging of sequential studies in neonates with encephalopathy. AJNR Am J Neuroradiol. 2006;27 :533 –547[Abstract/Free Full Text]
  21. Fan G, Wu Z, Chen L, Guo Q, Ye B, Mao J. Hypoxia-ischemic encephalopathy in full-term neonate: correlation proton MR spectroscopy with MR imaging. Eur J Radiol. 2003;45 :91 –98[CrossRef][ISI][Medline]
  22. Barkovich AJ, Baranski K, Vigneron DJ, et al. Proton MR spectroscopy for the evaluation of brain injury in asphyxiated, term neonates. AJNR Am J Neuroradiol. 1999;20 :1399 –1405[Abstract/Free Full Text]
  23. Hanrahan JD, Sargentoni J, Azzopardi D, et al. Cerebral metabolism within 18 hours of birth asphyxia: a proton magnetic resonance spectroscopy study. Pediatr Res. 1996;39 :584 –590[ISI][Medline]
  24. Roelants-Van Rijn AM, Van Der Grond J, de Vries LS, Groenendaal F. Value of 1H-MRS using different echo times in neonates with cerebral hypoxia-ischaemia. Pediatr Res. 2001;49 :356 –362[ISI][Medline]
  25. Smith MA. The technology of magnetic resonance imaging. Clin Radiol. 1985;36 :553 –559[CrossRef][ISI][Medline]
  26. Mathur-De Vre R. Biomedical implications of the relaxation behaviour of water related to NMR imaging. Br J Radiol. 1984;57 :955 –976[ISI][Medline]
  27. Rugg-Gunn PJ, Boulby PA, Symms MR, Barker GJ, Duncan JS. Whole-brain T2 mapping demonstrates occult abnormalities in focal epilepsy. Neurology. 2005;64 :318 –325[Abstract/Free Full Text]
  28. Stevenson VL, Parker GJ, Barker GJ, et al. Variations in T1 and T2 relaxation times of normal appearing white matter and lesions in multiple sclerosis. J Neurol Sci. 2000;178 :81 –87[CrossRef][ISI][Medline]
  29. Amiel Tison C, Grenier A. Neurological Assessment Within the First Year of Life. New York, NY: Oxford University Press; 1986
  30. Thornton JS, Amess PN, Penrice J, Chong WK, Wyatt JS, Ordidge RJ. Cerebral tissue water spin-spin relaxation times in human neonates at 2.4T: methodology and the effects of maturation. Magn Reson Imaging. 1999;17 :1289 –1295[CrossRef][ISI][Medline]
  31. Provencher SW. Estimation of metabolite concentrations from localized in vivo proton NMR spectra. Magn Reson Med. 1993;30 :672 –679[ISI][Medline]
  32. Griffiths R. The Abilities of Babies. A Study in Mental Measurement. Buckinghamshire, United Kingdom: Association for Research in Infant and Child Development; 1986
  33. Duncan JS, Bartlett P, Barker GJ. Technique for measuring hippocampal T2 relaxation time. AJNR Am J Neuroradiol. 1996;17 :1805 –1810[Abstract]
  34. Bartlett PA, Richardson MP, Duncan JS. Measurement of amygdala T2 relaxation time in temporal lobe epilepsy. J Neurol Neurosurg Psychiatry. 2002;73 :753 –755[Abstract/Free Full Text]
  35. MacKay A, Whittall K, Adler J, Li D, Paty D, Graeb D. In vivo visualization of myelin water in brain by magnetic resonance. Magn Reson Med. 1994;31 :673 –677[ISI][Medline]
  36. Rumpel H, Nedelcu J, Aguzzi A, Martin E. Late glial swelling after acute cerebral hypoxia-ischemia in the neonatal rat: a combined magnetic resonance and histochemical study. Pediatr Res. 1997;42 :54 –59[ISI][Medline]
  37. Aden U, Dahlberg V, Fredholm BB, Lai LJ, Chen Z, Bjelke B. MRI evaluation and functional assessment of brain injury after hypoxic ischemia in neonatal mice. Stroke. 2002;33 :1405 –1410[Abstract/Free Full Text]
  38. Albensi BC, Schweizer MP, Rarick TM, Filloux F. Magnetic resonance imaging of hypoxic-ischemic brain injury in the neonatal rat. Invest Radiol. 1998;33 :377 –385[CrossRef][ISI][Medline]
  39. Miller SP, Ferriero DM, Leonard C, et al. Early brain injury in premature newborns detected with magnetic resonance imaging is associated with adverse early neurodevelopmental outcome. J Pediatr. 2005;147 :609 –616[CrossRef][ISI][Medline]
  40. Ment LR, Bada HS, Barnes P, et al. Practice parameter: neuroimaging of the neonate—report of the Quality Standards Subcommittee of the American Academy of Neurology and the Practice Committee of the Child Neurology Society. Neurology. 2002;58 :1726 –1738[Abstract/Free Full Text]
  41. Kaiser R, Bartholdi E, Ernst RR. Diffusion and field-gradient effects in NMR Fourier spectroscopy. J Chem Phys. 1974;60 :2966 –2979[CrossRef]
  42. Ferrie JC, Barantin L, Saliba E, et al. MR assessment of the brain maturation during the perinatal period: quantitative T2 MR study in premature newborns. Magn Reson Imaging. 1999;17 :1275 –1288[CrossRef][ISI][Medline]
  43. Masumura M. Proton relaxation time of immature brain. II. In vivo measurement of proton relaxation time (T1 and T2) in pediatric brain by MRI. Childs Nerv Syst. 1987;3 :6 –11[CrossRef][ISI][Medline]
  44. Holland BA, Haas DK, Norman D, Brant-Zawadski M, Newton TH. MRI of normal brain maturation. AJNR Am J Neuroradiol. 1986;7 :201 –208[Abstract]
  45. van Dorsten FA, Olah L, Scwindt W, et al. Dynamic changes of ADC, perfusion, and NMR relaxation parameters in transient focal ischemia of rat brain. Magn Reson Med. 2002;47 :97 –104[CrossRef][ISI][Medline]
  46. Qiao M, Malisza K, Del Bigio M, Tuor U. Correlation of cerebral hypoxic-ischemic T2 changes with tissue alterations in water content and protein extravasation. Stroke. 2001;32 :958 –963[Abstract/Free Full Text]
  47. Martin LJ, Al-Abdulla NA, Brambrink AM, Kirsch JR, Sieber FE, Portera-Cailliau C. Neurodegeneration in excitotoxicity, global cerebral ischemia, and target deprivation: a perspective on the contributions of apoptosis and necrosis. Brain Res Bull. 1998;4 :281 –309
  48. Baird AE, Warach S. Magnetic resonance imaging of acute stroke. J Cereb Blood Flow Metab. 1998;18 :583 –609[CrossRef][ISI][Medline]
  49. Ning G, Malisza KL, Bigio MR, Bascaramurty S, Kozlowski P, Tuor UI. Magnetic resonance imaging during cerebral hypoxia-ischemia: T2 increases in 2-week-old but not 4-week-old rats. Pediatr Res. 1999;45 :173 –179[ISI][Medline]
  50. Neumann-Haefelin T, Kastrup A, de Crespigny A, et al. Serial MRI after transient focal cerebral ischemia in rats. Dynamics of tissue injury, blood-brain barrier damage, and edema formation. Stroke. 2000;31 :1965 –1973[Abstract/Free Full Text]
  51. Gadian DG, Calamante F, Kirkham FJ, et al. Diffusion and perfusion magnetic resonance in childhood stroke. J Child Neurol. 2000;15 :279 –283[Abstract/Free Full Text]
  52. O'Brien P, Sellar RJ, Wardlaw JM. Fogging on T2-weighted MR after acute ischaemic stroke: how often might this occur and what are the implications? Neuroradiology. 2004;46 :635 –641[ISI][Medline]
  53. Periera AC, Doyle VL, Clifton A, Howe FA, Griffiths JR, Brown MM. Case reports: the transient disappearance of cerebral infarction on T(2) weighted MRI. Clin Radiol. 2000;55 :725 –727[CrossRef][ISI][Medline]
  54. Lin SP, Schmidt RE, McKinstry RC, Ackerman JJH, Neil JJ. Investigation of mechanisms underlying transient T2 normalization in longitudinal studies of ischemic stroke. Magn Res Imag. 2002;15 :130 –136
  55. Lopez-Villegas D, Lenkinski RE, Wehrli SL, Ho W-Z, Douglas SD. Lactate production by human monocytes/macrophages determined by proton MR spectroscopy. Magn Reson Med. 1995;34 :28 –32
  56. McKinstry RC, Miller JH, Snyder AZ, et al. A prospective longitudinal diffusion tensor imaging study of brain injury in newborns. Neurology. 2002;59 :824 –833[Abstract/Free Full Text]
  57. Lorek A, Takei Y, Cady EB, et al. Delayed ("secondary") cerebral energy failure after acute hypoxia-ischemia in the newborn piglet: continuous 48-hour studies by phosphorus magnetic resonance spectroscopy. Pediatr Res. 1994;36 :699 –706[ISI][Medline]
  58. Cowan FM. Magnetic resonance imaging of the normal infant brain: term to 2 years. In: Rutherford M, ed. MRI of the Neonatal Brain. London, United Kingdom: WB Saunders; 2002:58–59
  59. Volpe JJ. Hypoxic-ischemic encephalopathy: neuropathology and pathogenesis. In: Volpe JJ, ed. Neurology of the Newborn. 4th ed. Philadelphia, PA: WB Saunders; 2001:296–330
  60. Mazumdar A, Mukherjee P, Miller JH, Malde H, McKinstry RC. Diffusion-weighted imaging of acute corticospinal tract injury preceding wallerian degeneration in the maturing human brain. AJNR Am J Neuroradiol. 2003;24 :1057 –1066[Abstract/Free Full Text]
  61. Takahashi T, Shirane R, Sato S, et al. Developmental changes of cerebral blood flow and oxygen metabolism in children. AJNR Am J Neuroradiol. 1999;20 :917 –922[Abstract/Free Full Text]
  62. Thorngren-Jerneck K, Ohlsson T, Sandell A, et al. Cerebral glucose metabolism measured by positron emission tomography in term newborn infants with hypoxic ischemic encephalopathy. Pediatr Res. 2001;49 :495 –501[ISI][Medline]
  63. Black SM, Bedolli MA, Martinez S, et al. Expression of neuronal nitric oxide synthase corresponds to regions of selective vulnerability to hypoxia-ischaemia in the developing rat brain. Neurobiol Dis. 1995;2 :145 –155[CrossRef][ISI][Medline]
  64. Jensen FE. The role of glutamate receptor maturation in perinatal seizures and injury. Int J Dev Neurosci. 2002;20 :399 –347
  65. Pell GS, Briellmann RS, Waites AB, Abbott DF, Jackson GD. Voxel-based relaxometry: a new approach for analysis of T2 relaxometry changes in epilepsy. Neuroimage. 2004;21 :707 –713[CrossRef][ISI][Medline]
PEDIATRICS (ISSN 1098-4275). ©2006 by the American Academy of Pediatrics



This article has been cited by other articles:


Home page
 PediatricsHome page
E. De Vita, A. Bainbridge, J. L. Y. Cheong, C. Hagmann, R. Lombard, W. K. Chong, J. S. Wyatt, E. B. Cady, R. J. Ordidge, and N. J. Robertson
Magnetic Resonance Imaging of Neonatal Encephalopathy at 4.7 Tesla: Initial Experiences
Pediatrics, December 1, 2006; 118(6): e1812 - e1821.
[Abstract] [Full Text] [PDF]

This Article
Right arrow Abstract Freely available
Right arrow Full Text (PDF)
Right arrow P3Rs: Submit a response
Right arrow Alert me when this article is cited
Right arrow Alert me when P3Rs are posted
Right arrow Alert me if a correction is posted
Right arrow Citation Map
Services
Right arrow E-mail this article to a friend
Right arrow Similar articles in this journal
Right arrow Similar articles in PubMed
Right arrow Alert me to new issues of the journal
Right arrow Add to My File Cabinet
Right arrow Download to citation manager
Right arrow reprints & permissions
Citing Articles
Right arrow Citing Articles via HighWire
Right arrow Citing Articles via CrossRef
Right arrow Citing Articles via ISI Web of Science (1)
Right arrow Citing Articles via Google Scholar
Google Scholar
Right arrow Articles by Shanmugalingam, S.
Right arrow Articles by Robertson, N. J.
Right arrow Search for Related Content
PubMed
Right arrow PubMed Citation
Right arrow Articles by Shanmugalingam, S.
Right arrow Articles by Robertson, N. J.
Related Collections
Right arrow Premature & Newborn