Literature DB >> 29246356

A Novel Magnetic Resonance Imaging Score Predicts Neurodevelopmental Outcome After Perinatal Asphyxia and Therapeutic Hypothermia.

Lauren C Weeke1, Floris Groenendaal1, Kalyani Mudigonda2, Mats Blennow2, Maarten H Lequin3, Linda C Meiners4, Ingrid C van Haastert1, Manon J Benders1, Boubou Hallberg2, Linda S de Vries5.   

Abstract

OBJECTIVE: To assess the predictive value of a novel magnetic resonance imaging (MRI) score, which includes diffusion-weighted imaging as well as assessment of the deep grey matter, white matter, and cerebellum, for neurodevelopmental outcome at 2 years and school age among term infants with hypoxic-ischemic encephalopathy treated with therapeutic hypothermia. STUDY
DESIGN: This retrospective cohort study (cohort 1, The Netherlands 2008-2014; cohort 2, Sweden 2007-2012) including infants born at >36 weeks of gestational age treated with therapeutic hypothermia who had an MRI in the first weeks of life. The MRI score consisted of 3 subscores: deep grey matter, white matter/cortex, and cerebellum. Primary adverse outcome was defined as death, cerebral palsy, Bayley Scales of Infant and Toddler Development, third edition, motor or cognitive composite scores at 2 years of <85, or IQ at school age of <85.
RESULTS: In cohort 1 (n = 97) and cohort 2 (n = 76) the grey matter subscore was an independent predictor of adverse outcome at 2 years (cohort 1, OR, 1.6; 95% CI, 1.3-1.9; cohort 2, OR, 1.4; 95% CI, 1.2-1.6), and school age (cohort 1, OR, 1.3; 95% CI, 1.2-1.5; cohort 2, OR, 1.3; 95% CI, 1.1-1.6). The white matter and cerebellum subscore did not add to the predictive value. The positive predictive value, negative predictive value, and area under the curve for the grey matter subscore were all >0.83 in both cohorts, whereas the specificity was >0.91 with variable sensitivity.
CONCLUSION: A novel MRI score, which includes diffusion-weighted imaging and assesses all brain areas of importance in infants with therapeutic hypothermia after perinatal asphyxia, has predictive value for outcome at 2 years of age and at school age, for which the grey matter subscore can be used independently.
Copyright © 2017 The Author(s). Published by Elsevier Inc. All rights reserved.

Entities:  

Keywords:  MRI; hypothermia; hypoxic-ischemic encephalopathy; outcome; score

Mesh:

Year:  2018        PMID: 29246356      PMCID: PMC5743051          DOI: 10.1016/j.jpeds.2017.09.043

Source DB:  PubMed          Journal:  J Pediatr        ISSN: 0022-3476            Impact factor:   4.406


Although therapeutic hypothermia after perinatal asphyxia has reduced the incidence of adverse outcome, 45% of infants still die or have neurodevelopmental impairment.1, 2, 3, 4, 5, 6, 7 Magnetic resonance imaging (MRI) and proton magnetic resonance spectroscopy (1H-MRS) have been shown to be excellent predictors of outcome4, 8, 9, 10, 11 and are often used as bridging biomarkers for neurodevelopmental outcome in infants with hypoxic-ischemic encephalopathy (HIE).12, 13 Quantifying the extent of brain injury in these infants is important for objective and accurate prognostication and guiding decisions on redirection of care. Many existing MRI scores do not include diffusion-weighted images (DWI),4, 9, 10, 14 even though DWI has been shown to be the most reliable MRI sequence to assess injury during the first week after an hypoxic-ischemic event. Early detection is important for the selection of future additional neuroprotective strategies, which may need to be initiated within the first week after birth. Some abnormalities encountered on MRIs of infants with HIE, such as intracranial hemorrhages, cerebellar lesions, and MRS abnormalities are not part of existing scores, although they may be of additional value. We developed a novel score based on assessment of all MRI abnormalities of suspected importance for prognostication in infants with HIE. We hypothesized that our novel MRI score, which includes DWI as well as assessment of the deep grey matter, white matter, and cerebellum, will have a better predictive value for neurodevelopmental outcome at 2 years of age and at school age than conventional MRI-based scoring systems that have been described previously.

Methods

The ethics committees of both participating centers waived the requirement to obtain informed consent for this retrospective study with anonymized data. Infants born after a gestational age of >36 weeks admitted to a level III neonatal intensive care unit in the Netherlands (cohort 1, January 2008-March 2014; n = 97) and Sweden (cohort 2, January 2007–December 2009; n = 76) treated with therapeutic hypothermia for HIE (defined as a Thompson score of >7 and/or a discontinuous electroencephalograph) owing to presumed perinatal asphyxia (5-minute Apgar score ≤5, pH ≤7.10, base deficit ≥16 mmol/L, or resuscitation 10 minutes after birth) and examined by brain MRI as part of routine clinical care were included. Infants with major congenital abnormalities, inborn errors of metabolism, and genetic syndromes were excluded. In both centers whole-body cooling was started as soon as possible within 6 hours after birth and continued for 72 hours. After 72 hours, the babies were rewarmed gradually to 36.5°C. After rewarming, the babies were kept at a temperature of 36.5°C for 12-24 hours. In both cohorts, MRI was performed on a 1.5-T or 3.0-T magnet (Philips Medical Systems, Best, The Netherlands, GE Healthcare, Chicago, Illinois), within the first weeks after birth. Standard MRI protocol included axial T1-weighted images or inversion recovery-weighted images, T2-weighted images, DWI including apparent diffusion coefficient (ADC) mapping. Only in cohort 1 were 1H-MRS measurements in the basal ganglia and thalamus performed (details published previously). The MRI score was designed based on previously published scores and the patterns of brain injury reported in the literature (Table I; available at www.jpeds.com).10, 13, 14 Our score assesses brain injury in 3 areas: (1) deep grey matter (items scored: thalamus, basal ganglia, posterior limb of the internal capsule, brainstem, perirolandic cortex, and hippocampus; maximum grey matter subscore, 23), (2) cerebral white matter/cortex (items scored: cortex, cerebral white matter, optic radiations, corpus callosum, punctate white matter lesions, and parenchymal hemorrhage; maximum white matter subscore, 21), and (3) cerebellum (items scored: cerebellum and cerebellar hemorrhage; maximum cerebellum subscore, 8). Each item was scored for extent of injury: 0 (no injury), 1 (focal, <50%), or 2 (extensive, ≥50%) and for unilateral (score of 1) or bilateral (score of 2) presence, the items were not weighted at this stage. A fourth group (additional) was included, assessing the presence of intraventricular or subdural hemorrhages and sinovenous thrombosis 0 if absent, 1 if present. The maximum additional subscore was 3. The total score was calculated by adding the 4 subscores (grey matter + white matter + cerebellum + additional; maximum score, 55). In cases where 1H-MRS was performed in the basal ganglia and thalamus, N-acetyl aspartate (NAA) and lactate were scored 0 (normal NAA peak, absent lactate peak) or 1 (reduced NAA peak, increased lactate peak), which was subsequently included in the grey matter subscore (maximum grey matter subscore, 24; total score, 57). The ADC measurements were performed when visual analysis of the ADC map was inconclusive, and items were scored as abnormal if the ADC values in the specific area were lower than previously defined cutoff values. MRI examples for each item of the score are shown in Figure 1.
Table I

MRI scoring form

ItemsSequence used to assess injuryDegree
Grey matter012
1Thalamus abnormal SI or diffusion restrictionT1/T2 DWINoFocal (<50%)Extensive (≥50%)
Specify locationUnilateralBilateral
2Basal ganglia abnormal SI or diffusion restrictionT1/T2 DWINoFocal (<50%)Extensive (≥50%)
Specify locationUnilateralBilateral
3PLIC myelination or diffusion restrictionT1/T2 DWINormal or no diffusion restrictionEquivocal/partially myelinated or partial (<50%) diffusion restrictionAbsent myelination or extensive (≥50%) diffusion restriction
Specify locationUnilateralBilateral
4Brainstem (peduncles) abnormal SI or diffusion restrictionT1/T2 DWINoFocal (<50%)Extensive (≥50%)
Specify locationUnilateralBilateral
5Perirolandic cortex diffusion restrictionDWINoMildClear
Specify locationUnilateralBilateral
6Hippocampus diffusion restrictionDWINoYes
Specify locationUnilateralBilateral
Grey matter subscore
Basal ganglia NAA1H-MRSNormalReduced
Basal ganglia lactate1H-MRSAbsentIncreased
Grey matter subscore (including 1H-MRS)
White matter/cortex012
1Cortex abnormal SI or diffusion restriction not being perirolandic cortexT1/T2 DWINoFocal (1 lobe)Extensive (>1 lobe)
Specify locationUnilateralBilateral
2White matter increased SI or diffusion restriction not being PWMLT1/T2 DWINoFocal (1 lobe)Extensive (>1 lobe)
Specify locationUnilateralBilateral
3PWMLT1/T2, DWI, SWINo<6≥6
Specify locationUnilateralBilateral
4Hemorrhage not being PWMLT1/T2, SWINoSingle hemorrhage <1.5 cm≥1.5 cm or multiple hemorrhages
Specify locationUnilateralBilateral
5Optic radiation diffusion restrictionDWINoMildClear
Specify locationUnilateralBilateral
6Corpus callosum diffusion restrictionDWINoYes
White matter subscore
Cerebellum012
1Cerebellum abnormal SI or diffusion restrictionT1/T2 DWINoFocal (<0.5 cm)Extensive (≥0.5 cm or multiple lesions)
Specify locationUnilateralBilateral
2Cerebellar hemorrhageT1/T2, SWINoSingle hemorrhage <0.5 cm≥0.5 cm or multiple hemorrhages
Specify locationUnilateralBilateral
Cerebellum subscore
Additional012
1IVHT1/T2, SWINoYes
2SDHT1/T2NoYes
3CSVTT1/T2, MRVNoYes
Additional subscore
Total score (grey matter + white matter + cerebellum + additional score)

CSVT, Cerebral sinovenous thrombosis; IVH, intraventricular hemorrhage; MRV, magnetic resonance venography; PLIC, posterior limb of the internal capsule; PWML, punctate white matter lesions; SDH, subdural hemorrhage; SI, signal intensity; SWI, susceptibility weighted imaging.

Figure 1

MRI examples of all items to be scored with the novel MRI score. The abnormalities of interest are marked by the white arrows. A, Focal bilateral thalamic lesions (high signal intensity [SI]) on an axial DWI. B, Extensive bilateral thalamic lesions (low SI) on an axial ADC map. C, Focal bilateral lesions (high SI) in the basal ganglia on an axial DWI. D, Extensive bilateral lesions (high SI) in the basal ganglia on an axial DWI. E, The posterior limb of the internal capsule (PLIC) is equivocal on both sides on an axial inversion recovery (IR) image. F, Absent PLIC bilaterally seen as an inverted signal (low SI) on an axial T1-weighted image (T1WI). G, Focal lesion (high SI) in the left cerebral peduncle on an axial DWI. H, Extensive diffusion changes (high SI) in the cerebral peduncles bilaterally on an axial DWI. I, Clear involvement (high SI) of the perirolandic gyrus bilaterally on an axial DWI. J, Bilateral involvement (low SI) of the hippocampus on an axial ADC map. K, Focal involvement (high SI) of the left cortex on an axial DWI. L, Extensive bilateral involvement of the cortex, seen as loss of the differentiation between the white matter and cortical grey matter in the occipital and frontal lobes bilaterally. M, Focal unilateral abnormal signal (low SI) in the left periventricular white matter on an axial ADC map. N, Extensive involvement of the white matter (high SI) on an axial DWI. O, Bilateral punctate white matter lesions (PWML) seen as high SI on an axial DWI. P, A small focal hemorrhage in the right occipital lobe (low SI) on an axial T2-weighted image (T2WI). Q, Bilateral involvement of the optic radiation (high SI) on an axial DWI. R, Involvement of the frontal part of the corpus callosum (high SI) on an axial DWI. S, Focal lesion (high SI) in the left cerebellar hemisphere on an axial T1WI. T, Extensive involvement of both cerebellar hemispheres (high SI) on an axial DWI. U, Bilateral intraventricular hemorrhage (IVH) seen as low SI on an axial T2WI. V, Subdural hemorrhage (SDH) supra- and infratentorial seen as high SI on a sagittal T1WI. W, Cerebral sinovenous thrombosis (CSVT) seen as high SI at the location of the superior sagittal and straight sinus on a sagittal T1WI. X, With corresponding lack flow (lack of high SI) in those veins on an MR venography (MRV) in sagittal view.

MRI examples of all items to be scored with the novel MRI score. The abnormalities of interest are marked by the white arrows. A, Focal bilateral thalamic lesions (high signal intensity [SI]) on an axial DWI. B, Extensive bilateral thalamic lesions (low SI) on an axial ADC map. C, Focal bilateral lesions (high SI) in the basal ganglia on an axial DWI. D, Extensive bilateral lesions (high SI) in the basal ganglia on an axial DWI. E, The posterior limb of the internal capsule (PLIC) is equivocal on both sides on an axial inversion recovery (IR) image. F, Absent PLIC bilaterally seen as an inverted signal (low SI) on an axial T1-weighted image (T1WI). G, Focal lesion (high SI) in the left cerebral peduncle on an axial DWI. H, Extensive diffusion changes (high SI) in the cerebral peduncles bilaterally on an axial DWI. I, Clear involvement (high SI) of the perirolandic gyrus bilaterally on an axial DWI. J, Bilateral involvement (low SI) of the hippocampus on an axial ADC map. K, Focal involvement (high SI) of the left cortex on an axial DWI. L, Extensive bilateral involvement of the cortex, seen as loss of the differentiation between the white matter and cortical grey matter in the occipital and frontal lobes bilaterally. M, Focal unilateral abnormal signal (low SI) in the left periventricular white matter on an axial ADC map. N, Extensive involvement of the white matter (high SI) on an axial DWI. O, Bilateral punctate white matter lesions (PWML) seen as high SI on an axial DWI. P, A small focal hemorrhage in the right occipital lobe (low SI) on an axial T2-weighted image (T2WI). Q, Bilateral involvement of the optic radiation (high SI) on an axial DWI. R, Involvement of the frontal part of the corpus callosum (high SI) on an axial DWI. S, Focal lesion (high SI) in the left cerebellar hemisphere on an axial T1WI. T, Extensive involvement of both cerebellar hemispheres (high SI) on an axial DWI. U, Bilateral intraventricular hemorrhage (IVH) seen as low SI on an axial T2WI. V, Subdural hemorrhage (SDH) supra- and infratentorial seen as high SI on a sagittal T1WI. W, Cerebral sinovenous thrombosis (CSVT) seen as high SI at the location of the superior sagittal and straight sinus on a sagittal T1WI. X, With corresponding lack flow (lack of high SI) in those veins on an MR venography (MRV) in sagittal view. Two reviewers blinded to patient outcomes assessed all MRIs using the score described above. In case of disagreement consensus was obtained with a third blinded reviewer. To determine inter-rater reliability, 2 additional blinded pediatric radiologists (one local to Utrecht one external to the institutions scored the injury on MRI on a subset of scans (n = 10).

Neurodevelopmental Outcome

The Bayley Scales of Infant and Toddler Development, third edition (BSITD-III), was used to assess outcome at 2 years. The Wechsler Preschool and Primary Scale of Intelligence, third edition, Dutch version (WPPSI-III-NL) and Wechsler Intelligence Scale for Children, fourth edition, Swedish version (WISC-IV-SE) was used to assess IQ at school age (cohort 1, 5.5-6.5 years; cohort 2, 6.5-8 years). Severity of cerebral palsy (CP) was classified according to the Gross Motor Function Classification System (GMFCS). For infants with CP who could not be tested with the BSITD-III, a motor composite score was assigned, 70 (-2 SD on the BSITD-III) for GMFCS III, and 45 (-3 SD) for GMFCS IV-V. For infants with severe CP (GMFCS V) who could not be tested with the BSITD-III, a cognitive composite score and for the WPPSI-III-NL or WISC-IV-SE a total IQ score of 45 was assigned. Abnormal outcome was defined at 2 years as death, CP (GMFCS ≥ II), or a BSITD score <85 (-1 SD) for motor or cognitive composite score, and at school age as death, CP (GMFCS ≥ II) or an IQ <85.

Statistical Analyses

GraphPad Prism 6 (GraphPad Software Inc, La Jolla, California) was used to generate receiver operating characteristic curves, calculate the area under the curve, and determine the cutoff values for the MRI score (total and subscores) based on the point on the receiver operating characteristic curve closest to the (0,1) point. Cronbach alpha was used to determine the intraclass correlation coefficient, as a measure of inter-rater reliability for the total score and all subscores. Sensitivity, specificity, positive predictive value, negative predictive value, and accuracy (total number of correctly predicted individuals [true positive + true negative/all observations × 100]) were calculated. SPSS 21 (IBM Corp, Armonk, New York) was used to determine differences between the 2 cohorts in baseline characteristics using the Mann Whitney U test and the χ2 or Fisher exact test and to perform univariate and multivariable logistic regression to investigate the association between adverse outcome, the BSITD-III and IQ scores, and the MRI subscores. BSITD-III and IQ scores were dichotomized for logistic regression, with 85 (−1 SD) being the cutoff level for adverse outcome. P < .05 was considered significant.

Results

MRI scans from cohort 1 were used to develop the score and scans from cohort 2 to validate it. In cohort 1, there were 27 infants with a normal scan and in cohort 2, there were 16 infants. The majority of scans were obtained in the first week after birth (81%). The quality of the scans was good (no movement artefacts, high resolution) in 85.6% for cohort 1 and 71.4% for cohort 2. The baseline characteristics are shown in Table II. Cohort 2 had a higher gestational age at birth, higher birth weights, lower Apgar scores at 5 minutes, and fewer deaths, but a higher survival rate with impairment at 2 years of age compared with cohort 1. One infant with CP had a GMFCS II (cohort 1), and the other infants with CP had a GMFCS ≥ III (all cohort 2); the GMFCS level did not change between 2 years of age and school age.
Table II

Baseline characteristics of the 2 cohorts

Cohort 1 n = 97Cohort 2 n = 76P value
Gestational age (wk), mean (SD)39.9 (1.6)40.3 (1.4).060
Birth weight (g), mean (SD)3497 (610)3708 (662).039
Male, n (%)53 (54.6)36 (47.4)0.342
Apgar at 5 min, median (IQR)4 (2-5)3 (2-4).032
Sarnat grade, n (%)*.056
 112 (12.4)4 (5.3)
 267 (69.1)62 (81.6)
 318 (18.6)7 (9.2)
MRI
 MRI age (day of life), median (IQR)6 (5-7)6 (5-8)0.315
 Total score, median (IQR)6 (0-22)3 (1-11.8)0.122
  Grey matter subscore0 (0-11.5)0 (0-4.5)
  White matter subscore4 (0-8)2 (0-7)
  Cerebellum subscore0 (0-4)0 (0-0)
Outcome
 Died, n (%)22 (22.7)5 (6.6).004
 Age at BSITD-III assessment in months, mean (SD)24.13 (0.42)25.92 (1.68)<.001
 BSITD-III motor composite score, mean (SD)112 (12)95 (23)<.001
 BSITD-III cognitive composite score, mean (SD)107 (14)95 (21)<.001
 Age at IQ assessment in years, mean (SD)5.9 (0.3)7.5 (0.8)<.001
 IQ, mean (SD)102 (17)100 (19)§0.555
 Impairment at 2 years, n (%)4 (4.1)14 (18.4).029
  BSITD-III motor composite score < 852 (2.1)13 (17.1)
  BSITD-III cognitive composite score < 852 (2.1)10 (13.2)0.773
 Impairment at school age, n (%)4 (7.5)5 (10.9)§
 CP1 (1.9)4 (8.7)
 IQ < 853 (5.7)4 (8.7)

Data available for 73 subjects in cohort 2.

Data available for 57 subjects.

Data available for 53 subjects.

Data available for 46 subjects.

Baseline characteristics of the 2 cohorts Data available for 73 subjects in cohort 2. Data available for 57 subjects. Data available for 53 subjects. Data available for 46 subjects. Cronbach alpha was 0.95 for the total score without 1H-MRS (0.96 including 1H-MRS), 0.98 for the grey matter subscore with and without 1H-MRS, 0.94 for the white matter subscore, 0.72 for the cerebellum subscore, and 0.89 for the additional subscore.

MRI Score and Neurodevelopmental Outcome

At 2 years of age, outcome data were available for all infants in both cohorts. The grey matter, white matter, and cerebellum subscores were significantly associated with death or adverse outcome in both cohorts and were subsequently included in a multivariable analysis. The multivariable regression model included grey matter subscore as an independent predictor of death or impairment at 2 years of age in cohort 1 (model without 1H-MRS: OR, 1.6, 95% CI, 1.3-1.9 [ß0 = −4.579, ß1 = 0.456]; model with 1H-MRS: OR, 1.6, 95% CI, 1.3-1.9 [ß0 = −5.017, ß1= 0.443]) and cohort 2 (model without 1H-MRS: OR 1.4, 95% CI 1.2-1.6 [ß0 = −2.310, ß1 = 0.322]). At school age (cohort 1, mean of 5.9 years; cohort 2, mean of 7.5 years), outcome data were available for 53 infants in cohort 1: 22 died and 31 had follow-up assessment. For 44 infants, no follow-up information was available at school age: 35 were too young, 1 was not testable owing to behavioral problems, and 8 were not tested for unknown reasons. In cohort 2, outcome data at school age were available for 46 infants: 5 died and 41 had follow-up assessment. For 30 infants, no follow-up information at school age was available: 19 were too young and 11 were not tested for unknown reasons. There were no differences in baseline characteristics between infants with follow-up assessment and those lost to follow-up. The grey matter and white matter subscores were significantly associated with death or adverse outcome in both cohorts. The grey matter, white matter, and cerebellum subscores were included in a multivariable analysis. The multivariable regression model included the grey matter subscore as an independent predictor of death or impairment at school age in both cohort 1 (model without 1H-MRS: OR, 1.3, 95% CI, 1.2-1.5 [ß0 = −2.394, ß1 = 0.292], model with 1H-MRS: OR, 1.3, 95% CI, 1.1-1.5 [ß0 = −2.333, ß1 = 0.262]) and cohort 2 (model without 1H-MRS: OR, 1.3, 95% CI, 1.1-1.6 [ß0 = −2.747, ß1 = 0.286]). The grey matter subscore was significantly correlated with the white matter and cerebellum subscore in both cohorts (P < .001). Entering white matter and/or cerebellum subscores in the models resulted in a reduction in the OR of the grey matter subscore, suggesting multicollinearity. Receiver operating characteristic curves for adverse outcome at 2 years of age and at school age were plotted for the grey matter subscore because injury to the grey matter subscore was an independent predictor of outcome. The area under the curve values with 95% CIs and sensitivity and specificity for the cutoff values are shown in Table III. Figure 2 shows the distribution of the individual scores in all infants with a normal vs an abnormal outcome at 2 years of age and at school age in both cohorts. A predicted probability graph for adverse outcome at 2 years of age and at school age was generated for the grey matter subscore in cohort 1 (Figure 3; available at www.jpeds.com).
Table III

Cross-tabulation of the MRI score results*

ScoreDiagnostic accuracy
CutoffNormalAbnormalAUC (95% CI)SensitivitySpecificityPPVNPVAccuracy
Cohort 1
 Outcome at 2 y
  Grey matter without 1H-MRS<9.506820.988 (0.973-1.000)0.9230.9580.8890.9710.948
  Grey matter without 1H-MRS≥9.50324
  Grey matter including 1H-MRS<11.506120.989 (0.973-1.000)0.9230.9530.8890.9680.944
  Grey matter including 1H-MRS≥11.50324
 Outcome at school age
  Grey matter without 1H-MRS<11.502540.945 (0.878-1.000)0.8460.9260.9170.8620.887
  Grey matter without 1H-MRS≥11.50222
  Grey matter including 1H-MRS<12.502030.935 (0.855-1.000)0.8850.9090.9200.8700.896
  Grey matter including 1H-MRS≥12.50223
Cohort 2
 Outcome at 2 y
  Grey matter without 1H-MRS<9.5056110.832 (0.708-0.955)0.4210.9820.8890.8360.842
  Grey matter without 1H-MRS≥9.5018
 Outcome at school age
  Grey matter without 1H-MRS<11.503650.861 (0.726-0.997)0.5001.0001.0000.8780.891
  Grey matter without 1H-MRS≥11.5005

AUC, Area under the curve; NPV, negative predictive value; PPV, positive predictive value.

Based on the optimal cutoff values for the grey matter subscore.

Figure 2

Individual score values on the grey matter subscore for infants with a normal (open circles) and infants with an abnormal outcome (death, black crosses; CP, black squares; other impairment, open squares) A, B, at 2 years of age; and C, D, at school age; A, C, in cohort 1; and B, D, cohort 2. The black horizontal lines indicate the median. The dotted horizontal lines indicate the cutoff values for risk of adverse outcome.

Figure 3

Predicted probability of death or impairment A, at 2 years of age and B, at school age based on the grey matter subscore in cohort 1.

Individual score values on the grey matter subscore for infants with a normal (open circles) and infants with an abnormal outcome (death, black crosses; CP, black squares; other impairment, open squares) A, B, at 2 years of age; and C, D, at school age; A, C, in cohort 1; and B, D, cohort 2. The black horizontal lines indicate the median. The dotted horizontal lines indicate the cutoff values for risk of adverse outcome. Cross-tabulation of the MRI score results* AUC, Area under the curve; NPV, negative predictive value; PPV, positive predictive value. Based on the optimal cutoff values for the grey matter subscore.

Adverse Outcome at 2 Years of Age and at School Age in Surviving Infants

The relationship between the MRI scores and the BSITD-III motor and cognitive composite scores at 2 years or the IQ at school age was assessed on the pooled cohort (cohorts 1 + 2), because the number of surviving infants with impairment was too small in the separate cohorts. At 2 years of age, the BSITD-III motor composite score was not available for 14 infants and a motor composite score was assigned for 5 infants with CP in cohort 2. At school age, an IQ score was assigned for 3 infants with CP in cohort 2. The grey matter and white matter subscores were significantly associated with a motor or cognitive composite score of <85 at 2 years of age. None of the subscores was significantly associated with an IQ <85 at school age. The multivariable logistic regression model included the grey matter subscore as an independent predictor of motor (model without 1H-MRS: OR, 1.3, 95% CI, 1.2-1.5 [ß0 = −3.126, ß1 = 0.294]) and cognitive impairment (model without 1H-MRS: OR, 1.3, 95% CI, 1.2-1.5 [ß0 = −3.504, ß1 = 0.290]) at 2 years of age. No analyses were performed on the scores, including 1H-MRS results, because these were only available for cohort 1.

Discussion

We developed an easily applicable, comprehensive MRI score that showed good predictive value in 2 independent, international cohorts, comprising a total of 173 infants treated with therapeutic hypothermia. In both cohorts, injury to the deep grey matter area was an independent predictor of adverse outcome at 2 years of age and at school age. The grey matter subscore may be useful for outcome prediction in hypothermia-treated infants with HIE. The presented cutoff values and predicted probability graphs could be used to aid clinical decision-making or as an outcome measure in clinical trials. The inter-rater reliability was high and the predictive value remained good in cohort 2. Most previously published MRI scoring systems that have been related to outcome9, 10, 14 were designed to be performed using T1- and T2-weighted images only and therefore use scans obtained in the second week of life, because abnormalities on these sequences may not yet be present in the first week. The predictive properties of our score are comparable with these previously published scores.9, 10, 14 Our score has the advantage of including DWI and can, therefore, be used in the first week of life, a period when important clinical decisions may have to be made and during which additional neuroprotective therapies could be initiated. Another advantage of our scoring system is that we use a point-by-point form with clear descriptions of what is considered moderate or severe injury, which can even be used by less experienced MRI readers. The scoring systems published by Barkovich et al, Rutherford et al (TOBY trial [Total Body Hypothermia for Neonatal Encephalopathy]), and Shankaran et al (National Institute of Child Health and Human Development [NICHD]) do not use an item-based scoring system, but group patterns of injury together.9, 10, 14 In our experience, it is sometimes difficult to score infants who have injury who do not fit the categories exactly. Additionally, the NICHD scoring system puts basal ganglia/thalamic injury and white matter injury in the same severity grade, although they do not have the same implications for outcome.21, 22, 23, 24 Four previously published scoring systems included DWI and target scans obtained in the first week of life as well.4, 25, 26, 27 The score presented by Jyoti et al had good predictive value, but included only 20 infants with a follow-up time of only 12 months. Conclusions about the predictive value of that score should therefore be considered with caution. Furthermore, the Jyoti score, similar to the NICHD score, also puts basal ganglia/thalamic injury and white matter injury in the same severity grade. The score presented by Cheong et al had a good specificity, but its sensitivity was suboptimal (0.68). Cavalleri et al used the summation score presented previously by Barkovich et al on DWI., This score showed a high sensitivity (1.00) but a lower specificity (0.67) and was based on ADC measurements, which are more complex and time consuming. The recently published score by Trivedi et al, which was weighted for grey matter injury, had a lower area under the curve of 0.72 (95% CI, 0.57-0.86), sensitivity of 0.77, and specificity of 0.46. Our results from a population of infants treated with therapeutic hypothermia confirm that injury to the deep grey matter is associated with adverse outcome in general and impaired motor function. White matter injury was not included in the prediction model for outcome at 2 years of age, because many infants with a high white matter subscore also had a high grey matter subscore. Only the grey matter score was included, suggesting that outcome was determined mainly by injury to the grey matter. These results support the findings of Harteman et al. We found no association between the white matter subscore and IQ at school age, which is different from other reports in the literature.21, 29, 30, 31 However, these studies were performed in normothermic infants and included infants with isolated severe white matter injury. In our cohort, infants with isolated white matter injury had only mild to moderate lesions, which did not have a significant impact on their cognition. For other populations, such as normothermic infants or infants with metabolic or infectious disorders, the score can be used to perform a complete assessment of the brain and quantify injury. However, the predictive value of the score will be different and needs to be ascertained for each population separately. Cerebellar injury was also not included in the prediction model, even though it was related to poor outcomes in cohort 1. Again, many infants with a high cerebellum subscore also had a high grey matter subscore, suggesting that deep grey matter injury is more important for outcome prediction than cerebellar injury. Besides, the majority of cerebellar injury was a rather unspecific increased signal on T2-weighted imaging, only 5.7% had a cerebellar hemorrhage. We were, unfortunately, unable to assess and compare the quality of the score in the first vs the second week of life, because only a limited number of MRIs were performed in the second week of life. During the first week of life, it is best to perform the score based on the T1- and T2-weighted images combined with DWI, because DWI has been shown to be the most reliable sequence to assess injury in HIE in the first week of life. In the second week of life DWI abnormalities may no longer be visible owing to pseudonormalization. The optimal time window for performing DWI in our opinion would be between days 4 and 7. At this point, rewarming has been completed and DWI abnormalities will have reached their full extent, and pseudonormalization will not yet have occurred. However, the score can also be performed in the second week using T1- and T2-weighted images only. ADC and 1H-MRS measurements (lactate and NAA) in the basal ganglia can add significantly to the predictive properties of MRI. In contrast with ADC, which shows pseudonormalization after the first week, 1H-MRS measurements remain abnormal for a prolonged period of time. The limitations of our study are the lack of 1H-MRS measurements in cohort 2; thus, the score including 1H-MRS measurements still requires validation in another cohort. Furthermore, not all infants had follow-up at school age, which could have led to sampling bias. A significant difference in age at WPPSI/WISC assessment was seen between cohorts 1 and 2; however, regression analysis (data not shown) showed no relation between age at assessment and IQ. A difference in mortality and survival with impairment was observed between cohorts 1 and 2 as well. However, the proportion of infants with adverse outcome, either death or impairment, was exactly the same. In cohort 1, more infants died owing to redirection of care, but this was compensated by a higher number of infants that survived with impairment in cohort 2. The OR for prediction of adverse outcome was, therefore, not affected and remained stable in both cohorts and when infants who died were excluded. The MRI magnet strength was variable in this study, but we do not expect this factor to have influenced our results because magnetic field strength has been demonstrated not to affect ADC or 1H-MRS values. Most of our MRIs were performed in the first week after birth, and the predictive value of the score in the second week after birth still needs to be assessed. The sensitivity of the grey matter subscore was not as good in cohort 2 compared with cohort 1 (0.42 at 2 years of age and 0.50 at school age), yet the specificity, positive predictive value, negative predictive value, and accuracy remained good (>0.84). The reduction in sensitivity might be explained by the greater proportion of MRIs of moderate to poor quality in the test cohort. A poor quality MRI could result in an underestimation of the brain lesions and a lower sensitivity, underlining the importance of a good quality MRI. Although white matter and cerebellum injury did not have additional predictive value in our cohort, these factors could well be predictive in preterm infants, and other high-risk newborns. Scoring systems often perform quite differently in other populations. We should, therefore, always be careful when using scoring systems in other populations. Ideally, the predictive value of scores and the reliability and applicability of cutoff values should be determined for each population separately. It is also possible that with a larger number of subjects or another cohort with a different distribution of injury, there may be a subset of HIE infants with predominant watershed/white matter patterns (without significant basal ganglia/thalamic injury) that would relate to cognitive outcomes. Our scoring system has some theoretical advantages over other systems, but these have not been validated from our study because we could not test other scores on our cohort, because these scores were different in that they do not use DWI. In summary, we developed a novel MRI score that includes DWI, assesses all relevant brain areas, and was tested in 2 independent, international cohorts. In infants with therapeutic hypothermia after perinatal asphyxia, the grey matter subscore with the presented cutoff values and predicted probability graphs may be of use in prognosticating outcome. We also provide additional evidence that in this population outcome is mainly determined by injury to the deep grey matter area, independent of lesions to other areas of the brain such as the white matter.
  30 in total

1.  Diffusion-weighted magnetic resonance imaging in term perinatal brain injury: a comparison with site of lesion and time from birth.

Authors:  Mary Rutherford; Serena Counsell; Joanna Allsop; James Boardman; Olga Kapellou; David Larkman; Jo Hajnal; David Edwards; Frances Cowan
Journal:  Pediatrics       Date:  2004-10       Impact factor: 7.124

2.  Patterns of brain injury in term neonatal encephalopathy.

Authors:  Steven P Miller; Vijay Ramaswamy; David Michelson; A James Barkovich; Barbara Holshouser; Nathaniel Wycliffe; David V Glidden; Douglas Deming; J Colin Partridge; Yvonne W Wu; Stephen Ashwal; Donna M Ferriero
Journal:  J Pediatr       Date:  2005-04       Impact factor: 4.406

3.  Predictors of neurological outcome in cooled neonates.

Authors:  Jingang Li; Masahisa Funato; Hiroshi Tamai; Hiroshi Wada; Masato Nishihara; Hirotaka Iwamoto; Yoko Okazaki; Haruo Shintaku
Journal:  Pediatr Int       Date:  2013-02-27       Impact factor: 1.524

4.  MRI and spectroscopy in (near) term neonates with perinatal asphyxia and therapeutic hypothermia.

Authors:  Thomas Alderliesten; Linda S de Vries; Liza Staats; Ingrid C van Haastert; Lauren Weeke; Manon J N L Benders; Corine Koopman-Esseboom; Floris Groenendaal
Journal:  Arch Dis Child Fetal Neonatal Ed       Date:  2016-08-23       Impact factor: 5.747

5.  Proton spectroscopy and diffusion imaging on the first day of life after perinatal asphyxia: preliminary report.

Authors:  A J Barkovich; K D Westmark; H S Bedi; J C Partridge; D M Ferriero; D B Vigneron
Journal:  AJNR Am J Neuroradiol       Date:  2001-10       Impact factor: 3.825

6.  MR imaging of term infants with hypoxic-ischaemic encephalopathy as a predictor of neurodevelopmental outcome and late MRI appearances.

Authors:  Eilish Twomey; Anne Twomey; Stephanie Ryan; John Murphy; Veronica B Donoghue
Journal:  Pediatr Radiol       Date:  2010-05-29

7.  Prognostic utility of magnetic resonance imaging in neonatal hypoxic-ischemic encephalopathy: substudy of a randomized trial.

Authors:  Jeanie L Y Cheong; Lee Coleman; Rod W Hunt; Katherine J Lee; Lex W Doyle; Terrie E Inder; Susan E Jacobs
Journal:  Arch Pediatr Adolesc Med       Date:  2012-07-01

8.  Brain injury following trial of hypothermia for neonatal hypoxic-ischaemic encephalopathy.

Authors:  Seetha Shankaran; Patrick D Barnes; Susan R Hintz; Abbott R Laptook; Kristin M Zaterka-Baxter; Scott A McDonald; Richard A Ehrenkranz; Michele C Walsh; Jon E Tyson; Edward F Donovan; Ronald N Goldberg; Rebecca Bara; Abhik Das; Neil N Finer; Pablo J Sanchez; Brenda B Poindexter; Krisa P Van Meurs; Waldemar A Carlo; Barbara J Stoll; Shahnaz Duara; Ronnie Guillet; Rosemary D Higgins
Journal:  Arch Dis Child Fetal Neonatal Ed       Date:  2012-11       Impact factor: 5.747

9.  Delayed neurological signs following isolated parasagittal injury in asphyxia at term.

Authors:  Yoshiaki Sato; Masahiro Hayakawa; Osuke Iwata; Akihisa Okumura; Toru Kato; Fumio Hayakawa; Tetsuo Kubota; Koichi Maruyama; Masayuki Hasegawa; Machiko Sato; Makoto Oshiro; Osamu Kito; Seiji Kojima
Journal:  Eur J Paediatr Neurol       Date:  2007-12-03       Impact factor: 3.140

10.  Effect of treatment of subclinical neonatal seizures detected with aEEG: randomized, controlled trial.

Authors:  Linda G M van Rooij; Mona C Toet; Alexander C van Huffelen; Floris Groenendaal; Wijnand Laan; Alexandra Zecic; Timo de Haan; Irma L M van Straaten; Sabine Vrancken; Gerda van Wezel; Jaqueline van der Sluijs; Henk Ter Horst; Danilo Gavilanes; Sabrina Laroche; Gunnar Naulaers; Linda S de Vries
Journal:  Pediatrics       Date:  2010-01-25       Impact factor: 7.124

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  29 in total

1.  Signal Change in the Mammillary Bodies after Perinatal Asphyxia.

Authors:  M Molavi; S D Vann; L S de Vries; F Groenendaal; M Lequin
Journal:  AJNR Am J Neuroradiol       Date:  2019-11-06       Impact factor: 3.825

2.  Maternal Obesity during Pregnancy is Associated with Lower Cortical Thickness in the Neonate Brain.

Authors:  X Na; N E Phelan; M R Tadros; Z Wu; A Andres; T M Badger; C M Glasier; R R Ramakrishnaiah; A C Rowell; L Wang; G Li; D K Williams; X Ou
Journal:  AJNR Am J Neuroradiol       Date:  2021-10-07       Impact factor: 3.825

3.  Limitations of Conventional Magnetic Resonance Imaging as a Predictor of Death or Disability Following Neonatal Hypoxic-Ischemic Encephalopathy in the Late Hypothermia Trial.

Authors:  Abbot R Laptook; Seetha Shankaran; Patrick Barnes; Nancy Rollins; Barbara T Do; Nehal A Parikh; Shannon Hamrick; Susan R Hintz; Jon E Tyson; Edward F Bell; Namasivayam Ambalavanan; Ronald N Goldberg; Athina Pappas; Carolyn Huitema; Claudia Pedroza; Aasma S Chaudhary; Angelita M Hensman; Abhik Das; Myra Wyckoff; Amir Khan; Michelle C Walsh; Kristi L Watterberg; Roger Faix; William Truog; Ronnie Guillet; Gregory M Sokol; Brenda B Poindexter; Rosemary D Higgins
Journal:  J Pediatr       Date:  2020-11-13       Impact factor: 4.406

4.  Interobserver Reliability of an MR Imaging Scoring System in Infants with Hypoxic-Ischemic Encephalopathy.

Authors:  E Szakmar; H Meunier; M El-Dib; E Yang; T E Inder
Journal:  AJNR Am J Neuroradiol       Date:  2021-03-25       Impact factor: 3.825

5.  MRI Score Ability to Detect Abnormalities in Mild Hypoxic-Ischemic Encephalopathy.

Authors:  Michelle Machie; Lauren Weeke; Linda S de Vries; Nancy Rollins; Larry Brown; Lina Chalak
Journal:  Pediatr Neurol       Date:  2020-11-28       Impact factor: 3.372

6.  Diffusion Tensor MRI of White Matter of Healthy Full-term Newborns: Relationship to Neurodevelopmental Outcomes.

Authors:  Kaiyang Feng; Amy C Rowell; Aline Andres; Betty Jayne Bellando; Xiangyang Lou; Charles M Glasier; Raghu H Ramakrishnaiah; Thomas M Badger; Xiawei Ou
Journal:  Radiology       Date:  2019-06-04       Impact factor: 29.146

7.  Profile of minor neurological findings after perinatal asphyxia.

Authors:  Anna Kivi; Marjo Metsäranta; Sanna Toiviainen-Salo; Sampsa Vanhatalo; Leena Haataja
Journal:  Acta Paediatr       Date:  2021-11-17       Impact factor: 4.056

8.  Low Variability of Blood Pressure Predicts Abnormal Electroencephalogram in Infants with Hypoxic Ischemic Encephalopathy.

Authors:  Abigail Flower; Daniel Vasiliu; Tianrui Zhu; Robert Andris; Maryam Abubakar; Karen Fairchild; Santina Zanelli; Julie Matsumoto; Amit M Mathur; John Delos; Zachary Vesoulis
Journal:  Am J Perinatol       Date:  2020-08-20       Impact factor: 1.862

9.  Thermal Index for early non-invasive assessment of brain injury in newborns treated with therapeutic hypothermia: preliminary report.

Authors:  W Walas; A Mączko; Z Halaba; M Bekiesińska-Figatowska; I Miechowicz; D Bandoła; Z Ostrowski; M Rojczyk; A J Nowak
Journal:  Sci Rep       Date:  2021-06-15       Impact factor: 4.379

10.  MRI combined with early clinical variables are excellent outcome predictors for newborn infants undergoing therapeutic hypothermia after perinatal asphyxia.

Authors:  Marianne Thoresen; Sally Jary; Lars Walløe; Mathias Karlsson; Miriam Martinez-Biarge; Ela Chakkarapani; Frances M Cowan
Journal:  EClinicalMedicine       Date:  2021-05-17
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