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Bültmann E, Zapf A, Mussgnug HJ, Kanzelmeyer N, Hartmann H. Cerebral microstructural changes in children suffering from hemolytic uremic syndrome. Eur J Pediatr 2023; 182:4663-4672. [PMID: 37558834 PMCID: PMC10587265 DOI: 10.1007/s00431-023-05130-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/04/2023] [Revised: 07/19/2023] [Accepted: 07/21/2023] [Indexed: 08/11/2023]
Abstract
To evaluate microstructural cerebral changes in children suffering from typical hemolytic uremic syndrome (HUS) based on apparent diffusion coefficient (ADC) maps. For 12 pediatric HUS patients (0.8 - 14.6 years of age) conventional magnetic resonance imaging (cMRI) at 1.5 T was retrospectively analyzed. ADC values were measured in 35 different brain regions and compared with age-related, previously published ADC reference values from a healthy pediatric control group. The HUS cohort was divided into 2 subgroups depending on clinical outcome. Subgroup A showed poor neurological outcome whereas subgroup B demonstrated improvement without lasting neurological deficits. Qualitative analysis revealed lesions by diffusion-weighted imaging (DWI) with hypointense correlate on the ADC map in basal ganglia and/or thalami and corresponding T2 hyperintensities in the majority of patients in Subgroup A (80%). Those in Subgroup B did not show qualitative DWI alterations with ADC correlate even when T2 hyperintense lesions were detected in basal ganglia and/or thalami. Quantitative analysis demonstrated abnormal ADC values in all HUS patients with a trend to a greater number of affected regions in Subgroup A compared to Subgroup B (16 versus 11 median number of regions respectively, p = 0.56). Conclusion: Using DWI qualitative and quantitative differences were found between HUS patients showing poor neurological outcome and those without neurological deficits at discharge. While ADC values indicated more extensive cerebral changes than conventional qualitative findings, both may provide early prognostic indicators for neurological outcome in pediatric HUS patients. What is Known: • In patients with STEC-HUS and neurological symptoms, MRI may show hyperintense signals on T2 and altered diffusivity mostly affecting basal ganglia, thalami and periventricular white matter. What is New: • In such patients, early MRI including quantitative ADC measurements over different brain regions may allow for detection of signal alterations possibly reflecting microstructural changes in such patients.
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Affiliation(s)
- Eva Bültmann
- Institute of Diagnostic and Interventional Neuroradiology, Hannover Medical School, Carl-Neuberg-Straße 1, D-30625, Hannover, Germany.
| | - Antonia Zapf
- Institute of Medical Biometry and Epidemiology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Hans Joachim Mussgnug
- Institute of Diagnostic and Interventional Neuroradiology, Hannover Medical School, Carl-Neuberg-Straße 1, D-30625, Hannover, Germany
| | - Nele Kanzelmeyer
- Clinic for Pediatric Kidney, Liver, and Metabolic Diseases, Hannover Medical School, Hannover, Germany
| | - Hans Hartmann
- Clinic for Pediatric Kidney, Liver, and Metabolic Diseases, Hannover Medical School, Hannover, Germany
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Yu N, Kim JY, Han D, Kim SY, Lee HM, Kim DH, Kim HG. Three-Dimensional Magnetic Resonance Fingerprinting in Neonates: Quantifying Regional Difference and Maturation in the Brain. Invest Radiol 2022; 57:44-51. [PMID: 34101674 DOI: 10.1097/rli.0000000000000800] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
Abstract
OBJECTIVES Magnetic resonance fingerprinting (MRF) allows the simultaneous measurement of multiple tissue properties in a single acquisition. Three-dimensional (3D) MRF with high spatial resolution can be used for neonatal brain imaging. The aim of this study is to apply 3D MRF to neonates and show regional differences and maturation in the brain. MATERIALS AND METHODS In this prospective study, 3D MRF using hybrid radial-interleaved acquisition was performed on phantoms and neonates from December 2019 to October 2020. For the reconstruction of 3D MRF, singular value decomposition was applied to reduce reconstruction time, and the iterative reconstruction technique was applied to improve image quality. The accuracies of T1 and T2 values derived from 3D MRF were evaluated in a phantom experiment. Regional T1 and T2 values were obtained from neonates' brain T1 and T2 maps derived from 3D MRF. Regional T1 and T2 values were compared, and their changes according to corrected gestational age were evaluated. RESULTS The acquisition time for 3D MRF with a spatial resolution of 0.7 × 0.7 × 2 mm3 was less than 5 minutes. The phantom study showed high correlation between T1 and T2 values derived from 3D MRF and those from conventional spin echo sequences (T1, R2 = 0.998, P < 0.001; T2, R2 = 0.998, P < 0.001). Three-dimensional MRF was performed in 25 neonates (15 boys, 10 girls; median corrected gestational age, 263 days; interquartile range, 10 days). In neonates, T1 and T2 values differed in the frontal (median [interquartile range], 2785 [2684-2888] milliseconds and 189.8 [176.7-222.9] milliseconds), parietal (2849 [2741-2950] milliseconds and 191.6 [167.5-232.9] milliseconds), and occipital white matter (2621 [2513-2722] milliseconds and 162.9 [143.5-186.1] milliseconds), showing lower values in occipital white matter (P < 0.001). Regional T1 values showed a negative relationship with corrected gestational age (coefficient, -0.775 to -0.480; P < 0.05). CONCLUSIONS Fast and high spatial resolution 3D MRF was applied to neonates. T1 and T2 maps derived from 3D MRF enabled the quantification of regional differences and maturation in the neonatal brain.
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Affiliation(s)
- Nali Yu
- From the Departments of Pediatrics
| | - Jee Young Kim
- Radiology, Eunpyeong St. Mary's Hospital, College of Medicine, The Catholic University of Korea
| | | | | | | | - Dong-Hyun Kim
- Department of Electrical and Electronic Engineering, College of Engineering, Yonsei University, Seoul, Republic of Korea
| | - Hyun Gi Kim
- Radiology, Eunpyeong St. Mary's Hospital, College of Medicine, The Catholic University of Korea
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Sotardi S, Gollub RL, Bates SV, Weiss R, Murphy SN, Grant PE, Ou Y. Voxelwise and Regional Brain Apparent Diffusion Coefficient Changes on MRI from Birth to 6 Years of Age. Radiology 2020; 298:415-424. [PMID: 33289612 DOI: 10.1148/radiol.2020202279] [Citation(s) in RCA: 17] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
Abstract
Background A framework for understanding rapid diffusion changes from 0 to 6 years of age is important in the detection of neurodevelopmental disorders. Purpose To quantify patterns of normal apparent diffusion coefficient (ADC) development from 0 to 6 years of age. Materials and Methods Previously constructed age-specific ADC atlases from 201 healthy full-term children (108 male; age range, 0-6 years) with MRI scans acquired from 2006 to 2013 at one large academic hospital were analyzed to quantify four patterns: ADC trajectory, rate of ADC change, age of ADC maturation, and hemispheric asymmetries of maturation ages. Patterns were quantified in whole-brain, segmented regional, and voxelwise levels by fitting a two-term exponential model. Hemispheric asymmetries in ADC maturation ages were assessed using t tests with Bonferroni correction. Results The posterior limb of the internal capsule (mean ADC: left hemisphere, 1.18 ×103μm2/sec; right hemisphere, 1.17 ×103μm2/sec), anterior limb of the internal capsule (left, 1.11 ×103μm2/sec; right, 1.09 ×103μm2/sec), vermis (1.26 ×103μm2/sec), thalami (left, 1.17 ×103μm2/sec; right, 1.15 ×103μm2/sec), and basal ganglia (left, 1.26 ×103μm2/sec; right, 1.23 ×103μm2/sec) demonstrate low initial ADC values, indicating an earlier prenatal time course of development. ADC maturation was completed between 1.3 and 2.4 years of age, depending on the region. The vermis and left thalamus matured earliest (1.3 years). The frontolateral gray matter matured latest (right, 2.3 years; left, 2.4 years). ADC maturation occurred earlier in the left hemisphere (P < .001) in several regions, including the frontal (mean ± standard deviation) (left, 2.16 years ± 0.29; right, 2.19 years ± 0.31), temporal (left, 1.93 years ± 0.22; right, 1.99 years ± 0.22), and parietal (left, 1.92 years ± 0.30; right, 2.03 years ± 0.28) white matter. Maturation occurred earlier in the right hemisphere (P < .001) in several regions, including the thalami (left, 1.63 years ± 0.32; right, 1.45 years ± 0.33), basal ganglia (left, 1.79 years ± 0.31; right, 1.70 years ± 0.37), and hippocampi (left, 1.93 years ± 0.34; right, 1.78 years ± 0.33). Conclusion Normative apparent diffusion coefficient developmental patterns on diffusion-weighted MRI scans were quantified in children aged 0 to 6 years. This work provides knowledge about early brain development and may guide the detection of abnormal patterns of maturation. © RSNA, 2020 Online supplemental material is available for this article. See also the editorial by Rollins in this issue.
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Affiliation(s)
- Susan Sotardi
- From the Departments of Radiology (S.S.) and Psychiatry (R.L.G.), Athinoula A. Martinos Center for Biomedical Imaging (R.L.G.), Division of Newborn Medicine, Department of Pediatrics (S.V.B., R.W.), and Laboratory of Computer Science (S.N.M.), Massachusetts General Hospital, Harvard Medical School, Boston, Mass; Department of Radiology, Children's Hospital of Philadelphia, Philadelphia, Pa (S.S.); and Fetal-Neonatal Neuroimaging and Developmental Science Center (P.E.G., Y.O.), Computational Health Informatics Program (Y.O.), Boston Children's Hospital, Harvard Medical School, 300 Longwood Ave, Boston, MA 02115
| | - Randy L Gollub
- From the Departments of Radiology (S.S.) and Psychiatry (R.L.G.), Athinoula A. Martinos Center for Biomedical Imaging (R.L.G.), Division of Newborn Medicine, Department of Pediatrics (S.V.B., R.W.), and Laboratory of Computer Science (S.N.M.), Massachusetts General Hospital, Harvard Medical School, Boston, Mass; Department of Radiology, Children's Hospital of Philadelphia, Philadelphia, Pa (S.S.); and Fetal-Neonatal Neuroimaging and Developmental Science Center (P.E.G., Y.O.), Computational Health Informatics Program (Y.O.), Boston Children's Hospital, Harvard Medical School, 300 Longwood Ave, Boston, MA 02115
| | - Sara V Bates
- From the Departments of Radiology (S.S.) and Psychiatry (R.L.G.), Athinoula A. Martinos Center for Biomedical Imaging (R.L.G.), Division of Newborn Medicine, Department of Pediatrics (S.V.B., R.W.), and Laboratory of Computer Science (S.N.M.), Massachusetts General Hospital, Harvard Medical School, Boston, Mass; Department of Radiology, Children's Hospital of Philadelphia, Philadelphia, Pa (S.S.); and Fetal-Neonatal Neuroimaging and Developmental Science Center (P.E.G., Y.O.), Computational Health Informatics Program (Y.O.), Boston Children's Hospital, Harvard Medical School, 300 Longwood Ave, Boston, MA 02115
| | - Rebecca Weiss
- From the Departments of Radiology (S.S.) and Psychiatry (R.L.G.), Athinoula A. Martinos Center for Biomedical Imaging (R.L.G.), Division of Newborn Medicine, Department of Pediatrics (S.V.B., R.W.), and Laboratory of Computer Science (S.N.M.), Massachusetts General Hospital, Harvard Medical School, Boston, Mass; Department of Radiology, Children's Hospital of Philadelphia, Philadelphia, Pa (S.S.); and Fetal-Neonatal Neuroimaging and Developmental Science Center (P.E.G., Y.O.), Computational Health Informatics Program (Y.O.), Boston Children's Hospital, Harvard Medical School, 300 Longwood Ave, Boston, MA 02115
| | - Shawn N Murphy
- From the Departments of Radiology (S.S.) and Psychiatry (R.L.G.), Athinoula A. Martinos Center for Biomedical Imaging (R.L.G.), Division of Newborn Medicine, Department of Pediatrics (S.V.B., R.W.), and Laboratory of Computer Science (S.N.M.), Massachusetts General Hospital, Harvard Medical School, Boston, Mass; Department of Radiology, Children's Hospital of Philadelphia, Philadelphia, Pa (S.S.); and Fetal-Neonatal Neuroimaging and Developmental Science Center (P.E.G., Y.O.), Computational Health Informatics Program (Y.O.), Boston Children's Hospital, Harvard Medical School, 300 Longwood Ave, Boston, MA 02115
| | - P Ellen Grant
- From the Departments of Radiology (S.S.) and Psychiatry (R.L.G.), Athinoula A. Martinos Center for Biomedical Imaging (R.L.G.), Division of Newborn Medicine, Department of Pediatrics (S.V.B., R.W.), and Laboratory of Computer Science (S.N.M.), Massachusetts General Hospital, Harvard Medical School, Boston, Mass; Department of Radiology, Children's Hospital of Philadelphia, Philadelphia, Pa (S.S.); and Fetal-Neonatal Neuroimaging and Developmental Science Center (P.E.G., Y.O.), Computational Health Informatics Program (Y.O.), Boston Children's Hospital, Harvard Medical School, 300 Longwood Ave, Boston, MA 02115
| | - Yangming Ou
- From the Departments of Radiology (S.S.) and Psychiatry (R.L.G.), Athinoula A. Martinos Center for Biomedical Imaging (R.L.G.), Division of Newborn Medicine, Department of Pediatrics (S.V.B., R.W.), and Laboratory of Computer Science (S.N.M.), Massachusetts General Hospital, Harvard Medical School, Boston, Mass; Department of Radiology, Children's Hospital of Philadelphia, Philadelphia, Pa (S.S.); and Fetal-Neonatal Neuroimaging and Developmental Science Center (P.E.G., Y.O.), Computational Health Informatics Program (Y.O.), Boston Children's Hospital, Harvard Medical School, 300 Longwood Ave, Boston, MA 02115
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Kim HG, Lee JH, Choi JW, Han M, Gho SM, Moon Y. Multidelay Arterial Spin-Labeling MRI in Neonates and Infants: Cerebral Perfusion Changes during Brain Maturation. AJNR Am J Neuroradiol 2018; 39:1912-1918. [PMID: 30213808 DOI: 10.3174/ajnr.a5774] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/19/2018] [Accepted: 07/08/2018] [Indexed: 11/07/2022]
Abstract
BACKGROUND AND PURPOSE Arterial spin-labeling with multiple postlabeling delays can correct transit times. We tried to evaluate CBF in neonates and infants using multidelay arterial spin-labeling. MATERIALS AND METHODS Multidelay arterial spin-labeling was applied to 13 preterm neonates (mean postmenstrual age, 34.9 weeks), 13 term-equivalent-age neonates (mean postmenstrual age, 39.2 weeks), and 6 infants (mean postmenstrual age, 57.8 weeks). Transit time-corrected CBF in the caudate, thalamus, frontal GM, occipital GM, frontal WM, and occipital WM was measured, and relative CBF compared with the whole-brain CBF was calculated. Inter- and intragroup comparisons were performed among the 3 age groups. A correlation and nonlinear regression analysis were performed between postmenstrual age and CBF. RESULTS Intergroup comparisons showed significantly higher whole-brain CBF in infants (38.3 mL/100 g/min) compared with preterm (15.5 mL/100 g/min) and term-equivalent-age (18.3 mL/100 g/min) neonates (P < .001). In the intragroup comparison, all 3 groups showed significantly higher relative CBF values in the occipital WM (63.6%-90.3%) compared with the frontal WM (46.3%-73.9%). In term-equivalent-age neonates, the occipital GM (120.8%) had significantly higher relative CBF values than the frontal GM (103.5%). There was a significant negative correlation between postmenstrual age and the relative CBF of the thalamus (r = - 0.449, P = .010). There were significant positive relationships between postmenstrual age and the relative CBF of the frontal WM (R 2 = 0.298, P = .001) and occipital WM (R 2 = 0.452, P < .001). CONCLUSIONS Multidelay arterial spin-labeling with transit time-corrected CBF showed developmental changes and regional differences of CBF in neonates and infants.
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Affiliation(s)
- H G Kim
- From the Departments of Radiology (H.G.K., J.W.C., M.H.)
| | | | - J W Choi
- From the Departments of Radiology (H.G.K., J.W.C., M.H.)
| | - M Han
- From the Departments of Radiology (H.G.K., J.W.C., M.H.)
| | - S-M Gho
- MR Clinical Research and Development (S.-M.G.), GE Healthcare Korea, Seoul, Korea
| | - Y Moon
- Office of Biostatistics (Y.M.), Institute of Medical Sciences, Ajou University School of Medicine, Ajou University Medical Center, Suwon, Korea
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