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Wu J, Qin F, Tian F, Li H, Yong X, Liu T, Zhang H, Wu D. Age-specific optimization of the T 2-weighted MRI contrast in infant and toddler brain. Magn Reson Med 2024. [PMID: 39428905 DOI: 10.1002/mrm.30339] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/26/2024] [Revised: 07/26/2024] [Accepted: 09/15/2024] [Indexed: 10/22/2024]
Abstract
PURPOSE In 0-2-year-old brains, the T2-weighted (T2w) contrast between white matter (WM) and gray matter (GM) is weaker compared with that in adult brains and rapidly changes with age. This study aims to design variable-flip-angle (VFA) trains in 3D fast spin-echo sequence that adapt to the dynamically changing relaxation times to improve the contrast in the T2w images of the developing brains. METHODS T1 and T2 relaxation times in 0-2-year-old brains were measured, and several age groups were defined according to the age-dependent pattern of T2 values. Based on the static pseudo-steady-state theory and the extended phase graph algorithm, VFA trains were designed for each age group to maximize WM/GM contrast, constrained by the maximum specific absorption rate and overall signal intensity. The optimized VFA trains were compared with the default one used for adult brains based on the relative contrast between WM and GM. Dice coefficient was used to demonstrate the advantage of contrast-improved images as inputs for automatic tissue segmentation in infant brains. RESULTS The 0-2-year-old pool was divided into groups of 0-8 months, 8-12 months, and 12-24 months. The optimal VFA trains were tested in each age group in comparison with the default sequence. Quantitative analyses demonstrated improved relative contrasts in infant and toddler brains by 1.5-2.3-fold at different ages. The Dice coefficient for contrast-optimized images was improved compared with default images (p < 0.001). CONCLUSION An effective strategy was proposed to improve the 3D T2w contrast in 0-2-year-old brains.
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Affiliation(s)
- Jiani Wu
- Key Laboratory for Biomedical Engineering of Ministry of Education, Department of Biomedical Engineering, College of Biomedical Engineering & Instrument Science, Zhejiang University, Hangzhou, Zhejiang, China
| | - Fenjie Qin
- Department of Radiology, Children's Hospital, Zhejiang University School of Medicine, National Clinical Research Center for Child Health, Hangzhou, Zhejiang, China
| | - Fengyu Tian
- Department of Radiology, Children's Hospital, Zhejiang University School of Medicine, National Clinical Research Center for Child Health, Hangzhou, Zhejiang, China
| | - Haotian Li
- Key Laboratory for Biomedical Engineering of Ministry of Education, Department of Biomedical Engineering, College of Biomedical Engineering & Instrument Science, Zhejiang University, Hangzhou, Zhejiang, China
| | - Xingwang Yong
- Key Laboratory for Biomedical Engineering of Ministry of Education, Department of Biomedical Engineering, College of Biomedical Engineering & Instrument Science, Zhejiang University, Hangzhou, Zhejiang, China
| | - Tingting Liu
- Key Laboratory for Biomedical Engineering of Ministry of Education, Department of Biomedical Engineering, College of Biomedical Engineering & Instrument Science, Zhejiang University, Hangzhou, Zhejiang, China
| | - Hongxi Zhang
- Department of Radiology, Children's Hospital, Zhejiang University School of Medicine, National Clinical Research Center for Child Health, Hangzhou, Zhejiang, China
| | - Dan Wu
- Key Laboratory for Biomedical Engineering of Ministry of Education, Department of Biomedical Engineering, College of Biomedical Engineering & Instrument Science, Zhejiang University, Hangzhou, Zhejiang, China
- Department of Radiology, Children's Hospital, Zhejiang University School of Medicine, National Clinical Research Center for Child Health, Hangzhou, Zhejiang, China
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Geng X, Chan PH, Lam HS, Chu WC, Wong PC. Brain templates for Chinese babies from newborn to three months of age. Neuroimage 2024; 289:120536. [PMID: 38346529 DOI: 10.1016/j.neuroimage.2024.120536] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/06/2023] [Revised: 01/20/2024] [Accepted: 02/08/2024] [Indexed: 02/22/2024] Open
Abstract
The infant brain develops rapidly and this area of research has great clinical implications. Neurodevelopmental disorders such as autism and developmental delay have their origins, potentially, in abnormal early brain maturation. Searching for potential early neural markers requires a priori knowledge about infant brain development and anatomy. One of the most common methods of characterizing brain features requires normalization of individual images into a standard stereotactic space and conduct of group-based analyses in this space. A population representative brain template is critical for these population-based studies. Little research is available on constructing brain templates for typical developing Chinese infants. In the present work, a total of 120 babies from 5 to 89 days of age were included with high resolution structural magnetic resonance imaging scans. T1-weighted and T2-weighted templates were constructed using an unbiased registration approach for babies from newborn to 3 months of age. Age-specific templates were also estimated for babies aged at 0, 1, 2 and 3 months old. Then we conducted a series of evaluations and statistical analyses over whole tissue segmentations and brain parcellations. Compared to the use of population mismatched templates, using our established templates resulted in lower deformation energy to transform individual images into the template space and produced a smaller registration error, i.e., smaller standard deviation of the registered images. Significant volumetric growth was observed across total brain tissues and most of the brain regions within the first three months of age. The total brain tissues exhibited larger volumes in baby boys compared to baby girls. To the best of our knowledge, this is the first study focusing on the construction of Chinese infant brain templates. These templates can be used for investigating birth related conditions such as preterm birth, detecting neural biomarkers for neurological and neurodevelopmental disorders in Chinese populations, and exploring genetic and cultural effects on the brain.
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Affiliation(s)
- Xiujuan Geng
- Brain and Mind Institute The Chinese University of Hong Kong, Shatin, NT, Hong Kong SAR, China; Department of Linguistics and Modern Languages, The Chinese University of Hong Kong, Shatin, NT, Hong Kong SAR, China
| | - Peggy Hy Chan
- Department of Paediatrics, Faculty of Medicine, The Chinese University of Hong Kong, Shatin, NT, Hong Kong SAR, China
| | - Hugh Simon Lam
- Department of Paediatrics, Faculty of Medicine, The Chinese University of Hong Kong, Shatin, NT, Hong Kong SAR, China
| | - Winnie Cw Chu
- Department of Imaging and Interventional Radiology, Faculty of Medicine, The Chinese University of Hong Kong, Shatin, NT, Hong Kong SAR, China.
| | - Patrick Cm Wong
- Brain and Mind Institute The Chinese University of Hong Kong, Shatin, NT, Hong Kong SAR, China; Department of Linguistics and Modern Languages, The Chinese University of Hong Kong, Shatin, NT, Hong Kong SAR, China.
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Otani S, Fushimi Y, Iwanaga K, Tomotaki S, Shimotsuma T, Nakajima S, Sakata A, Okuchi S, Hinoda T, Wicaksono KP, Takita J, Kawai M, Nakamoto Y. Evaluation of deep gray matter for early brain development using quantitative susceptibility mapping. Eur Radiol 2022; 33:4488-4499. [PMID: 36418626 DOI: 10.1007/s00330-022-09267-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/21/2022] [Revised: 08/31/2022] [Accepted: 10/23/2022] [Indexed: 11/25/2022]
Abstract
OBJECTIVES To evaluate susceptibility values associated with iron accumulation in the deep gray matter during postnatal development and to compare magnetic susceptibility between patients with normal and delayed development. METHODS Patients with postmenstrual age (PMA) ≤ 1000 days underwent MR scans between August 2015 and April 2020 at our hospital. Quantitative susceptibility mapping (QSM) was performed, and magnetic susceptibility was measured using three-dimensional volumes of interest (VOIs) for the caudate nucleus (CN), globus pallidus (GP), putamen (PT), and ventrolateral thalamic nucleus (VL). Cross-sectional analysis was performed for 99 patients with normal development and 39 patients with delayed development. Longitudinal analysis was also performed to interpret changes over time in 13 patients with normal development. Correlations between magnetic susceptibility in VOIs and PMA or chronological age (CA) were assessed. RESULTS Susceptibility values for CN, GP, PT, and VL showed positive moderate correlations with both PMA (ρ = 0.45, 0.69, 0.62, and 0.33, respectively) and CA (ρ = 0.53, 0.69, 0.66, and 0.39, respectively). The slope of the correlation between susceptibility values and age was highest in the GP among the four gray matter areas. Susceptibility values for the CN, GP, PT, and VL were higher with normal development than with delayed development at early postnatal age, although a significant difference was only observed for the CN. Susceptibility values also increased with age in the longitudinal analysis. CONCLUSIONS Magnetic susceptibility values in deep gray matter increased with age ≤ 1000 days. The normal development group showed higher susceptibility values than the delayed development group at early postnatal age (PMA ≤ 285 days). KEY POINTS • Magnetic susceptibilities in deep gray matter nuclei increased with age (postmenstrual age ≤ 1000 days) in a large number of pediatric patients. • The normal development group showed higher susceptibility values than the delayed development group in the basal ganglia and ventrolateral thalamic nucleus at early postnatal age (PMA ≤ 285 days).
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Affiliation(s)
- Sayo Otani
- Department of Diagnostic Imaging and Nuclear Medicine, Graduate School of Medicine, Kyoto University, 54 Shogoin Kawahara-cho, Sakyo-ku, Kyoto, 606-8507, Japan
| | - Yasutaka Fushimi
- Department of Diagnostic Imaging and Nuclear Medicine, Graduate School of Medicine, Kyoto University, 54 Shogoin Kawahara-cho, Sakyo-ku, Kyoto, 606-8507, Japan.
| | - Kogoro Iwanaga
- Department of Pediatrics, Graduate School of Medicine, Kyoto University, Kyoto, 606-8507, Japan
| | - Seiichi Tomotaki
- Department of Pediatrics, Graduate School of Medicine, Kyoto University, Kyoto, 606-8507, Japan
| | - Taiki Shimotsuma
- Department of Pediatrics, Graduate School of Medicine, Kyoto University, Kyoto, 606-8507, Japan
| | - Satoshi Nakajima
- Department of Diagnostic Imaging and Nuclear Medicine, Graduate School of Medicine, Kyoto University, 54 Shogoin Kawahara-cho, Sakyo-ku, Kyoto, 606-8507, Japan
| | - Akihiko Sakata
- Department of Diagnostic Imaging and Nuclear Medicine, Graduate School of Medicine, Kyoto University, 54 Shogoin Kawahara-cho, Sakyo-ku, Kyoto, 606-8507, Japan
| | - Sachi Okuchi
- Department of Diagnostic Imaging and Nuclear Medicine, Graduate School of Medicine, Kyoto University, 54 Shogoin Kawahara-cho, Sakyo-ku, Kyoto, 606-8507, Japan
| | - Takuya Hinoda
- Department of Diagnostic Imaging and Nuclear Medicine, Graduate School of Medicine, Kyoto University, 54 Shogoin Kawahara-cho, Sakyo-ku, Kyoto, 606-8507, Japan
| | - Krishna Pandu Wicaksono
- Department of Diagnostic Imaging and Nuclear Medicine, Graduate School of Medicine, Kyoto University, 54 Shogoin Kawahara-cho, Sakyo-ku, Kyoto, 606-8507, Japan
| | - Junko Takita
- Department of Pediatrics, Graduate School of Medicine, Kyoto University, Kyoto, 606-8507, Japan
| | - Masahiko Kawai
- Department of Pediatrics, Graduate School of Medicine, Kyoto University, Kyoto, 606-8507, Japan
| | - Yuji Nakamoto
- Department of Diagnostic Imaging and Nuclear Medicine, Graduate School of Medicine, Kyoto University, 54 Shogoin Kawahara-cho, Sakyo-ku, Kyoto, 606-8507, Japan
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Jia X, Wang W, Liang J, Ma X, Chen W, Wu D, Lai C, Zhang Y. Risk stratification of abdominal tumors in children with amide proton transfer imaging. Eur Radiol 2022; 32:2158-2167. [PMID: 35031842 DOI: 10.1007/s00330-021-08376-w] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/09/2021] [Revised: 09/01/2021] [Accepted: 09/30/2021] [Indexed: 11/25/2022]
Abstract
OBJECTIVES To evaluate the potential of molecular amide proton transfer (APT) MRI for predicting the risk group of abdominal tumors in children, and compare it with quantitative T1 and T2 mapping. METHODS This prospective study enrolled 133 untreated pediatric patients with suspected abdominal tumors from February 2019 to September 2020. APT-weighted (APTw) imaging and quantitative relaxation time mapping sequences were executed for each subject. The region of interest (ROI) was generated with automatic artifact detection and ROI-shrinking algorithms, within which the APTw, T1, and T2 indices were calculated and compared between different risk groups. The prediction performance of different imaging parameters was assessed with the receiver operating characteristics (ROC) analysis and Student's t-test. RESULTS Fifty-seven patients were included in the final analysis, including 24 neuroblastomas (NB), 18 Wilms' tumors (WT), and 15 hepatoblastomas (HB). The APTw signal was significantly (p < .001) higher in patients with high-risk NB than those with low-risk NB, while the difference between patients with low-risk and high-risk WT (p = .69) or HB (p = .35) was not statistically significant. The associated areas under the curve (AUC) for APT to differentiate low-risk and high-risk NB, WT, and HB were 0.93, 0.58, and 0.71, respectively. The quantitative T1 and T2 values generated AUCs of 0.61-0.70 for the risk stratification of abdominal tumors. CONCLUSIONS APT MRI is a potential imaging biomarker for stratifying the risk group of pediatric neuroblastoma in the abdomen preoperatively and provides added value to structural MRI. KEY POINTS • Amide proton transfer (APT) imaging showed significantly (p < .001) higher values in pediatric patients with high-risk neuroblastoma than those with low-risk neuroblastoma, but did not demonstrate a significant difference in patients with Wilms' tumor (p = .69) or hepatoblastoma (p = .35). • The associated areas under the curve (AUC) for APT to differentiate low-risk and high-risk neuroblastoma, Wilms' tumor, and hepatoblastoma were 0.93, 0.58, and 0.71, respectively. • The quantitative T1 and T2 indices generated AUCs of 0.61-0.70 for dichotomizing the risk group of abdominal tumors.
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Affiliation(s)
- Xuan Jia
- Department of Radiology, Children's Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China
| | - Wenqi Wang
- Key Laboratory for Biomedical Engineering of Ministry of Education, Department of Biomedical Engineering, College of Biomedical Engineering & Instrument Science, Zhejiang University, Hangzhou, Zhejiang, China
| | - Jiawei Liang
- Department of Radiology, Children's Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China
| | - Xiaohui Ma
- Department of Radiology, Children's Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China
| | | | - Dan Wu
- Key Laboratory for Biomedical Engineering of Ministry of Education, Department of Biomedical Engineering, College of Biomedical Engineering & Instrument Science, Zhejiang University, Hangzhou, Zhejiang, China
| | - Can Lai
- Department of Radiology, Children's Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China
| | - Yi Zhang
- Key Laboratory for Biomedical Engineering of Ministry of Education, Department of Biomedical Engineering, College of Biomedical Engineering & Instrument Science, Zhejiang University, Hangzhou, Zhejiang, China.
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Dubois J, Alison M, Counsell SJ, Hertz‐Pannier L, Hüppi PS, Benders MJ. MRI of the Neonatal Brain: A Review of Methodological Challenges and Neuroscientific Advances. J Magn Reson Imaging 2021; 53:1318-1343. [PMID: 32420684 PMCID: PMC8247362 DOI: 10.1002/jmri.27192] [Citation(s) in RCA: 67] [Impact Index Per Article: 22.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/23/2019] [Revised: 04/24/2020] [Accepted: 04/24/2020] [Indexed: 01/04/2023] Open
Abstract
In recent years, exploration of the developing brain has become a major focus for researchers and clinicians in an attempt to understand what allows children to acquire amazing and unique abilities, as well as the impact of early disruptions (eg, prematurity, neonatal insults) that can lead to a wide range of neurodevelopmental disorders. Noninvasive neuroimaging methods such as MRI are essential to establish links between the brain and behavioral changes in newborns and infants. In this review article, we aim to highlight recent and representative studies using the various techniques available: anatomical MRI, quantitative MRI (relaxometry, diffusion MRI), multiparametric approaches, and functional MRI. Today, protocols use 1.5 or 3T MRI scanners, and specialized methodologies have been put in place for data acquisition and processing to address the methodological challenges specific to this population, such as sensitivity to motion. MR sequences must be adapted to the brains of newborns and infants to obtain relevant good soft-tissue contrast, given the small size of the cerebral structures and the incomplete maturation of tissues. The use of age-specific image postprocessing tools is also essential, as signal and contrast differ from the adult brain. Appropriate methodologies then make it possible to explore multiple neurodevelopmental mechanisms in a precise way, and assess changes with age or differences between groups of subjects, particularly through large-scale projects. Although MRI measurements only indirectly reflect the complex series of dynamic processes observed throughout development at the molecular and cellular levels, this technique can provide information on brain morphology, structural connectivity, microstructural properties of gray and white matter, and on the functional architecture. Finally, MRI measures related to clinical, behavioral, and electrophysiological markers have a key role to play from a diagnostic and prognostic perspective in the implementation of early interventions to avoid long-term disabilities in children. EVIDENCE LEVEL: 2 TECHNICAL EFFICACY STAGE: 1.
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Affiliation(s)
- Jessica Dubois
- University of ParisNeuroDiderot, INSERM,ParisFrance
- UNIACT, NeuroSpin, CEA; Paris‐Saclay UniversityGif‐sur‐YvetteFrance
| | - Marianne Alison
- University of ParisNeuroDiderot, INSERM,ParisFrance
- Department of Pediatric RadiologyAPHP, Robert‐Debré HospitalParisFrance
| | - Serena J. Counsell
- Centre for the Developing BrainSchool of Biomedical Engineering & Imaging Sciences, King's College LondonLondonUK
| | - Lucie Hertz‐Pannier
- University of ParisNeuroDiderot, INSERM,ParisFrance
- UNIACT, NeuroSpin, CEA; Paris‐Saclay UniversityGif‐sur‐YvetteFrance
| | - Petra S. Hüppi
- Division of Development and Growth, Department of Woman, Child and AdolescentUniversity Hospitals of GenevaGenevaSwitzerland
| | - Manon J.N.L. Benders
- Department of NeonatologyUniversity Medical Center Utrecht, Utrecht UniversityUtrechtthe Netherlands
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