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Payette K, Uus AU, Kollstad E, Aviles Verdera J, Gallo D, Hall M, Hajnal JV, Rutherford MA, Story L, Hutter J. T 2* relaxometry of fetal brain structures using low-field (0.55T) MRI. Magn Reson Med 2025; 93:1942-1953. [PMID: 39737688 PMCID: PMC11893027 DOI: 10.1002/mrm.30409] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/30/2024] [Revised: 11/28/2024] [Accepted: 12/05/2024] [Indexed: 01/01/2025]
Abstract
PURPOSE Human brain development during gestation is complex, as both structure and function are rapidly forming. Structural imaging methods using MRI are well developed to explore these changes, but functional imaging tools are lacking. Low-field MRI is a promising modality to bridge this gap. The longer intrinsic T2* values at low field strengths increase the dynamic range and enable the quantification of individual brain regions with low T2* values, such as deep gray matter. This study investigates regional brain T2* quantification throughout the second half of gestation on low-field 0.55T MRI. METHODS Dynamic multi-echo gradient-echo sequences were acquired in 135 cases at 0.55 T between 20 and 40 weeks' gestation. Automatic high-resolution reconstruction and segmentation tools were developed, resulting in T2* values of seven individual anatomical brain structures for each subject. These regional brain T2* values were analyzed throughout gestation. RESULTS All regional fetal brain T2* values decreased throughout gestation (p < 0.01). Each anatomical brain structure had varying ranges and decay rates, with the cerebellum and white matter displaying the highest (nonfluid structure) values, with the maximum values between 350 and 400 ms at about 20 weeks. The brainstem and deep gray matter had the lowest range of T2* values, reaching values of 250 ms early in gestation. The matched volumetric assessment of the different structures demonstrated expected growth, matching current literature. CONCLUSION Low-field MRI allows for a detailed, regional T2* analysis of the fetal brain, with more inclusive norms to be developed due to its wider bore.
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Affiliation(s)
- Kelly Payette
- Research Department of Early Life ImagingSchool of Biomedical Engineering and Imaging Sciences, King's College LondonLondonUK
- Biomedical Engineering DepartmentSchool of Biomedical Engineering and Imaging Sciences, King's College LondonLondonUK
| | - Alena U. Uus
- Research Department of Early Life ImagingSchool of Biomedical Engineering and Imaging Sciences, King's College LondonLondonUK
- Biomedical Engineering DepartmentSchool of Biomedical Engineering and Imaging Sciences, King's College LondonLondonUK
| | - Ella Kollstad
- Department of Women & Children's HealthKing's College LondonLondonUK
- Brighton and Sussex Medical SchoolBrightonUK
| | - Jordina Aviles Verdera
- Research Department of Early Life ImagingSchool of Biomedical Engineering and Imaging Sciences, King's College LondonLondonUK
- Biomedical Engineering DepartmentSchool of Biomedical Engineering and Imaging Sciences, King's College LondonLondonUK
| | - Dario Gallo
- Research Department of Early Life ImagingSchool of Biomedical Engineering and Imaging Sciences, King's College LondonLondonUK
- Guys and St. Thomas' NHS Foundation TrustLondonUK
| | - Megan Hall
- Research Department of Early Life ImagingSchool of Biomedical Engineering and Imaging Sciences, King's College LondonLondonUK
- Biomedical Engineering DepartmentSchool of Biomedical Engineering and Imaging Sciences, King's College LondonLondonUK
- Department of Women & Children's HealthKing's College LondonLondonUK
| | - Joseph V. Hajnal
- Research Department of Early Life ImagingSchool of Biomedical Engineering and Imaging Sciences, King's College LondonLondonUK
- Biomedical Engineering DepartmentSchool of Biomedical Engineering and Imaging Sciences, King's College LondonLondonUK
| | - Mary A. Rutherford
- Research Department of Early Life ImagingSchool of Biomedical Engineering and Imaging Sciences, King's College LondonLondonUK
| | - Lisa Story
- Research Department of Early Life ImagingSchool of Biomedical Engineering and Imaging Sciences, King's College LondonLondonUK
- Biomedical Engineering DepartmentSchool of Biomedical Engineering and Imaging Sciences, King's College LondonLondonUK
- Department of Women & Children's HealthKing's College LondonLondonUK
| | - Jana Hutter
- Research Department of Early Life ImagingSchool of Biomedical Engineering and Imaging Sciences, King's College LondonLondonUK
- Biomedical Engineering DepartmentSchool of Biomedical Engineering and Imaging Sciences, King's College LondonLondonUK
- Smart Imaging Lab, Radiological InstituteUniversity Hospital ErlangenErlangenGermany
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Utkur M, Timms L, Kurugol S, Afacan O. Ultrafast and robust T 2 mapping using optimized single-shot multi-echo planar imaging with alternating blips. Magn Reson Med 2025. [PMID: 40294097 DOI: 10.1002/mrm.30516] [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: 11/19/2024] [Revised: 02/15/2025] [Accepted: 03/12/2025] [Indexed: 04/30/2025]
Abstract
PURPOSE To develop a rapid, motion-robustT 2 $$ {\mathrm{T}}_2 $$ mapping technique suitable for clinical use across the body, including traditionally challenging, motion-prone patient populations or body parts. METHODS A novel single-shot multi-echo spin-echo EPI sequence with alternating phase encoding direction on each echo was implemented. This sequence acquires multiple echoes to measureT 2 $$ {\mathrm{T}}_2 $$ from a single RF excitation. The alternating phase encoding gradient polarity enables the correction of geometric distortions in EPI using post-processing software. Stimulated echoes were removed by optimizing spoiler gradients. Diffusion MRI can also be achieved by incorporating diffusion-encoding gradients. RESULTS Phantom experiments showed no significant difference between measured and referenceT 2 $$ {\mathrm{T}}_2 $$ values, indicating high precision and repeatability. In vivo, brainT 2 $$ {\mathrm{T}}_2 $$ maps exhibited similar anatomical detail and tissue contrast as a reference sequence, withT 2 $$ {\mathrm{T}}_2 $$ values of 70.0 ± $$ \kern0.5em \pm \kern0.5em $$ 4.0 ms for gray matter, 56.8 ± $$ \kern0.5em \pm \kern0.5em $$ 3.4 ms for the white matter at a magnetic field strength of 3 Tesla. High-quality diffusion-weighted images with minimal distortion were generated, even at high b-values.T 2 $$ {\mathrm{T}}_2 $$ mapping results from the kidney and fetal brain showcased the method's applicability across different anatomical regions and patient populations. CONCLUSION The single-shot multi-echo EPI sequence provided a basis for rapid, accurateT 2 $$ {\mathrm{T}}_2 $$ relaxation mapping by correcting distortion and mitigating motion artifacts. This sequence enhances the clinical feasibility of quantitativeT 2 $$ {\mathrm{T}}_2 $$ mapping across diverse patient populations and body areas.
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Affiliation(s)
- Mustafa Utkur
- Department of Radiology, Boston Children's Hospital and Harvard Medical School, Boston, Massachusetts
| | - Liam Timms
- Department of Radiology, Boston Children's Hospital and Harvard Medical School, Boston, Massachusetts
| | - Sila Kurugol
- Department of Radiology, Boston Children's Hospital and Harvard Medical School, Boston, Massachusetts
| | - Onur Afacan
- Department of Radiology, Boston Children's Hospital and Harvard Medical School, Boston, Massachusetts
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Lajous H, Le Boeuf Fló A, Gordaliza PM, Esteban O, Marques F, Dunet V, Koob M, Bach Cuadra M. A dataset of synthetic, maturation-informed magnetic resonance images of the human fetal brain. Sci Data 2025; 12:602. [PMID: 40210647 PMCID: PMC11986055 DOI: 10.1038/s41597-025-04926-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/10/2024] [Accepted: 03/31/2025] [Indexed: 04/12/2025] Open
Abstract
Magnetic resonance imaging (MRI) is a powerful modality for investigating abnormal developmental patterns in utero. However, since it is not the first-line diagnostic tool in this sensitive population, data remain scarce and heterogeneous across scanners and hospitals. To address this, we present a novel dataset of synthetic images representative of real fetal brain MRI. Our dataset comprises 594 two-dimensional, low-resolution series of T2-weighted images corresponding to 78 developing human fetal brains between 20.0 and 34.8 weeks of gestational age. Data are generated using a new version of the Fetal Brain MR Acquisition Numerical phantom (FaBiAN) to account for local white matter heterogeneities throughout maturation. Both healthy and pathological anatomies are simulated with standard clinical settings. Two independent radiologists qualitatively assessed the realism of the simulated images. A quantitative analysis confirms an enhanced fidelity compared to the original version of the software, with further validation through its applicability to fetal brain tissue segmentation. The cohort is publicly available to support the continuous endeavor of developing advanced post-processing methods as well as cutting-edge artificial intelligence models.
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Affiliation(s)
- Hélène Lajous
- Department of Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland.
- CIBM Center for Biomedical Imaging, Lausanne, Switzerland.
| | - Andrés Le Boeuf Fló
- Department of Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
- CIBM Center for Biomedical Imaging, Lausanne, Switzerland
- Department of Signal Theory and Communications, Universitat Politécnica de Catalunya, BarcelonaTech, Barcelona, Spain
| | - Pedro M Gordaliza
- Department of Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
- CIBM Center for Biomedical Imaging, Lausanne, Switzerland
| | - Oscar Esteban
- Department of Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
| | - Ferran Marques
- Department of Signal Theory and Communications, Universitat Politécnica de Catalunya, BarcelonaTech, Barcelona, Spain
| | - Vincent Dunet
- Department of Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
| | - Mériam Koob
- Department of Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
| | - Meritxell Bach Cuadra
- Department of Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
- CIBM Center for Biomedical Imaging, Lausanne, Switzerland
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Cromb D, Steinweg J, Aviles Verdera J, van Poppel MP, Bonthrone AF, Lloyd DF, Pushparajah K, Simpson J, Razavi R, Rutherford M, Counsell SJ, Hutter J. T2*-Relaxometry MRI to Assess Third Trimester Placental and Fetal Brain Oxygenation and Placental Characteristics in Healthy Fetuses and Fetuses With Congenital Heart Disease. J Magn Reson Imaging 2025; 61:1246-1255. [PMID: 38994701 PMCID: PMC11803691 DOI: 10.1002/jmri.29498] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/05/2024] [Revised: 06/06/2024] [Accepted: 06/07/2024] [Indexed: 07/13/2024] Open
Abstract
BACKGROUND Congenital heart disease (CHD) has been linked to impaired placental and fetal brain development. Assessing the placenta and fetal brain in parallel may help further our understanding of the relationship between development of these organs. HYPOTHESIS 1) Placental and fetal brain oxygenation are correlated, 2) oxygenation in these organs is reduced in CHD compared to healthy controls, and 3) placental structure is altered in CHD. STUDY TYPE Retrospective case-control. POPULATION Fifty-one human fetuses with CHD (32 male; median [IQR] gestational age [GA] = 32.0 [30.9-32.9] weeks) and 30 from uncomplicated pregnancies with normal birth outcomes (18 male; median [IQR] GA = 34.5 [31.9-36.7] weeks). FIELD STRENGTH/SEQUENCE 1.5 T single-shot multi-echo-gradient-echo echo-planar imaging. ASSESSMENT Masking was performed using an automated nnUnet model. Mean brain and placental T2* and quantitative measures of placental texture, volume, and morphology were calculated. STATISTICAL TESTS Spearman's correlation coefficient for determining the association between brain and placental T2*, and between brain and placental characteristics with GA. P-values for comparing brain T2*, placenta T2*, and placental characteristics between groups derived from ANOVA. Significance level P < 0.05. RESULTS There was a significant positive association between placental and fetal brain T2* (⍴ = 0.46). Placental and fetal brain T2* showed a significant negative correlation with GA (placental T2* ⍴ = -0.65; fetal brain T2* ⍴ = -0.32). Both placental and fetal brain T2* values were significantly reduced in CHD, after adjusting for GA (placental T2*: control = 97 [±24] msec, CHD = 83 [±23] msec; brain T2*: control = 218 [±26] msec, CHD = 202 [±25] msec). Placental texture and morphology were also significantly altered in CHD (Texture: control = 0.84 [0.83-0.87], CHD = 0.80 [0.78-0.84]; Morphology: control = 9.9 [±2.2], CHD = 10.8 [±2.0]). For all fetuses, there was a significant positive association between placental T2* and placental texture (⍴ = 0.46). CONCLUSION Placental and fetal brain T2* values are associated in healthy fetuses and those with CHD. Placental and fetal brain oxygenation are reduced in CHD. Placental appearance is significantly altered in CHD and shows associations with placental oxygenation, suggesting altered placental development and function may be related. EVIDENCE LEVEL 3 TECHNICAL EFFICACY: Stage 3.
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Affiliation(s)
- Daniel Cromb
- Centre for the Developing BrainSchool of Biomedical and Engineering Sciences, King's College LondonLondonUK
| | - Johannes Steinweg
- Department of Cardiovascular ImagingSchool of Biomedical Engineering & Imaging Science, King's College LondonLondonUK
| | - Jordina Aviles Verdera
- Centre for the Developing BrainSchool of Biomedical and Engineering Sciences, King's College LondonLondonUK
- Biomedical Engineering Department, School of Biomedical Engineering and Imaging SciencesKing's College LondonLondonUK
| | - Milou P.M. van Poppel
- Department of Cardiovascular ImagingSchool of Biomedical Engineering & Imaging Science, King's College LondonLondonUK
| | - Alexandra F. Bonthrone
- Centre for the Developing BrainSchool of Biomedical and Engineering Sciences, King's College LondonLondonUK
| | - David F.A. Lloyd
- Centre for the Developing BrainSchool of Biomedical and Engineering Sciences, King's College LondonLondonUK
- Department of Cardiovascular ImagingSchool of Biomedical Engineering & Imaging Science, King's College LondonLondonUK
| | - Kuberan Pushparajah
- Department of Cardiovascular ImagingSchool of Biomedical Engineering & Imaging Science, King's College LondonLondonUK
| | - John Simpson
- Department of Cardiovascular ImagingSchool of Biomedical Engineering & Imaging Science, King's College LondonLondonUK
| | - Reza Razavi
- Biomedical Engineering Department, School of Biomedical Engineering and Imaging SciencesKing's College LondonLondonUK
| | - Mary Rutherford
- Centre for the Developing BrainSchool of Biomedical and Engineering Sciences, King's College LondonLondonUK
- MRC Centre for Neurodevelopmental DisordersKing's College LondonLondonUK
| | - Serena J. Counsell
- Centre for the Developing BrainSchool of Biomedical and Engineering Sciences, King's College LondonLondonUK
| | - Jana Hutter
- Centre for the Developing BrainSchool of Biomedical and Engineering Sciences, King's College LondonLondonUK
- Biomedical Engineering Department, School of Biomedical Engineering and Imaging SciencesKing's College LondonLondonUK
- Smart Imaging Lab, Radiological InstituteUniversity Hospital ErlangenErlangenGermany
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Hall M, Uus A, Kollstad E, Shangaris P, Sankaran S, Rutherford M, Tribe RM, Shennan A, Hutter J, Story L. Assessment of the thymus in fetuses prior to spontaneous preterm birth using functional MRI. Early Hum Dev 2025; 201:106188. [PMID: 39813902 DOI: 10.1016/j.earlhumdev.2024.106188] [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: 10/21/2024] [Revised: 12/28/2024] [Accepted: 12/29/2024] [Indexed: 01/18/2025]
Abstract
OBJECTIVES The aim of this study was to utilise T2* relaxometry (an indirect method of quantifying tissue oxygenation) to assess the fetal thymus in uncomplicated pregnancies throughout gestation and in a cohort of fetuses that subsequently deliver very preterm. METHODS A control group of participants with low-risk pregnancies were recruited and retrospectively excluded if they developed any pregnancy related complications after scanning. Participants were recruited who were deemed to be at very high risk of delivery prior to 32 weeks' gestation and retrospectively excluded if they did not deliver prior to this gestation. All participants underwent a fetal MRI scan on a 3 T system incorporating the fetal thorax. T2 and T2* data were aligned and the mean T2* of the thymus tissue determined. RESULTS Mean thymus T2* decreased with gestation in control fetuses (n = 49). In fetuses who went on to deliver prior to 32 weeks' gestation (n = 15), thymus volume was reduced as was mean T2* (p ≤ 0.001) as compared to controls. This finding persisted in a subgroup analysis of participants with PPROM (p = 0.002), although not in those with intact membranes (p = 0.067). CONCLUSION These data demonstrates both a likely reduction in perfusion of the thymuses prior to extreme preterm birth, and also the potential for advanced MRI techniques to better interrogate the fetal immune changes prior to preterm birth in vivo.
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Affiliation(s)
- Megan Hall
- Department of Women and Children's Health, St Thomas' Hospital, King's College London, London, UK; Department of Perinatal Imaging, St Thomas' Hospital, King's College London, London, UK.
| | - Alena Uus
- Department of Perinatal Imaging, St Thomas' Hospital, King's College London, London, UK
| | - Ella Kollstad
- Department of Women and Children's Health, St Thomas' Hospital, King's College London, London, UK
| | - Panicos Shangaris
- Department of Women and Children's Health, St Thomas' Hospital, King's College London, London, UK; Peter Gorer Department of Immunobiology, School of Immunology and Microbial Sciences, King's College London, UK; Fetal Medicine Research Institute, King's College Hospital, London, UK
| | - Srividhya Sankaran
- Department of Obstetrics and Gynaecology, St Thomas' Hospital, Guy's and St Thomas' NHS Foundation Trust, London, UK
| | - Mary Rutherford
- Department of Perinatal Imaging, St Thomas' Hospital, King's College London, London, UK
| | - Rachel M Tribe
- Department of Women and Children's Health, St Thomas' Hospital, King's College London, London, UK
| | - Andrew Shennan
- Department of Women and Children's Health, St Thomas' Hospital, King's College London, London, UK
| | - Jana Hutter
- Department of Perinatal Imaging, St Thomas' Hospital, King's College London, London, UK
| | - Lisa Story
- Department of Women and Children's Health, St Thomas' Hospital, King's College London, London, UK; Department of Perinatal Imaging, St Thomas' Hospital, King's College London, London, UK
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Ji L, Duffy M, Chen B, Majbri A, Trentacosta CJ, Thomason M. Whole Brain MRI Assessment of Age and Sex-Related R2* Changes in the Human Fetal Brain. Hum Brain Mapp 2025; 46:e70073. [PMID: 39844450 PMCID: PMC11754245 DOI: 10.1002/hbm.70073] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/29/2024] [Revised: 10/16/2024] [Accepted: 10/28/2024] [Indexed: 01/24/2025] Open
Abstract
Iron in the brain is essential to neurodevelopmental processes, as it supports neural functions, including processes of oxygen delivery, electron transport, and enzymatic activity. However, the development of brain iron before birth is scarcely understood. By estimating R2* (1/T2*) relaxometry from a sizable sample of fetal multiecho echo-planar imaging (EPI) scans, which is the standard sequence for functional magnetic resonance imaging (fMRI), across gestation, this study investigates age and sex-related changes in iron, across regions and tissue segments. Our findings reveal that brain R2* levels significantly increase throughout gestation spanning many different regions, except the frontal lobe. Furthermore, females exhibit a faster rate of R2* increase compared to males, in both gray matter and white matter. This sex effect is particularly notable within the left insula. This work represents the first MRI examination of iron accumulation and sex differences in developing fetal brains. This is also the first study to establish R2* estimation methodology in fetal multiecho functional MRI.
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Affiliation(s)
- Lanxin Ji
- Department of Child and Adolescent PsychiatryNew York University School of MedicineNew YorkNew YorkUSA
| | - Mark Duffy
- Department of Child and Adolescent PsychiatryNew York University School of MedicineNew YorkNew YorkUSA
| | - Bosi Chen
- Department of Child and Adolescent PsychiatryNew York University School of MedicineNew YorkNew YorkUSA
| | - Amyn Majbri
- Department of Child and Adolescent PsychiatryNew York University School of MedicineNew YorkNew YorkUSA
| | | | - Moriah Thomason
- Department of Child and Adolescent PsychiatryNew York University School of MedicineNew YorkNew YorkUSA
- Department of Population HealthNew York University School of MedicineNew YorkNew YorkUSA
- Neuroscience InstituteNew York University School of MedicineNew YorkNew YorkUSA
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Wang X, Fan H, Tan Z, Vasylechko S, Yang E, Didier R, Afacan O, Uecker M, Warfield SK, Gholipour A. Rapid, High-resolution and Distortion-free R 2 * Mapping of Fetal Brain using Multi-echo Radial FLASH and Model-based Reconstruction. ARXIV 2025:arXiv:2501.00256v2. [PMID: 39801623 PMCID: PMC11722525] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 01/23/2025]
Abstract
Purpose To develop a rapid, high-resolution and distortion-free quantitativeR 2 * mapping technique for fetal brain at 3 T. Methods A 2D multi-echo radial FLASH sequence with blip gradients is adapted for fetal brain data acquisition during maternal free breathing at 3 T. A calibrationless model-based reconstruction with sparsity constraints is developed to jointly estimate water, fat,R 2 * andB 0 field maps directly from the acquired k-space data. Validations have been performed on numerical and NIST phantoms and five fetal subjects ranging from 27 weeks to 36 weeks gestation age. Results Both numerical and experimental phantom studies confirm good accuracy and precision of the proposed method. In fetal studies, both the parallel imaging compressed sensing (PICS) technique with a Graph Cut algorithm and the model-based approach proved effective for parameter quantification, with the latter providing enhanced image details. Compared to commonly used multi-echo EPI approaches, the proposed radial technique shows improved spatial resolution (1.1 × 1.1 × 3 mm3 vs. 2-3 × 2-3 × 3 mm3) and reduced distortion. QuantitativeR 2 * results confirm good agreement between the two acquisition strategies. Additionally, high-resolution, distortion-freeR 2 * -weighted images can be synthesized, offering complementary information to HASTE. Conclusion This work demonstrates the feasibility of radial acquisition for motion-robust quantitativeR 2 * mapping of the fetal brain. This proposed multi-echo radial FLASH, combined with calibrationless model-based reconstruction, achieves accurate, distortion-free fetal brainR 2 * mapping at a nominal resolution of 1.1 × 1.1 × 3 mm3 within 2 seconds.
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Affiliation(s)
- Xiaoqing Wang
- Department of Radiology, Boston Children's Hospital, Harvard Medical School, Boston, Massachusetts, USA
| | - Hongli Fan
- Siemens Medical Solutions, Boston, Massachusetts, USA
| | - Zhengguo Tan
- Department of Radiology, University of Michigan, Ann Arbor, Michigan, USA
| | - Serge Vasylechko
- Department of Radiology, Boston Children's Hospital, Harvard Medical School, Boston, Massachusetts, USA
| | - Edward Yang
- Department of Radiology, Boston Children's Hospital, Harvard Medical School, Boston, Massachusetts, USA
| | - Ryne Didier
- Department of Radiology, Boston Children's Hospital, Harvard Medical School, Boston, Massachusetts, USA
| | - Onur Afacan
- Department of Radiology, Boston Children's Hospital, Harvard Medical School, Boston, Massachusetts, USA
| | - Martin Uecker
- Institute of Biomedical Imaging, Graz University of Technology, Graz, Austria
| | - Simon K Warfield
- Department of Radiology, Boston Children's Hospital, Harvard Medical School, Boston, Massachusetts, USA
| | - Ali Gholipour
- Department of Radiology, Boston Children's Hospital, Harvard Medical School, Boston, Massachusetts, USA
- Department of Radiological Sciences, University of California Irvine, Irvine, California, USA
- Department of Electrical Engineering and Computer Science, University of California Irvine, Irvine, California, USA
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Payette K, Uus AU, Aviles Verdera J, Hall M, Egloff A, Deprez M, Tomi-Tricot R, Hajnal JV, Rutherford MA, Story L, Hutter J. Fetal body organ T2* relaxometry at low field strength (FOREST). Med Image Anal 2025; 99:103352. [PMID: 39326224 DOI: 10.1016/j.media.2024.103352] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/23/2023] [Revised: 05/29/2024] [Accepted: 09/16/2024] [Indexed: 09/28/2024]
Abstract
Fetal Magnetic Resonance Imaging (MRI) at low field strengths is an exciting new field in both clinical and research settings. Clinical low field (0.55T) scanners are beneficial for fetal imaging due to their reduced susceptibility-induced artifacts, increased T2* values, and wider bore (widening access for the increasingly obese pregnant population). However, the lack of standard automated image processing tools such as segmentation and reconstruction hampers wider clinical use. In this study, we present the Fetal body Organ T2* RElaxometry at low field STrength (FOREST) pipeline that analyzes ten major fetal body organs. Dynamic multi-echo multi-gradient sequences were acquired and automatically reoriented to a standard plane, reconstructed into a high-resolution volume using deformable slice-to-volume reconstruction, and then automatically segmented into ten major fetal organs. We extensively validated FOREST using an inter-rater quality analysis. We then present fetal T2* body organ growth curves made from 100 control subjects from a wide gestational age range (17-40 gestational weeks) in order to investigate the relationship of T2* with gestational age. The T2* values for all organs except the stomach and spleen were found to have a relationship with gestational age (p<0.05). FOREST is robust to fetal motion, and can be used for both normal and fetuses with pathologies. Low field fetal MRI can be used to perform advanced MRI analysis, and is a viable option for clinical scanning.
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Affiliation(s)
- Kelly Payette
- Research Department of Early Life Imaging, School of Biomedical Engineering & Imaging Sciences, King's College London, London, UK; Department of Biomedical Engineering, School of Biomedical Engineering & Imaging Sciences, King's College London, London, UK.
| | - Alena U Uus
- Research Department of Early Life Imaging, School of Biomedical Engineering & Imaging Sciences, King's College London, London, UK; Department of Biomedical Engineering, School of Biomedical Engineering & Imaging Sciences, King's College London, London, UK
| | - Jordina Aviles Verdera
- Research Department of Early Life Imaging, School of Biomedical Engineering & Imaging Sciences, King's College London, London, UK; Department of Biomedical Engineering, School of Biomedical Engineering & Imaging Sciences, King's College London, London, UK
| | - Megan Hall
- Research Department of Early Life Imaging, School of Biomedical Engineering & Imaging Sciences, King's College London, London, UK; Department of Women & Children's Health, King's College London, London, UK
| | - Alexia Egloff
- Department of Women & Children's Health, King's College London, London, UK
| | - Maria Deprez
- Research Department of Early Life Imaging, School of Biomedical Engineering & Imaging Sciences, King's College London, London, UK; Department of Biomedical Engineering, School of Biomedical Engineering & Imaging Sciences, King's College London, London, UK
| | | | - Joseph V Hajnal
- Research Department of Early Life Imaging, School of Biomedical Engineering & Imaging Sciences, King's College London, London, UK; Department of Biomedical Engineering, School of Biomedical Engineering & Imaging Sciences, King's College London, London, UK
| | - Mary A Rutherford
- Research Department of Early Life Imaging, School of Biomedical Engineering & Imaging Sciences, King's College London, London, UK
| | - Lisa Story
- Research Department of Early Life Imaging, School of Biomedical Engineering & Imaging Sciences, King's College London, London, UK; Department of Women & Children's Health, King's College London, London, UK
| | - Jana Hutter
- Research Department of Early Life Imaging, School of Biomedical Engineering & Imaging Sciences, King's College London, London, UK; Department of Biomedical Engineering, School of Biomedical Engineering & Imaging Sciences, King's College London, London, UK; Smart Imaging Lab, Radiological Institute, University Hospital Erlangen, Erlangen, Germany
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9
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Chen R, Tian C, Zhu K, Ren G, Bao A, Shen Y, Li X, Zhang Y, Qiu W, Ma C, Zhang J, Wu D. Ex vivo Magnetic Resonance Imaging of the Human Fetal Brain. Dev Neurosci 2024:1-18. [PMID: 39467518 DOI: 10.1159/000542276] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/14/2023] [Accepted: 10/15/2024] [Indexed: 10/30/2024] Open
Abstract
BACKGROUND The fetal brain undergoes a dynamic process of development during gestation, marked by well-orchestrated events such as neuronal proliferation, migration, axonal outgrowth, and dendritic arborization, mainly elucidated through histological studies. Ex vivo magnetic resonance imaging (MRI) has emerged as a useful tool for 3D visualization of the developing fetal brain, serving as a complementary tool to traditional histology. SUMMARY In this review, we summarized the commonly employed ex vivo MRI techniques and their advances in fetal brain imaging, and proposed a standard protocol for postmortem fetal brain specimen collection and fixation. We then provided an overview of ex vivo MRI-based studies on the fetal brain. KEY MESSAGES According to our review, ex vivo T1- or T2-weighted structural MRI has contributed to the characterization of the anatomy of transient neuronal proliferative zones, the basal ganglia, and the cortex. Diffusion MRI-related techniques, such as diffusion tensor imaging and tractography, have helped investigate the microstructural patterns of fetal brain tissue, as well as the early emergence and development of neuronal migration pathways and white matter bundles. Ex vivo MRI findings have shown strong histological correlations, supporting the potential of MRI in evaluating the developmental events in the fetal brain. Postmortem MRI examinations have also demonstrated comparable, and in certain cases, superior performance to traditional autopsy in revealing fetal brain abnormalities. In conclusion, ex vivo fetal brain MRI is an invaluable tool that provides unique insights into the early stages of brain development.
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Affiliation(s)
- Ruike Chen
- Key Laboratory for Biomedical Engineering of Ministry of Education, Department of Biomedical Engineering, College of Biomedical Engineering & Instrument Science, Zhejiang University, Hangzhou, China,
| | - Chen Tian
- Department of Pathology, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Keqing Zhu
- National Health and Disease Human Brain Tissue Resource Center, Zhejiang University, Hangzhou, China
| | - Guoliang Ren
- National Health and Disease Human Brain Tissue Resource Center, Zhejiang University, Hangzhou, China
| | - Aimin Bao
- National Health and Disease Human Brain Tissue Resource Center, Zhejiang University, Hangzhou, China
| | - Yi Shen
- National Health and Disease Human Brain Tissue Resource Center, Zhejiang University, Hangzhou, China
| | - Xiao Li
- Biobank of Women's Hospital, School of Medicine Zhejiang University, Hangzhou, China
| | - Yaoyao Zhang
- Key Laboratory of Birth Defects and Related Diseases of Women and Children of MOE, West China Second University Hospital, Sichuan University, Chengdu, China
- Department of Obstetrics and Gynecology, West China Second University Hospital, Sichuan University, Chengdu, China
| | - Wenying Qiu
- Department of Human Anatomy, Histology and Embryology, Institute of Basic Medical Sciences, Chinese Academy of Medical Sciences, Peking Union Medical College, Beijing, China
- National Human Brain Bank for Development and Function, Beijing, China
| | - Chao Ma
- Department of Human Anatomy, Histology and Embryology, Institute of Basic Medical Sciences, Chinese Academy of Medical Sciences, Peking Union Medical College, Beijing, China
- National Human Brain Bank for Development and Function, Beijing, China
| | - Jing Zhang
- Department of Pathology, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
- National Health and Disease Human Brain Tissue Resource Center, Zhejiang University, Hangzhou, 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, China
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Bhattacharya S, Price AN, Uus A, Sousa HS, Marenzana M, Colford K, Murkin P, Lee M, Cordero-Grande L, Teixeira RPAG, Malik SJ, Deprez M. In vivo T2 measurements of the fetal brain using single-shot fast spin echo sequences. Magn Reson Med 2024; 92:715-729. [PMID: 38623934 PMCID: PMC7617281 DOI: 10.1002/mrm.30094] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/26/2023] [Revised: 02/18/2024] [Accepted: 03/08/2024] [Indexed: 04/17/2024]
Abstract
PURPOSE We propose a quantitative framework for motion-corrected T2 fetal brain measurements in vivo and validate the single-shot fast spin echo (SS-FSE) sequence to perform these measurements. METHODS Stacks of two-dimensional SS-FSE slices are acquired with different echo times (TE) and motion-corrected with slice-to-volume reconstruction (SVR). The quantitative T2 maps are obtained by a fit to a dictionary of simulated signals. The sequence is selected using simulated experiments on a numerical phantom and validated on a physical phantom scanned on a 1.5T system. In vivo quantitative T2 maps are obtained for five fetuses with gestational ages (GA) 21-35 weeks on the same 1.5T system. RESULTS The simulated experiments suggested that a TE of 400 ms combined with the clinically utilized TEs of 80 and 180 ms were most suitable for T2 measurements in the fetal brain. The validation on the physical phantom confirmed that the SS-FSE T2 measurements match the gold standard multi-echo spin echo measurements. We measured average T2s of around 200 and 280 ms in the fetal brain grey and white matter, respectively. This was slightly higher than fetal T2* and the neonatal T2 obtained from previous studies. CONCLUSION The motion-corrected SS-FSE acquisitions with varying TEs offer a promising practical framework for quantitative T2 measurements of the moving fetus.
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Affiliation(s)
- Suryava Bhattacharya
- School of Biomedical Engineering and Imaging Sciences, King’s College London, London, UK
| | - Anthony N. Price
- School of Biomedical Engineering and Imaging Sciences, King’s College London, London, UK
- Guy’s and St Thomas’ NHS Foundation Trust, London, UK
- Centre for the Developing Brain, King’s College London, London, UK
| | - Alena Uus
- School of Biomedical Engineering and Imaging Sciences, King’s College London, London, UK
- Centre for the Developing Brain, King’s College London, London, UK
| | - Helena S. Sousa
- School of Biomedical Engineering and Imaging Sciences, King’s College London, London, UK
| | | | - Kathleen Colford
- Centre for the Developing Brain, King’s College London, London, UK
| | - Peter Murkin
- Guy’s and St Thomas’ NHS Foundation Trust, London, UK
- Centre for the Developing Brain, King’s College London, London, UK
| | - Maggie Lee
- Guy’s and St Thomas’ NHS Foundation Trust, London, UK
- Centre for the Developing Brain, King’s College London, London, UK
| | - Lucilio Cordero-Grande
- Biomedical Image Technologies, ETSI Telecomunicración, Universidad Politécnica de Madrid and CIBER-BBN, Madrid, Spain
| | - Rui Pedro A. G. Teixeira
- School of Biomedical Engineering and Imaging Sciences, King’s College London, London, UK
- Centre for the Developing Brain, King’s College London, London, UK
| | - Shaihan J. Malik
- School of Biomedical Engineering and Imaging Sciences, King’s College London, London, UK
- Centre for the Developing Brain, King’s College London, London, UK
| | - Maria Deprez
- School of Biomedical Engineering and Imaging Sciences, King’s College London, London, UK
- Centre for the Developing Brain, King’s College London, London, UK
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11
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Avena-Zampieri CL, Hutter J, Uus A, Deprez M, Payette K, Hall M, Bafadhel M, Russell REK, Milan A, Rutherford M, Shennan A, Greenough A, Story L. Functional MRI assessment of the lungs in fetuses that deliver very Preterm: An MRI pilot study. Eur J Obstet Gynecol Reprod Biol 2024; 293:106-114. [PMID: 38141484 PMCID: PMC10929943 DOI: 10.1016/j.ejogrb.2023.12.015] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/09/2023] [Accepted: 12/11/2023] [Indexed: 12/25/2023]
Abstract
OBJECTIVES To compare mean pulmonary T2* values and pulmonary volumes in fetuses that subsequently spontaneously delivered before 32 weeks with a control cohort with comparable gestational ages and to assess the value of mean pulmonary T2* as a predictor of preterm birth < 32 weeks' gestation. METHODS MRI datasets scanned at similar gestational ages were selected from fetuses who spontaneously delivered < 32 weeks of gestation and a control group who subsequently delivered at term with no complications. All women underwent a fetal MRI on a 3 T MRI imaging system. Sequences included T2-weighted single shot fast spin echo and T2* sequences, using gradient echo single shot echo planar sequencing of the fetal thorax. Motion correction was performed using slice-to-volume reconstruction and T2* maps generated using in-house pipelines. Lungs were manually segmented and volumes and mean T2* values calculated for both lungs combined and left and right lung separately. Linear regression was used to compare values between the preterm and control cohorts accounting for the effects of gestation. Receiver operating curves were generated for mean T2* values and pulmonary volume as predictors of preterm birth < 32 weeks' gestation. RESULTS Datasets from twenty-eight preterm and 74 control fetuses were suitable for analysis. MRI images were taken at similar fetal gestational ages (preterm cohort (mean ± SD) 24.9 ± 3.3 and control cohort (mean ± SD) 26.5 ± 3.0). Mean gestational age at delivery was 26.4 ± 3.3 for the preterm group and 39.9 ± 1.3 for the control group. Mean pulmonary T2* values remained constant with increasing gestational age while pulmonary volumes increased. Both T2* and pulmonary volumes were lower in the preterm group than in the control group for all parameters (both combined, left, and right lung (p < 0.001 in all cases). Adjusted for gestational age, pulmonary volumes and mean T2* values were good predictors of premature delivery in fetuses < 32 weeks (area under the curve of 0.828 and 0.754 respectively). CONCLUSION These findings indicate that mean pulmonary T2* values and volumes were lower in fetuses that subsequently delivered very preterm. This may suggest potentially altered oxygenation and indicate that pulmonary morbidity associated with prematurity has an antenatal antecedent. Future work should explore these results correlating antenatal findings with long term pulmonary outcomes.
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Affiliation(s)
- Carla L Avena-Zampieri
- Department of Women and Children's Health King's College London, United Kingdom; Centre for the Developing Brain, School of Biomedical Engineering & Imaging Sciences, King's College London, United Kingdom.
| | - Jana Hutter
- Centre for the Developing Brain, School of Biomedical Engineering & Imaging Sciences, King's College London, United Kingdom
| | - Alena Uus
- Centre for the Developing Brain, School of Biomedical Engineering & Imaging Sciences, King's College London, United Kingdom; Department of Biomedical Engineering, School of Biomedical Engineering & Imaging Sciences, King's College London, United Kingdom
| | - Maria Deprez
- Centre for the Developing Brain, School of Biomedical Engineering & Imaging Sciences, King's College London, United Kingdom; Department of Biomedical Engineering, School of Biomedical Engineering & Imaging Sciences, King's College London, United Kingdom
| | - Kelly Payette
- Centre for the Developing Brain, School of Biomedical Engineering & Imaging Sciences, King's College London, United Kingdom; Department of Biomedical Engineering, School of Biomedical Engineering & Imaging Sciences, King's College London, United Kingdom
| | - Megan Hall
- Department of Women and Children's Health King's College London, United Kingdom; Centre for the Developing Brain, School of Biomedical Engineering & Imaging Sciences, King's College London, United Kingdom; Fetal Medicine Unit, Guy's and St Thomas' NHS Foundation Trust, United Kingdom
| | - Mona Bafadhel
- King's Centre for Lung Health, School of Immunology and Microbial Sciences, Faculty of Life Sciences and Medicine, King's College London, London, United Kingdom
| | - Richard E K Russell
- King's Centre for Lung Health, School of Immunology and Microbial Sciences, Faculty of Life Sciences and Medicine, King's College London, London, United Kingdom
| | - Anna Milan
- Neonatal Unit, Guy's and St Thomas' NHS Foundation Trust, United Kingdom
| | - Mary Rutherford
- Centre for the Developing Brain, School of Biomedical Engineering & Imaging Sciences, King's College London, United Kingdom
| | - Andrew Shennan
- Department of Women and Children's Health King's College London, United Kingdom
| | - Anne Greenough
- Department of Women and Children's Health King's College London, United Kingdom
| | - Lisa Story
- Department of Women and Children's Health King's College London, United Kingdom; Centre for the Developing Brain, School of Biomedical Engineering & Imaging Sciences, King's College London, United Kingdom; Fetal Medicine Unit, Guy's and St Thomas' NHS Foundation Trust, United Kingdom
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12
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Story L, Uus A, Hall M, Payette K, Bakalis S, Arichi T, Shennan A, Rutherford M, Hutter J. Functional assessment of brain development in fetuses that subsequently deliver very preterm: An MRI pilot study. Prenat Diagn 2024; 44:49-56. [PMID: 38126921 PMCID: PMC10952951 DOI: 10.1002/pd.6498] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/11/2023] [Revised: 11/14/2023] [Accepted: 12/02/2023] [Indexed: 12/23/2023]
Abstract
OBJECTIVES To evaluate changes occurring in the fetal brain prior to very preterm delivery using MRI T2* relaxometry, an indirect assessment of tissue perfusion. METHOD Fetuses that subsequently delivered spontaneously <32 weeks gestation and a control cohort were identified from pre-existing datasets. Participants had undergone a 3T MRI assessment including T2* relaxometry of the fetal brain using a 2D multi-slice gradient echo single shot echo planar imaging sequence. T2* maps were generated, supratentorial brain tissue was manually segmented and mean T2* values were generated. Groups were compared using quadratic regression. RESULTS Twenty five fetuses that subsequently delivered <32 weeks and 67 that delivered at term were included. Mean gestation at MRI was 24.5 weeks (SD 3.3) and 25.4 weeks (SD 3.1) and gestation at delivery 25.5 weeks (SD 3.4) and 39.7 weeks (SD 1.2) in the preterm and term cohorts respectively. Brain mean T2* values were significantly lower in fetuses that subsequently delivered before 32 weeks gestation (p < 0.001). CONCLUSION Alterations in brain maturation appear to occur prior to preterm delivery. Further work is required to explore these associations, but these findings suggest a potential window for therapeutic neuroprotective agents in fetuses at high risk of preterm delivery in the future.
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Affiliation(s)
- Lisa Story
- Department of Women's and Children's HealthKing's College LondonSt Thomas' Hospital LondonLondonUK
- Centre for the Developing BrainSchool of Biomedical Engineering and Imaging SciencesKing's College LondonSt Thomas' Hospital LondonLondonUK
- Fetal Medicine UnitSt Thomas' Hospital LondonLondonUK
| | - Alena Uus
- Department of Women's and Children's HealthKing's College LondonSt Thomas' Hospital LondonLondonUK
| | - Megan Hall
- Department of Women's and Children's HealthKing's College LondonSt Thomas' Hospital LondonLondonUK
- Centre for the Developing BrainSchool of Biomedical Engineering and Imaging SciencesKing's College LondonSt Thomas' Hospital LondonLondonUK
| | - Kelly Payette
- Department of Women's and Children's HealthKing's College LondonSt Thomas' Hospital LondonLondonUK
| | | | - Tomoki Arichi
- Centre for the Developing BrainSchool of Biomedical Engineering and Imaging SciencesKing's College LondonSt Thomas' Hospital LondonLondonUK
| | - Andrew Shennan
- Department of Women's and Children's HealthKing's College LondonSt Thomas' Hospital LondonLondonUK
| | - Mary Rutherford
- Centre for the Developing BrainSchool of Biomedical Engineering and Imaging SciencesKing's College LondonSt Thomas' Hospital LondonLondonUK
| | - Jana Hutter
- Centre for the Developing BrainSchool of Biomedical Engineering and Imaging SciencesKing's College LondonSt Thomas' Hospital LondonLondonUK
- Radiological InstituteUniversity Hospital ErlangenErlangenGermany
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13
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Payette K, Uus A, Verdera JA, Zampieri CA, Hall M, Story L, Deprez M, Rutherford MA, Hajnal JV, Ourselin S, Tomi-Tricot R, Hutter J. An automated pipeline for quantitative T2* fetal body MRI and segmentation at low field. MEDICAL IMAGE COMPUTING AND COMPUTER-ASSISTED INTERVENTION : MICCAI ... INTERNATIONAL CONFERENCE ON MEDICAL IMAGE COMPUTING AND COMPUTER-ASSISTED INTERVENTION 2023; 14226:358-367. [PMID: 39404664 PMCID: PMC7616578 DOI: 10.1007/978-3-031-43990-2_34] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Indexed: 10/19/2024]
Abstract
Fetal Magnetic Resonance Imaging at low field strengths is emerging as an exciting direction in perinatal health. Clinical low field (0.55T) scanners are beneficial for fetal imaging due to their reduced susceptibility-induced artefacts, increased T2* values, and wider bore (widening access for the increasingly obese pregnant population). However, the lack of standard automated image processing tools such as segmentation and reconstruction hampers wider clinical use. In this study, we introduce a semi-automatic pipeline using quantitative MRI for the fetal body at low field strength resulting in fast and detailed quantitative T2* relaxometry analysis of all major fetal body organs. Multi-echo dynamic sequences of the fetal body were acquired and reconstructed into a single high-resolution volume using deformable slice-to-volume reconstruction, generating both structural and quantitative T2* 3D volumes. A neural network trained using a semi-supervised approach was created to automatically segment these fetal body 3D volumes into ten different organs (resulting in dice values > 0.74 for 8 out of 10 organs). The T2* values revealed a strong relationship with GA in the lungs, liver, and kidney parenchyma (R2 >0.5). This pipeline was used successfully for a wide range of GAs (17-40 weeks), and is robust to motion artefacts. Low field fetal MRI can be used to perform advanced MRI analysis, and is a viable option for clinical scanning.
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Affiliation(s)
- Kelly Payette
- Centre for the Developing Brain, School of Biomedical Engineering & Imaging Sciences, King’s College London, London, UK
- Department of Biomedical Engineering, School of Biomedical Engineering & Imaging Sciences, King’s College London, London, UK
| | - Alena Uus
- Centre for the Developing Brain, School of Biomedical Engineering & Imaging Sciences, King’s College London, London, UK
- Department of Biomedical Engineering, School of Biomedical Engineering & Imaging Sciences, King’s College London, London, UK
| | - Jordina Aviles Verdera
- Centre for the Developing Brain, School of Biomedical Engineering & Imaging Sciences, King’s College London, London, UK
- Department of Biomedical Engineering, School of Biomedical Engineering & Imaging Sciences, King’s College London, London, UK
| | - Carla Avena Zampieri
- Centre for the Developing Brain, School of Biomedical Engineering & Imaging Sciences, King’s College London, London, UK
- Department of Biomedical Engineering, School of Biomedical Engineering & Imaging Sciences, King’s College London, London, UK
| | - Megan Hall
- Centre for the Developing Brain, School of Biomedical Engineering & Imaging Sciences, King’s College London, London, UK
- Department of Women & Children’s Health, King’s College London, London, UK: MR Research Collaborations, Siemens Healthcare Limited, Camberley, UK
| | - Lisa Story
- Centre for the Developing Brain, School of Biomedical Engineering & Imaging Sciences, King’s College London, London, UK
- Department of Biomedical Engineering, School of Biomedical Engineering & Imaging Sciences, King’s College London, London, UK
| | - Maria Deprez
- Centre for the Developing Brain, School of Biomedical Engineering & Imaging Sciences, King’s College London, London, UK
- Department of Biomedical Engineering, School of Biomedical Engineering & Imaging Sciences, King’s College London, London, UK
| | - Mary A. Rutherford
- Centre for the Developing Brain, School of Biomedical Engineering & Imaging Sciences, King’s College London, London, UK
| | - Joseph V. Hajnal
- Centre for the Developing Brain, School of Biomedical Engineering & Imaging Sciences, King’s College London, London, UK
- Department of Biomedical Engineering, School of Biomedical Engineering & Imaging Sciences, King’s College London, London, UK
| | - Sebastien Ourselin
- Centre for the Developing Brain, School of Biomedical Engineering & Imaging Sciences, King’s College London, London, UK
- Department of Biomedical Engineering, School of Biomedical Engineering & Imaging Sciences, King’s College London, London, UK
| | - Raphael Tomi-Tricot
- Department of Biomedical Engineering, School of Biomedical Engineering & Imaging Sciences, King’s College London, London, UK
| | - Jana Hutter
- Centre for the Developing Brain, School of Biomedical Engineering & Imaging Sciences, King’s College London, London, UK
- Department of Biomedical Engineering, School of Biomedical Engineering & Imaging Sciences, King’s College London, London, UK
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14
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Payette K, Uus A, Verdera JA, Zampieri CA, Hall M, Story L, Deprez M, Rutherford MA, Hajnal JV, Ourselin S, Tomi-Tricot R, Hutter J. An automated pipeline for quantitative T2* fetal body MRI and segmentation at low field. ARXIV 2023:arXiv:2308.04903v1. [PMID: 37608939 PMCID: PMC10441444] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Subscribe] [Scholar Register] [Indexed: 08/24/2023]
Abstract
Fetal Magnetic Resonance Imaging at low field strengths is emerging as an exciting direction in perinatal health. Clinical low field (0.55T) scanners are beneficial for fetal imaging due to their reduced susceptibility-induced artefacts, increased T2* values, and wider bore (widening access for the increasingly obese pregnant population). However, the lack of standard automated image processing tools such as segmentation and reconstruction hampers wider clinical use. In this study, we introduce a semi-automatic pipeline using quantitative MRI for the fetal body at low field strength resulting in fast and detailed quantitative T2* relaxometry analysis of all major fetal body organs. Multi-echo dynamic sequences of the fetal body were acquired and reconstructed into a single high-resolution volume using deformable slice-to-volume reconstruction, generating both structural and quantitative T2* 3D volumes. A neural network trained using a semi-supervised approach was created to automatically segment these fetal body 3D volumes into ten different organs (resulting in dice values > 0.74 for 8 out of 10 organs). The T2* values revealed a strong relationship with GA in the lungs, liver, and kidney parenchyma (R2 >0.5). This pipeline was used successfully for a wide range of GAs (17-40 weeks), and is robust to motion artefacts. Low field fetal MRI can be used to perform advanced MRI analysis, and is a viable option for clinical scanning.
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Affiliation(s)
- Kelly Payette
- Centre for the Developing Brain, School of Biomedical Engineering & Imaging Sciences, King’s College London, London, UK
- Department of Biomedical Engineering, School of Biomedical Engineering & Imaging Sciences, King’s College London, London, UK
| | - Alena Uus
- Centre for the Developing Brain, School of Biomedical Engineering & Imaging Sciences, King’s College London, London, UK
- Department of Biomedical Engineering, School of Biomedical Engineering & Imaging Sciences, King’s College London, London, UK
| | - Jordina Aviles Verdera
- Centre for the Developing Brain, School of Biomedical Engineering & Imaging Sciences, King’s College London, London, UK
- Department of Biomedical Engineering, School of Biomedical Engineering & Imaging Sciences, King’s College London, London, UK
| | - Carla Avena Zampieri
- Centre for the Developing Brain, School of Biomedical Engineering & Imaging Sciences, King’s College London, London, UK
- Department of Biomedical Engineering, School of Biomedical Engineering & Imaging Sciences, King’s College London, London, UK
| | - Megan Hall
- Centre for the Developing Brain, School of Biomedical Engineering & Imaging Sciences, King’s College London, London, UK
- Department of Women & Children’s Health, King’s College London, London, UK: MR Research Collaborations, Siemens Healthcare Limited, Camberley, UK
| | - Lisa Story
- Centre for the Developing Brain, School of Biomedical Engineering & Imaging Sciences, King’s College London, London, UK
- Department of Biomedical Engineering, School of Biomedical Engineering & Imaging Sciences, King’s College London, London, UK
| | - Maria Deprez
- Centre for the Developing Brain, School of Biomedical Engineering & Imaging Sciences, King’s College London, London, UK
- Department of Biomedical Engineering, School of Biomedical Engineering & Imaging Sciences, King’s College London, London, UK
| | - Mary A. Rutherford
- Centre for the Developing Brain, School of Biomedical Engineering & Imaging Sciences, King’s College London, London, UK
| | - Joseph V. Hajnal
- Centre for the Developing Brain, School of Biomedical Engineering & Imaging Sciences, King’s College London, London, UK
- Department of Biomedical Engineering, School of Biomedical Engineering & Imaging Sciences, King’s College London, London, UK
| | - Sebastien Ourselin
- Centre for the Developing Brain, School of Biomedical Engineering & Imaging Sciences, King’s College London, London, UK
- Department of Biomedical Engineering, School of Biomedical Engineering & Imaging Sciences, King’s College London, London, UK
| | - Raphael Tomi-Tricot
- Department of Biomedical Engineering, School of Biomedical Engineering & Imaging Sciences, King’s College London, London, UK
| | - Jana Hutter
- Centre for the Developing Brain, School of Biomedical Engineering & Imaging Sciences, King’s College London, London, UK
- Department of Biomedical Engineering, School of Biomedical Engineering & Imaging Sciences, King’s College London, London, UK
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15
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Hutter J, Al-Wakeel A, Kyriakopoulou V, Matthew J, Story L, Rutherford M. Exploring the role of a time-efficient MRI assessment of the placenta and fetal brain in uncomplicated pregnancies and these complicated by placental insufficiency. Placenta 2023; 139:25-33. [PMID: 37295055 DOI: 10.1016/j.placenta.2023.05.014] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/21/2022] [Revised: 02/24/2023] [Accepted: 05/20/2023] [Indexed: 06/12/2023]
Abstract
INTRODUCTION The development of placenta and fetal brain are intricately linked. Placental insufficiency is related to poor neonatal outcomes with impacts on neurodevelopment. This study sought to investigate whether simultaneous fast assessment of placental and fetal brain oxygenation using MRI T2* relaxometry can play a complementary role to US and Doppler US. METHODS This study is a retrospective case-control study with uncomplicated pregnancies (n = 99) and cases with placental insufficiency (PI) (n = 49). Participants underwent placental and fetal brain MRI and contemporaneous ultrasound imaging, resulting in quantitative assessment including a combined MRI score called Cerebro-placental-T2*-Ratio (CPTR). This was assessed in comparison with US-derived Cerebro-Placental-Ratio (CPR), placental histopathology, assessed using the Amsterdam criteria [1], and delivery details. RESULTS Pplacental and fetal brain T2* decreased with increasing gestational age in both low and high risk pregnancies and were corrected for gestational-age alsosignificantly decreased in PI. Both CPR and CPTR score were significantly correlated with gestational age at delivery for the entire cohort. CPTR was, however, also correlated independently with gestational age at delivery in the PI cohort. It furthermore showed a correlation to birth-weight-centile in healthy controls. DISCUSSION This study indicates that MR analysis of the placenta and brain may play a complementary role in the investigation of fetal development. The additional correlation to birth-weight-centile in controls may suggest a role in the determination of placental health even in healthy controls. To our knowledge, this is the first study assessing quantitatively both placental and fetal brain development over gestation in a large cohort of low and high risk pregnancies. Future larger prospective studies will include additional cohorts.
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Affiliation(s)
- Jana Hutter
- Centre for the Developing Brain, King's College London, UK; Centre for Medical Engineering, King's College London, UK.
| | - Ayman Al-Wakeel
- GKT School of Medical Education, King's College London, London, UK
| | - Vanessa Kyriakopoulou
- Centre for the Developing Brain, King's College London, UK; Centre for Medical Engineering, King's College London, UK
| | - Jacqueline Matthew
- Centre for the Developing Brain, King's College London, UK; Centre for Medical Engineering, King's College London, UK
| | - Lisa Story
- Centre for the Developing Brain, King's College London, UK; Institute for Women's and Children's Health, King's College London, UK; Fetal Medicine Unit, St Thomas' Hospital, London, UK
| | - Mary Rutherford
- Centre for the Developing Brain, King's College London, UK; Centre for Medical Engineering, King's College London, UK
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16
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Avena-Zampieri CL, Hutter J, Deprez M, Payette K, Hall M, Uus A, Nanda S, Milan A, Seed PT, Rutherford M, Greenough A, Story L. Assessment of normal pulmonary development using functional magnetic resonance imaging techniques. Am J Obstet Gynecol MFM 2023; 5:100935. [PMID: 36933803 PMCID: PMC10711505 DOI: 10.1016/j.ajogmf.2023.100935] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/06/2023] [Revised: 03/10/2023] [Accepted: 03/13/2023] [Indexed: 03/18/2023]
Abstract
BACKGROUND The mainstay of assessment of the fetal lungs in clinical practice is via evaluation of pulmonary size, primarily using 2D ultrasound and more recently with anatomical magnetic resonance imaging. The emergence of advanced magnetic resonance techniques such as T2* relaxometry in combination with the latest motion correction post-processing tools now facilitates assessment of the metabolic activity or perfusion of fetal pulmonary tissue in vivo. OBJECTIVE This study aimed to characterize normal pulmonary development using T2* relaxometry, accounting for fetal motion across gestation. METHODS Datasets from women with uncomplicated pregnancies that delivered at term, were analyzed. All subjects had undergone T2-weighted imaging and T2* relaxometry on a Phillips 3T magnetic resonance imaging system antenatally. T2* relaxometry of the fetal thorax was performed using a gradient echo single-shot echo planar imaging sequence. Following correction for fetal motion using slice-to-volume reconstruction, T2* maps were generated using in-house pipelines. Lungs were manually segmented and mean T2* values calculated for the right and left lungs individually, and for both lungs combined. Lung volumes were generated from the segmented images, and the right and left lungs, as well as both lungs combined were assessed. RESULTS Eighty-seven datasets were suitable for analysis. The mean gestation at scan was 29.9±4.3 weeks (range: 20.6-38.3) and mean gestation at delivery was 40±1.2 weeks (range: 37.1-42.4). Mean T2* values of the lungs increased over gestation for right and left lungs individually and for both lungs assessed together (P=.003; P=.04; P=.003, respectively). Right, left, and total lung volumes were also strongly correlated with increasing gestational age (P<.001 in all cases). CONCLUSION This large study assessed developing lungs using T2* imaging across a wide gestational age range. Mean T2* values increased with gestational age, which may reflect increasing perfusion and metabolic requirements and alterations in tissue composition as gestation advances. In the future, evaluation of findings in fetuses with conditions known to be associated with pulmonary morbidity may lead to enhanced prognostication antenatally, consequently improving counseling and perinatal care planning.
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Affiliation(s)
- Carla L Avena-Zampieri
- Department of Women and Children's Health, King's College London, London, United Kingdom (XX Avena-Zampieri, XX Hall, XX Seed, XX Greenough, and XX Story); Centre for the Developing Brain, School of Biomedical Engineering & Imaging Sciences, King's College London, London, United Kingdom (Ms Avena-Zampieri, Dr Hutter, Mr Deprez, Ms Payette, Dr Hall, Ms Uus, Prof Rutherford, and Dr Story).
| | - Jana Hutter
- Centre for the Developing Brain, School of Biomedical Engineering & Imaging Sciences, King's College London, London, United Kingdom (Ms Avena-Zampieri, Dr Hutter, Mr Deprez, Ms Payette, Dr Hall, Ms Uus, Prof Rutherford, and Dr Story)
| | - Maria Deprez
- Centre for the Developing Brain, School of Biomedical Engineering & Imaging Sciences, King's College London, London, United Kingdom (Ms Avena-Zampieri, Dr Hutter, Mr Deprez, Ms Payette, Dr Hall, Ms Uus, Prof Rutherford, and Dr Story); Department of Biomedical Engineering, School of Biomedical Engineering & Imaging Sciences, King's College London, London, United Kingdom (Ms Deprez, Ms Payette, and Ms Uus)
| | - Kelly Payette
- Centre for the Developing Brain, School of Biomedical Engineering & Imaging Sciences, King's College London, London, United Kingdom (Ms Avena-Zampieri, Dr Hutter, Mr Deprez, Ms Payette, Dr Hall, Ms Uus, Prof Rutherford, and Dr Story); Department of Biomedical Engineering, School of Biomedical Engineering & Imaging Sciences, King's College London, London, United Kingdom (Ms Deprez, Ms Payette, and Ms Uus)
| | - Megan Hall
- Department of Women and Children's Health, King's College London, London, United Kingdom (XX Avena-Zampieri, XX Hall, XX Seed, XX Greenough, and XX Story); Centre for the Developing Brain, School of Biomedical Engineering & Imaging Sciences, King's College London, London, United Kingdom (Ms Avena-Zampieri, Dr Hutter, Mr Deprez, Ms Payette, Dr Hall, Ms Uus, Prof Rutherford, and Dr Story); Fetal Medicine Unit, Guy's and St Thomas' NHS Foundation Trust, London, United Kingdom (Dr Hall, Dr Nanda, and Dr Story)
| | - Alena Uus
- Centre for the Developing Brain, School of Biomedical Engineering & Imaging Sciences, King's College London, London, United Kingdom (Ms Avena-Zampieri, Dr Hutter, Mr Deprez, Ms Payette, Dr Hall, Ms Uus, Prof Rutherford, and Dr Story); Department of Biomedical Engineering, School of Biomedical Engineering & Imaging Sciences, King's College London, London, United Kingdom (Ms Deprez, Ms Payette, and Ms Uus)
| | - Surabhi Nanda
- Fetal Medicine Unit, Guy's and St Thomas' NHS Foundation Trust, London, United Kingdom (Dr Hall, Dr Nanda, and Dr Story)
| | - Anna Milan
- Neonatal Unit, Guy's and St Thomas' NHS Foundation Trust, London, United Kingdom (Dr Milan)
| | - Paul T Seed
- Department of Women and Children's Health, King's College London, London, United Kingdom (XX Avena-Zampieri, XX Hall, XX Seed, XX Greenough, and XX Story)
| | - Mary Rutherford
- Centre for the Developing Brain, School of Biomedical Engineering & Imaging Sciences, King's College London, London, United Kingdom (Ms Avena-Zampieri, Dr Hutter, Mr Deprez, Ms Payette, Dr Hall, Ms Uus, Prof Rutherford, and Dr Story)
| | - Anne Greenough
- Department of Women and Children's Health, King's College London, London, United Kingdom (XX Avena-Zampieri, XX Hall, XX Seed, XX Greenough, and XX Story); Neonatal Unit, King's College Hospital, London, United Kingdom (Prof Greenough); National Institute for Health and Care Research Biomedical Research Centre based at Guy's & St Thomas NHS Foundation Trusts and King's College London, London, United Kingdom (Prof Greenough)
| | - Lisa Story
- Department of Women and Children's Health, King's College London, London, United Kingdom (XX Avena-Zampieri, XX Hall, XX Seed, XX Greenough, and XX Story); Centre for the Developing Brain, School of Biomedical Engineering & Imaging Sciences, King's College London, London, United Kingdom (Ms Avena-Zampieri, Dr Hutter, Mr Deprez, Ms Payette, Dr Hall, Ms Uus, Prof Rutherford, and Dr Story); Fetal Medicine Unit, Guy's and St Thomas' NHS Foundation Trust, London, United Kingdom (Dr Hall, Dr Nanda, and Dr Story)
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17
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Ji L, Majbri A, Hendrix CL, Thomason ME. Fetal behavior during MRI changes with age and relates to network dynamics. Hum Brain Mapp 2023; 44:1683-1694. [PMID: 36564934 PMCID: PMC9921243 DOI: 10.1002/hbm.26167] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/23/2022] [Revised: 10/31/2022] [Accepted: 11/23/2022] [Indexed: 12/25/2022] Open
Abstract
Fetal motor behavior is an important clinical indicator of healthy development. However, our understanding of associations between fetal behavior and fetal brain development is limited. To fill this gap, this study introduced an approach to automatically and objectively classify long durations of fetal movement from a continuous four-dimensional functional magnetic resonance imaging (fMRI) data set, and paired behavior features with brain activity indicated by the fMRI time series. Twelve-minute fMRI scans were conducted in 120 normal fetuses. Postnatal motor function was evaluated at 7 and 36 months age. Fetal motor behavior was quantified by calculating the frame-wise displacement (FD) of fetal brains extracted by a deep-learning model along the whole time series. Analyzing only low motion data, we characterized the recurring coactivation patterns (CAPs) of the supplementary motor area (SMA). Results showed reduced motor activity with advancing gestational age (GA), likely due in part to loss of space (r = -.51, p < .001). Evaluation of individual variation in motor movement revealed a negative association between movement and the occurrence of coactivations within the left parietotemporal network, controlling for age and sex (p = .003). Further, we found that the occurrence of coactivations between the SMA to posterior brain regions, including visual cortex, was prospectively associated with postnatal motor function at 7 months (r = .43, p = .03). This is the first study to pair fetal movement and fMRI, highlighting potential for comparisons of fetal behavior and neural network development to enhance our understanding of fetal brain organization.
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Affiliation(s)
- Lanxin Ji
- Department of Child & Adolescent PsychiatryNew York University School of MedicineNew YorkNew YorkUSA
| | - Amyn Majbri
- Department of Child & Adolescent PsychiatryNew York University School of MedicineNew YorkNew YorkUSA
| | - Cassandra L. Hendrix
- Department of Child & Adolescent PsychiatryNew York University School of MedicineNew YorkNew YorkUSA
| | - Moriah E. Thomason
- Department of Child & Adolescent PsychiatryNew York University School of MedicineNew YorkNew YorkUSA
- Department of Population HealthNew York University School of MedicineNew YorkNew YorkUSA
- Neuroscience InstituteNew York University School of MedicineNew YorkNew YorkUSA
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18
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Baadsgaard K, Hansen DN, Peters DA, Frøkjær JB, Sinding M, Sørensen A. T2* weighted fetal MRI and the correlation with placental dysfunction. Placenta 2023; 131:90-97. [PMID: 36565490 DOI: 10.1016/j.placenta.2022.12.002] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/28/2022] [Revised: 11/29/2022] [Accepted: 12/12/2022] [Indexed: 12/23/2022]
Abstract
INTRODUCTION Transverse relaxation time (T2*) is related to tissue oxygenation and morphology. We aimed to describe T2* weighted MRI in selected fetal organs in normal pregnancies, and to investigate the correlation between fetal organ T2* and placental T2*, birthweight (BW) deviation, and redistribution of fetal blood flow. METHODS T2*-weighted MRI was performed in 126 singleton pregnancies between 23+6- and 41+3-weeks' gestation. The T2* value was obtained from the placenta and fetal organs (brain, lungs, heart, liver, kidneys, and spleen). In normal BW pregnancies (BW > 10th centile), the correlation between the T2* value and gestational age (GA) at MRI was estimated by linear regression. The correlation between fetal organ Z-score and BW group was demonstrated by boxplots and investigated by analysis of variance (ANOVA) for each organ. RESULTS In normal BW pregnancies fetal organ T2* was negatively correlated with GA. We found a significant correlation between BW group and fetal organ T2* z-score in the fetal heart, kidney, lung and spleen. A positive linear correlation was demonstrated between fetal organ T2* and outcomes related to placental function such as BW deviation and placenta T2* in all investigated fetal organs except for the fetal liver. In the fetal heart, kidneys, and spleen the T2* value showed a significant correlation with fetal redistribution of blood flow (Middle cerebral artery Pulsatility Index) before delivery. DISCUSSION Fetal T2* is correlated with BW, placental function, and redistribution of fetal blood flow, suggesting that fetal organ T2* reflects fetal oxygenation and morphological changes related to placental dysfunction.
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Affiliation(s)
- Kirstine Baadsgaard
- Department of Clinical Medicine Aalborg University, Søndre Skovvej 15, 9000, Aalborg, Denmark; Department of Obstetrics and Gynecology, Aalborg University Hospital, Reberbansgade 15, 9000, Aalborg, Denmark.
| | - Ditte N Hansen
- Department of Clinical Medicine Aalborg University, Søndre Skovvej 15, 9000, Aalborg, Denmark; Department of Obstetrics and Gynecology, Aalborg University Hospital, Reberbansgade 15, 9000, Aalborg, Denmark
| | - David A Peters
- Department of Clinical Engineering, Central Denmark Region, Universitetsbyen 25, 8000, Aarhus C, Denmark
| | - Jens B Frøkjær
- Department of Clinical Medicine Aalborg University, Søndre Skovvej 15, 9000, Aalborg, Denmark; Department of Radiology, Aalborg University Hospital, Reberbansgade 15, 9000, Aalborg, Denmark
| | - Marianne Sinding
- Department of Clinical Medicine Aalborg University, Søndre Skovvej 15, 9000, Aalborg, Denmark; Department of Obstetrics and Gynecology, Aalborg University Hospital, Reberbansgade 15, 9000, Aalborg, Denmark
| | - Anne Sørensen
- Department of Clinical Medicine Aalborg University, Søndre Skovvej 15, 9000, Aalborg, Denmark; Department of Obstetrics and Gynecology, Aalborg University Hospital, Reberbansgade 15, 9000, Aalborg, Denmark
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19
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De Asis-Cruz J, Limperopoulos C. Harnessing the Power of Advanced Fetal Neuroimaging to Understand In Utero Footprints for Later Neuropsychiatric Disorders. Biol Psychiatry 2022; 93:867-879. [PMID: 36804195 DOI: 10.1016/j.biopsych.2022.11.019] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/01/2022] [Revised: 11/03/2022] [Accepted: 11/25/2022] [Indexed: 12/12/2022]
Abstract
Adverse intrauterine events may profoundly impact fetal risk for future adult diseases. The mechanisms underlying this increased vulnerability are complex and remain poorly understood. Contemporary advances in fetal magnetic resonance imaging (MRI) have provided clinicians and scientists with unprecedented access to in vivo human fetal brain development to begin to identify emerging endophenotypes of neuropsychiatric disorders such as autism spectrum disorder, attention-deficit/hyperactivity disorder, and schizophrenia. In this review, we discuss salient findings of normal fetal neurodevelopment from studies using advanced, multimodal MRI that have provided unparalleled characterization of in utero prenatal brain morphology, metabolism, microstructure, and functional connectivity. We appraise the clinical utility of these normative data in identifying high-risk fetuses before birth. We highlight available studies that have investigated the predictive validity of advanced prenatal brain MRI findings and long-term neurodevelopmental outcomes. We then discuss how ex utero quantitative MRI findings can inform in utero investigations toward the pursuit of early biomarkers of risk. Lastly, we explore future opportunities to advance our understanding of the prenatal origins of neuropsychiatric disorders using precision fetal imaging.
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20
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A Fetal Brain magnetic resonance Acquisition Numerical phantom (FaBiAN). Sci Rep 2022; 12:8682. [PMID: 35606398 PMCID: PMC9127105 DOI: 10.1038/s41598-022-10335-4] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/13/2021] [Accepted: 04/05/2022] [Indexed: 11/28/2022] Open
Abstract
Accurate characterization of in utero human brain maturation is critical as it involves complex and interconnected structural and functional processes that may influence health later in life. Magnetic resonance imaging is a powerful tool to investigate equivocal neurological patterns during fetal development. However, the number of acquisitions of satisfactory quality available in this cohort of sensitive subjects remains scarce, thus hindering the validation of advanced image processing techniques. Numerical phantoms can mitigate these limitations by providing a controlled environment with a known ground truth. In this work, we present FaBiAN, an open-source Fetal Brain magnetic resonance Acquisition Numerical phantom that simulates clinical T2-weighted fast spin echo sequences of the fetal brain. This unique tool is based on a general, flexible and realistic setup that includes stochastic fetal movements, thus providing images of the fetal brain throughout maturation comparable to clinical acquisitions. We demonstrate its value to evaluate the robustness and optimize the accuracy of an algorithm for super-resolution fetal brain magnetic resonance imaging from simulated motion-corrupted 2D low-resolution series compared to a synthetic high-resolution reference volume. We also show that the images generated can complement clinical datasets to support data-intensive deep learning methods for fetal brain tissue segmentation.
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21
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Early development of sleep and brain functional connectivity in term-born and preterm infants. Pediatr Res 2022; 91:771-786. [PMID: 33859364 DOI: 10.1038/s41390-021-01497-4] [Citation(s) in RCA: 16] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/28/2020] [Revised: 03/11/2021] [Accepted: 03/11/2021] [Indexed: 12/22/2022]
Abstract
The proper development of sleep and sleep-wake rhythms during early neonatal life is crucial to lifelong neurological well-being. Recent data suggests that infants who have poor quality sleep demonstrate a risk for impaired neurocognitive outcomes. Sleep ontogenesis is a complex process, whereby alternations between rudimentary brain states-active vs. wake and active sleep vs. quiet sleep-mature during the last trimester of pregnancy. If the infant is born preterm, much of this process occurs in the neonatal intensive care unit, where environmental conditions might interfere with sleep. Functional brain connectivity (FC), which reflects the brain's ability to process and integrate information, may become impaired, with ensuing risks of compromised neurodevelopment. However, the specific mechanisms linking sleep ontogenesis to the emergence of FC are poorly understood and have received little investigation, mainly due to the challenges of studying causal links between developmental phenomena and assessing FC in newborn infants. Recent advancements in infant neuromonitoring and neuroimaging strategies will allow for the design of interventions to improve infant sleep quality and quantity. This review discusses how sleep and FC develop in early life, the dynamic relationship between sleep, preterm birth, and FC, and the challenges associated with understanding these processes. IMPACT: Sleep in early life is essential for proper functional brain development, which is essential for the brain to integrate and process information. This process may be impaired in infants born preterm. The connection between preterm birth, early development of brain functional connectivity, and sleep is poorly understood. This review discusses how sleep and brain functional connectivity develop in early life, how these processes might become impaired, and the challenges associated with understanding these processes. Potential solutions to these challenges are presented to provide direction for future research.
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22
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Pietsch M, Ho A, Bardanzellu A, Zeidan AMA, Chappell LC, Hajnal JV, Rutherford M, Hutter J. APPLAUSE: Automatic Prediction of PLAcental health via U-net Segmentation and statistical Evaluation. Med Image Anal 2021; 72:102145. [PMID: 34229190 PMCID: PMC8350147 DOI: 10.1016/j.media.2021.102145] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/23/2020] [Revised: 04/26/2021] [Accepted: 06/21/2021] [Indexed: 02/04/2023]
Abstract
PURPOSE Artificial-intelligence population-based automated quantification of placental maturation and health from a rapid functional Magnetic Resonance scan. The placenta plays a crucial role for any successful human pregnancy. Deviations from the normal dynamic maturation throughout gestation are closely linked to major pregnancy complications. Antenatal assessment in-vivo using T2* relaxometry has shown great promise to inform management and possible interventions but clinical translation is hampered by time consuming manual segmentation and analysis techniques based on comparison against normative curves over gestation. METHODS This study proposes a fully automatic pipeline to predict the biological age and health of the placenta based on a free-breathing rapid (sub-30 second) T2* scan in two steps: Automatic segmentation using a U-Net and a Gaussian process regression model to characterize placental maturation and health. These are trained and evaluated on 108 3T MRI placental data sets, the evaluation included 20 high-risk pregnancies diagnosed with pre-eclampsia and/or fetal growth restriction. An independent cohort imaged at 1.5 T is used to assess the generalization of the training and evaluation pipeline. RESULTS Across low- and high-risk groups, automatic segmentation performs worse than inter-rater performance (mean Dice coefficients of 0.58 and 0.68, respectively) but is sufficient for estimating placental mean T2* (0.986 Pearson Correlation Coefficient). The placental health prediction achieves an excellent ability to differentiate cases of placental insufficiency between 27 and 33 weeks. High abnormality scores correlate with low birth weight, premature birth and histopathological findings. Retrospective application on a different cohort imaged at 1.5 T illustrates the ability for direct clinical translation. CONCLUSION The presented automatic pipeline facilitates a fast, robust and reliable prediction of placental maturation. It yields human-interpretable and verifiable intermediate results and quantifies uncertainties on the cohort-level and for individual predictions. The proposed machine-learning pipeline runs in close to real-time and, deployed in clinical settings, has the potential to become a cornerstone of diagnosis and intervention of placental insufficiency. APPLAUSE generalizes to an independent cohort imaged at 1.5 T, demonstrating robustness to different operational and clinical environments.
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Affiliation(s)
- Maximilian Pietsch
- Centre for Medical Engineering, King's College London, London, UK; Centre for the Developing Brain, King's College London, London, UK.
| | - Alison Ho
- Department of Women and Children's Health, King's College London, London, UK
| | - Alessia Bardanzellu
- Centre for Medical Engineering, King's College London, London, UK; Centre for the Developing Brain, King's College London, London, UK
| | - Aya Mutaz Ahmad Zeidan
- Centre for Medical Engineering, King's College London, London, UK; Centre for the Developing Brain, King's College London, London, UK
| | - Lucy C Chappell
- Department of Women and Children's Health, King's College London, London, UK
| | - Joseph V Hajnal
- Centre for Medical Engineering, King's College London, London, UK; Centre for the Developing Brain, King's College London, London, UK
| | - Mary Rutherford
- Centre for Medical Engineering, King's College London, London, UK; Centre for the Developing Brain, King's College London, London, UK
| | - Jana Hutter
- Centre for Medical Engineering, King's College London, London, UK; Centre for the Developing Brain, King's College London, London, UK
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23
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Peyvandi S, Xu D, Wang Y, Hogan W, Moon-Grady A, Barkovich AJ, Glenn O, McQuillen P, Liu J. Fetal Cerebral Oxygenation Is Impaired in Congenital Heart Disease and Shows Variable Response to Maternal Hyperoxia. J Am Heart Assoc 2020; 10:e018777. [PMID: 33345557 PMCID: PMC7955474 DOI: 10.1161/jaha.120.018777] [Citation(s) in RCA: 26] [Impact Index Per Article: 5.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
Abstract
Background Impairments in fetal oxygen delivery have been implicated in brain dysmaturation seen in congenital heart disease (CHD), suggesting a role for in utero transplacental oxygen therapy. We applied a novel imaging tool to quantify fetal cerebral oxygenation by measuring T2* decay. We compared T2* in fetuses with CHD with controls with a focus on cardiovascular physiologies (transposition or left‐sided obstruction) and described the effect of brief administration of maternal hyperoxia on T2* decay. Methods and Results This is a prospective study performed on pregnant mothers with a prenatal diagnosis of CHD compared with controls in the third trimester. Participants underwent a fetal brain magnetic resonance imaging scan including a T2* sequence before and after maternal hyperoxia. Comparisons were made between control and CHD fetuses including subgroup analyses by cardiac physiology. Forty‐four mothers (CHD=24, control=20) participated. Fetuses with CHD had lower total brain volume (238.2 mm3, 95% CI, 224.6–251.9) compared with controls (262.4 mm3, 95% CI, 245.0–279.8, P=0.04). T2* decay time was faster in CHD compared with controls (beta=−14.4, 95% CI, −23.3 to −5.6, P=0.002). The magnitude of change in T2* with maternal hyperoxia was higher in fetuses with transposition compared with controls (increase of 8.4 ms, 95% CI, 0.5–14.3, P=0.01), though between‐subject variability was noted. Conclusions Cerebral tissue oxygenation is lower in fetuses with complex CHD. There was variability in the response to maternal hyperoxia by CHD subgroup that can be tested in future larger studies. Cardiovascular physiology is critical when designing neuroprotective clinical trials in the fetus with CHD.
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Affiliation(s)
- Shabnam Peyvandi
- Department of Pediatrics Division of Cardiology University of California San Francisco San Francisco CA.,Department of Epidemiology and Biostatistics University of California San Francisco San Francisco CA
| | - Duan Xu
- Department of Radiology and Biomedical Imaging University of California San Francisco San Francisco CA
| | - Yan Wang
- Department of Radiology and Biomedical Imaging University of California San Francisco San Francisco CA
| | - Whitnee Hogan
- Department of Pediatrics Division of Cardiology University of California San Francisco San Francisco CA
| | - Anita Moon-Grady
- Department of Pediatrics Division of Cardiology University of California San Francisco San Francisco CA
| | - A James Barkovich
- Department of Radiology and Biomedical Imaging University of California San Francisco San Francisco CA
| | - Orit Glenn
- Department of Radiology and Biomedical Imaging University of California San Francisco San Francisco CA
| | - Patrick McQuillen
- Department of Pediatrics, Division of Critical Care University of California San Francisco San Francisco CA
| | - Jing Liu
- Department of Radiology and Biomedical Imaging University of California San Francisco San Francisco CA
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24
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Thomason ME. Development of Brain Networks In Utero: Relevance for Common Neural Disorders. Biol Psychiatry 2020; 88:40-50. [PMID: 32305217 PMCID: PMC7808399 DOI: 10.1016/j.biopsych.2020.02.007] [Citation(s) in RCA: 43] [Impact Index Per Article: 8.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/24/2019] [Revised: 01/05/2020] [Accepted: 02/05/2020] [Indexed: 01/27/2023]
Abstract
Magnetic resonance imaging, histological, and gene analysis approaches in living and nonliving human fetuses and in prematurely born neonates have provided insight into the staged processes of prenatal brain development. Increased understanding of micro- and macroscale brain network development before birth has spurred interest in understanding the relevance of prenatal brain development to common neurological diseases. Questions abound as to the sensitivity of the intrauterine brain to environmental programming, to windows of plasticity, and to the prenatal origin of disorders of childhood that involve disruptions in large-scale network connectivity. Much of the available literature on human prenatal neural development comes from cross-sectional or case studies that are not able to resolve the longitudinal consequences of individual variation in brain development before birth. This review will 1) detail specific methodologies for studying the human prenatal brain, 2) summarize large-scale human prenatal neural network development, integrating findings from across a variety of experimental approaches, 3) explore the plasticity of the early developing brain as well as potential sex differences in prenatal susceptibility, and 4) evaluate opportunities to link specific prenatal brain developmental processes to the forms of aberrant neural connectivity that underlie common neurological disorders of childhood.
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Affiliation(s)
- Moriah E Thomason
- Department of Child and Adolescent Psychiatry, Department of Population Health, and Neuroscience Institute, New York University Langone Health, New York, New York.
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25
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Abstract
Developmental pathoconnectomics is an emerging field that aims to unravel the events leading to and outcome from disrupted brain connectivity development. Advanced magnetic resonance imaging (MRI) technology enables the portrayal of human brain connectivity before birth and has the potential to offer novel insights into normal and pathological human brain development. This review gives an overview of the currently used MRI techniques for connectomic imaging, with a particular focus on recent studies that have successfully translated these to the in utero or postmortem fetal setting. Possible mechanisms of how pathologies, maternal, or environmental factors may interfere with the emergence of the connectome are considered. The review highlights the importance of advanced image post processing and the need for reproducibility studies for connectomic imaging. Further work and novel data-sharing efforts would be required to validate or disprove recent observations from in utero connectomic studies, which are typically limited by low case numbers and high data drop out. Novel knowledge with regard to the ontogenesis, architecture, and temporal dynamics of the human brain connectome would lead to the more precise understanding of the etiological background of neurodevelopmental and mental disorders. To achieve this goal, this review considers the growing evidence from advanced fetal connectomic imaging for the increased vulnerability of the human brain during late gestation for pathologies that might lead to impaired connectome development and subsequently interfere with the development of neural substrates serving higher cognition.
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26
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Afacan O, Estroff JA, Yang E, Barnewolt CE, Connolly SA, Parad RB, Mulkern RV, Warfield SK, Gholipour A. Fetal Echoplanar Imaging: Promises and Challenges. Top Magn Reson Imaging 2019; 28:245-254. [PMID: 31592991 PMCID: PMC6788763 DOI: 10.1097/rmr.0000000000000219] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/21/2022]
Abstract
Fetal magnetic resonance imaging (MRI) has been gaining increasing interest in both clinical radiology and research. Echoplanar imaging (EPI) offers a unique potential, as it can be used to acquire images very fast. It can be used to freeze motion, or to get multiple images with various contrast mechanisms that allow studying the microstructure and function of the fetal brain and body organs. In this article, we discuss the current clinical and research applications of fetal EPI. This includes T2*-weighted imaging to better identify blood products and vessels, using diffusion-weighted MRI to investigate connections of the developing brain and using functional MRI (fMRI) to identify the functional networks of the developing brain. EPI can also be used as an alternative structural sequence when banding or standing wave artifacts adversely affect the mainstream sequences used routinely in structural fetal MRI. We also discuss the challenges with EPI acquisitions, and potential solutions. As EPI acquisitions are inherently sensitive to susceptibility artifacts, geometric distortions limit the use of high-resolution EPI acquisitions. Also, interslice motion and transmit and receive field inhomogeneities may create significant artifacts in fetal EPI. We conclude by discussing promising research directions to overcome these challenges to improve the use of EPI in clinical and research applications.
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Affiliation(s)
- Onur Afacan
- Department of Radiology, Boston Children’s Hospital, Boston, MA, United States
- Harvard Medical School, Boston, MA, United States
| | - Judy A. Estroff
- Department of Radiology, Boston Children’s Hospital, Boston, MA, United States
- Advanced Fetal Care Center, Boston Children’s Hospital, Boston, MA, United States
- Harvard Medical School, Boston, MA, United States
| | - Edward Yang
- Department of Radiology, Boston Children’s Hospital, Boston, MA, United States
- Advanced Fetal Care Center, Boston Children’s Hospital, Boston, MA, United States
- Harvard Medical School, Boston, MA, United States
| | - Carol E. Barnewolt
- Department of Radiology, Boston Children’s Hospital, Boston, MA, United States
- Advanced Fetal Care Center, Boston Children’s Hospital, Boston, MA, United States
- Harvard Medical School, Boston, MA, United States
| | - Susan A. Connolly
- Department of Radiology, Boston Children’s Hospital, Boston, MA, United States
- Advanced Fetal Care Center, Boston Children’s Hospital, Boston, MA, United States
- Harvard Medical School, Boston, MA, United States
| | - Richard B. Parad
- Advanced Fetal Care Center, Boston Children’s Hospital, Boston, MA, United States
- Harvard Medical School, Boston, MA, United States
- Department of Pediatric Newborn Medicine, Brigham and Women’s Hospital, Boston, Massachusetts, USA
| | - Robert V. Mulkern
- Department of Radiology, Boston Children’s Hospital, Boston, MA, United States
- Harvard Medical School, Boston, MA, United States
| | - Simon K. Warfield
- Department of Radiology, Boston Children’s Hospital, Boston, MA, United States
- Harvard Medical School, Boston, MA, United States
| | - Ali Gholipour
- Department of Radiology, Boston Children’s Hospital, Boston, MA, United States
- Harvard Medical School, Boston, MA, United States
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27
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Smyser CD, Wheelock MD, Limbrick DD, Neil JJ. Neonatal brain injury and aberrant connectivity. Neuroimage 2019; 185:609-623. [PMID: 30059733 PMCID: PMC6289815 DOI: 10.1016/j.neuroimage.2018.07.057] [Citation(s) in RCA: 54] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/02/2017] [Revised: 06/21/2018] [Accepted: 07/24/2018] [Indexed: 12/12/2022] Open
Abstract
Brain injury sustained during the neonatal period may disrupt development of critical structural and functional connectivity networks leading to subsequent neurodevelopmental impairment in affected children. These networks can be characterized using structural (via diffusion MRI) and functional (via resting state-functional MRI) neuroimaging techniques. Advances in neuroimaging have led to expanded application of these approaches to study term- and prematurely-born infants, providing improved understanding of cerebral development and the deleterious effects of early brain injury. Across both modalities, neuroimaging data are conducive to analyses ranging from characterization of individual white matter tracts and/or resting state networks through advanced 'connectome-style' approaches capable of identifying highly connected network hubs and investigating metrics of network topology such as modularity and small-worldness. We begin this review by summarizing the literature detailing structural and functional connectivity findings in healthy term and preterm infants without brain injury during the postnatal period, including discussion of early connectome development. We then detail common forms of brain injury in term- and prematurely-born infants. In this context, we next review the emerging body of literature detailing studies employing diffusion MRI, resting state-functional MRI and other complementary neuroimaging modalities to characterize structural and functional connectivity development in infants with brain injury. We conclude by reviewing technical challenges associated with neonatal neuroimaging, highlighting those most relevant to studying infants with brain injury and emphasizing the need for further targeted study in this high-risk population.
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Affiliation(s)
- Christopher D Smyser
- Departments of Neurology, Pediatrics and Radiology, Washington University School of Medicine, 660 South Euclid Avenue, Campus Box 8111, St. Louis, MO, 63110, USA.
| | - Muriah D Wheelock
- Department of Psychiatry, Washington University School of Medicine, 660 South Euclid Avenue, Campus Box 8134, St. Louis, MO, 63110, USA.
| | - David D Limbrick
- Departments of Neurosurgery and Pediatrics, Washington University School of Medicine, One Children's Place, Suite S20, St. Louis, MO, 63110, USA.
| | - Jeffrey J Neil
- Department of Pediatric Neurology, Boston Children's Hospital, 300 Longwood Avenue, BCH3443, Boston, MA, 02115, USA.
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Neil JJ, Smyser CD. Recent advances in the use of MRI to assess early human cortical development. JOURNAL OF MAGNETIC RESONANCE (SAN DIEGO, CALIF. : 1997) 2018; 293:56-69. [PMID: 29894905 PMCID: PMC6047926 DOI: 10.1016/j.jmr.2018.05.013] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/01/2018] [Revised: 05/17/2018] [Accepted: 05/21/2018] [Indexed: 05/18/2023]
Abstract
Over the past decade, a number of advanced magnetic resonance-based methods have been brought to bear on questions related to early development of the human cerebral cortex. Herein, we describe studies employing analysis of cortical surface folding (cortical cartography), cortical microstructure (diffusion anisotropy), and cortically-based functional networks (resting state-functional connectivity MRI). The fundamentals of each MR method are described, followed by a discussion of application of the method to developing cortex and potential clinical uses. We use premature birth as an exemplar of how these modalities can be used to investigate the effects of medical and environmental variables on early cortical development.
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Affiliation(s)
- Jeffrey J Neil
- Department of Pediatric Neurology, Boston Children's Hospital, 300 Longwood Avenue, Boston, MA 02115, United States.
| | - Christopher D Smyser
- Departments of Neurology, Pediatrics and Radiology, Washington University School of Medicine, 660 S. Euclid Ave., Campus Box 8111, St. Louis, MO 63110, United States.
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Yarnykh VL, Prihod'ko IY, Savelov AA, Korostyshevskaya AM. Quantitative Assessment of Normal Fetal Brain Myelination Using Fast Macromolecular Proton Fraction Mapping. AJNR Am J Neuroradiol 2018; 39:1341-1348. [PMID: 29748201 DOI: 10.3174/ajnr.a5668] [Citation(s) in RCA: 26] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/08/2017] [Accepted: 03/23/2018] [Indexed: 01/08/2023]
Abstract
BACKGROUND AND PURPOSE Fast macromolecular proton fraction mapping is a recently emerged MRI method for quantitative myelin imaging. Our aim was to develop a clinically targeted technique for macromolecular proton fraction mapping of the fetal brain and test its capability to characterize normal prenatal myelination. MATERIALS AND METHODS This prospective study included 41 pregnant women (gestational age range, 18-38 weeks) without abnormal findings on fetal brain MR imaging performed for clinical indications. A fast fetal brain macromolecular proton fraction mapping protocol was implemented on a clinical 1.5T MR imaging scanner without software modifications and was performed after a clinical examination with an additional scan time of <5 minutes. 3D macromolecular proton fraction maps were reconstructed from magnetization transfer-weighted, T1-weighted, and proton density-weighted images by the single-point method. Mean macromolecular proton fraction in the brain stem, cerebellum, and thalamus and frontal, temporal, and occipital WM was compared between structures and pregnancy trimesters using analysis of variance. Gestational age dependence of the macromolecular proton fraction was assessed using the Pearson correlation coefficient (r). RESULTS The mean macromolecular proton fraction in the fetal brain structures varied between 2.3% and 4.3%, being 5-fold lower than macromolecular proton fraction in adult WM. The macromolecular proton fraction in the third trimester was higher compared with the second trimester in the brain stem, cerebellum, and thalamus. The highest macromolecular proton fraction was observed in the brain stem, followed by the thalamus, cerebellum, and cerebral WM. The macromolecular proton fraction in the brain stem, cerebellum, and thalamus strongly correlated with gestational age (r = 0.88, 0.80, and 0.73; P < .001). No significant correlations were found for cerebral WM regions. CONCLUSIONS Myelin is the main factor determining macromolecular proton fraction in brain tissues. Macromolecular proton fraction mapping is sensitive to the earliest stages of the fetal brain myelination and can be implemented in a clinical setting.
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Affiliation(s)
- V L Yarnykh
- From the Department of Radiology (V.L.Y.), University of Washington, Seattle, Washington .,Research Institute of Biology and Biophysics (V.L.Y.), Tomsk State University, Tomsk, Russian Federation
| | - I Y Prihod'ko
- Institute "International Tomography Center" of the Siberian Branch of the Russian Academy of Sciences (I.Y.P., A.A.S., A.M.K.), Novosibirsk, Russian Federation
| | - A A Savelov
- Institute "International Tomography Center" of the Siberian Branch of the Russian Academy of Sciences (I.Y.P., A.A.S., A.M.K.), Novosibirsk, Russian Federation
| | - A M Korostyshevskaya
- Institute "International Tomography Center" of the Siberian Branch of the Russian Academy of Sciences (I.Y.P., A.A.S., A.M.K.), Novosibirsk, Russian Federation
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Nunes RG, Ferrazzi G, Price AN, Hutter J, Gaspar AS, Rutherford MA, Hajnal JV. Inner-volume echo volumar imaging (IVEVI) for robust fetal brain imaging. Magn Reson Med 2017; 80:279-285. [PMID: 29115686 DOI: 10.1002/mrm.26998] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/18/2017] [Revised: 10/17/2017] [Accepted: 10/18/2017] [Indexed: 11/08/2022]
Abstract
PURPOSE Fetal functional MRI studies using conventional 2-dimensional single-shot echo-planar imaging sequences may require discarding a large data fraction as a result of fetal and maternal motion. Increasing the temporal resolution using echo volumar imaging (EVI) could provide an effective alternative strategy. Echo volumar imaging was combined with inner volume (IV) imaging (IVEVI) to locally excite the fetal brain and acquire full 3-dimensional images, fast enough to freeze most fetal head motion. METHODS IVEVI was implemented by modifying a standard multi-echo echo-planar imaging sequence. A spin echo with orthogonal excitation and refocusing ensured localized excitation. To introduce T2* weighting and to save time, the k-space center was shifted relative to the spin echo. Both single and multi-shot variants were tested. Acoustic noise was controlled by adjusting the amplitude and switching frequency of the readout gradient. Image-based shimming was used to minimize B0 inhomogeneities within the fetal brain. RESULTS The sequence was first validated in an adult. Eight fetuses were scanned using single-shot IVEVI at a 3.5 × 3.5 × 5.0 mm3 resolution with a readout duration of 383 ms. Multishot IVEVI showed reduced geometric distortions along the second phase-encode direction. CONCLUSIONS Fetal EVI remains challenging. Although effective echo times comparable to the T2* values of fetal cortical gray matter at 3 T could be achieved, controlling acoustic noise required longer readouts, leading to substantial distortions in single-shot images. Although multishot variants enabled us to reduce susceptibility-induced geometric distortions, sensitivity to motion was increased. Future studies should therefore focus on improvements to multishot variants. Magn Reson Med 80:279-285, 2018. © 2017 International Society for Magnetic Resonance in Medicine.
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Affiliation(s)
- Rita G Nunes
- Instituto de Biofísica e Engenharia Biomédica, Faculdade de Ciências, Universidade de Lisboa, Lisboa, Portugal.,Institute for Systems and Robotics and Department of Bioengineering, Instituto Superior Técnico, Universidade de Lisboa, Lisboa, Portugal.,Division of Imaging Sciences and Biomedical Engineering, King's College London, London, United Kingdom
| | - Giulio Ferrazzi
- Division of Imaging Sciences and Biomedical Engineering, King's College London, London, United Kingdom.,Centre for the Developing Brain, King's College London, London, United Kingdom
| | - Anthony N Price
- Division of Imaging Sciences and Biomedical Engineering, King's College London, London, United Kingdom.,Centre for the Developing Brain, King's College London, London, United Kingdom
| | - Jana Hutter
- Division of Imaging Sciences and Biomedical Engineering, King's College London, London, United Kingdom.,Centre for the Developing Brain, King's College London, London, United Kingdom
| | - Andreia S Gaspar
- Instituto de Biofísica e Engenharia Biomédica, Faculdade de Ciências, Universidade de Lisboa, Lisboa, Portugal.,Institute for Systems and Robotics and Department of Bioengineering, Instituto Superior Técnico, Universidade de Lisboa, Lisboa, Portugal.,Division of Imaging Sciences and Biomedical Engineering, King's College London, London, United Kingdom
| | - Mary A Rutherford
- Division of Imaging Sciences and Biomedical Engineering, King's College London, London, United Kingdom.,Centre for the Developing Brain, King's College London, London, United Kingdom
| | - Joseph V Hajnal
- Division of Imaging Sciences and Biomedical Engineering, King's College London, London, United Kingdom.,Centre for the Developing Brain, King's College London, London, United Kingdom
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