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Vellvé K, Garcia-Canadilla P, Nogueira M, Youssef L, Arranz A, Nakaki A, Boada D, Blanco I, Faner R, Figueras F, Agustí À, Gratacós E, Crovetto F, Bijnens B, Crispi F. Pulmonary vascular reactivity in growth restricted fetuses using computational modelling and machine learning analysis of fetal Doppler waveforms. Sci Rep 2024; 14:5919. [PMID: 38467666 PMCID: PMC10928161 DOI: 10.1038/s41598-024-54603-x] [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: 07/16/2023] [Accepted: 02/14/2024] [Indexed: 03/13/2024] Open
Abstract
The aim of this study was to investigate the pulmonary vasculature in baseline conditions and after maternal hyperoxygenation in growth restricted fetuses (FGR). A prospective cohort study of singleton pregnancies including 97 FGR and 111 normally grown fetuses was carried out. Ultrasound Doppler of the pulmonary vessels was obtained at 24-37 weeks of gestation and data were acquired before and after oxygen administration. After, Machine Learning (ML) and a computational model were used on the Doppler waveforms to classify individuals and estimate pulmonary vascular resistance (PVR). Our results showed lower mean velocity time integral (VTI) in the main pulmonary and intrapulmonary arteries in baseline conditions in FGR individuals. Delta changes of the main pulmonary artery VTI and intrapulmonary artery pulsatility index before and after hyperoxygenation were significantly greater in FGR when compared with controls. Also, ML identified two clusters: A (including 66% controls and 34% FGR) with similar Doppler traces over time and B (including 33% controls and 67% FGR) with changes after hyperoxygenation. The computational model estimated the ratio of PVR before and after maternal hyperoxygenation which was closer to 1 in cluster A (cluster A 0.98 ± 0.33 vs cluster B 0.78 ± 0.28, p = 0.0156). Doppler ultrasound allows the detection of significant changes in pulmonary vasculature in most FGR at baseline, and distinct responses to hyperoxygenation. Future studies are warranted to assess its potential applicability in the clinical management of FGR.
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Affiliation(s)
- Kilian Vellvé
- BCNatal Fetal Medicine Research Center (Hospital Clínic and Hospital Sant Joan de Déu), University of Barcelona, Sabino Arana 1, 08028, Barcelona, Spain
- Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain
| | - Patricia Garcia-Canadilla
- BCNatal Fetal Medicine Research Center (Hospital Clínic and Hospital Sant Joan de Déu), University of Barcelona, Sabino Arana 1, 08028, Barcelona, Spain
- Interdisciplinary Cardiovascular Research Group, Institut de Recerca Sant Joan de Déu, Esplugues de Llobregat, Barcelona, Spain
| | - Mariana Nogueira
- Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain
| | - Lina Youssef
- BCNatal Fetal Medicine Research Center (Hospital Clínic and Hospital Sant Joan de Déu), University of Barcelona, Sabino Arana 1, 08028, Barcelona, Spain
- Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain
| | - Angela Arranz
- BCNatal Fetal Medicine Research Center (Hospital Clínic and Hospital Sant Joan de Déu), University of Barcelona, Sabino Arana 1, 08028, Barcelona, Spain
- Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain
| | - Ayako Nakaki
- BCNatal Fetal Medicine Research Center (Hospital Clínic and Hospital Sant Joan de Déu), University of Barcelona, Sabino Arana 1, 08028, Barcelona, Spain
- Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain
| | - David Boada
- BCNatal Fetal Medicine Research Center (Hospital Clínic and Hospital Sant Joan de Déu), University of Barcelona, Sabino Arana 1, 08028, Barcelona, Spain
| | - Isabel Blanco
- Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain
- Pneumology Department, Respiratory Institute, Hospital Clínic, University of Barcelona, Barcelona, Spain
- Centre for Biomedical Research on Respiratory Diseases (CIBER-ES), Madrid, Spain
| | - Rosa Faner
- Centre for Biomedical Research on Respiratory Diseases (CIBER-ES), Madrid, Spain
| | - Francesc Figueras
- BCNatal Fetal Medicine Research Center (Hospital Clínic and Hospital Sant Joan de Déu), University of Barcelona, Sabino Arana 1, 08028, Barcelona, Spain
- Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain
| | - Àlvar Agustí
- Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain
- Pneumology Department, Respiratory Institute, Hospital Clínic, University of Barcelona, Barcelona, Spain
- Centre for Biomedical Research on Respiratory Diseases (CIBER-ES), Madrid, Spain
- Cathedra Salud Respiratoria, University of Barcelona, Barcelona, Spain
| | - Eduard Gratacós
- BCNatal Fetal Medicine Research Center (Hospital Clínic and Hospital Sant Joan de Déu), University of Barcelona, Sabino Arana 1, 08028, Barcelona, Spain
- Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain
- Centre for Biomedical Research on Rare Diseases (CIBER-ER), Madrid, Spain
| | - Francesca Crovetto
- BCNatal Fetal Medicine Research Center (Hospital Clínic and Hospital Sant Joan de Déu), University of Barcelona, Sabino Arana 1, 08028, Barcelona, Spain
- Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain
- Centre for Biomedical Research on Rare Diseases (CIBER-ER), Madrid, Spain
| | | | - Fàtima Crispi
- BCNatal Fetal Medicine Research Center (Hospital Clínic and Hospital Sant Joan de Déu), University of Barcelona, Sabino Arana 1, 08028, Barcelona, Spain.
- Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain.
- Centre for Biomedical Research on Rare Diseases (CIBER-ER), Madrid, Spain.
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Abaci Turk E, Yun HJ, Feldman HA, Lee JY, Lee HJ, Bibbo C, Zhou C, Tamen R, Grant PE, Im K. Association between placental oxygen transport and fetal brain cortical development: a study in monochorionic diamniotic twins. Cereb Cortex 2024; 34:bhad383. [PMID: 37885155 PMCID: PMC11032198 DOI: 10.1093/cercor/bhad383] [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: 06/28/2023] [Revised: 09/25/2023] [Accepted: 09/26/2023] [Indexed: 10/28/2023] Open
Abstract
Normal cortical growth and the resulting folding patterns are crucial for normal brain function. Although cortical development is largely influenced by genetic factors, environmental factors in fetal life can modify the gene expression associated with brain development. As the placenta plays a vital role in shaping the fetal environment, affecting fetal growth through the exchange of oxygen and nutrients, placental oxygen transport might be one of the environmental factors that also affect early human cortical growth. In this study, we aimed to assess the placental oxygen transport during maternal hyperoxia and its impact on fetal brain development using MRI in identical twins to control for genetic and maternal factors. We enrolled 9 pregnant subjects with monochorionic diamniotic twins (30.03 ± 2.39 gestational weeks [mean ± SD]). We observed that the fetuses with slower placental oxygen delivery had reduced volumetric and surface growth of the cerebral cortex. Moreover, when the difference between placenta oxygen delivery increased between the twin pairs, sulcal folding patterns were more divergent. Thus, there is a significant relationship between placental oxygen transport and fetal brain cortical growth and folding in monochorionic twins.
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Affiliation(s)
- Esra Abaci Turk
- Department of Pediatrics, Harvard Medical School, 300 Longwood Ave, Boston, MA 02115, United States
- Division of Newborn Medicine, Boston Children’s Hospital, 300 Longwood Ave, Boston, MA 02115, United States
- Fetal Neonatal Neuroimaging and Developmental Science Center, Boston Children’s Hospital, 401 Park Dr, Boston, MA 02115, United States
| | - Hyuk Jin Yun
- Department of Pediatrics, Harvard Medical School, 300 Longwood Ave, Boston, MA 02115, United States
- Division of Newborn Medicine, Boston Children’s Hospital, 300 Longwood Ave, Boston, MA 02115, United States
- Fetal Neonatal Neuroimaging and Developmental Science Center, Boston Children’s Hospital, 401 Park Dr, Boston, MA 02115, United States
| | - Henry A Feldman
- Department of Pediatrics, Harvard Medical School, 300 Longwood Ave, Boston, MA 02115, United States
- Division of Newborn Medicine, Boston Children’s Hospital, 300 Longwood Ave, Boston, MA 02115, United States
- Institutional Centers for Clinical and Translational Research, Boston Children’s Hospital, 300 Longwood Ave, Boston, MA 02115, United States
| | - Joo Young Lee
- Department of Pediatrics, Hanyang University College of Medicine, 222, Wangsimni-ro, Seongdong-gu, Seoul, 04763, South Korea
| | - Hyun Ju Lee
- Department of Pediatrics, Hanyang University College of Medicine, 222, Wangsimni-ro, Seongdong-gu, Seoul, 04763, South Korea
| | - Carolina Bibbo
- Department of Obstetrics and Gynecology, Brigham and Women's Hospital, 75 Francis St, Boston, MA 02115, United States
| | - Cindy Zhou
- Division of Newborn Medicine, Boston Children’s Hospital, 300 Longwood Ave, Boston, MA 02115, United States
- Fetal Neonatal Neuroimaging and Developmental Science Center, Boston Children’s Hospital, 401 Park Dr, Boston, MA 02115, United States
| | - Rubii Tamen
- Division of Newborn Medicine, Boston Children’s Hospital, 300 Longwood Ave, Boston, MA 02115, United States
- Fetal Neonatal Neuroimaging and Developmental Science Center, Boston Children’s Hospital, 401 Park Dr, Boston, MA 02115, United States
| | - Patricia Ellen Grant
- Department of Pediatrics, Harvard Medical School, 300 Longwood Ave, Boston, MA 02115, United States
- Division of Newborn Medicine, Boston Children’s Hospital, 300 Longwood Ave, Boston, MA 02115, United States
- Fetal Neonatal Neuroimaging and Developmental Science Center, Boston Children’s Hospital, 401 Park Dr, Boston, MA 02115, United States
- Department of Radiology, Boston Children’s Hospital, 300 Longwood Ave, Boston, MA 02115, United States
| | - Kiho Im
- Department of Pediatrics, Harvard Medical School, 300 Longwood Ave, Boston, MA 02115, United States
- Division of Newborn Medicine, Boston Children’s Hospital, 300 Longwood Ave, Boston, MA 02115, United States
- Fetal Neonatal Neuroimaging and Developmental Science Center, Boston Children’s Hospital, 401 Park Dr, Boston, MA 02115, United States
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3
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Herrera CL, Kim MJ, Do QN, Owen DM, Fei B, Twickler DM, Spong CY. The human placenta project: Funded studies, imaging technologies, and future directions. Placenta 2023; 142:27-35. [PMID: 37634371 PMCID: PMC11257151 DOI: 10.1016/j.placenta.2023.08.067] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/13/2023] [Revised: 08/16/2023] [Accepted: 08/19/2023] [Indexed: 08/29/2023]
Abstract
The placenta plays a critical role in fetal development. It serves as a multi-functional organ that protects and nurtures the fetus during pregnancy. However, despite its importance, the intricacies of placental structure and function in normal and diseased states have remained largely unexplored. Thus, in 2014, the National Institute of Child Health and Human Development launched the Human Placenta Project (HPP). As of May 2023, the HPP has awarded over $101 million in research funds, resulting in 41 funded studies and 459 publications. We conducted a comprehensive review of these studies and publications to identify areas of funded research, advances in those areas, limitations of current research, and continued areas of need. This paper will specifically review the funded studies by the HPP, followed by an in-depth discussion on advances and gaps within placental-focused imaging. We highlight the progress within magnetic reasonance imaging and ultrasound, including development of tools for the assessment of placental function and structure.
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Affiliation(s)
- Christina L Herrera
- Department of Obstetrics and Gynecology, UT Southwestern Medical Center, and Parkland Health Dallas, Texas, USA; Green Center for Reproductive Biology Sciences, UT Southwestern Medical Center, Dallas, TX, USA.
| | - Meredith J Kim
- University of Texas Southwestern Medical School, Dallas, TX, USA
| | - Quyen N Do
- Department of Radiology, UT Southwestern Medical Center, Dallas, TX, USA
| | - David M Owen
- Department of Obstetrics and Gynecology, UT Southwestern Medical Center, and Parkland Health Dallas, Texas, USA; Green Center for Reproductive Biology Sciences, UT Southwestern Medical Center, Dallas, TX, USA
| | - Baowei Fei
- Department of Radiology, UT Southwestern Medical Center, Dallas, TX, USA; Advanced Imaging Research Center, UT Southwestern Medical Center, Dallas, TX, USA; Department of Bioengineering, University of Texas at Dallas, Dallas, TX, USA
| | - Diane M Twickler
- Department of Obstetrics and Gynecology, UT Southwestern Medical Center, and Parkland Health Dallas, Texas, USA; Department of Radiology, UT Southwestern Medical Center, Dallas, TX, USA
| | - Catherine Y Spong
- Department of Obstetrics and Gynecology, UT Southwestern Medical Center, and Parkland Health Dallas, Texas, USA
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Taymourtash A, Schwartz E, Nenning KH, Sobotka D, Licandro R, Glatter S, Diogo MC, Golland P, Grant E, Prayer D, Kasprian G, Langs G. Fetal development of functional thalamocortical and cortico-cortical connectivity. Cereb Cortex 2023; 33:5613-5624. [PMID: 36520481 PMCID: PMC10152101 DOI: 10.1093/cercor/bhac446] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/24/2022] [Revised: 08/22/2022] [Accepted: 08/23/2022] [Indexed: 12/23/2022] Open
Abstract
Measuring and understanding functional fetal brain development in utero is critical for the study of the developmental foundations of our cognitive abilities, possible early detection of disorders, and their prevention. Thalamocortical connections are an intricate component of shaping the cortical layout, but so far, only ex-vivo studies provide evidence of how axons enter the sub-plate and cortex during this highly dynamic phase. Evidence for normal in-utero development of the functional thalamocortical connectome in humans is missing. Here, we modeled fetal functional thalamocortical connectome development using in-utero functional magnetic resonance imaging in fetuses observed from 19th to 40th weeks of gestation (GW). We observed a peak increase of thalamocortical functional connectivity strength between 29th and 31st GW, right before axons establish synapses in the cortex. The cortico-cortical connectivity increases in a similar time window, and exhibits significant functional laterality in temporal-superior, -medial, and -inferior areas. Homologous regions exhibit overall similar mirrored connectivity profiles, but this similarity decreases during gestation giving way to a more diverse cortical interconnectedness. Our results complement the understanding of structural development of the human connectome and may serve as the basis for the investigation of disease and deviations from a normal developmental trajectory of connectivity development.
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Affiliation(s)
- Athena Taymourtash
- Computational Imaging Research Lab, Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Waehringer Guertel 18-20, A-1090 Vienna, Austria
| | - Ernst Schwartz
- Computational Imaging Research Lab, Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Waehringer Guertel 18-20, A-1090 Vienna, Austria
| | - Karl-Heinz Nenning
- Computational Imaging Research Lab, Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Waehringer Guertel 18-20, A-1090 Vienna, Austria
- Center for Biomedical Imaging and Neuromodulation, Nathan Kline Institute, 140, Old Orangeburg Road, Orangeburg, NY 10962, United States
| | - Daniel Sobotka
- Computational Imaging Research Lab, Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Waehringer Guertel 18-20, A-1090 Vienna, Austria
| | - Roxane Licandro
- Computational Imaging Research Lab, Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Waehringer Guertel 18-20, A-1090 Vienna, Austria
- Laboratory for Computational Neuroimaging, A.A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, Bldg. 149, 13th Street, Charlestown, MA 02129, United States
| | - Sarah Glatter
- Division of Neuroradiology and Musculoskeletal Radiology, Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Waehringer Guertel 18-20, A-1090 Vienna, Austria
| | - Mariana Cardoso Diogo
- Division of Neuroradiology and Musculoskeletal Radiology, Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Waehringer Guertel 18-20, A-1090 Vienna, Austria
- Radiology Department, Hospital CUF Tejo, Av. 24 de Julho 171A, 1350-352 Lisboa, Portugal
| | - Polina Golland
- Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology, 77, Massachusetts Avenue, Cambridge, MA 02139, United States
| | - Ellen Grant
- Fetal-Neonatal Neuroimaging and Developmental Science Center, Boston Children's Hospital, Harvard Medical School, 300, Longwood Avenue, Boston, MA 02115, United States
| | - Daniela Prayer
- Division of Neuroradiology and Musculoskeletal Radiology, Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Waehringer Guertel 18-20, A-1090 Vienna, Austria
| | - Gregor Kasprian
- Division of Neuroradiology and Musculoskeletal Radiology, Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Waehringer Guertel 18-20, A-1090 Vienna, Austria
| | - Georg Langs
- Computational Imaging Research Lab, Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Waehringer Guertel 18-20, A-1090 Vienna, Austria
- Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology, 77, Massachusetts Avenue, Cambridge, MA 02139, United States
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Sobotka D, Ebner M, Schwartz E, Nenning KH, Taymourtash A, Vercauteren T, Ourselin S, Kasprian G, Prayer D, Langs G, Licandro R. Motion correction and volumetric reconstruction for fetal functional magnetic resonance imaging data. Neuroimage 2022; 255:119213. [PMID: 35430359 DOI: 10.1016/j.neuroimage.2022.119213] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/19/2021] [Revised: 03/21/2022] [Accepted: 04/13/2022] [Indexed: 10/18/2022] Open
Abstract
Motion correction is an essential preprocessing step in functional Magnetic Resonance Imaging (fMRI) of the fetal brain with the aim to remove artifacts caused by fetal movement and maternal breathing and consequently to suppress erroneous signal correlations. Current motion correction approaches for fetal fMRI choose a single 3D volume from a specific acquisition timepoint with least motion artefacts as reference volume, and perform interpolation for the reconstruction of the motion corrected time series. The results can suffer, if no low-motion frame is available, and if reconstruction does not exploit any assumptions about the continuity of the fMRI signal. Here, we propose a novel framework, which estimates a high-resolution reference volume by using outlier-robust motion correction, and by utilizing Huber L2 regularization for intra-stack volumetric reconstruction of the motion-corrected fetal brain fMRI. We performed an extensive parameter study to investigate the effectiveness of motion estimation and present in this work benchmark metrics to quantify the effect of motion correction and regularised volumetric reconstruction approaches on functional connectivity computations. We demonstrate the proposed framework's ability to improve functional connectivity estimates, reproducibility and signal interpretability, which is clinically highly desirable for the establishment of prognostic noninvasive imaging biomarkers. The motion correction and volumetric reconstruction framework is made available as an open-source package of NiftyMIC.
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Affiliation(s)
- Daniel Sobotka
- Computational Imaging Research Lab, Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Vienna, Austria
| | - Michael Ebner
- School of Biomedical Engineering & Imaging Sciences, King's College London, London, United Kingdom
| | - Ernst Schwartz
- Computational Imaging Research Lab, Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Vienna, Austria
| | - Karl-Heinz Nenning
- Computational Imaging Research Lab, Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Vienna, Austria; Center for Biomedical Imaging and Neuromodulation, Nathan Kline Institute, Orangeburg, NY, USA
| | - Athena Taymourtash
- Computational Imaging Research Lab, Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Vienna, Austria
| | - Tom Vercauteren
- School of Biomedical Engineering & Imaging Sciences, King's College London, London, United Kingdom
| | - Sebastien Ourselin
- School of Biomedical Engineering & Imaging Sciences, King's College London, London, United Kingdom
| | - Gregor Kasprian
- Division of Neuroradiology and Musculoskeletal Radiology, Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Vienna, Austria
| | - Daniela Prayer
- Division of Neuroradiology and Musculoskeletal Radiology, Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Vienna, Austria
| | - Georg Langs
- Computational Imaging Research Lab, Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Vienna, Austria.
| | - Roxane Licandro
- Computational Imaging Research Lab, Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Vienna, Austria; Laboratory for Computational Neuroimaging, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, Charlestown, MA, USA.
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Abulnaga SM, Turk EA, Bessmeltsev M, Grant PE, Solomon J, Golland P. Volumetric Parameterization of the Placenta to a Flattened Template. IEEE TRANSACTIONS ON MEDICAL IMAGING 2022; 41:925-936. [PMID: 34784274 PMCID: PMC9069541 DOI: 10.1109/tmi.2021.3128743] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/13/2023]
Abstract
We present a volumetric mesh-based algorithm for parameterizing the placenta to a flattened template to enable effective visualization of local anatomy and function. MRI shows potential as a research tool as it provides signals directly related to placental function. However, due to the curved and highly variable in vivo shape of the placenta, interpreting and visualizing these images is difficult. We address interpretation challenges by mapping the placenta so that it resembles the familiar ex vivo shape. We formulate the parameterization as an optimization problem for mapping the placental shape represented by a volumetric mesh to a flattened template. We employ the symmetric Dirichlet energy to control local distortion throughout the volume. Local injectivity in the mapping is enforced by a constrained line search during the gradient descent optimization. We validate our method using a research study of 111 placental shapes extracted from BOLD MRI images. Our mapping achieves sub-voxel accuracy in matching the template while maintaining low distortion throughout the volume. We demonstrate how the resulting flattening of the placenta improves visualization of anatomy and function. Our code is freely available at https://github.com/mabulnaga/placenta-flattening.
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Rajagopalan V, Deoni S, Panigrahy A, Thomason ME. Is fetal MRI ready for neuroimaging prime time? An examination of progress and remaining areas for development. Dev Cogn Neurosci 2021; 51:100999. [PMID: 34391003 PMCID: PMC8365463 DOI: 10.1016/j.dcn.2021.100999] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/12/2021] [Revised: 07/08/2021] [Accepted: 08/03/2021] [Indexed: 11/25/2022] Open
Abstract
A major challenge in designing large-scale, multi-site studies is developing a core, scalable protocol that retains the innovation of scientific advances while also lending itself to the variability in experience and resources across sites. In the development of a common Healthy Brain and Child Development (HBCD) protocol, one of the chief questions is "is fetal MRI ready for prime-time?" While there is agreement about the value of prenatal data obtained non-invasively through MRI, questions about practicality abound. There has been rapid progress over the past years in fetal and placental MRI methodology but there is uncertainty about whether the gains afforded outweigh the challenges in supporting fetal MRI protocols at scale. Here, we will define challenges inherent in building a common protocol across sites with variable expertise and will propose a tentative framework for evaluation of design decisions. We will compare and contrast various design considerations for both normative and high-risk populations, in the setting of the post-COVID era. We will conclude with articulation of the benefits of overcoming these challenges and would lend to the primary questions articulated in the HBCD initiative.
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Affiliation(s)
- Vidya Rajagopalan
- Department of Radiology, Keck School of Medicine, University of Southern California and Childrens Hospital of Los Angeles, United States.
| | - Sean Deoni
- Department of Pediatrics, Memorial Hospital of Rhode Island, United States
| | - Ashok Panigrahy
- Department of Radiology, University of Pittsburgh Medical School and Children's Hospital of Pittsburgh, United States
| | - Moriah E Thomason
- Departments of Child and Adolescent Psychiatry and Population Health, Hassenfeld Children's Hospital at NYU Langone, United States
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8
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Andescavage N, Limperopoulos C. Emerging placental biomarkers of health and disease through advanced magnetic resonance imaging (MRI). Exp Neurol 2021; 347:113868. [PMID: 34562472 DOI: 10.1016/j.expneurol.2021.113868] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/02/2021] [Revised: 09/09/2021] [Accepted: 09/19/2021] [Indexed: 12/12/2022]
Abstract
Placental dysfunction is a major cause of fetal demise, fetal growth restriction, and preterm birth, as well as significant maternal morbidity and mortality. Infant survivors of placental dysfunction are at elevatedrisk for lifelong neuropsychiatric morbidity. However, despite the significant consequences of placental disease, there are no clinical tools to directly and non-invasively assess and measure placental function in pregnancy. In this work, we will review advanced MRI techniques applied to the study of the in vivo human placenta in order to better detail placental structure, architecture, and function. We will discuss the potential of these measures to serve as optimal biomarkers of placental dysfunction and review the evidence of these tools in the discrimination of health and disease in pregnancy. Efforts to advance our understanding of in vivo placental development are necessary if we are to optimize healthy pregnancy outcomes and prevent brain injury in successive generations. Current management of many high-risk pregnancies cannot address placental maldevelopment or injury, given the standard tools available to clinicians. Once accurate biomarkers of placental development and function are constructed, the subsequent steps will be to introduce maternal and fetal therapeutics targeting at optimizing placental function. Applying these biomarkers in future studies will allow for real-time assessments of safety and efficacy of novel interventions aimed at improving maternal-fetal well-being.
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Affiliation(s)
- Nickie Andescavage
- Developing Brain Institute, Department of Radiology, Children's National, Washington DC, USA; Department of Neonatology, Children's National, Washington DC, USA
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9
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Davidson L, Boland MR. Towards deep phenotyping pregnancy: a systematic review on artificial intelligence and machine learning methods to improve pregnancy outcomes. Brief Bioinform 2021; 22:6065792. [PMID: 33406530 PMCID: PMC8424395 DOI: 10.1093/bib/bbaa369] [Citation(s) in RCA: 26] [Impact Index Per Article: 8.7] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/22/2020] [Revised: 10/13/2020] [Accepted: 11/18/2020] [Indexed: 12/16/2022] Open
Abstract
Objective Development of novel informatics methods focused on improving pregnancy outcomes remains an active area of research. The purpose of this study is to systematically review the ways that artificial intelligence (AI) and machine learning (ML), including deep learning (DL), methodologies can inform patient care during pregnancy and improve outcomes. Materials and methods We searched English articles on EMBASE, PubMed and SCOPUS. Search terms included ML, AI, pregnancy and informatics. We included research articles and book chapters, excluding conference papers, editorials and notes. Results We identified 127 distinct studies from our queries that were relevant to our topic and included in the review. We found that supervised learning methods were more popular (n = 69) than unsupervised methods (n = 9). Popular methods included support vector machines (n = 30), artificial neural networks (n = 22), regression analysis (n = 17) and random forests (n = 16). Methods such as DL are beginning to gain traction (n = 13). Common areas within the pregnancy domain where AI and ML methods were used the most include prenatal care (e.g. fetal anomalies, placental functioning) (n = 73); perinatal care, birth and delivery (n = 20); and preterm birth (n = 13). Efforts to translate AI into clinical care include clinical decision support systems (n = 24) and mobile health applications (n = 9). Conclusions Overall, we found that ML and AI methods are being employed to optimize pregnancy outcomes, including modern DL methods (n = 13). Future research should focus on less-studied pregnancy domain areas, including postnatal and postpartum care (n = 2). Also, more work on clinical adoption of AI methods and the ethical implications of such adoption is needed.
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Affiliation(s)
- Lena Davidson
- MS degree at College of St. Scholastica, Duluth, MN, USA
| | - Mary Regina Boland
- Department of Biostatistics, Epidemiology, and Informatics at the University of Pennsylvania
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Critchley HOD, Babayev E, Bulun SE, Clark S, Garcia-Grau I, Gregersen PK, Kilcoyne A, Kim JYJ, Lavender M, Marsh EE, Matteson KA, Maybin JA, Metz CN, Moreno I, Silk K, Sommer M, Simon C, Tariyal R, Taylor HS, Wagner GP, Griffith LG. Menstruation: science and society. Am J Obstet Gynecol 2020; 223:624-664. [PMID: 32707266 PMCID: PMC7661839 DOI: 10.1016/j.ajog.2020.06.004] [Citation(s) in RCA: 123] [Impact Index Per Article: 30.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/20/2020] [Revised: 05/13/2020] [Accepted: 06/03/2020] [Indexed: 12/11/2022]
Abstract
Women's health concerns are generally underrepresented in basic and translational research, but reproductive health in particular has been hampered by a lack of understanding of basic uterine and menstrual physiology. Menstrual health is an integral part of overall health because between menarche and menopause, most women menstruate. Yet for tens of millions of women around the world, menstruation regularly and often catastrophically disrupts their physical, mental, and social well-being. Enhancing our understanding of the underlying phenomena involved in menstruation, abnormal uterine bleeding, and other menstruation-related disorders will move us closer to the goal of personalized care. Furthermore, a deeper mechanistic understanding of menstruation-a fast, scarless healing process in healthy individuals-will likely yield insights into a myriad of other diseases involving regulation of vascular function locally and systemically. We also recognize that many women now delay pregnancy and that there is an increasing desire for fertility and uterine preservation. In September 2018, the Gynecologic Health and Disease Branch of the Eunice Kennedy Shriver National Institute of Child Health and Human Development convened a 2-day meeting, "Menstruation: Science and Society" with an aim to "identify gaps and opportunities in menstruation science and to raise awareness of the need for more research in this field." Experts in fields ranging from the evolutionary role of menstruation to basic endometrial biology (including omic analysis of the endometrium, stem cells and tissue engineering of the endometrium, endometrial microbiome, and abnormal uterine bleeding and fibroids) and translational medicine (imaging and sampling modalities, patient-focused analysis of menstrual disorders including abnormal uterine bleeding, smart technologies or applications and mobile health platforms) to societal challenges in health literacy and dissemination frameworks across different economic and cultural landscapes shared current state-of-the-art and future vision, incorporating the patient voice at the launch of the meeting. Here, we provide an enhanced meeting report with extensive up-to-date (as of submission) context, capturing the spectrum from how the basic processes of menstruation commence in response to progesterone withdrawal, through the role of tissue-resident and circulating stem and progenitor cells in monthly regeneration-and current gaps in knowledge on how dysregulation leads to abnormal uterine bleeding and other menstruation-related disorders such as adenomyosis, endometriosis, and fibroids-to the clinical challenges in diagnostics, treatment, and patient and societal education. We conclude with an overview of how the global agenda concerning menstruation, and specifically menstrual health and hygiene, are gaining momentum, ranging from increasing investment in addressing menstruation-related barriers facing girls in schools in low- to middle-income countries to the more recent "menstrual equity" and "period poverty" movements spreading across high-income countries.
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Affiliation(s)
- Hilary O D Critchley
- Medical Research Council Centre for Reproductive Health, The University of Edinburgh, United Kingdom.
| | - Elnur Babayev
- Department of Obstetrics and Gynecology, Feinberg School of Medicine, Northwestern University, Chicago, IL
| | - Serdar E Bulun
- Department of Obstetrics and Gynecology, Feinberg School of Medicine, Northwestern University, Chicago, IL
| | | | - Iolanda Garcia-Grau
- Igenomix Foundation-Instituto de Investigación Sanitaria Hospital Clínico, INCLIVA, Valencia, Spain; Department of Pediatrics, Obstetrics and Gynecology, School of Medicine, University of Valencia, Valencia, Spain
| | - Peter K Gregersen
- The Feinstein Institutes for Medical Research, Northwell Health, Manhasset, NY
| | | | | | | | - Erica E Marsh
- Division of Reproductive Endocrinology and Infertility, Department of Obstetrics and Gynecology, University of Michigan Medical School, Ann Arbor, MI
| | - Kristen A Matteson
- Division of Research, Department of Obstetrics and Gynecology, Women and Infants Hospital, Warren Alpert Medical School of Brown University, Providence, RI
| | - Jacqueline A Maybin
- Medical Research Council Centre for Reproductive Health, The University of Edinburgh, United Kingdom
| | - Christine N Metz
- The Feinstein Institutes for Medical Research, Northwell Health, Manhasset, NY
| | - Inmaculada Moreno
- Igenomix Foundation-Instituto de Investigación Sanitaria Hospital Clínico, INCLIVA, Valencia, Spain
| | - Kami Silk
- Department of Communication, University of Delaware, Newark, DE
| | - Marni Sommer
- Department of Sociomedical Sciences, Columbia University Mailman School of Public Health, New York, NY
| | - Carlos Simon
- Igenomix Foundation-Instituto de Investigación Sanitaria Hospital Clínico, INCLIVA, Valencia, Spain; Department of Pediatrics, Obstetrics and Gynecology, School of Medicine, University of Valencia, Valencia, Spain; Beth Israel Deaconess Medical Center, Harvard University, Boston, MA; Department of Obstetrics and Gynecology, Baylor College of Medicine, Houston, TX
| | | | - Hugh S Taylor
- Department of Obstetrics, Gynecology and Reproductive Sciences, Yale School of Medicine, New Haven, CT
| | - Günter P Wagner
- Department of Ecology and Evolutionary Biology, Department of Obstetrics, Gynecology and Reproductive Sciences, Systems Biology Institute, Yale University, New Haven, CT; Department of Obstetrics and Gynecology, Wayne State University, Detroit, MI
| | - Linda G Griffith
- Center for Gynepathology Research, Massachusetts Institute of Technology, Cambridge, MA
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11
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Abaci Turk E, Abulnaga SM, Luo J, Stout JN, Feldman HA, Turk A, Gagoski B, Wald LL, Adalsteinsson E, Roberts DJ, Bibbo C, Robinson JN, Golland P, Grant PE, Barth WH. Placental MRI: Effect of maternal position and uterine contractions on placental BOLD MRI measurements. Placenta 2020; 95:69-77. [PMID: 32452404 DOI: 10.1016/j.placenta.2020.04.008] [Citation(s) in RCA: 19] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/22/2020] [Revised: 04/16/2020] [Accepted: 04/17/2020] [Indexed: 12/24/2022]
Abstract
INTRODUCTION Before using blood-oxygen-level-dependent magnetic resonance imaging (BOLD MRI) during maternal hyperoxia as a method to detect individual placental dysfunction, it is necessary to understand spatiotemporal variations that represent normal placental function. We investigated the effect of maternal position and Braxton-Hicks contractions on estimates obtained from BOLD MRI of the placenta during maternal hyperoxia. METHODS For 24 uncomplicated singleton pregnancies (gestational age 27-36 weeks), two separate BOLD MRI datasets were acquired, one in the supine and one in the left lateral maternal position. The maternal oxygenation was adjusted as 5 min of room air (21% O2), followed by 5 min of 100% FiO2. After datasets were corrected for signal non-uniformities and motion, global and regional BOLD signal changes in R2* and voxel-wise Time-To-Plateau (TTP) in the placenta were measured. The overall placental and uterine volume changes were determined across time to detect contractions. RESULTS In mothers without contractions, increases in global placental R2* in the supine position were larger compared to the left lateral position with maternal hyperoxia. Maternal position did not alter global TTP but did result in regional changes in TTP. 57% of the subjects had Braxton-Hicks contractions and 58% of these had global placental R2* decreases during the contraction. CONCLUSION Both maternal position and Braxton-Hicks contractions significantly affect global and regional changes in placental R2* and regional TTP. This suggests that both factors must be taken into account in analyses when comparing placental BOLD signals over time within and between individuals.
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Affiliation(s)
- Esra Abaci Turk
- Fetal-Neonatal Neuroimaging & Developmental Science Center, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA.
| | - S Mazdak Abulnaga
- Computer Science and Artificial Intelligence Laboratory (CSAIL), Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Jie Luo
- Fetal-Neonatal Neuroimaging & Developmental Science Center, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA; School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China
| | - Jeffrey N Stout
- Fetal-Neonatal Neuroimaging & Developmental Science Center, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA
| | - Henry A Feldman
- Institutional Centers for Clinical and Translational Research, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA
| | - Ata Turk
- Electrical Computer Engineering Department, Boston University, Boston, MA, USA
| | - Borjan Gagoski
- Fetal-Neonatal Neuroimaging & Developmental Science Center, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA
| | - Lawrence L Wald
- Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology, Cambridge, MA, USA; Radiology, Harvard Medical School, Boston, MA, United States; Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, United States
| | - Elfar Adalsteinsson
- Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology, Cambridge, MA, USA; Harvard-MIT Health Sciences and Technology; Massachusetts Institute of Technology, Cambridge, MA, USA; Institute for Medical Engineering and Science, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Drucilla J Roberts
- Department of Pathology, Massachusetts General Hospital, Boston, MA, USA
| | - Carolina Bibbo
- Maternal Fetal Medicine, Brigham and Women's Hospital, Boston, MA, USA
| | - Julian N Robinson
- Maternal Fetal Medicine, Brigham and Women's Hospital, Boston, MA, USA
| | - Polina Golland
- Computer Science and Artificial Intelligence Laboratory (CSAIL), Massachusetts Institute of Technology, Cambridge, MA, USA; Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - P Ellen Grant
- Fetal-Neonatal Neuroimaging & Developmental Science Center, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA
| | - William H Barth
- Maternal-Fetal Medicine, Obstetrics and Gynecology, Massachusetts General Hospital, Boston, MA, USA
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12
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Sørensen A, Hutter J, Seed M, Grant PE, Gowland P. T2*-weighted placental MRI: basic research tool or emerging clinical test for placental dysfunction? ULTRASOUND IN OBSTETRICS & GYNECOLOGY : THE OFFICIAL JOURNAL OF THE INTERNATIONAL SOCIETY OF ULTRASOUND IN OBSTETRICS AND GYNECOLOGY 2020; 55:293-302. [PMID: 31452271 DOI: 10.1002/uog.20855] [Citation(s) in RCA: 38] [Impact Index Per Article: 9.5] [Reference Citation Analysis] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/11/2019] [Revised: 08/12/2019] [Accepted: 08/19/2019] [Indexed: 06/10/2023]
Affiliation(s)
- A Sørensen
- Department of Obstetrics and Gynecology, Aalborg University Hospital, Aalborg, Denmark
| | - J Hutter
- Center for Medical Engineering, King's College London, London, UK
| | - M Seed
- Department of Cardiology, The Hospital for Sick Children, Toronto, Canada
| | - P E Grant
- Fetal-Neonatal Neuroimaging and Developmental Science Center, Boston Children's Hospital, Boston, MA, USA
| | - P Gowland
- Sir Peter Mansfield Imaging Centre, Nottingham University, Nottingham, UK
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13
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You W, Andescavage NN, Kapse K, Donofrio MT, Jacobs M, Limperopoulos C. Hemodynamic Responses of the Placenta and Brain to Maternal Hyperoxia in Fetuses with Congenital Heart Disease by Using Blood Oxygen-Level Dependent MRI. Radiology 2019; 294:141-148. [PMID: 31687920 DOI: 10.1148/radiol.2019190751] [Citation(s) in RCA: 33] [Impact Index Per Article: 6.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
Abstract
Background Impaired brain development in fetuses with congenital heart disease (CHD) may result from inadequate cerebral oxygen supply in utero. Purpose To test whether fetal cerebral oxygenation can be increased by maternal oxygen administration, effects of maternal hyperoxia on blood oxygenation of the placenta and fetal brain were examined by using blood oxygenation level-dependent (BOLD) functional MRI. Materials and Methods In this prospective study, BOLD MRI was performed in 86 fetuses (56 healthy fetuses and 30 fetuses diagnosed with CHD) between 22 and 39 weeks gestational age (GA) from May 2015 to December 2017, with the following study design: phase I, 2-minute resting state at baseline (room air); phase II, 6-minute maternal hyperoxia with 100% oxygen; and phase III, 5.6-minute return to resting state. After motion correction, the signals were averaged over the placenta and fetal brain and converted to the change in R2* (ΔR2*). Fetuses with CHD were categorized into those with a single ventricle (SV) or two ventricles (TVs) and those with aortic obstruction (AO) or non-AO. Data were analyzed by using generalized linear mixed models controlling for GA and sex. Results Placental ΔR2* increased during maternal hyperoxia in healthy fetuses and fetuses with CHD, but it was higher in SV CHD (mean ΔR2*, 1.3 sec-1 ± 0.1 [standard error; P < .01], 1.9 sec-1 ± 0.2 [P < .01], and 1.0 sec-1 ± 0.3 [P < .01], respectively, for control fetuses, fetuses with SV CHD, and fetuses with TV CHD). Placental ΔR2* during maternal hyperoxia changed with GA in healthy control fetuses and fetuses with SV or AO CHD (ΔR2* per week, 0.1 sec-1 ± 0 [P < .01], 0.2 sec-1 ± 0 [P = .01], and 0.2 sec-1 ± 0 [P = .01], respectively), but not in fetuses with CHD and TV or non-AO. Fetal brain ΔR2* was constant across all phases in healthy control fetuses and fetuses with TV CHD but increased during maternal hyperoxia in fetuses with SV or AO CHD (mean ΔR2*, 0.7 sec-1 ± 0.2 [P = .01] and 0.5 sec-1 ± 0.2 [P = .02], respectively). Conclusion Six minutes of maternal hyperoxia increased placental oxygenation in healthy fetuses and fetuses with congenital heart disease, and it selectively increased cerebral blood oxygenation in fetuses with single ventricle or aortic obstruction. © RSNA, 2019 Online supplemental material is available for this article.
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Affiliation(s)
- Wonsang You
- From the Divisions of Diagnostic Imaging & Radiology (W.Y., K.K., C.L.), Neonatology (N.N.A.), Cardiology (M.T.D.), Fetal & Transitional Medicine (M.T.D., C.L.), and Epidemiology and Biostatistics (M.J.), Children's National Hospital, 111 Michigan Ave NW, Washington, DC 20010; and Department of Pediatrics, George Washington University School of Medicine, Washington, DC (N.N.A., M.T.D., C.L.)
| | - Nickie N Andescavage
- From the Divisions of Diagnostic Imaging & Radiology (W.Y., K.K., C.L.), Neonatology (N.N.A.), Cardiology (M.T.D.), Fetal & Transitional Medicine (M.T.D., C.L.), and Epidemiology and Biostatistics (M.J.), Children's National Hospital, 111 Michigan Ave NW, Washington, DC 20010; and Department of Pediatrics, George Washington University School of Medicine, Washington, DC (N.N.A., M.T.D., C.L.)
| | - Kushal Kapse
- From the Divisions of Diagnostic Imaging & Radiology (W.Y., K.K., C.L.), Neonatology (N.N.A.), Cardiology (M.T.D.), Fetal & Transitional Medicine (M.T.D., C.L.), and Epidemiology and Biostatistics (M.J.), Children's National Hospital, 111 Michigan Ave NW, Washington, DC 20010; and Department of Pediatrics, George Washington University School of Medicine, Washington, DC (N.N.A., M.T.D., C.L.)
| | - Mary T Donofrio
- From the Divisions of Diagnostic Imaging & Radiology (W.Y., K.K., C.L.), Neonatology (N.N.A.), Cardiology (M.T.D.), Fetal & Transitional Medicine (M.T.D., C.L.), and Epidemiology and Biostatistics (M.J.), Children's National Hospital, 111 Michigan Ave NW, Washington, DC 20010; and Department of Pediatrics, George Washington University School of Medicine, Washington, DC (N.N.A., M.T.D., C.L.)
| | - Marni Jacobs
- From the Divisions of Diagnostic Imaging & Radiology (W.Y., K.K., C.L.), Neonatology (N.N.A.), Cardiology (M.T.D.), Fetal & Transitional Medicine (M.T.D., C.L.), and Epidemiology and Biostatistics (M.J.), Children's National Hospital, 111 Michigan Ave NW, Washington, DC 20010; and Department of Pediatrics, George Washington University School of Medicine, Washington, DC (N.N.A., M.T.D., C.L.)
| | - Catherine Limperopoulos
- From the Divisions of Diagnostic Imaging & Radiology (W.Y., K.K., C.L.), Neonatology (N.N.A.), Cardiology (M.T.D.), Fetal & Transitional Medicine (M.T.D., C.L.), and Epidemiology and Biostatistics (M.J.), Children's National Hospital, 111 Michigan Ave NW, Washington, DC 20010; and Department of Pediatrics, George Washington University School of Medicine, Washington, DC (N.N.A., M.T.D., C.L.)
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14
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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: 1.2] [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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15
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Turk EA, Stout JN, Ha C, Luo J, Gagoski B, Yetisir F, Golland P, Wald LL, Adalsteinsson E, Robinson JN, Roberts DJ, Barth WH, Grant PE. Placental MRI: Developing Accurate Quantitative Measures of Oxygenation. Top Magn Reson Imaging 2019; 28:285-297. [PMID: 31592995 PMCID: PMC7323862 DOI: 10.1097/rmr.0000000000000221] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/28/2023]
Abstract
The Human Placenta Project has focused attention on the need for noninvasive magnetic resonance imaging (MRI)-based techniques to diagnose and monitor placental function throughout pregnancy. The hope is that the management of placenta-related pathologies would be improved if physicians had more direct, real-time measures of placental health to guide clinical decision making. As oxygen alters signal intensity on MRI and oxygen transport is a key function of the placenta, many of the MRI methods under development are focused on quantifying oxygen transport or oxygen content of the placenta. For example, measurements from blood oxygen level-dependent imaging of the placenta during maternal hyperoxia correspond to outcomes in twin pregnancies, suggesting that some aspects of placental oxygen transport can be monitored by MRI. Additional methods are being developed to accurately quantify baseline placental oxygenation by MRI relaxometry. However, direct validation of placental MRI methods is challenging and therefore animal studies and ex vivo studies of human placentas are needed. Here we provide an overview of the current state of the art of oxygen transport and quantification with MRI. We suggest that as these techniques are being developed, increased focus be placed on ensuring they are robust and reliable across individuals and standardized to enable predictive diagnostic models to be generated from the data. The field is still several years away from establishing the clinical benefit of monitoring placental function in real time with MRI, but the promise of individual personalized diagnosis and monitoring of placental disease in real time continues to motivate this effort.
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Affiliation(s)
- Esra Abaci Turk
- Fetal-Neonatal Neuroimaging & Developmental Science Center, Boston Children’s Hospital, MA, USA
| | - Jeffrey N. Stout
- Fetal-Neonatal Neuroimaging & Developmental Science Center, Boston Children’s Hospital, MA, USA
| | - Christopher Ha
- Fetal-Neonatal Neuroimaging & Developmental Science Center, Boston Children’s Hospital, MA, USA
| | - Jie Luo
- School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China
| | - Borjan Gagoski
- Fetal-Neonatal Neuroimaging & Developmental Science Center, Boston Children’s Hospital, MA, USA
| | - Filiz Yetisir
- Fetal-Neonatal Neuroimaging & Developmental Science Center, Boston Children’s Hospital, MA, USA
| | - Polina Golland
- Computer Science and Artificial Intelligence Laboratory (CSAIL), Massachusetts Institute of Technology, Cambridge, MA, USA
- Department of Electrical Engineering and Computer Science Massachusetts Institute of Technology, Cambridge, MA, United States
| | - Lawrence L. Wald
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, USA
| | - Elfar Adalsteinsson
- Department of Electrical Engineering and Computer Science Massachusetts Institute of Technology, Cambridge, MA, United States
- Institute for Medical Engineering and Science, Massachusetts Institute of Technology, Cambridge, MA, United States
| | - Julian N. Robinson
- Department of Obstetrics and Gynecology, Brigham and Women’s Hospital, Boston, USA
| | | | - William H. Barth
- Maternal-Fetal Medicine, Obstetrics and Gynecology, Massachusetts General Hospital, Boston, MA, USA
| | - P. Ellen Grant
- Fetal-Neonatal Neuroimaging & Developmental Science Center, Boston Children’s Hospital, MA, USA
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16
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Vasung L, Abaci Turk E, Ferradal SL, Sutin J, Stout JN, Ahtam B, Lin PY, Grant PE. Exploring early human brain development with structural and physiological neuroimaging. Neuroimage 2019; 187:226-254. [PMID: 30041061 PMCID: PMC6537870 DOI: 10.1016/j.neuroimage.2018.07.041] [Citation(s) in RCA: 80] [Impact Index Per Article: 16.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/23/2017] [Revised: 07/16/2018] [Accepted: 07/16/2018] [Indexed: 12/11/2022] Open
Abstract
Early brain development, from the embryonic period to infancy, is characterized by rapid structural and functional changes. These changes can be studied using structural and physiological neuroimaging methods. In order to optimally acquire and accurately interpret this data, concepts from adult neuroimaging cannot be directly transferred. Instead, one must have a basic understanding of fetal and neonatal structural and physiological brain development, and the important modulators of this process. Here, we first review the major developmental milestones of transient cerebral structures and structural connectivity (axonal connectivity) followed by a summary of the contributions from ex vivo and in vivo MRI. Next, we discuss the basic biology of neuronal circuitry development (synaptic connectivity, i.e. ensemble of direct chemical and electrical connections between neurons), physiology of neurovascular coupling, baseline metabolic needs of the fetus and the infant, and functional connectivity (defined as statistical dependence of low-frequency spontaneous fluctuations seen with functional magnetic resonance imaging (fMRI)). The complementary roles of magnetic resonance imaging (MRI), electroencephalography (EEG), magnetoencephalography (MEG), and near-infrared spectroscopy (NIRS) are discussed. We include a section on modulators of brain development where we focus on the placenta and emerging placental MRI approaches. In each section we discuss key technical limitations of the imaging modalities and some of the limitations arising due to the biology of the system. Although neuroimaging approaches have contributed significantly to our understanding of early brain development, there is much yet to be done and a dire need for technical innovations and scientific discoveries to realize the future potential of early fetal and infant interventions to avert long term disease.
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Affiliation(s)
- Lana Vasung
- Fetal-Neonatal Neuroimaging and Developmental Science Center, Boston Children's Hospital, Harvard Medical School, 300 Longwood Avenue, Boston, MA 02115, USA.
| | - Esra Abaci Turk
- Fetal-Neonatal Neuroimaging and Developmental Science Center, Boston Children's Hospital, Harvard Medical School, 300 Longwood Avenue, Boston, MA 02115, USA.
| | - Silvina L Ferradal
- Fetal-Neonatal Neuroimaging and Developmental Science Center, Boston Children's Hospital, Harvard Medical School, 300 Longwood Avenue, Boston, MA 02115, USA.
| | - Jason Sutin
- Fetal-Neonatal Neuroimaging and Developmental Science Center, Boston Children's Hospital, Harvard Medical School, 300 Longwood Avenue, Boston, MA 02115, USA.
| | - Jeffrey N Stout
- Fetal-Neonatal Neuroimaging and Developmental Science Center, Boston Children's Hospital, Harvard Medical School, 300 Longwood Avenue, Boston, MA 02115, USA.
| | - Banu Ahtam
- Fetal-Neonatal Neuroimaging and Developmental Science Center, Boston Children's Hospital, Harvard Medical School, 300 Longwood Avenue, Boston, MA 02115, USA.
| | - Pei-Yi Lin
- Fetal-Neonatal Neuroimaging and Developmental Science Center, Boston Children's Hospital, Harvard Medical School, 300 Longwood Avenue, Boston, MA 02115, USA.
| | - P Ellen Grant
- Fetal-Neonatal Neuroimaging and Developmental Science Center, Boston Children's Hospital, Harvard Medical School, 300 Longwood Avenue, Boston, MA 02115, USA.
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17
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Hutter J, Slator PJ, Jackson L, Gomes ADS, Ho A, Story L, O’Muircheartaigh J, Teixeira RPAG, Chappell LC, Alexander DC, Rutherford MA, Hajnal JV. Multi-modal functional MRI to explore placental function over gestation. Magn Reson Med 2019; 81:1191-1204. [PMID: 30242899 PMCID: PMC6585747 DOI: 10.1002/mrm.27447] [Citation(s) in RCA: 53] [Impact Index Per Article: 10.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/15/2018] [Revised: 06/08/2018] [Accepted: 06/12/2018] [Indexed: 01/16/2023]
Abstract
PURPOSE To investigate, visualize and quantify the physiology of the human placenta in several dimensions - functional, temporal over gestation, and spatial over the whole organ. METHODS Bespoke MRI techniques, combining a rich diffusion protocol, anatomical data and T2* mapping together with a multi-modal pipeline including motion correction and extracted quantitative features were developed and employed on pregnant women between 22 and 38 weeks gestational age including two pregnancies diagnosed with pre-eclampsia. RESULTS A multi-faceted assessment was demonstrated showing trends of increasing lacunarity, and decreasing T2* and diffusivity over gestation. CONCLUSIONS The obtained multi-modal acquisition and quantification shows promising opportunities for studying evolution, adaptation and compensation processes.
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Affiliation(s)
- Jana Hutter
- Centre for the Developing BrainKing's College LondonUnited Kingdom
- Biomedical Engineering DepartmentKing's College LondonUnited Kingdom
| | - Paddy J. Slator
- Biomedical Engineering DepartmentKing's College LondonUnited Kingdom
| | - Laurence Jackson
- Centre for the Developing BrainKing's College LondonUnited Kingdom
- Biomedical Engineering DepartmentKing's College LondonUnited Kingdom
| | - Ana Dos Santos Gomes
- Centre for the Developing BrainKing's College LondonUnited Kingdom
- Biomedical Engineering DepartmentKing's College LondonUnited Kingdom
| | - Alison Ho
- Women's Health Academic CentreKing's College LondonLondonUnited Kingdom
| | - Lisa Story
- Centre for the Developing BrainKing's College LondonUnited Kingdom
- Women's Health Academic CentreKing's College LondonLondonUnited Kingdom
| | | | - Rui P. A. G. Teixeira
- Centre for the Developing BrainKing's College LondonUnited Kingdom
- Biomedical Engineering DepartmentKing's College LondonUnited Kingdom
| | - Lucy C. Chappell
- Women's Health Academic CentreKing's College LondonLondonUnited Kingdom
| | - Daniel C. Alexander
- Centre for Medical Image Computing and Department of Computer ScienceUniversity College LondonUnited Kingdom
| | | | - Joseph V. Hajnal
- Centre for the Developing BrainKing's College LondonUnited Kingdom
- Biomedical Engineering DepartmentKing's College LondonUnited Kingdom
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18
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Chapman T, Alazraki AL, Eklund MJ. A survey of pediatric diagnostic radiologists in North America: current practices in fetal magnetic resonance imaging. Pediatr Radiol 2018; 48:1924-1935. [PMID: 30178081 DOI: 10.1007/s00247-018-4236-3] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/07/2018] [Revised: 06/30/2018] [Accepted: 08/10/2018] [Indexed: 01/07/2023]
Abstract
BACKGROUND Fetal magnetic resonance imaging (MRI) is an imaging examination in evolution. Rapid developments over recent decades have led to better image quality, an increased number of examinations and greater impact on patient care. OBJECTIVE To gather data regarding current practices among established programs in North America and provide information to radiologists interested in implementing or growing a fetal MRI service. MATERIALS AND METHODS An electronic survey containing 15 questions relevant to the use of fetal MRI was submitted to pediatric radiologists and neuroradiologists. Items regarded scheduling and reporting logistics, magnet strength, patient positioning and patient preparation. Answers and comments were collected, and descriptive statistics were summarized. RESULTS One hundred and six survey responses were evaluated. Of the survey responses, 62/106 (58.5%) allow fetal MR scheduling any time during the day and 72/105 (68.6%) exclusively use 1.5-T strength platforms for fetal MRI, while only 7/105 (6.7%) use exclusively 3 T. Patient positioning is variable: supine, 40/106 (37.8%); left lateral decubitus, 22/106 (20.8%), and, patient's choice, 43/106 (40.6%). Of the centers responding, 51/104 (49.0%) require no particular fasting instructions, while 20/104 (19.2%) request the patient avoid caffeine before the scanning. CONCLUSION Logistical trends in performing fetal MRI may supplement the American College of Radiology's published technical standards and offer guidance to radiologists new to the field.
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Affiliation(s)
- Teresa Chapman
- Department of Radiology, Seattle Children's Hospital, Mail Stop MA.07.220, 4800 Sand Point Way NE, Seattle, WA, 98105, USA.
| | - Adina L Alazraki
- Department of Radiology and Imaging Sciences,Children's Healthcare of Atlanta, Emory University School of Medicine, Atlanta, GA, USA
| | - Meryle J Eklund
- Department of Radiology and Radiological Science, Medical University of South Carolina, Charleston, SC, USA
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19
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Slator PJ, Hutter J, McCabe L, Gomes ADS, Price AN, Panagiotaki E, Rutherford MA, Hajnal JV, Alexander DC. Placenta microstructure and microcirculation imaging with diffusion MRI. Magn Reson Med 2018; 80:756-766. [PMID: 29230859 PMCID: PMC5947291 DOI: 10.1002/mrm.27036] [Citation(s) in RCA: 47] [Impact Index Per Article: 7.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/24/2017] [Revised: 11/14/2017] [Accepted: 11/17/2017] [Indexed: 12/30/2022]
Abstract
PURPOSE To assess which microstructural models best explain the diffusion-weighted MRI signal in the human placenta. METHODS The placentas of nine healthy pregnant subjects were scanned with a multishell, multidirectional diffusion protocol at 3T. A range of multicompartment biophysical models were fit to the data, and ranked using the Bayesian information criterion. RESULTS Anisotropic extensions to the intravoxel incoherent motion model, which consider the effect of coherent orientation in both microvascular structure and tissue microstructure, consistently had the lowest Bayesian information criterion values. Model parameter maps and model selection results were consistent with the physiology of the placenta and surrounding tissue. CONCLUSION Anisotropic intravoxel incoherent motion models explain the placental diffusion signal better than apparent diffusion coefficient, intravoxel incoherent motion, and diffusion tensor models, in information theoretic terms, when using this protocol. Future work will aim to determine if model-derived parameters are sensitive to placental pathologies associated with disorders, such as fetal growth restriction and early-onset pre-eclampsia. Magn Reson Med 80:756-766, 2018. © 2017 The Authors Magnetic Resonance in Medicine published by Wiley Periodicals, Inc. on behalf of International Society for Magnetic Resonance in Medicine. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
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Affiliation(s)
- Paddy J. Slator
- Centre for Medical Image Computing and Department of Computer ScienceUniversity College LondonLondonUK
| | - Jana Hutter
- Centre for the Developing Brain, King's College LondonLondonUK,Biomedical Engineering DepartmentKing's College LondonLondonUK
| | - Laura McCabe
- Centre for the Developing Brain, King's College LondonLondonUK
| | | | - Anthony N. Price
- Centre for the Developing Brain, King's College LondonLondonUK,Biomedical Engineering DepartmentKing's College LondonLondonUK
| | - Eleftheria Panagiotaki
- Centre for Medical Image Computing and Department of Computer ScienceUniversity College LondonLondonUK
| | | | - Joseph V. Hajnal
- Centre for the Developing Brain, King's College LondonLondonUK,Biomedical Engineering DepartmentKing's College LondonLondonUK
| | - Daniel C. Alexander
- Centre for Medical Image Computing and Department of Computer ScienceUniversity College LondonLondonUK
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20
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Luo J, Abaci Turk E, Bibbo C, Gagoski B, Roberts DJ, Vangel M, Tempany-Afdhal CM, Barnewolt C, Estroff J, Palanisamy A, Barth WH, Zera C, Malpica N, Golland P, Adalsteinsson E, Robinson JN, Grant PE. In Vivo Quantification of Placental Insufficiency by BOLD MRI: A Human Study. Sci Rep 2017. [PMID: 28623277 PMCID: PMC5473907 DOI: 10.1038/s41598-017-03450-0] [Citation(s) in RCA: 54] [Impact Index Per Article: 7.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/24/2022] Open
Abstract
Fetal health is critically dependent on placental function, especially placental transport of oxygen from mother to fetus. When fetal growth is compromised, placental insufficiency must be distinguished from modest genetic growth potential. If placental insufficiency is present, the physician must trade off the risk of prolonged fetal exposure to placental insufficiency against the risks of preterm delivery. Current ultrasound methods to evaluate the placenta are indirect and insensitive. We propose to use Blood-Oxygenation-Level-Dependent (BOLD) MRI with maternal hyperoxia to quantitatively assess mismatch in placental function in seven monozygotic twin pairs naturally matched for genetic growth potential. In-utero BOLD MRI time series were acquired at 29 to 34 weeks gestational age. Maps of oxygen Time-To-Plateau (TTP) were obtained in the placentas by voxel-wise fitting of the time series. Fetal brain and liver volumes were measured based on structural MR images. After delivery, birth weights were obtained and placental pathological evaluations were performed. Mean placental TTP negatively correlated with fetal liver and brain volumes at the time of MRI as well as with birth weights. Mean placental TTP positively correlated with placental pathology. This study demonstrates the potential of BOLD MRI with maternal hyperoxia to quantify regional placental function in vivo.
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Affiliation(s)
- Jie Luo
- Fetal-Neonatal Neuroimaging and Developmental Science Center, Boston Children's Hospital, Boston, 02115, USA.,Madrid-MIT M+Vision Consortium, RLE, Massachusetts Institute of Technology, Cambridge, 02139, USA
| | - Esra Abaci Turk
- Fetal-Neonatal Neuroimaging and Developmental Science Center, Boston Children's Hospital, Boston, 02115, USA.,Madrid-MIT M+Vision Consortium, RLE, Massachusetts Institute of Technology, Cambridge, 02139, USA
| | - Carolina Bibbo
- Maternal Fetal Medicine, Brigham and Women's Hospital, Boston, 02115, USA
| | - Borjan Gagoski
- Fetal-Neonatal Neuroimaging and Developmental Science Center, Boston Children's Hospital, Boston, 02115, USA
| | | | - Mark Vangel
- Radiology, Massachusetts General Hospital, Boston, 02114, USA
| | | | | | - Judy Estroff
- Radiology, Boston Children's Hospital, Boston, 02115, USA
| | | | - William H Barth
- Obstetrics and Gynecology, Massachusetts General Hospital, Boston, 02114, USA
| | - Chloe Zera
- Maternal Fetal Medicine, Brigham and Women's Hospital, Boston, 02115, USA
| | - Norberto Malpica
- Madrid-MIT M+Vision Consortium, RLE, Massachusetts Institute of Technology, Cambridge, 02139, USA.,Medical Image Analysis and Biometry Laboratory, Universidad Rey Juan Carlos, Madrid, 28933, Spain
| | - Polina Golland
- Electrical Engineering and Computer Science, Massachusetts Institute of Technology, Cambridge, 02139, USA.,Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology, Cambridge, 02139, USA
| | - Elfar Adalsteinsson
- Madrid-MIT M+Vision Consortium, RLE, Massachusetts Institute of Technology, Cambridge, 02139, USA.,Electrical Engineering and Computer Science, Massachusetts Institute of Technology, Cambridge, 02139, USA.,Institute for Medical Engineering and Science, Massachusetts Institute of Technology, Cambridge, 02139, USA
| | - Julian N Robinson
- Maternal Fetal Medicine, Brigham and Women's Hospital, Boston, 02115, USA
| | - Patricia Ellen Grant
- Fetal-Neonatal Neuroimaging and Developmental Science Center, Boston Children's Hospital, Boston, 02115, USA.
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