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Coleman J, Grewal S, Warland J, Hobson S, Liu K, Kember A. Maternal positional therapy for fetal growth and customised birth weight centile benefit in a Bayesian reanalysis of a double-blind, sham-controlled, randomised clinical trial. BMJ Open 2024; 14:e078315. [PMID: 38684260 PMCID: PMC11057287 DOI: 10.1136/bmjopen-2023-078315] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/29/2023] [Accepted: 03/28/2024] [Indexed: 05/02/2024] Open
Abstract
OBJECTIVES To update the Ghana PrenaBelt Trial's (GPT) primary outcome data with the latest fetal growth standard and reanalyse it. To estimate the posterior probability, under various clinically relevant prior probabilities, of maternal nightly positional therapy (PT) throughout the third-trimester having a beneficial effect on customised birth weight centile (CBWC) using Bayesian analyses. DESIGN A reanalysis of a double-blind, sham-controlled, randomised clinical trial. SETTING A single, tertiary-level centre in Accra, Ghana. PARTICIPANTS Two-hundred participants entered, 181 completed and 167 were included in the final analysis. Participants were Ghanaian, healthy, aged 18-35 years, with low-risk, singleton pregnancies in their third-trimester, with Body Mass Index<35 kg/m2 at the first antenatal appointment for the index pregnancy and without known fetal abnormalities, pregnancy complications or medical conditions complicating sleep. INTERVENTIONS Participants were randomised to receive treatment with either a PT or sham-PT device. PRIMARY AND SECONDARY OUTCOME MEASURES The primary outcome was the CBWC using the latest Perinatal Institute, Gestation-Related Optimal Weight calculator. Using Bayesian methods, posterior probabilities of achieving a greater than 0%, 5% and 10% benefit in CBWC with PT were estimated. There was no secondary outcome. RESULTS The median (IQR) CBWC was 42% (15-71) and 28% (9-52) in the PT and sham-PT groups, respectively (difference 8.4%; 95% CI -0.30 to 18.2; p=0.06). For achieving a >0%, >5% and >10% gain in CBWC with PT, the posterior probabilities were highly probable, probable and unlikely, respectively, given a range of prior probabilities reflecting varying degrees of pre-existing enthusiasm and scepticism. CONCLUSIONS Maternal nightly PT throughout the third-trimester did not have a statistically significant effect on CBWC on a frequentist analysis using the latest fetal growth standard. However, from a Bayesian analysis, clinicians can infer that PT is likely to benefit fetal growth but with a modest effect size. TRIAL REGISTRATION NUMBER NCT02379728.
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Affiliation(s)
- Jerry Coleman
- Obstetrics & Gynaecology, Korle Bu Teaching Hospital, Accra, Greater Accra, Ghana
| | - Sahibjot Grewal
- University of Toronto Faculty of Medicine, Toronto, Ontario, Canada
| | - Jane Warland
- The University of Adelaide Faculty of Health and Medical Sciences, Adelaide, South Australia, Australia
| | - Sebastian Hobson
- Department of Obstetrics & Gynaecology, University of Toronto Faculty of Medicine, Toronto, Ontario, Canada
- Maternal-Fetal Medicine Division, Department of Obstetrics and Gynaecology, Mount Sinai Hospital, Toronto, Ontario, Canada
| | - Kuan Liu
- Institute of Health Policy, Management, and Evaluation, University of Toronto Dalla Lana School of Public Health, Toronto, Ontario, Canada
| | - Allan Kember
- Department of Obstetrics & Gynaecology, University of Toronto Faculty of Medicine, Toronto, Ontario, Canada
- Institute of Health Policy, Management, and Evaluation, University of Toronto Dalla Lana School of Public Health, Toronto, Ontario, Canada
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Rajagopalan V, Truong V, Wang S, Lopez J, Rosas V, Borzage M, Votava-Smith JK, Ponrartana S, Panigrahy A, Detterich J, Wood J. Non-invasive in-utero quantification of vascular reactivity in human placenta. Ultrasound Obstet Gynecol 2024; 63:481-488. [PMID: 37820067 DOI: 10.1002/uog.27512] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/15/2023] [Revised: 09/26/2023] [Accepted: 10/02/2023] [Indexed: 10/13/2023]
Abstract
OBJECTIVE Placental vascular reactivity (PlVR) indicates the ability of the placental vasculature to match blood supply to fetal demand. Many pregnancy disorders alter the characteristics of PlVR, resulting in suboptimal oxygen delivery, although current understanding is limited by the lack of non-invasive, repeatable methods to measure PlVR in utero. Our objective was to quantify PlVR by measuring the placental response to transient changes in maternal carbon dioxide (CO2) using blood-oxygen-level-dependent (BOLD) magnetic resonance imaging (MRI). We hypothesized that PlVR will increase with gestational age to meet the changing demands of a growing fetus, and that PlVR will be driven by a maternal response to changes in CO2 concentration. METHODS This was a cross-sectional study of 35 women with a healthy singleton pregnancy, of whom 31 were included in the analysis. The median gestational age was 32.6 (range, 22.6-38.4) weeks. Pregnant women were instructed to follow audiovisual breathing cues during a MRI scan. Maternal end-tidal CO2 (EtCO2) was measured concurrently with resting placental BOLD MRI for a total of 7-8 min. Preprocessing of magnetic resonance images consisted of manual delineation of placental anatomy and motion correction. In each placental voxel, vascular reactivity was computed using a coherence-weighted general linear model between MRI signal and EtCO2 stimulus. Global PlVR was computed as the mean of voxel-wise PlVR values across the placenta. RESULTS PlVR, quantified by the placental response to induced, transient changes in maternal CO2, was consistently measured in utero using BOLD MRI. PlVR increased non-linearly with advancing gestational age (P < 0.001) and was higher on the fetal side of the placenta. PlVR was associated positively with fetal brain volume after accounting for gestational age. PlVR did not show any significant associations with maternal characteristics. CONCLUSIONS We present, for the first time, a non-invasive paradigm to quantify PlVR in ongoing human pregnancies without the use of exogenous gases or contrast agents. Our findings suggest that PlVR is driven by a fetal response to changes in maternal CO2. Ease of translation to the clinical setting makes PlVR a promising biomarker for the identification and management of high-risk pregnancies. © 2023 The Authors. Ultrasound in Obstetrics & Gynecology published by John Wiley & Sons Ltd on behalf of International Society of Ultrasound in Obstetrics and Gynecology.
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Affiliation(s)
- V Rajagopalan
- Department of Radiology, Children's Hospital Los Angeles, Keck School of Medicine University of Southern California, Los Angeles, CA, USA
| | - V Truong
- University of Southern California, Los Angeles, CA, USA
| | - S Wang
- Division of Cardiology, Department of Pediatrics, Children's Hospital Los Angeles, Keck School of Medicine University of Southern California, Los Angeles, CA, USA
| | - J Lopez
- Children's Hospital Los Angeles, Los Angeles, CA, USA
| | - V Rosas
- Children's Hospital Los Angeles, Los Angeles, CA, USA
| | - M Borzage
- Division of Neonatology, Department of Pediatrics, Children's Hospital Los Angeles, Keck School of Medicine University of Southern California, Los Angeles, CA, USA
| | - J K Votava-Smith
- Division of Cardiology, Department of Pediatrics, Children's Hospital Los Angeles, Keck School of Medicine University of Southern California, Los Angeles, CA, USA
| | - S Ponrartana
- University of Southern California, Los Angeles, CA, USA
| | - A Panigrahy
- Pediatric Imaging Research Lab, Department of Radiology, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA
| | - J Detterich
- Division of Cardiology, Department of Pediatrics, Children's Hospital Los Angeles, Keck School of Medicine University of Southern California, Los Angeles, CA, USA
| | - J Wood
- Division of Cardiology, Department of Pediatrics, Children's Hospital Los Angeles, Keck School of Medicine University of Southern California, Los Angeles, CA, USA
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Melbourne A, Schabel MC, David AL, Roberts VHJ. Magnetic resonance imaging of placental Intralobule structure and function in a pre-clinical nonhuman primate model. Biol Reprod 2024:ioae035. [PMID: 38442734 DOI: 10.1093/biolre/ioae035] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/07/2024] Open
Abstract
The placenta has a critical role in delivery of oxygen and an array of nutrients, hormones, antibodies and other biochemicals to the fetus, as well as the elimination of carbon dioxide and other waste products from the fetal circulation. Interrogating placental function is therefore essential for assessment of fetal and maternal health during gestation. Although the central role of adequate blood flow and oxygen delivery is clear, the lack of optimized imaging modalities to study placental structure has impeded our understanding of its vascular function. MRI is increasingly being applied in this field, but gaps in knowledge remain and further MRI methodological developments are needed. In particular, the ability to distinguish maternal from fetal placental perfusion, and the understanding of how individual placental lobules are functioning is lacking. The potential clinical benefits of developing noninvasive tools for the in vivo assessment of blood flow and oxygenation, two key determinants of placental function, are tremendous. Here we summarize a number of structural and functional MRI techniques that have been developed and applied in animal models and studies of human pregnancy over the past decade. We briefly discuss potential applications and limitations for these approaches. Their combination provides a novel source of contrast to allow analysis of placental structure and function at the level of the lobule. We outline physiological mechanisms of placental T2 and T2* decay and devise a model of how tissue composition affects the observed relaxation properties. We apply this modelling to longitudinal MRI data obtained from a pre-clinical pregnant nonhuman primate (NHP) model to provide initial proof-of-concept data for this methodology which quantifies oxygen transfer and placental structure across and between lobules. This method has the potential to improve our understanding and clinical management of placental insufficiency once validation in a larger NHP cohort is complete.
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Affiliation(s)
- Andrew Melbourne
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK
- Elizabeth Garrett Anderson Institute for Women's Health, University College London, London, UK
| | - Matthias C Schabel
- Advanced Imaging Research Center, Oregon Health and Science University (OHSU), Portland, OR, USA
- Utah Center for Advanced Imaging Research, University of Utah, Salt Lake City, Utah, USA
| | - Anna L David
- Elizabeth Garrett Anderson Institute for Women's Health, University College London, London, UK
| | - Victoria H J Roberts
- Division of Reproductive and Developmental Sciences, Oregon National Primate Research Center (ONPRC), OHSU, Portland, OR, USA
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Neves Silva S, Aviles Verdera J, Tomi‐Tricot R, Neji R, Uus A, Grigorescu I, Wilkinson T, Ozenne V, Lewin A, Story L, De Vita E, Rutherford M, Pushparajah K, Hajnal J, Hutter J. Real-time fetal brain tracking for functional fetal MRI. Magn Reson Med 2023; 90:2306-2320. [PMID: 37465882 PMCID: PMC10952752 DOI: 10.1002/mrm.29803] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/28/2023] [Revised: 07/03/2023] [Accepted: 07/03/2023] [Indexed: 07/20/2023]
Abstract
PURPOSE To improve motion robustness of functional fetal MRI scans by developing an intrinsic real-time motion correction method. MRI provides an ideal tool to characterize fetal brain development and growth. It is, however, a relatively slow imaging technique and therefore extremely susceptible to subject motion, particularly in functional MRI experiments acquiring multiple Echo-Planar-Imaging-based repetitions, for example, diffusion MRI or blood-oxygen-level-dependency MRI. METHODS A 3D UNet was trained on 125 fetal datasets to track the fetal brain position in each repetition of the scan in real time. This tracking, inserted into a Gadgetron pipeline on a clinical scanner, allows updating the position of the field of view in a modified echo-planar imaging sequence. The method was evaluated in real-time in controlled-motion phantom experiments and ten fetal MR studies (17 + 4-34 + 3 gestational weeks) at 3T. The localization network was additionally tested retrospectively on 29 low-field (0.55T) datasets. RESULTS Our method achieved real-time fetal head tracking and prospective correction of the acquisition geometry. Localization performance achieved Dice scores of 84.4% and 82.3%, respectively for both the unseen 1.5T/3T and 0.55T fetal data, with values higher for cephalic fetuses and increasing with gestational age. CONCLUSIONS Our technique was able to follow the fetal brain even for fetuses under 18 weeks GA in real-time at 3T and was successfully applied "offline" to new cohorts on 0.55T. Next, it will be deployed to other modalities such as fetal diffusion MRI and to cohorts of pregnant participants diagnosed with pregnancy complications, for example, pre-eclampsia and congenital heart disease.
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Affiliation(s)
- Sara Neves Silva
- Centre for the Developing Brain, School of Biomedical Engineering & Imaging SciencesKing's College LondonLondonUK
- Biomedical Engineering Department, School of Biomedical Engineering & Imaging SciencesKing's College LondonLondonUK
| | - Jordina Aviles Verdera
- Centre for the Developing Brain, School of Biomedical Engineering & Imaging SciencesKing's College LondonLondonUK
- Biomedical Engineering Department, School of Biomedical Engineering & Imaging SciencesKing's College LondonLondonUK
| | - Raphael Tomi‐Tricot
- Centre for the Developing Brain, School of Biomedical Engineering & Imaging SciencesKing's College LondonLondonUK
- Biomedical Engineering Department, School of Biomedical Engineering & Imaging SciencesKing's College LondonLondonUK
- MR Research CollaborationsSiemens Healthcare LimitedCamberleyUK
| | - Radhouene Neji
- Biomedical Engineering Department, School of Biomedical Engineering & Imaging SciencesKing's College LondonLondonUK
- MR Research CollaborationsSiemens Healthcare LimitedCamberleyUK
| | - Alena Uus
- Centre for the Developing Brain, School of Biomedical Engineering & Imaging SciencesKing's College LondonLondonUK
- Biomedical Engineering Department, School of Biomedical Engineering & Imaging SciencesKing's College LondonLondonUK
| | - Irina Grigorescu
- Centre for the Developing Brain, School of Biomedical Engineering & Imaging SciencesKing's College LondonLondonUK
- Biomedical Engineering Department, School of Biomedical Engineering & Imaging SciencesKing's College LondonLondonUK
| | - Thomas Wilkinson
- Centre for the Developing Brain, School of Biomedical Engineering & Imaging SciencesKing's College LondonLondonUK
- Biomedical Engineering Department, School of Biomedical Engineering & Imaging SciencesKing's College LondonLondonUK
| | - Valery Ozenne
- CNRS, CRMSB, UMR 5536, IHU LirycUniversité de BordeauxBordeauxFrance
| | - Alexander Lewin
- Institute of Neuroscience and Medicine 11, INM‐11Forschungszentrum JülichJülichGermany
- RWTHAachen UniversityAachenGermany
| | - Lisa Story
- Centre for the Developing Brain, School of Biomedical Engineering & Imaging SciencesKing's College LondonLondonUK
- Department of Women & Children's HealthKing's College LondonLondonUK
| | - Enrico De Vita
- Biomedical Engineering Department, School of Biomedical Engineering & Imaging SciencesKing's College LondonLondonUK
- MRI Physics GroupGreat Ormond Street HospitalLondonUK
| | - Mary Rutherford
- Centre for the Developing Brain, School of Biomedical Engineering & Imaging SciencesKing's College LondonLondonUK
- Biomedical Engineering Department, School of Biomedical Engineering & Imaging SciencesKing's College LondonLondonUK
| | - Kuberan Pushparajah
- Biomedical Engineering Department, School of Biomedical Engineering & Imaging SciencesKing's College LondonLondonUK
| | - Jo Hajnal
- Centre for the Developing Brain, School of Biomedical Engineering & Imaging SciencesKing's College LondonLondonUK
- Biomedical Engineering Department, School of Biomedical Engineering & Imaging SciencesKing's College LondonLondonUK
| | - Jana Hutter
- Centre for the Developing Brain, School of Biomedical Engineering & Imaging SciencesKing's College LondonLondonUK
- Biomedical Engineering Department, School of Biomedical Engineering & Imaging SciencesKing's College LondonLondonUK
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Kember AJ, Selvarajan R, Park E, Huang H, Zia H, Rahman F, Akbarian S, Taati B, Hobson SR, Dolatabadi E. Vision-based detection and quantification of maternal sleeping position in the third trimester of pregnancy in the home setting-Building the dataset and model. PLOS Digit Health 2023; 2:e0000353. [PMID: 37788239 PMCID: PMC10547173 DOI: 10.1371/journal.pdig.0000353] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/01/2022] [Accepted: 08/17/2023] [Indexed: 10/05/2023]
Abstract
In 2021, the National Guideline Alliance for the Royal College of Obstetricians and Gynaecologists reviewed the body of evidence, including two meta-analyses, implicating supine sleeping position as a risk factor for growth restriction and stillbirth. While they concluded that pregnant people should be advised to avoid going to sleep on their back after 28 weeks' gestation, their main critique of the evidence was that, to date, all studies were retrospective and sleeping position was not objectively measured. As such, the Alliance noted that it would not be possible to prospectively study the associations between sleeping position and adverse pregnancy outcomes. Our aim was to demonstrate the feasibility of building a vision-based model for automated and accurate detection and quantification of sleeping position throughout the third trimester-a model with the eventual goal to be developed further and used by researchers as a tool to enable them to either confirm or disprove the aforementioned associations. We completed a Canada-wide, cross-sectional study in 24 participants in the third trimester. Infrared videos of eleven simulated sleeping positions unique to pregnancy and a sitting position both with and without bed sheets covering the body were prospectively collected. We extracted 152,618 images from 48 videos, semi-randomly down-sampled and annotated 5,970 of them, and fed them into a deep learning algorithm, which trained and validated six models via six-fold cross-validation. The performance of the models was evaluated using an unseen testing set. The models detected the twelve positions, with and without bed sheets covering the body, achieving an average precision of 0.72 and 0.83, respectively, and an average recall ("sensitivity") of 0.67 and 0.76, respectively. For the supine class with and without bed sheets covering the body, the models achieved an average precision of 0.61 and 0.75, respectively, and an average recall of 0.74 and 0.81, respectively.
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Affiliation(s)
- Allan J. Kember
- Department of Obstetrics and Gynaecology, University of Toronto, Toronto, Canada
- Institute of Health Policy, Management, and Evaluation, University of Toronto, Toronto, Canada
- Shiphrah Biomedical Inc., Toronto, Canada
| | - Rahavi Selvarajan
- Department of Electrical and Computer Engineering, University of Toronto, Toronto, Canada
| | - Emma Park
- Shiphrah Biomedical Inc., Toronto, Canada
| | - Henry Huang
- Institute of Biomedical Engineering, University of Toronto, Toronto, Canada
| | - Hafsa Zia
- Temerty Faculty of Medicine, University of Toronto, Toronto, Canada
| | - Farhan Rahman
- Department of Electrical and Computer Engineering, University of Toronto, Toronto, Canada
| | | | - Babak Taati
- Institute of Biomedical Engineering, University of Toronto, Toronto, Canada
- Vector Institute, Toronto, Canada
- Department of Computer Science, University of Toronto, Toronto, Canada
| | - Sebastian R. Hobson
- Department of Obstetrics and Gynaecology, University of Toronto, Toronto, Canada
- Department of Obstetrics and Gynaecology, Maternal-Fetal Medicine Division, Mount Sinai Hospital, Toronto, Canada
| | - Elham Dolatabadi
- Institute of Health Policy, Management, and Evaluation, University of Toronto, Toronto, Canada
- Vector Institute, Toronto, Canada
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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 DOI: 10.1016/j.placenta.2023.08.067] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [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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Cromb D, Slator PJ, De La Fuente M, Price AN, Rutherford M, Egloff A, Counsell SJ, Hutter J. Assessing within-subject rates of change of placental MRI diffusion metrics in normal pregnancy. Magn Reson Med 2023; 90:1137-1150. [PMID: 37183839 PMCID: PMC10962570 DOI: 10.1002/mrm.29665] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/29/2022] [Revised: 03/14/2023] [Accepted: 03/22/2023] [Indexed: 05/16/2023]
Abstract
PURPOSE Studying placental development informs when development is abnormal. Most placental MRI studies are cross-sectional and do not study the extent of individual variability throughout pregnancy. We aimed to explore how diffusion MRI measures of placental function and microstructure vary in individual healthy pregnancies throughout gestation. METHODS Seventy-nine pregnant, low-risk participants (17 scanned twice and 62 scanned once) were included. T2 -weighted anatomical imaging and a combined multi-echo spin-echo diffusion-weighted sequence were acquired at 3 T. Combined diffusion-relaxometry models were performed using both aT 2 * $$ {\mathrm{T}}_2^{\ast } $$ -ADC and a bicompartmentalT 2 * $$ {\mathrm{T}}_2^{\ast } $$ -intravoxel-incoherent-motion (T 2 * IVIM $$ {\mathrm{T}}_2^{\ast}\;\mathrm{IVIM} $$ ) model fit. RESULTS There was a significant decline in placentalT 2 * $$ {\mathrm{T}}_2^{\ast } $$ and ADC (both P < 0.01) over gestation. These declines are consistent in individuals forT 2 * $$ {\mathrm{T}}_2^{\ast } $$ (covariance = -0.47), but not ADC (covariance = -1.04). TheT 2 * IVIM $$ {\mathrm{T}}_2^{\ast}\;\mathrm{IVIM} $$ model identified a consistent decline in individuals over gestation inT 2 * $$ {\mathrm{T}}_2^{\ast } $$ from both the perfusing and diffusing placental compartments, but not in ADC values from either. The placental perfusing compartment fraction increased over gestation (P = 0.0017), but this increase was not consistent in individuals (covariance = 2.57). CONCLUSION Whole placentalT 2 * $$ {\mathrm{T}}_2^{\ast } $$ and ADC values decrease over gestation, although onlyT 2 * $$ {\mathrm{T}}_2^{\ast } $$ values showed consistent trends within subjects. There was minimal individual variation in rates of change ofT 2 * $$ {\mathrm{T}}_2^{\ast } $$ values from perfusing and diffusing placental compartments, whereas trends in ADC values from these compartments were less consistent. These findings probably relate to the increased complexity of the bicompartmentalT 2 * IVIM $$ {\mathrm{T}}_2^{\ast}\;\mathrm{IVIM} $$ model, and differences in how different placental regions evolve at a microstructural level. These placental MRI metrics from low-risk pregnancies provide a useful benchmark for clinical cohorts.
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Affiliation(s)
- Daniel Cromb
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging SciencesKing's College LondonLondonUK
| | - Paddy J. Slator
- Centre for Medical Image Computing, Department of Computer ScienceUniversity College LondonLondonUK
| | - Miguel De La Fuente
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging SciencesKing's College LondonLondonUK
| | - Anthony N. Price
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging SciencesKing's College LondonLondonUK
- Centre for Medical EngineeringSchool of Biomedical Engineering and Imaging Sciences, King's College LondonLondonUK
| | - Mary Rutherford
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging SciencesKing's College LondonLondonUK
- MRC Centre for Neurodevelopmental DisordersKing's College LondonLondonUK
| | - Alexia Egloff
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging SciencesKing's College LondonLondonUK
| | - Serena J. Counsell
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging SciencesKing's College LondonLondonUK
| | - Jana Hutter
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging SciencesKing's College LondonLondonUK
- Centre for Medical EngineeringSchool of Biomedical Engineering and Imaging Sciences, King's College LondonLondonUK
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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: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [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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Clark A, Flouri D, Mufti N, James J, Clements E, Aughwane R, Aertsen M, David A, Melbourne A. Developments in functional imaging of the placenta. Br J Radiol 2023; 96:20211010. [PMID: 35234516 PMCID: PMC10321248 DOI: 10.1259/bjr.20211010] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2021] [Revised: 01/26/2022] [Accepted: 02/22/2022] [Indexed: 12/21/2022] Open
Abstract
The placenta is both the literal and metaphorical black box of pregnancy. Measurement of the function of the placenta has the potential to enhance our understanding of this enigmatic organ and serve to support obstetric decision making. Advanced imaging techniques are key to support these measurements. This review summarises emerging imaging technology being used to measure the function of the placenta and new developments in the computational analysis of these data. We address three important examples where functional imaging is supporting our understanding of these conditions: fetal growth restriction, placenta accreta, and twin-twin transfusion syndrome.
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Affiliation(s)
- Alys Clark
- Auckland Bioengineering Institute, University of Auckland, Auckland, New Zealand
| | | | | | - Joanna James
- Department of Obstetrics and Gynaecology, Faculty of Medical and Health Sciences, University of Auckland, Auckland, New Zealand
| | - Eleanor Clements
- School of Biomedical Engineering and Imaging Sciences, King’s College London, London, UK
| | - Rosalind Aughwane
- Elizabeth Garrett Anderson Institute for Women’s Health, University College London, London, UK
| | - Michael Aertsen
- Department of Radiology, University Hospitals KU Leuven, Leuven, Belgium
| | - Anna David
- Elizabeth Garrett Anderson Institute for Women’s Health, University College London, London, UK
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10
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Hutter J, Kohli V, Dellschaft N, Uus A, Story L, Steinweg JK, Gowland P, Hajnal JV, Rutherford MA. Dynamics of T2* and deformation in the placenta and myometrium during pre-labour contractions. Sci Rep 2022; 12:18542. [PMID: 36329074 DOI: 10.1038/s41598-022-22008-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/12/2022] [Accepted: 10/07/2022] [Indexed: 11/06/2022] Open
Abstract
Pre-labour uterine contractions, occurring throughout pregnancy, are an important phenomenon involving the placenta in addition to the myometrium. They alter the uterine environment and thus potentially the blood supply to the fetus and may thus provide crucial insights into the processes of labour. Assessment in-vivo is however restricted due to their unpredictability and the inaccessible nature of the utero-placental compartment. While clinical cardiotocography (CTG) only allows global, pressure-based assessment, functional magnetic resonance imaging (MRI) provides an opportunity to study contractile activity and its effects on the placenta and the fetus in-vivo. This study aims to provide both descriptive and quantitative structural and functional MR assessments of pre-labour contractions in the human uterus. A total of 226 MRI scans (18-41 weeks gestation) from ongoing research studies were analysed, focusing on free-breathing dynamic quantitative whole uterus dynamic T2* maps. These provide an indirect measure of tissue properties such as oxygenation. 22 contractile events were noted visually and both descriptive and quantitative analysis of the myometrial and placental changes including volumetric and T2* variations were undertaken. Processing and analysis was successfully performed, qualitative analysis shows distinct and highly dynamic contraction related characteristics including; alterations in the thickness of the low T2* in the placental bed and other myometrial areas, high intensity vessel-like structures in the myometrium, low-intensity vessel structures within the placental parenchyma and close to the chorionic plate. Quantitative evaluation shows a significant negative correlation between T2* in both contractile and not-contractile regions with gestational age (p < 0.05) as well as a significant reduction in T2* during contractions. The T2* values in the myometrium were however not correlated to gestational age (p > 0.5). The quantitative and qualitative description of uterine pre-labour contractions including dynamic changes and key characteristics aims to contribute to the sparsely available in-vivo information and to provide an in-vivo tool to study this important phenomenon. Further work is required to analyse the origins of these subclinical contractions, their effects in high-risk pregnancies and their ability to determine the likelihood of a successful labour. Assessing T2* distribution as a marker for placental oxygenation could thus potentially complement clinically used cardiotocography measurements in the future.
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11
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Abaci Turk E, Stout JN, Feldman HA, Gagoski B, Zhou C, Tamen R, Manhard MK, Adalsteinsson E, Roberts DJ, Golland P, Grant PE, Barth WH. Change in T2* measurements of placenta and fetal organs during Braxton Hicks contractions. Placenta 2022; 128:69-71. [PMID: 36087451 PMCID: PMC9674925 DOI: 10.1016/j.placenta.2022.08.011] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/12/2022] [Revised: 08/18/2022] [Accepted: 08/24/2022] [Indexed: 11/15/2022]
Abstract
Maternal-placental perfusion can be temporarily compromised by Braxton Hicks (BH) uterine contractions. Although prior studies have employed T2* changes to investigate the effect of BH contractions on placental oxygen, the effect of these contractions on the fetus has not been fully characterized. We investigated the effect of BH contractions on quantitative fetal organ T2* across gestation together with the birth information. We observed a slight but significant decrease in fetal brain and liver T2* during contractions.
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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.
| | - 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
| | - Borjan Gagoski
- Fetal-Neonatal Neuroimaging & Developmental Science Center, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA
| | - Cindy Zhou
- Fetal-Neonatal Neuroimaging & Developmental Science Center, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA
| | - Rubii Tamen
- Fetal-Neonatal Neuroimaging & Developmental Science Center, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA
| | - Mary Katherine Manhard
- Department of Radiology,Cincinnati Children's Hospital Medical Center, Cincinnati, OH, USA
| | - 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
| | | | - Polina Golland
- Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology, Cambridge, MA, USA; Institute for Medical Engineering and Science, Massachusetts Institute of Technology, Cambridge, MA, USA; Computer Science and Artificial Intelligence Laboratory (CSAIL), 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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Abulnaga SM, Turk EA, Bessmeltsev M, Grant PE, Solomon J, Golland P. Volumetric Parameterization of the Placenta to a Flattened Template. IEEE Trans Med 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] [What about the content of this article? (0)] [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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Ho A, Chappell LC, Story L, Al-Adnani M, Egloff A, Routledge E, Rutherford M, Hutter J. Visual assessment of the placenta in antenatal magnetic resonance imaging across gestation in normal and compromised pregnancies: Observations from a large cohort study. Placenta 2022; 117:29-38. [PMID: 34768166 PMCID: PMC8761363 DOI: 10.1016/j.placenta.2021.10.006] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/20/2020] [Revised: 09/12/2021] [Accepted: 10/06/2021] [Indexed: 01/03/2023]
Abstract
INTRODUCTION Visual assessment of the placenta in antenatal magnetic resonance imaging is important to confirm healthy appearances or to identify pathology complicating fetal anomaly or maternal disease. METHODS We assessed the placenta in a large cohort of 228 women with low and high risk pregnancies across gestation. All women gave written informed consent and were imaged using either a 3T Philips Achieva or 1.5T Philips Ingenia scanner. Images were acquired with a T2-weighted single shot turbo spin echo sequence of the whole uterus (thereby including placenta) for anatomical information. RESULTS A structured approach to visual assessment of the placenta on T2-weighted imaging has been provided including determination of key anatomical landmarks to aid orientation, placental shape, signal intensity, lobularity and granularity. Transient factors affecting imaging are shown including the effect of fetal movement, gross fetal motion and contractions. Placental appearances across gestation in low risk pregnancies are shown and compared to pregnancies complicated by preeclampsia and chronic hypertension. The utility of other magnetic resonance techniques (T2* mapping as an indirect marker for quantifying oxygenation) and histological assessment alongside visual assessment of placental T2-weighted imaging are demonstrated. DISCUSSION A systematic approach with qualitative descriptors for placental visual assessment using T2-weighted imaging allows confirmation of normal placental development and can detect placental abnormalities in pregnancy complications. T2-weighted imaging can be visually assessed alongside functional imaging (such as T2* maps) in order to further probe the visual characteristics seen.
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Affiliation(s)
- Alison Ho
- Department of Women and Children’s Health, School of Life Course Sciences, King’s College London, London, United Kingdom
| | - Lucy C. Chappell
- Department of Women and Children’s Health, School of Life Course Sciences, King’s College London, London, United Kingdom
| | - Lisa Story
- Department of Women and Children’s Health, School of Life Course Sciences, King’s College London, London, United Kingdom
| | - Mudher Al-Adnani
- Department of Cellular Pathology, Guy’s and St Thomas’ Hospital, London, United Kingdom
| | - Alexia Egloff
- Centre for the Developing Brain, King’s College London, London, United Kingdom
| | - Emma Routledge
- Centre for the Developing Brain, King’s College London, London, United Kingdom
| | - Mary Rutherford
- Centre for the Developing Brain, King’s College London, London, United Kingdom
| | - Jana Hutter
- Centre for the Developing Brain, King’s College London, London, United Kingdom,Biomedical Engineering Department, King’s College London, London, United Kingdom
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14
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Stout JN, Bedoya MA, Grant PE, Estroff JA. Fetal Neuroimaging Updates. Magn Reson Imaging Clin N Am 2021; 29:557-581. [PMID: 34717845 PMCID: PMC8562558 DOI: 10.1016/j.mric.2021.06.007] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Abstract
MR imaging is used in conjunction with ultrasound screening for fetal brain abnormalities because it offers better contrast, higher resolution, and has multiplanar capabilities that increase the accuracy and confidence of diagnosis. Fetal motion still severely limits the MR imaging sequences that can be acquired. We outline the current acquisition strategies for fetal brain MR imaging and discuss the near term advances that will improve its reliability. Prospective and retrospective motion correction aim to make the complement of MR neuroimaging modalities available for fetal diagnosis, improve the performance of existing modalities, and open new horizons to understanding in utero brain development.
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Affiliation(s)
- Jeffrey N Stout
- Fetal and Neonatal Neuroimaging and Developmental Science Center, Boston Children's Hospital, 300 Longwood Avenue, Boston, MA 02115, USA.
| | - M Alejandra Bedoya
- Department of Radiology, Boston Children's Hospital, 300 Longwood Avenue, Boston, MA 02115, USA
| | - P Ellen Grant
- Fetal and Neonatal Neuroimaging and Developmental Science Center, Boston Children's Hospital, 300 Longwood Avenue, Boston, MA 02115, USA; Department of Radiology, Boston Children's Hospital, 300 Longwood Avenue, Boston, MA 02115, USA; Department of Pediatrics, Boston Children's Hospital, 300 Longwood Avenue, Boston, MA 02115, USA
| | - Judy A Estroff
- Department of Radiology, Boston Children's Hospital, 300 Longwood Avenue, Boston, MA 02115, USA; Maternal Fetal Care Center, Boston Children's Hospital, 300 Longwood Avenue, Boston, MA 02115, USA
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15
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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] [What about the content of this article? (0)] [Affiliation(s)] [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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16
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Stout JN, Liao C, Gagoski B, Turk EA, Feldman HA, Bibbo C, Barth WH, Shainker SA, Wald LL, Grant PE, Adalsteinsson E. Quantitative T 1 and T 2 mapping by magnetic resonance fingerprinting (MRF) of the placenta before and after maternal hyperoxia. Placenta 2021; 114:124-132. [PMID: 34537569 DOI: 10.1016/j.placenta.2021.08.058] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/15/2021] [Revised: 06/16/2021] [Accepted: 08/05/2021] [Indexed: 11/13/2022]
Abstract
INTRODUCTION MR relaxometry has been used to assess placental exchange function, but methods to date are not sufficiently fast to be robust to placental motion. Magnetic resonance fingerprinting (MRF) permits rapid, voxel-wise, intrinsically co-registered T1 and T2 mapping. After characterizing measurement error, we scanned pregnant women during air and oxygen breathing to demonstrate MRF's ability to detect placental oxygenation changes. METHODS The accuracy of FISP-based, sliding-window reconstructed MRF was tested on phantoms. MRF scans in 9-s breath holds were acquired at 3T in 31 pregnant women during air and oxygen breathing. A mixed effects model was used to test for changes in placenta relaxation times between physiological states, to assess the dependency on gestational age (GA), and the impact of placental motion. RESULTS MRF estimates of known phantom relaxation times resulted in mean absolute errors for T1 of 92 ms (4.8%), but T2 was less accurate at 16 ms (13.6%). During normoxia, placental T1 = 1825 ± 141 ms (avg ± standard deviation) and T2 = 60 ± 16 ms (gestational age range 24.3-36.7, median 32.6 weeks). In the statistical model, placental T2 rose and T1 remained contant after hyperoxia, and no GA dependency was observed for T1 or T2. DISCUSSION Well-characterized, motion-robust MRF was used to acquire T1 and T2 maps of the placenta. Changes with hyperoxia are consistent with a net increase in oxygen saturation. Toward the goal of whole-placenta quantitative oxygenation imaging over time, we aim to implement 3D MRF with integrated motion correction to improve T2 accuracy.
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Affiliation(s)
- Jeffrey N Stout
- Fetal and Neonatal Neuroimaging and Developmental Science Center, Boston Children's Hospital, Boston, MA, 02115, USA.
| | - Congyu Liao
- Department of Radiology, Stanford University, Stanford, CA, 94305, USA
| | - Borjan Gagoski
- Fetal and Neonatal Neuroimaging and Developmental Science Center, Boston Children's Hospital, Boston, MA, 02115, USA
| | - Esra Abaci Turk
- Fetal and Neonatal Neuroimaging and Developmental Science Center, Boston Children's Hospital, Boston, MA, 02115, USA
| | - Henry A Feldman
- Centers for Clinical and Translational Research, Boston Children's Hospital, Boston, MA, 02115, USA
| | - Carolina Bibbo
- Brigham and Women's Hospital, Division of Maternal-Fetal Medicine, Boston, MA, 02115, USA
| | - William H Barth
- Maternal-Fetal Medicine, Obstetrics and Gynecology, Massachusetts General Hospital, Boston, MA, 02114, USA
| | - Scott A Shainker
- Maternal-Fetal Medicine, Obstetrics and Gynecology, Beth Israel Deaconess Medical Center, Boston, MA, 02115, USA
| | - Lawrence L Wald
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Boston, MA, 02129, USA
| | - P Ellen Grant
- Fetal and Neonatal Neuroimaging and Developmental Science Center, Boston Children's Hospital, Boston, MA, 02115, USA
| | - Elfar Adalsteinsson
- Electrical Engineering and Computer Science, Massachusetts Institute of Technology, Cambridge, MA, 02139, USA; Institute for Medical Engineering and Science, Massachusetts Institute of Technology, Cambridge, MA, 02139, USA
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Xu J, Turk EA, Grant PE, Golland P, Adalsteinsson E. STRESS: Super-Resolution for Dynamic Fetal MRI using Self-Supervised Learning. Med Image Comput Comput Assist Interv 2021; 12907:197-206. [PMID: 37103468 PMCID: PMC10129053 DOI: 10.1007/978-3-030-87234-2_19] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/28/2023]
Abstract
Fetal motion is unpredictable and rapid on the scale of conventional MR scan times. Therefore, dynamic fetal MRI, which aims at capturing fetal motion and dynamics of fetal function, is limited to fast imaging techniques with compromises in image quality and resolution. Super-resolution for dynamic fetal MRI is still a challenge, especially when multi-oriented stacks of image slices for oversampling are not available and high temporal resolution for recording the dynamics of the fetus or placenta is desired. Further, fetal motion makes it difficult to acquire high-resolution images for supervised learning methods. To address this problem, in this work, we propose STRESS (Spatio-Temporal Resolution Enhancement with Simulated Scans), a self-supervised super-resolution framework for dynamic fetal MRI with interleaved slice acquisitions. Our proposed method simulates an interleaved slice acquisition along the high-resolution axis on the originally acquired data to generate pairs of low- and high-resolution images. Then, it trains a super-resolution network by exploiting both spatial and temporal correlations in the MR time series, which is used to enhance the resolution of the original data. Evaluations on both simulated and in utero data show that our proposed method outperforms other self-supervised super-resolution methods and improves image quality, which is beneficial to other downstream tasks and evaluations.
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Affiliation(s)
- Junshen Xu
- Department of Electrical Engineering and Computer Science, MIT, Cambridge, MA, USA
| | - Esra Abaci Turk
- Fetal-Neonatal Neuroimaging and Developmental Science Center, Boston Children's Hospital, Boston, MA, USA
| | - P Ellen Grant
- Fetal-Neonatal Neuroimaging and Developmental Science Center, Boston Children's Hospital, Boston, MA, USA
- Harvard Medical School, Boston, MA, USA
| | - Polina Golland
- Department of Electrical Engineering and Computer Science, MIT, Cambridge, MA, USA
- Computer Science and Artificial Intelligence Laboratory, MIT, Cambridge, MA, USA
| | - Elfar Adalsteinsson
- Department of Electrical Engineering and Computer Science, MIT, Cambridge, MA, USA
- Institute for Medical Engineering and Science, MIT, Cambridge, MA, USA
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18
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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: 2.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [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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19
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Melbourne A. On the use of multicompartment models of diffusion and relaxation for placental imaging. Placenta 2021; 112:197-203. [PMID: 34392172 DOI: 10.1016/j.placenta.2021.07.302] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/11/2021] [Revised: 04/27/2021] [Accepted: 07/27/2021] [Indexed: 12/14/2022]
Abstract
Multi-compartment models of diffusion and relaxation are ubiquitous in magnetic resonance research especially applied to neuroimaging applications. These models are increasingly making their way into the world of placental imaging. This review provides a framework for their motivation and implementation and describes some of the outstanding questions that need to be answered before they can be routinely adopted.
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Srinivasan V, Melbourne A, Oyston C, James JL, Clark AR. Multiscale and multimodal imaging of utero-placental anatomy and function in pregnancy. Placenta 2021; 112:111-122. [PMID: 34329969 DOI: 10.1016/j.placenta.2021.07.290] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/13/2020] [Revised: 06/09/2021] [Accepted: 07/19/2021] [Indexed: 12/12/2022]
Abstract
Placental structures at the nano-, micro-, and macro scale each play important roles in contributing to its function. As such, quantifying the dynamic way in which placental structure evolves during pregnancy is critical to both clinical diagnosis of pregnancy disorders, and mechanistic understanding of their pathophysiology. Imaging the placenta, both exvivo and invivo, can provide a wealth of structural and/or functional information. This review outlines how imaging across modalities and spatial scales can ultimately come together to improve our understanding of normal and pathological pregnancies. We discuss how imaging technologies are evolving to provide new insights into placental physiology across disciplines, and how advanced computational algorithms can be used alongside state-of-the-art imaging to obtain a holistic view of placental structure and its associated functions to improve our understanding of placental function in health and disease.
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Affiliation(s)
| | - Andrew Melbourne
- School of Biomedical Engineering & Imaging Sciences, Kings College London, UK
| | - Charlotte Oyston
- Department of Obstetrics and Gynaecology, Faculty of Medical and Health Sciences, University of Auckland, New Zealand
| | - Joanna L James
- Department of Obstetrics and Gynaecology, Faculty of Medical and Health Sciences, University of Auckland, New Zealand
| | - Alys R Clark
- Auckland Bioengineering Institute, University of Auckland, New Zealand
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21
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León RL, Brown BP, Persohn SA, Norris CD, Steinhardt NP, Lin C, Territo PR. Intravoxel incoherent motion MR imaging analysis for diagnosis of placenta accrete spectrum disorders: A pilot feasibility study. Magn Reson Imaging 2021; 80:26-32. [PMID: 33766730 DOI: 10.1016/j.mri.2021.03.007] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/26/2020] [Revised: 12/04/2020] [Accepted: 03/11/2021] [Indexed: 11/21/2022]
Abstract
BACKGROUND Placenta accreta spectrum (PAS) disorders occur when the placenta adheres abnormally to the uterine myometrium and can have devastating effects on maternal health due to risks of massive postpartum hemorrhage and possible need for emergency hysterectomy. PAS can be difficult to diagnose using routine clinical imaging with ultrasound and structural MRI. OBJECTIVE To determine feasibility of using intravoxel incoherent motion (IVIM) magnetic resonance imaging (MRI) analysis in the diagnosis of the placenta accreta spectrum disorders in pregnant women. METHODS A total of 49 pregnant women were recruited including 14 with pathologically confirmed cases of PAS and 35 health controls without prior cesarean delivery and no suspected PAS by ultrasound. All women underwent diffusion-weighted imaging with an 8 b-value scanning sequence. A semi-automated method for image processing was used, creating a 3D object map, which was then fit to a biexponential signal decay curve for IVIM modeling to determine slow diffusion (Ds), fast diffusion (Df), and perfusion fraction (Pf). RESULTS Our results demonstrated a high degree of model fitting (R2 ≥ 0.98), with Pf significantly higher in those with PAS compared to healthy controls (0.451 ± 0.019 versus 0.341 ± 0.022, p = 0.002). By contrast, no statistical difference in the Df (1.70 × 10-2 ± 0.38 × 10-2 versus 1.48 × 10-2 ± 0.08 × 10-2 mm2/s, p = 0.211) or Ds (1.34 × 10-3 ± 0.10 × 10-3 versus 1.45 × 10-3 ± 0.007 × 10-3 mm2/s, p = 0.215) was found between subjects with PAS and healthy controls. CONCLUSIONS The use of MRI, and IVIM modeling in particular, may have potential in aiding in the diagnosis of PAS when other imaging modalities are equivocal. However, the widespread use of these techniques will require generation of large normative data sets, consistent sequencing protocols, and streamlined analysis techniques.
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Steinweg JK, Hui GTY, Pietsch M, Ho A, van Poppel MP, Lloyd D, Colford K, Simpson JM, Razavi R, Pushparajah K, Rutherford M, Hutter J. T2* placental MRI in pregnancies complicated with fetal congenital heart disease. Placenta 2021; 108:23-31. [PMID: 33798991 DOI: 10.1016/j.placenta.2021.02.015] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/22/2020] [Revised: 02/05/2021] [Accepted: 02/25/2021] [Indexed: 11/28/2022]
Abstract
BACKGROUND Congenital heart disease (CHD) is one of the most important and common group of congenital malformations in humans. Concurrent development and close functional links between the fetal heart and placenta emphasise the importance of understanding placental function and its influence in pregnancy outcomes. The aim of this study was to evaluate placental oxygenation by relaxometry (T2*) to assess differences in placental phenotype and function in CHD. METHODS In this prospective cross-sectional observational study, 69 women with a fetus affected with CHD and 37 controls, whole placental T2* was acquired using a 1.5-Tesla MRI scanner. Gaussian Process Regression was used to assess differences in placental phenotype in CHD cohorts compared to our controls. RESULTS Placental T2* maps demonstrated significant differences in CHD compared to controls at equivalent gestational age. Mean T2* values over the entire placental volume were lowest compared to predicted normal in right sided obstructive lesions (RSOL) (Z-Score 2.30). This cohort also showed highest lacunarity indices (Z-score -1.7), as a marker of lobule size. Distribution patterns of T2* values over the entire placental volume were positively skewed in RSOL (Z-score -4.69) and suspected, not confirmed coarctation of the aorta (CoA-) (Z-score -3.83). Deviations were also reflected in positive kurtosis in RSOL (Z-score -3.47) and CoA- (Z-score -2.86). CONCLUSION Placental structure and function appear to deviate from normal development in pregnancies with fetal CHD. Specific patterns of altered placental function assessed by T2* deliver crucial complementary information to antenatal assessments in the presence of fetal CHD.
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Affiliation(s)
- Johannes K Steinweg
- Department of Cardiovascular Imaging, School of Biomedical Engineering & Imaging Science, King's College London, London, United Kingdom.
| | - Grace Tin Yan Hui
- Centre for the Developing Brain, King's College London, London, United Kingdom
| | - Maximilian Pietsch
- Centre for the Developing Brain, King's College London, London, United Kingdom; Department of Biomedical Engineering, School of Biomedical Engineering & Imaging Science, King's College London, London, United Kingdom
| | - Alison Ho
- Centre for the Developing Brain, King's College London, London, United Kingdom
| | - Milou Pm van Poppel
- Department of Cardiovascular Imaging, School of Biomedical Engineering & Imaging Science, King's College London, London, United Kingdom
| | - David Lloyd
- Department of Cardiovascular Imaging, School of Biomedical Engineering & Imaging Science, King's College London, London, United Kingdom; Department of Congenital Heart Disease, Evelina Children's Hospital, London, United Kingdom
| | - Kathleen Colford
- Centre for the Developing Brain, King's College London, London, United Kingdom
| | - John M Simpson
- Department of Cardiovascular Imaging, School of Biomedical Engineering & Imaging Science, King's College London, London, United Kingdom; Department of Congenital Heart Disease, Evelina Children's Hospital, London, United Kingdom
| | - Reza Razavi
- Department of Cardiovascular Imaging, School of Biomedical Engineering & Imaging Science, King's College London, London, United Kingdom; Department of Congenital Heart Disease, Evelina Children's Hospital, London, United Kingdom
| | - Kuberan Pushparajah
- Department of Cardiovascular Imaging, School of Biomedical Engineering & Imaging Science, King's College London, London, United Kingdom; Department of Congenital Heart Disease, Evelina Children's Hospital, London, United Kingdom
| | - Mary Rutherford
- Centre for the Developing Brain, King's College London, London, United Kingdom
| | - Jana Hutter
- Centre for the Developing Brain, King's College London, London, United Kingdom; Department of Biomedical Engineering, School of Biomedical Engineering & Imaging Science, King's College London, London, United Kingdom
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Bianchi DW, Maron JL. Conversations With the Editors: The Past, Present, and Future of Placental Research at the Eunice Kennedy Shriver National Institute of Child Health and Human Development. Clin Ther 2021; 43:211-217. [PMID: 33526313 DOI: 10.1016/j.clinthera.2020.12.020] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/31/2020] [Accepted: 12/31/2020] [Indexed: 12/21/2022]
Affiliation(s)
- Diana W Bianchi
- Eunice Kennedy Shriver National Institute of Child Health and Human Development, Bethesda, MD, USA
| | - Jill L Maron
- Mother Infant Research Institute at Tufts Medical Center, Boston, MA, USA.
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Weinberg DH. Real-time Assessment of the Development and Function of the Placenta Across Gestation to Support Therapeutics in Pregnancy. Clin Ther 2021; 43:279-86. [PMID: 33246660 DOI: 10.1016/j.clinthera.2020.11.002] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/08/2020] [Revised: 11/02/2020] [Accepted: 11/02/2020] [Indexed: 12/19/2022]
Abstract
The placenta is vital to the health and development of the fetus, serving to deliver oxygen and nutrients, facilitate the removal of waste products, and provide a barrier to pathogens and other harmful substances present in the maternal circulation. When these processes fail to operate normally, they can lead to complications of pregnancy such as preeclampsia or fetal growth restriction. The development of novel therapeutics for the mother, fetus, or placenta requires a mechanistic understanding of the development and functions of the placenta. For the obstetric clinician, being able to monitor the placenta throughout the pregnancy and to measure the impact of any treatment modality on the mother and the developing fetus are essential for providing the best possible care. The Eunice Kennedy Shriver National Institute of Child Health and Human Development at the National Institutes of Health has been a longtime supporter of research on the placenta. In 2014, the Human Placenta Project was initiated to help to drive an understanding of the biology of the human placenta and to facilitate the development of novel tools and approaches to allow for safe, noninvasive, real-time assessment of the placenta across pregnancy. Those efforts, along with others from around the globe, are showing promise. Although not yet ready for clinical application, these advances are moving the field forward and are certain to have a tremendous impact on the development and assessment of therapeutics designed for treating conditions of pregnancy.
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