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Matthew J, Uus A, Egloff Collado A, Luis A, Arulkumaran S, Fukami-Gartner A, Kyriakopoulou V, Cromb D, Wright R, Colford K, Deprez M, Hutter J, O’Muircheartaigh J, Malamateniou C, Razavi R, Story L, Hajnal JV, Rutherford MA. Automated craniofacial biometry with 3D T2w fetal MRI. PLOS DIGITAL HEALTH 2024; 3:e0000663. [PMID: 39774200 PMCID: PMC11684610 DOI: 10.1371/journal.pdig.0000663] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 08/20/2024] [Accepted: 10/09/2024] [Indexed: 01/11/2025]
Abstract
OBJECTIVES Evaluating craniofacial phenotype-genotype correlations prenatally is increasingly important; however, it is subjective and challenging with 3D ultrasound. We developed an automated label propagation pipeline using 3D motion- corrected, slice-to-volume reconstructed (SVR) fetal MRI for craniofacial measurements. METHODS A literature review and expert consensus identified 31 craniofacial biometrics for fetal MRI. An MRI atlas with defined anatomical landmarks served as a template for subject registration, auto-labelling, and biometric calculation. We assessed 108 healthy controls and 24 fetuses with Down syndrome (T21) in the third trimester (29-36 weeks gestational age, GA) to identify meaningful biometrics in T21. Reliability and reproducibility were evaluated in 10 random datasets by four observers. RESULTS Automated labels were produced for all 132 subjects with a 0.3% placement error rate. Seven measurements, including anterior base of skull length and maxillary length, showed significant differences with large effect sizes between T21 and control groups (ANOVA, p<0.001). Manual measurements took 25-35 minutes per case, while automated extraction took approximately 5 minutes. Bland-Altman plots showed agreement within manual observer ranges except for mandibular width, which had higher variability. Extended GA growth charts (19-39 weeks), based on 280 control fetuses, were produced for future research. CONCLUSION This is the first automated atlas-based protocol using 3D SVR MRI for fetal craniofacial biometrics, accurately revealing morphological craniofacial differences in a T21 cohort. Future work should focus on improving measurement reliability, larger clinical cohorts, and technical advancements, to enhance prenatal care and phenotypic characterisation.
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Affiliation(s)
- Jacqueline Matthew
- Department of Early Life Imaging, School of Biomedical Engineering and Imaging Sciences, King’s College London, St Thomas’ Hospital, London, United Kingdom
- Guy’s and St Thomas’ NHS Foundation Trust, London, United Kingdom
| | - Alena Uus
- Department of Early Life Imaging, School of Biomedical Engineering and Imaging Sciences, King’s College London, St Thomas’ Hospital, London, United Kingdom
| | - Alexia Egloff Collado
- Department of Early Life Imaging, School of Biomedical Engineering and Imaging Sciences, King’s College London, St Thomas’ Hospital, London, United Kingdom
- Guy’s and St Thomas’ NHS Foundation Trust, London, United Kingdom
| | - Aysha Luis
- Department of Early Life Imaging, School of Biomedical Engineering and Imaging Sciences, King’s College London, St Thomas’ Hospital, London, United Kingdom
- Guy’s and St Thomas’ NHS Foundation Trust, London, United Kingdom
| | - Sophie Arulkumaran
- Department of Early Life Imaging, School of Biomedical Engineering and Imaging Sciences, King’s College London, St Thomas’ Hospital, London, United Kingdom
- Guy’s and St Thomas’ NHS Foundation Trust, London, United Kingdom
| | - Abi Fukami-Gartner
- Department of Early Life Imaging, School of Biomedical Engineering and Imaging Sciences, King’s College London, St Thomas’ Hospital, London, United Kingdom
| | - Vanessa Kyriakopoulou
- Department of Early Life Imaging, School of Biomedical Engineering and Imaging Sciences, King’s College London, St Thomas’ Hospital, London, United Kingdom
| | - Daniel Cromb
- Department of Early Life Imaging, School of Biomedical Engineering and Imaging Sciences, King’s College London, St Thomas’ Hospital, London, United Kingdom
- Guy’s and St Thomas’ NHS Foundation Trust, London, United Kingdom
| | - Robert Wright
- Department of Early Life Imaging, School of Biomedical Engineering and Imaging Sciences, King’s College London, St Thomas’ Hospital, London, United Kingdom
- Guy’s and St Thomas’ NHS Foundation Trust, London, United Kingdom
| | - Kathleen Colford
- Department of Early Life Imaging, School of Biomedical Engineering and Imaging Sciences, King’s College London, St Thomas’ Hospital, London, United Kingdom
| | - Maria Deprez
- Department of Early Life Imaging, School of Biomedical Engineering and Imaging Sciences, King’s College London, St Thomas’ Hospital, London, United Kingdom
| | - Jana Hutter
- Department of Early Life Imaging, School of Biomedical Engineering and Imaging Sciences, King’s College London, St Thomas’ Hospital, London, United Kingdom
- Smart Imaging Lab, Radiological Institute, University Hospital Erlangen, Erlangen, Germany
| | - Jonathan O’Muircheartaigh
- Department of Early Life Imaging, School of Biomedical Engineering and Imaging Sciences, King’s College London, St Thomas’ Hospital, London, United Kingdom
| | - Christina Malamateniou
- Division of Midwifery and Radiography, City University of London, London, United Kingdom
| | - Reza Razavi
- Department of Early Life Imaging, School of Biomedical Engineering and Imaging Sciences, King’s College London, St Thomas’ Hospital, London, United Kingdom
- Guy’s and St Thomas’ NHS Foundation Trust, London, United Kingdom
| | - Lisa Story
- Department of Early Life Imaging, School of Biomedical Engineering and Imaging Sciences, King’s College London, St Thomas’ Hospital, London, United Kingdom
- Guy’s and St Thomas’ NHS Foundation Trust, London, United Kingdom
| | - Joseph V. Hajnal
- Department of Early Life Imaging, School of Biomedical Engineering and Imaging Sciences, King’s College London, St Thomas’ Hospital, London, United Kingdom
| | - Mary A. Rutherford
- Department of Early Life Imaging, School of Biomedical Engineering and Imaging Sciences, King’s College London, St Thomas’ Hospital, London, United Kingdom
- Guy’s and St Thomas’ NHS Foundation Trust, London, United Kingdom
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Matthew J, Uus A, Collado AE, Luis A, Arulkumaran S, Fukami-Gartner A, Kyriakopoulou V, Cromb D, Wright R, Colford K, Deprez M, Hutter J, O’Muircheartaigh J, Malamateniou C, Razavi R, Story L, Hajnal J, Rutherford MA. Automated Craniofacial Biometry with 3D T2w Fetal MRI. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2024.08.13.24311408. [PMID: 39185514 PMCID: PMC11343257 DOI: 10.1101/2024.08.13.24311408] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Indexed: 08/27/2024]
Abstract
Objectives Evaluating craniofacial phenotype-genotype correlations prenatally is increasingly important; however, it is subjective and challenging with 3D ultrasound. We developed an automated landmark propagation pipeline using 3D motion-corrected, slice-to-volume reconstructed (SVR) fetal MRI for craniofacial measurements. Methods A literature review and expert consensus identified 31 craniofacial biometrics for fetal MRI. An MRI atlas with defined anatomical landmarks served as a template for subject registration, auto-labelling, and biometric calculation. We assessed 108 healthy controls and 24 fetuses with Down syndrome (T21) in the third trimester (29-36 weeks gestational age, GA) to identify meaningful biometrics in T21. Reliability and reproducibility were evaluated in 10 random datasets by four observers. Results Automated labels were produced for all 132 subjects with a 0.03% placement error rate. Seven measurements, including anterior base of skull length and maxillary length, showed significant differences with large effect sizes between T21 and control groups (ANOVA, p<0.001). Manual measurements took 25-35 minutes per case, while automated extraction took approximately 5 minutes. Bland-Altman plots showed agreement within manual observer ranges except for mandibular width, which had higher variability. Extended GA growth charts (19-39 weeks), based on 280 control fetuses, were produced for future research. Conclusion This is the first automated atlas-based protocol using 3D SVR MRI for fetal craniofacial biometrics, accurately revealing morphological craniofacial differences in a T21 cohort. Future work should focus on improving measurement reliability, larger clinical cohorts, and technical advancements, to enhance prenatal care and phenotypic characterisation.
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Affiliation(s)
- Jacqueline Matthew
- Department of Early Life Imaging, School of Biomedical Engineering and Imaging Sciences, King’s College London, St Thomas’ Hospital, London, UK
- Guy’s and St Thomas’ NHS Foundation Trust, London, UK
| | - Alena Uus
- Department of Early Life Imaging, School of Biomedical Engineering and Imaging Sciences, King’s College London, St Thomas’ Hospital, London, UK
| | - Alexia Egloff Collado
- Department of Early Life Imaging, School of Biomedical Engineering and Imaging Sciences, King’s College London, St Thomas’ Hospital, London, UK
- Guy’s and St Thomas’ NHS Foundation Trust, London, UK
| | - Aysha Luis
- Department of Early Life Imaging, School of Biomedical Engineering and Imaging Sciences, King’s College London, St Thomas’ Hospital, London, UK
- Guy’s and St Thomas’ NHS Foundation Trust, London, UK
| | - Sophie Arulkumaran
- Department of Early Life Imaging, School of Biomedical Engineering and Imaging Sciences, King’s College London, St Thomas’ Hospital, London, UK
- Guy’s and St Thomas’ NHS Foundation Trust, London, UK
| | - Abi Fukami-Gartner
- Department of Early Life Imaging, School of Biomedical Engineering and Imaging Sciences, King’s College London, St Thomas’ Hospital, London, UK
| | - Vanessa Kyriakopoulou
- Department of Early Life Imaging, School of Biomedical Engineering and Imaging Sciences, King’s College London, St Thomas’ Hospital, London, UK
| | - Daniel Cromb
- Department of Early Life Imaging, School of Biomedical Engineering and Imaging Sciences, King’s College London, St Thomas’ Hospital, London, UK
- Guy’s and St Thomas’ NHS Foundation Trust, London, UK
| | - Robert Wright
- Department of Early Life Imaging, School of Biomedical Engineering and Imaging Sciences, King’s College London, St Thomas’ Hospital, London, UK
- Guy’s and St Thomas’ NHS Foundation Trust, London, UK
| | - Kathleen Colford
- Department of Early Life Imaging, School of Biomedical Engineering and Imaging Sciences, King’s College London, St Thomas’ Hospital, London, UK
| | - Maria Deprez
- Department of Early Life Imaging, School of Biomedical Engineering and Imaging Sciences, King’s College London, St Thomas’ Hospital, London, UK
| | - Jana Hutter
- Department of Early Life Imaging, School of Biomedical Engineering and Imaging Sciences, King’s College London, St Thomas’ Hospital, London, UK
- Smart Imaging Lab, Radiological Institute, University Hospital Erlangen, Erlangen, Germany
| | - Jonathan O’Muircheartaigh
- Department of Early Life Imaging, School of Biomedical Engineering and Imaging Sciences, King’s College London, St Thomas’ Hospital, London, UK
| | | | - Reza Razavi
- Department of Early Life Imaging, School of Biomedical Engineering and Imaging Sciences, King’s College London, St Thomas’ Hospital, London, UK
- Guy’s and St Thomas’ NHS Foundation Trust, London, UK
| | - Lisa Story
- Department of Early Life Imaging, School of Biomedical Engineering and Imaging Sciences, King’s College London, St Thomas’ Hospital, London, UK
- Guy’s and St Thomas’ NHS Foundation Trust, London, UK
| | - Jo Hajnal
- Department of Early Life Imaging, School of Biomedical Engineering and Imaging Sciences, King’s College London, St Thomas’ Hospital, London, UK
| | - Mary A. Rutherford
- Department of Early Life Imaging, School of Biomedical Engineering and Imaging Sciences, King’s College London, St Thomas’ Hospital, London, UK
- Guy’s and St Thomas’ NHS Foundation Trust, London, UK
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Liu Q, Li Q, Pang Y, Wang J, Hu Q, Tang D, Xia L, Sun Z. Accelerated three-dimensional susceptibility weighted imaging of the whole spine of fetus at 3T. Eur J Radiol 2023; 158:110622. [PMID: 36481479 DOI: 10.1016/j.ejrad.2022.110622] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/10/2022] [Revised: 11/07/2022] [Accepted: 11/21/2022] [Indexed: 11/27/2022]
Abstract
OBJECTIVES To investigate the image quality and capability of generalized auto-calibrating partially parallel acquisition (GRAPPA) accelerated Three-dimensional (3D) susceptibility weighted imaging (SWI) of the whole spine at 3T. METHODS A total of 37 pregnant women (gestation age 22 to 39 weeks, average 29 ± 3 weeks) with suspected fetal vertebral anomalies by ultrasound (US) screening underwent 3.0T MR imaging with 3D SWI, conventional two-dimensional (2D) half-flourier acquisition single-shot turbo spin-echo (HASTE) and 3D true fast imaging with steady-state precession (True FISP). The acquisition time of each protocol was recorded. Signal-to-noise ratios (SNRs) and contrast-to-noise ratios (CNRs) were determined in representative interest regions of fetal thoracic vertebrae and compared among three pulse sequences. Two radiologists rated image quality independently in random order on a 5-point scale. Kappa coefficients were computed to assess inter-observer reliability. Receiver operating characteristic curves were generated, and the area under the curve (AUC) was used to compare the diagnostic performance of each protocol in vertebral deformities. RESULTS The acquisition time was 15 s for 3D-SWI and 17 s for 3D True FISP, significantly shorter than conventional HASTE (37 s; both P < 0.01). Of the three protocols, The SNR was highest on 3D True FISP, while the CNR was highest on 3D SWI. Visualization of all segments of the whole spine by 3D SWI was comparable with 3D True FISP. In contrast, 3D SWI and 3D True FISP depicted cervical and sacrococcygeal vertebrae better than HASTE. The weighted kappa statistic was 0.70-0.89 to evaluate the image quality of all segments of the whole spine, indicating good to excellent interobserver agreement. 3D SWI had the highest diagnostic performance for detecting fetal vertebral anomalies (AUC = 0.92). CONCLUSIONS 3D-SWI is feasible for improved visualization of the whole fetal vertebral column and its congenital malformations with adequate image quality and high accuracy, thereby providing a supplementary method to conventional MR imaging.
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Affiliation(s)
- Qiuyu Liu
- Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China.
| | - Qian Li
- Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China
| | - Ying Pang
- Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China
| | - Juan Wang
- Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China
| | - Qiongjie Hu
- Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China
| | - Dazhong Tang
- Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China
| | - Liming Xia
- Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China
| | - Ziyan Sun
- Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China.
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Yin X, Zhao X, Lu L, Zhang L, Xing Q, Yuan R, Niu Z, Zhang L. Fetal magnetic resonance imaging of lumbar spine development in vivo: a retrospective study. Childs Nerv Syst 2022; 38:2113-2118. [PMID: 35972535 PMCID: PMC9617832 DOI: 10.1007/s00381-022-05645-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/22/2022] [Accepted: 08/02/2022] [Indexed: 11/03/2022]
Abstract
OBJECTIVE The aim of this study is to describe MR imaging appearances of the fetal lumbar spine in vivo at different gestational ages (GAs). METHODS This retrospective study was approved by the Third Affiliated Hospital of Zhengzhou University. We collected MR images and clinical data of 93 fetuses in our hospital. All the MR images were obtained by 3-T MR. All had the mid-sagittal plane of steady state free precession sequence (Trufi) of the lumbar spine, which could show the lumbar vertebra and conus medullaris (CM). Regression analysis was made between GA and heights of lumbar vertebral body ossification center (LVBOC), lengths of LVBOC, and heights of intervertebral gap (IVG). RESULTS There were good linear correlations between the heights of LVBOC and GA (P < 0.001), lengths of LVBOC and GA (P < 0.001), and heights of IVG and GA (P < 0.001). CONCLUSION We showed the different development of each LVBOC and IVG which caused the difference of the shape of LVBOC and IVG.
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Affiliation(s)
- Xing Yin
- Department of Radiology, The Third Affiliated Hospital of Zhengzhou University, Zhengzhou, China.
| | - Xin Zhao
- grid.412719.8Department of Radiology, The Third Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Lin Lu
- grid.412719.8Department of Radiology, The Third Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Liying Zhang
- grid.412719.8Department of Radiology, The Third Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Qingna Xing
- grid.412719.8Department of Radiology, The Third Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Rui Yuan
- grid.412719.8Department of Ultrasound, The Third Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Zhijun Niu
- grid.412719.8Department of Obstetrics and Gynecology, The Third Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Linlin Zhang
- grid.412719.8Department of Laboratory Medicine, The Third Affiliated Hospital of Zhengzhou University, Zhengzhou, China
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Jakab A, Payette K, Mazzone L, Schauer S, Muller CO, Kottke R, Ochsenbein-Kölble N, Tuura R, Moehrlen U, Meuli M. Emerging magnetic resonance imaging techniques in open spina bifida in utero. Eur Radiol Exp 2021; 5:23. [PMID: 34136989 PMCID: PMC8209133 DOI: 10.1186/s41747-021-00219-z] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/29/2020] [Accepted: 04/01/2021] [Indexed: 11/25/2022] Open
Abstract
Magnetic resonance imaging (MRI) has become an essential diagnostic modality for congenital disorders of the central nervous system. Recent advancements have transformed foetal MRI into a clinically feasible tool, and in an effort to find predictors of clinical outcomes in spinal dysraphism, foetal MRI began to unveil its potential. The purpose of our review is to introduce MRI techniques to experts with diverse backgrounds, who are involved in the management of spina bifida. We introduce advanced foetal MRI postprocessing potentially improving the diagnostic work-up. Importantly, we discuss how postprocessing can lead to a more efficient utilisation of foetal or neonatal MRI data to depict relevant anatomical characteristics. We provide a critical perspective on how structural, diffusion and metabolic MRI are utilised in an endeavour to shed light on the correlates of impaired development. We found that the literature is consistent about the value of MRI in providing morphological cues about hydrocephalus development, hindbrain herniation or outcomes related to shunting and motor functioning. MRI techniques, such as foetal diffusion MRI or diffusion tractography, are still far from clinical use; however, postnatal studies using these methods revealed findings that may reflect early neural correlates of upstream neuronal damage in spinal dysraphism.
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Affiliation(s)
- Andras Jakab
- Center for MR-Research, University Children's Hospital Zürich, Zürich, Switzerland. .,Neuroscience Center Zürich, University of Zürich, Zürich, Switzerland.
| | - Kelly Payette
- Center for MR-Research, University Children's Hospital Zürich, Zürich, Switzerland.,Neuroscience Center Zürich, University of Zürich, Zürich, Switzerland
| | - Luca Mazzone
- Department of Pediatric Surgery, University Children's Hospital Zurich, Zürich, Switzerland.,The Zurich Center for Fetal Diagnosis and Therapy, Zürich, Switzerland
| | - Sonja Schauer
- Department of Pediatric Surgery, University Children's Hospital Zurich, Zürich, Switzerland
| | | | - Raimund Kottke
- Department of Diagnostic Imaging, University Children's Hospital Zurich, Zurich, Switzerland
| | | | - Ruth Tuura
- Center for MR-Research, University Children's Hospital Zürich, Zürich, Switzerland
| | - Ueli Moehrlen
- Department of Pediatric Surgery, University Children's Hospital Zurich, Zürich, Switzerland.,The Zurich Center for Fetal Diagnosis and Therapy, Zürich, Switzerland.,University of Zurich, Zürich, Switzerland
| | - Martin Meuli
- Department of Pediatric Surgery, University Children's Hospital Zurich, Zürich, Switzerland.,The Zurich Center for Fetal Diagnosis and Therapy, Zürich, Switzerland.,University of Zurich, Zürich, Switzerland
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Goodall AF, Barrett A, Whitby E, Fry A. T2*-weighted MRI produces viable fetal "Black-Bone" contrast with significant benefits when compared to current sequences. Br J Radiol 2021; 94:20200940. [PMID: 33989027 DOI: 10.1259/bjr.20200940] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/14/2023] Open
Abstract
OBJECTIVES Fetal "black bone" MRI could be useful in the diagnosis of various skeletal conditions during pregnancy without exposure to ionizing radiation. Previously suggested susceptibility-weighted imaging (SWI) is not available in the suggested form on all scanners leading to long imaging times that are susceptible to motion artefacts. We aimed to assess if an optimized T2*-weighted GRE sequence can provide viable "black bone" contrast and compared it to other sequences in the literature. METHODS A retrospective study was conducted on 17 patients who underwent fetal MRI. Patients were imaged with an optimized T2*-weighted GRE sequence, as well as at least one other "black-bone" sequence. Image quality was scored by four blinded observers on a five-point scale. RESULTS The T2*-weighted GRE sequence offered adequate to excellent image quality in 63% of cases and scored consistently higher than the three other comparison sequences when comparing images from the same patient. Image quality was found to be dependent on gestational age with good image quality achieved on almost all patients after 26 weeks. CONCLUSIONS T2*-weighted GRE imaging can provide adequate fetal "black bone" contrast and performs at least as well as other sequences in the literature due to good bone to soft tissue contrast and minimal motion artefacts. ADVANCES IN KNOWLEDGE T2*-weighted fetal "black-bone" imaging can provide excellent bone to soft tissue contrast without using ionizing radiation. It is as good as other "black bone" sequences and may be simpler and more widely implemented, with less motion artefacts.
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Affiliation(s)
| | - Alex Barrett
- Sheffield Teaching Hospital NHS Foundation Trust, Sheffield, UK.,The Clatterbridge Cancer Centre NHS Foundation Trust, Birkenhead, UK
| | - Elspeth Whitby
- Sheffield Teaching Hospital NHS Foundation Trust, Sheffield, UK
| | - Andrew Fry
- Sheffield Teaching Hospital NHS Foundation Trust, Sheffield, UK
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