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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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2
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Thomas MA, Bedard T, Crawford S, Lowry RB. Prenatal findings in 11 cases with craniofacial microsomia using the Alberta Congenital Anomalies Surveillance System, 1997-2019. Am J Med Genet A 2024; 194:e63594. [PMID: 38553895 DOI: 10.1002/ajmg.a.63594] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/21/2024] [Revised: 02/29/2024] [Accepted: 03/04/2024] [Indexed: 07/05/2024]
Abstract
Craniofacial microsomia (CFM) primarily includes specific head and neck anomalies that co-occur more frequently than expected. The anomalies are usually asymmetric and affect craniofacial features; however, there are frequently additional anomalies of variable severity. Published prenatal findings for CFM are limited. This study contributes 11 cases with CFM and their anomalies identified prenatally. Cases born between January 1, 1997 and December 31, 2019 with CFM were abstracted from the Alberta Congenital Anomalies Surveillance System, which is a population-based program ascertaining congenital anomalies for livebirths, stillbirths, and termination of pregnancies for fetal anomalies. There were 11 cases ascertained with prenatal findings including facial anomalies: one each with left cleft lip, right microtia, and bilateral microphthalmia. Two cases had vertebral anomalies. In addition, anomalies of the kidneys, brain, heart, and radial ray were identified. Six (55%) had a single umbilical artery, five (45%) were small for gestational age, and three (27%) were from a twin pregnancy that were discordant for anomalies. Four (36%) overlapped another proposed recurrent constellations of embryonic malformation condition. This study describes prenatal findings for 11 cases with CFM. Comparable to prior published cases, there were recurring anomalies on prenatal imaging, including anomalies of the brain, eye, heart, kidneys, and radial ray, which may aid in the prenatal diagnosis of CFM.
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Affiliation(s)
- Mary Ann Thomas
- Alberta Congenital Anomalies Surveillance System, Alberta Health Services, Calgary, Alberta, Canada
- Department of Pediatrics, University of Calgary and Alberta Children's Hospital, Calgary, Alberta, Canada
- Department of Medical Genetics, University of Calgary and Alberta Children's Hospital, Calgary, Alberta, Canada
- Alberta Children's Hospital Research Institute, Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada
| | - Tanya Bedard
- Alberta Congenital Anomalies Surveillance System, Alberta Health Services, Calgary, Alberta, Canada
| | - Susan Crawford
- Alberta Perinatal Health Program, Alberta Health Services, Calgary, Alberta, Canada
| | - R Brian Lowry
- Alberta Congenital Anomalies Surveillance System, Alberta Health Services, Calgary, Alberta, Canada
- Department of Pediatrics, University of Calgary and Alberta Children's Hospital, Calgary, Alberta, Canada
- Department of Medical Genetics, University of Calgary and Alberta Children's Hospital, Calgary, Alberta, Canada
- Alberta Children's Hospital Research Institute, Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada
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Zheng C, Yue P, Cao K, Wang Y, Zhang C, Zhong J, Xu X, Lin C, Liu Q, Zou Y, Huang B. Predicting intraoperative blood loss during cesarean sections based on multi-modal information: a two-center study. Abdom Radiol (NY) 2024; 49:2325-2339. [PMID: 38896245 DOI: 10.1007/s00261-024-04419-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/25/2024] [Revised: 05/27/2024] [Accepted: 05/29/2024] [Indexed: 06/21/2024]
Abstract
PURPOSE To develop and validate a nomogram model that combines radiomics features, clinical factors, and coagulation function indexes (CFI) to predict intraoperative blood loss (IBL) during cesarean sections, and to explore its application in optimizing perioperative management and reducing maternal morbidity. METHODS In this retrospective consecutive series study, a total of 346 patients who underwent magnetic resonance imaging (156 for training and 68 for internal test, center 1; 122 for external test, center 2) were included. IBL+ was defined as more than 1000 mL estimated blood loss during cesarean sections. The prediction models of IBL were developed based on machine-learning algorithms using CFI, radiomics features, and clinical factors. ROC analysis was performed to evaluate the performance for IBL diagnosis. RESULTS The support vector machine model incorporating all three modalities achieved an AUC of 0.873 (95% CI 0.769-0.941) and a sensitivity of 1.000 (95% CI 0.846-1.000) in the internal test set, with an AUC of 0.806 (95% CI 0.725-0.872) and a sensitivity of 0.873 (95% CI 0.799-0.922) in the external test set. It was also scored significantly higher than the CFI model (P = 0.035) on the internal test set, and both the CFI (P = 0.002) and radiomics-CFI models (P = 0.007) on the external test set. Additionally, the nomogram constructed based on three modalities achieved an internal testing set AUC of 0.960 (95% CI 0.806-0.999) and an external testing set AUC of 0.869 (95% CI 0.684-0.967) in the pregnant population without a pernicious placenta previa. It is noteworthy that the AUC of the proposed model did not show a statistically significant improvement compared to the Clinical-CFI model in both internal (P = 0.115) and external test sets (P = 0.533). CONCLUSION The proposed model demonstrated good performance in predicting intraoperative blood loss (IBL), exhibiting high sensitivity and robust generalizability, with potential applicability to other surgeries such as vaginal delivery and postpartum hysterectomy. However, the performance of the proposed model was not statistically significantly better than that of the Clinical-CFI model.
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Affiliation(s)
- Changye Zheng
- Department of Radiology, The Tenth Affiliated Hospital of Southern Medical University (Dongguan People's Hospital), Dongguan, Guangdong, China
| | - Peiyan Yue
- Medical AI Lab, School of Biomedical Engineering, Shenzhen University Medical School, Shenzhen University, Shenzhen, China
| | - Kangyang Cao
- Medical AI Lab, School of Biomedical Engineering, Shenzhen University Medical School, Shenzhen University, Shenzhen, China
| | - Ya Wang
- Dongguan Maternal and Child Health Care Hospital, Dongguan, Guangdong, China
| | - Chang Zhang
- Medical AI Lab, School of Biomedical Engineering, Shenzhen University Medical School, Shenzhen University, Shenzhen, China
| | - Jian Zhong
- Medical AI Lab, School of Biomedical Engineering, Shenzhen University Medical School, Shenzhen University, Shenzhen, China
| | - Xiaoyang Xu
- Department of Radiology, The Tenth Affiliated Hospital of Southern Medical University (Dongguan People's Hospital), Dongguan, Guangdong, China
| | - Chuxuan Lin
- Medical AI Lab, School of Biomedical Engineering, Shenzhen University Medical School, Shenzhen University, Shenzhen, China
| | - Qinghua Liu
- Dongguan Maternal and Child Health Care Hospital, Dongguan, Guangdong, China
| | - Yujian Zou
- Department of Radiology, The Tenth Affiliated Hospital of Southern Medical University (Dongguan People's Hospital), Dongguan, Guangdong, China.
| | - Bingsheng Huang
- Medical AI Lab, School of Biomedical Engineering, Shenzhen University Medical School, Shenzhen University, Shenzhen, China.
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Dhaifalah I, Godava M, Havalova J, Hanzlikova P, Michalkova K, Bakaj Zbrozkova L, Civrny J, Cuckle H. Fetal magnetic resonance imaging in the confirmation of congenital anomalies found on routine mid-trimester ultrasound. Biomed Pap Med Fac Univ Palacky Olomouc Czech Repub 2024. [PMID: 38445385 DOI: 10.5507/bp.2024.008] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/07/2024] Open
Abstract
OBJECTIVE To determine the added value of fetal magnetic resonance imaging (MRI) when clarifying a suspected anomaly detected by mid-trimester scan. METHODS Women attending two centers of fetal medicine between January 2017 and December 2021 were identified. The centers carried out routine mid-trimester ultrasound scans to detect fetal anomalies. Those with a suspected anomaly which required further clarification were referred for fetal magnetic resonance imaging (MRI). The medical records of all referred women were examined to determine the anomalies found at scan, MRI and termination of pregnancy or delivery. A total of 9571 women had a routine mid-trimester scan and an anomaly was either diagnosed or suspected in 449 (4.7%); an MRI examination was made in 76 cases (0.79%). RESULTS MRI confirmed the presence of an abnormality in 61 referrals (80%) and failed to yield a result in one case. Outcome information was available for 69 cases: the MRI confirmation rate was 89% (48/54) in those with abnormal outcome and 40% (6/15) if the outcome was normal, P<0.0001. Among defects in the most common anatomical systems identified at ultrasound, the highest confirmation rates were for urinary tract abnormalities (94%, 15/16) and facial abnormalities (100%, 8/8). Results in other systems varied according to the specific defect but the confirmation rate was high for ventriculomegaly (86%, 6/7) and neural tube defects (83%, 5/6). CONCLUSIONS We have shown that in women with suspected anomaly scan results, requiring further clarification, MRI confirmed ultrasound at a high rate, particularly for urinary tract and facial anomalies.
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Affiliation(s)
- Ishraq Dhaifalah
- FETMED (Fetal Medicine Center, Genetics and Gynecology), Olomouc, Czech Republic
- Department of Obstetrics and Gynecology, Tomas Bata Regional Hospital, Zlin, Czech Republic
| | - Marek Godava
- FETMED (Fetal Medicine Center, Genetics and Gynecology), Olomouc, Czech Republic
| | - Jana Havalova
- Department of Obstetrics and Gynecology, Tomas Bata Regional Hospital, Zlin, Czech Republic
| | - Pavla Hanzlikova
- Department of Imaging Methods, Faculty of Medicine, University of Ostrava, Czech Republic
| | - Kamila Michalkova
- Department of Imaging Methods, Faculty of Medicine, University of Olomouc, Czech Republic
| | - Lenka Bakaj Zbrozkova
- Department of Imaging Methods, Faculty of Medicine, University of Olomouc, Czech Republic
| | - Jakub Civrny
- Department of Imaging Methods, Faculty of Medicine, University of Olomouc, Czech Republic
| | - Howard Cuckle
- Department of Obstetrics and Gynaecology, Faculty of Medicine, Tel Aviv University, Israel
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Yetisir F, Abaci Turk E, Adalsteinsson E, Wald LL, Grant PE. Local SAR management strategies to use two-channel RF shimming for fetal MRI at 3 T. Magn Reson Med 2024; 91:1165-1178. [PMID: 37929768 PMCID: PMC10843691 DOI: 10.1002/mrm.29913] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/12/2023] [Revised: 10/10/2023] [Accepted: 10/16/2023] [Indexed: 11/07/2023]
Abstract
PURPOSE This study evaluates the imaging performance of two-channel RF-shimming for fetal MRI at 3 T using four different local specific absorption rate (SAR) management strategies. METHODS Due to the ambiguity of safe local SAR levels for fetal MRI, local SAR limits for RF shimming were determined based on either each individual's own SAR levels in standard imaging mode (CP mode) or the maximum SAR level observed across seven pregnant body models in CP mode. Local SAR was constrained either indirectly by further constraining the whole-body SAR (wbSAR) or directly by using subject-specific local SAR models. Each strategy was evaluated by the improvement of the transmit field efficiency (average |B1 + |) and nonuniformity (|B1 + | variation) inside the fetus compared with CP mode for the same wbSAR. RESULTS Constraining wbSAR when using RF shimming decreases B1 + efficiency inside the fetus compared with CP mode (by 12%-30% on average), making it inefficient for SAR management. Using subject-specific models with SAR limits based on each individual's own CP mode SAR value, B1 + efficiency and nonuniformity are improved on average by 6% and 13% across seven pregnant models. In contrast, using SAR limits based on maximum CP mode SAR values across seven models, B1 + efficiency and nonuniformity are improved by 13% and 25%, compared with the best achievable improvement without SAR constraints: 15% and 26%. CONCLUSION Two-channel RF-shimming can safely and significantly improve the transmit field inside the fetus when subject-specific models are used with local SAR limits based on maximum CP mode SAR levels in the pregnant population.
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Affiliation(s)
- Filiz Yetisir
- Fetal-Neonatal Neuroimaging & Developmental Science Center, Boston Children’s Hospital, Boston, MA, USA
| | - Esra Abaci Turk
- Fetal-Neonatal Neuroimaging & Developmental Science Center, Boston Children’s Hospital, Boston, MA, USA
- Department of Pediatrics, Harvard Medical School, Boston, MA 02115, USA
| | - Elfar Adalsteinsson
- Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology, Cambridge, MA, USA
- Harvard-MIT Division of Health Sciences and Technology, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Lawrence L. Wald
- Harvard-MIT Division of Health Sciences and Technology, Massachusetts Institute of Technology, Cambridge, MA, USA
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, USA
- Department of Radiology, Harvard Medical School, Boston, MA, USA
| | - P. Ellen Grant
- Fetal-Neonatal Neuroimaging & Developmental Science Center, Boston Children’s Hospital, Boston, MA, USA
- Department of Pediatrics, Harvard Medical School, Boston, MA 02115, USA
- Department of Radiology, Harvard Medical School, Boston, MA, USA
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Matthew J, Uus A, De Souza L, Wright R, Fukami-Gartner A, Priego G, Saija C, Deprez M, Collado AE, Hutter J, Story L, Malamateniou C, Rhode K, Hajnal J, Rutherford MA. Craniofacial phenotyping with fetal MRI: a feasibility study of 3D visualisation, segmentation, surface-rendered and physical models. BMC Med Imaging 2024; 24:52. [PMID: 38429666 PMCID: PMC10905839 DOI: 10.1186/s12880-024-01230-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/04/2023] [Accepted: 02/19/2024] [Indexed: 03/03/2024] Open
Abstract
This study explores the potential of 3D Slice-to-Volume Registration (SVR) motion-corrected fetal MRI for craniofacial assessment, traditionally used only for fetal brain analysis. In addition, we present the first description of an automated pipeline based on 3D Attention UNet trained for 3D fetal MRI craniofacial segmentation, followed by surface refinement. Results of 3D printing of selected models are also presented.Qualitative analysis of multiplanar volumes, based on the SVR output and surface segmentations outputs, were assessed with computer and printed models, using standardised protocols that we developed for evaluating image quality and visibility of diagnostic craniofacial features. A test set of 25, postnatally confirmed, Trisomy 21 fetal cases (24-36 weeks gestational age), revealed that 3D reconstructed T2 SVR images provided 66-100% visibility of relevant craniofacial and head structures in the SVR output, and 20-100% and 60-90% anatomical visibility was seen for the baseline and refined 3D computer surface model outputs respectively. Furthermore, 12 of 25 cases, 48%, of refined surface models demonstrated good or excellent overall quality with a further 9 cases, 36%, demonstrating moderate quality to include facial, scalp and external ears. Additional 3D printing of 12 physical real-size models (20-36 weeks gestational age) revealed good/excellent overall quality in all cases and distinguishable features between healthy control cases and cases with confirmed anomalies, with only minor manual adjustments required before 3D printing.Despite varying image quality and data heterogeneity, 3D T2w SVR reconstructions and models provided sufficient resolution for the subjective characterisation of subtle craniofacial features. We also contributed a publicly accessible online 3D T2w MRI atlas of the fetal head, validated for accurate representation of normal fetal anatomy.Future research will focus on quantitative analysis, optimizing the pipeline, and exploring diagnostic, counselling, and educational applications in fetal craniofacial assessment.
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Affiliation(s)
- Jacqueline Matthew
- 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
- School of Biomedical Engineering and Imaging Sciences, King's College London, St Thomas' Hospital, London, UK
| | - Leah De Souza
- School of Biomedical Engineering and Imaging Sciences, King's College London, St Thomas' Hospital, London, UK
| | - Robert Wright
- School of Biomedical Engineering and Imaging Sciences, King's College London, St Thomas' Hospital, London, UK
| | - Abi Fukami-Gartner
- School of Biomedical Engineering and Imaging Sciences, King's College London, St Thomas' Hospital, London, UK
| | - Gema Priego
- School of Biomedical Engineering and Imaging Sciences, King's College London, St Thomas' Hospital, London, UK
- Barking, Havering and Redbridge University Hospitals NHS Trust, London, UK
| | - Carlo Saija
- School of Biomedical Engineering and Imaging Sciences, King's College London, St Thomas' Hospital, London, UK
| | - Maria Deprez
- School of Biomedical Engineering and Imaging Sciences, King's College London, St Thomas' Hospital, London, UK
| | - Alexia Egloff Collado
- 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
| | - Jana Hutter
- School of Biomedical Engineering and Imaging Sciences, King's College London, St Thomas' Hospital, London, UK
| | - Lisa Story
- 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
| | | | - Kawal Rhode
- School of Biomedical Engineering and Imaging Sciences, King's College London, St Thomas' Hospital, London, UK
| | - Jo Hajnal
- School of Biomedical Engineering and Imaging Sciences, King's College London, St Thomas' Hospital, London, UK
| | - Mary A Rutherford
- 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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7
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Papaioannou G, Caro-Domínguez P, Klein WM, Garel C, Cassart M. Indications for magnetic resonance imaging of the fetal body (extra-central nervous system): recommendations from the European Society of Paediatric Radiology Fetal Task Force. Pediatr Radiol 2023; 53:297-312. [PMID: 36161506 DOI: 10.1007/s00247-022-05495-4] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/03/2022] [Revised: 07/06/2022] [Accepted: 08/25/2022] [Indexed: 02/04/2023]
Abstract
The indications for fetal body MRI are amplifying because of the expanding possibilities of fetal and perinatal therapy. However, huge heterogeneity regarding the indications for fetal body MRI is seen among different European countries that is mostly related to local use of US, but also to local fetal MRI expertise and legislation on pregnancy termination. The purpose of this article is to summarize the precise indications for fetal MRI, excluding the central nervous system. MRI indications arise from the sonographic findings, based on the operator's experience and the various practices in the countries and institutions represented on the European Society of Paediatric Radiology Fetal Task Force. We also highlight the strengths and weaknesses of fetal US and MRI of the fetal body.
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Affiliation(s)
- Georgia Papaioannou
- Department of Pediatric Radiology, Mitera Maternity and Children's Hospital, 6 Erythrou Stavrou str, Maroussi 15123, Athens, Greece.
| | - Pablo Caro-Domínguez
- Pediatric Imaging Unit, Department of Radiology, Hospital Universitario Virgen del Rocío, Sevilla, Spain
| | - Willemijn M Klein
- Department of Medical Imaging, Radiology, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Catherine Garel
- Department of Radiology, Armand-Trousseau Hospital, Paris, France
| | - Marie Cassart
- Department of Radiology and Fetal Medicine, Iris South Hospitals, Brussels, Belgium
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8
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Gai S, Wang L, Zheng W. Comparison of prenatal ultrasound with MRI in the evaluation and prediction of fetal orofacial clefts. BMC Med Imaging 2022; 22:213. [PMID: 36471263 PMCID: PMC9720929 DOI: 10.1186/s12880-022-00929-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/30/2022] [Accepted: 11/05/2022] [Indexed: 12/12/2022] Open
Abstract
BACKGROUND Orofacial clefts (OFCs) are common craniofacial abnormalities. This study aimed to compare the diagnostic and predictive values of prenatal ultrasonography (US) and magnetic resonance imaging (MRI). METHODS We reviewed the newborn physical examinations or fetal autopsy data with OFCs. Between January 2013 and December 2018, the diagnoses resulting from prenatal US and MRI examination were compared retrospectively with the postpartum diagnoses. The diagnostic prediction of prenatal imaging was then determined. RESULTS 334 infants were identified with OFCs by either newborn physical exam or stillborn autopsy. For detection of OFCs by US, the total accuracy (ACC), true positive rate (TPR), true negative rate (TNR), positive predictive value (PPV), and negative predictive value (NPV) were 99.9% (111,178/110,286), 81.9% (230/281), 99.9% (109,948/110,005), 80.1% (230/287), and 99.9% (109,948/109,999), respectively. For MRI, the ACC, TPR, TNR, PPV, and NPV were 99.8% (4,125/4,132), 89.8% (44/49), 99.9% (4,081/4,083), 95.7% (44/46), and 99.9% (4,081/4,086), respectively. When we compared the predictive values between prenatal US and MRI, there were significant differences in the PPV of OFCs (P < 0.05), NPV of OFCs (P < 0.05), TPR of CLO (P < 0.001), PPV of CLP (P < 0.05), and TPR of CPO (P < 0.05). CONCLUSION Our results suggest that prenatal US could be effective for diagnosing and ruling out fetal OFCs. Diagnostic confidence is significantly improved when fetal MRI is used to assess fetal OFCs as an adjunct to US examination.
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Affiliation(s)
- Shuangshuang Gai
- grid.13402.340000 0004 1759 700XDepartment of Ultrasound, The Second Affiliated Hospital, Zhejiang University School of Medicine, Jiefang Rd No.88, Hangzhou, 310029 Zhejiang People’s Republic of China ,grid.13402.340000 0004 1759 700XDepartment of Ultrasound, Women’s Hospital, Zhejiang University School of Medicine, Xueshi Rd No.1, Hangzhou, 310006 Zhejiang People’s Republic of China
| | - Lixiu Wang
- grid.13402.340000 0004 1759 700XDepartment of Ultrasound, Women’s Hospital, Zhejiang University School of Medicine, Xueshi Rd No.1, Hangzhou, 310006 Zhejiang People’s Republic of China
| | - Weizeng Zheng
- grid.13402.340000 0004 1759 700XDepartment of Radiology, Women’s Hospital, Zhejiang University School of Medicine, Xueshi Rd No.1, Hangzhou, 310006 Zhejiang People’s Republic of China
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Eshiba SM, Zahran MH, Elnekeidy AM, Abdeldayem TM, Hassan HHM. Added value of fetal MRI as a complementary method to antenatal ultrasound in the assessment of non-CNS fetal congenital anomalies. THE EGYPTIAN JOURNAL OF RADIOLOGY AND NUCLEAR MEDICINE 2022. [DOI: 10.1186/s43055-022-00708-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022] Open
Abstract
Abstract
Background
Birth defects and congenital anomalies are different words used to describe developmental abnormalities that occur at birth. Congenital anomalies diagnosis during pregnancy is a difficult topic to which ultrasonography has made significant contributions. The availability of a generally safe, independent technique in the evaluation of prenatal anomalies would be a welcomed clinical and scientific alternative. Ultrasound (US) is the predominant modality for evaluating disorders related to fetus and pregnancy. In most situations, this examination by a professional operator offers sufficient information about fetal morphology, surroundings, and well-being. The abnormalities revealed by ultrasound can be subtle or inconclusive at times. MRI has been demonstrated to be useful in such circumstances in various studies. So the effective use of fetal MRI in the evaluation of non-CNS abnormalities of the body is a reason for adopting fetal MRI as an adjunct to US in obstetric imaging. This study aimed to examine the role of fetal MRI as a complementary method to the antenatal US in assessing non-CNS anomalies and how it changed or modified the diagnosis of anomalies.
Results
By analyzing the data of 30 pregnant females with fetal non-CNS congenital anomalies, the diagnostic accuracy of prenatal ultrasound alone in the detection of congenital anomalies was 76%, with a sensitivity of about 76%. And diagnostic accuracy of MRI alone was 96.6%, with a sensitivity of approximately 96.6%. Moreover, the diagnostic accuracy of combined prenatal US and prenatal MRI in the detection of congenital anomalies was 100%, with sensitivity about 100% and PPV about 100%.
Conclusion
Fetal MRI raises confidence in non-CNS malformation assessment. Compared to US, MRI overcomes many of the obstacles faced by the antenatal US. MRI is superior to the US in refining, changing, or adding more diagnostic information about the disease.
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Powers AM, White C, Neuberger I, Maloney JA, Stence NV, Mirsky D. Fetal MRI Neuroradiology: Indications. Clin Perinatol 2022; 49:573-586. [PMID: 36113923 DOI: 10.1016/j.clp.2022.05.001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
Fetal MRI is a safe, noninvasive examination of the fetus and placenta, a complement to ultrasonography. MRI provides detailed CNS evaluation, including depicting parenchymal architecture and posterior fossa morphology, and is key in prenatal assessment of spinal dysraphism, neck masses, and ventriculomegaly. Fetal MRI is typically performed after 22 weeks gestation, and ultrafast T1 and T2-weighted MRI sequences are the core of the exam, with advanced sequences such as diffusion weighted imaging used for specific questions. The fetal brain grows and develops rapidly, and familiarity with gestational age specific norms is essential to MRI interpretation.
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Affiliation(s)
- Andria M Powers
- Children's Hospital and Medical Center, University of Nebraska Medical Center, 8200 Dodge Street, Omaha, NE 68114, USA.
| | - Christina White
- Department of Radiology, Children's Hospital Colorado, University of Colorado, 13123 E. 16th Avenue, Box 125, Aurora, CO, 80045, USA
| | - Ilana Neuberger
- Department of Radiology, Children's Hospital Colorado, University of Colorado, 13123 E. 16th Avenue, Box 125, Aurora, CO, 80045, USA
| | - John A Maloney
- Department of Radiology, Children's Hospital Colorado, University of Colorado, 13123 E. 16th Avenue, Box 125, Aurora, CO, 80045, USA
| | - Nicholas V Stence
- Department of Radiology, Children's Hospital Colorado, University of Colorado, 13123 E. 16th Avenue, Box 125, Aurora, CO, 80045, USA
| | - David Mirsky
- Department of Radiology, Children's Hospital Colorado, University of Colorado, 13123 E. 16th Avenue, Box 125, Aurora, CO, 80045, USA
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Prayer D, Deprest J. The use of MRI in fetal conditions amenable for antenatal management. Prenat Diagn 2020; 40:3-5. [PMID: 31860748 DOI: 10.1002/pd.5629] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/14/2019] [Accepted: 11/16/2019] [Indexed: 11/12/2022]
Affiliation(s)
- Daniela Prayer
- Department of Biomedical Imaging and Image-guided Therapy, Division of Neuroradiology and Musculoskeletal Radiology, Medical University of Vienna, Austria
| | - Jan Deprest
- Clinical Department of Obstetrics and Gynaecology, University Hospitals Leuven, and Academic Development and Regeneration, Cluster Woman and Child, Leuven, Belgium.,Institute for Women's Health, University College London, London, UK
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