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Purbasari U, Asih D, H H, Manurung RT, Dewi P, Eureka AN. A rare case report: The value of fetal MRI to detect diprosopus twins. Radiol Case Rep 2024; 19:4940-4944. [PMID: 39247475 PMCID: PMC11378094 DOI: 10.1016/j.radcr.2024.07.055] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/17/2024] [Revised: 07/09/2024] [Accepted: 07/11/2024] [Indexed: 09/10/2024] Open
Abstract
Diprosopus is one of the rarest types of conjoined twins, caused by incomplete zygote separation in early pregnancy. It defines a condition with duplication of facial structures, monocephalic and 1 trunk. Early detection is difficult, but fetal MRI plays an important role in strengthening antenatal diagnosis of conjoined twin pregnancies and other major congenital abnormalities, complementing antenatal ultrasonography. A 28-year-old patient (G2P1A0) was referred from the regional general hospital for suspected malformations, including Dandy-Walker syndrome and a small mandible Antenatal 3-D ultrasound at 35 weeks revealed a single baby with macrosomia, hypoplasia of the vermis, and cleft lip with malformation of facial structures. A 3 Tesla MRI (Signa, GE Healthcare) revealed various developmental brain anomalies, including duplication of the frontotemporal lobes, corpus callosum agenesis, and small posterior fossa. The identification of 4 orbital structures raised suspicions of face duplication. This patient underwent a caesarean section and delivered a diprosopus twin baby. MRI emerged as an indispensable adjunct, complementing ultrasound in detecting congenital malformations. The success of this approach emphasizes collaborative efforts between clinicians and radiologists for accurate identification and management of complex fetal anomalies.
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Affiliation(s)
- Utami Purbasari
- Department of Radiology, Fatmawati General Hospital, Jl. RS. Fatmawati Raya, Num4, RT.4/RW.9, West Cilandak, South Jakarta 12430, Indonesia
- Department of Clinical Epidemiology, Faculty of Public Health, University of Indonesia, Jl. Lingkar Kampus Raya Universitas, Depok, West Java 16424, Indonesia
| | - Dewi Asih
- Department of Radiology, University of Prima Indonesia, Jl. Ayahanda No.68a, Sei Putih Tengah, District Medan Petisah, Medan, North Sumatra 20118, Indonesia
| | - Helda H
- Department of Clinical Epidemiology, Faculty of Public Health, University of Indonesia, Jl. Lingkar Kampus Raya Universitas, Depok, West Java 16424, Indonesia
| | - Reza Tigor Manurung
- Department of Obstetrics and Gynecology, Fatmawati General Hospital, Jl. RS. Fatmawati Raya, Num4, RT.4/RW.9, West Cilandak, South Jakarta 12430, Indonesia
| | - Puspa Dewi
- Department of Radiology, Fatmawati General Hospital, Jl. RS. Fatmawati Raya, Num4, RT.4/RW.9, West Cilandak, South Jakarta 12430, Indonesia
| | - Agnes Nina Eureka
- Department of Clinical Epidemiology, Faculty of Public Health, University of Indonesia, Jl. Lingkar Kampus Raya Universitas, Depok, West Java 16424, Indonesia
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Xu X, Sun C, Yu H, Yan G, Zhu Q, Kong X, Pan Y, Xu H, Zheng T, Zhou C, Wang Y, Xiao J, Chen R, Li M, Zhang S, Hu H, Zou Y, Wang J, Wang G, Wu D. Site effects in multisite fetal brain MRI: morphological insights into early brain development. Eur Radiol 2024:10.1007/s00330-024-11084-w. [PMID: 39299951 DOI: 10.1007/s00330-024-11084-w] [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: 03/21/2024] [Revised: 06/06/2024] [Accepted: 08/26/2024] [Indexed: 09/22/2024]
Abstract
OBJECTIVE To evaluate multisite effects on fetal brain MRI. Specifically, to identify crucial acquisition factors affecting fetal brain structural measurements and developmental patterns, while assessing the effectiveness of existing harmonization methods in mitigating site effects. MATERIALS AND METHODS Between May 2017 and March 2022, T2-weighted fast spin-echo sequences in-utero MRI were performed on healthy fetuses from retrospectively recruited pregnant volunteers on four different scanners at four sites. A generalized additive model (GAM) was used to quantitatively assess site effects, including field strength (FS), manufacturer (M), in-plane resolution (R), and slice thickness (ST), on subcortical volume and cortical morphological measurements, including cortical thickness, curvature, and sulcal depth. Growth models were selected to elucidate the developmental trajectories of these morphological measurements. Welch's test was performed to evaluate the influence of site effects on developmental trajectories. The comBat-GAM harmonization method was applied to mitigate site-related biases. RESULTS The final analytic sample consisted of 340 MRI scans from 218 fetuses (mean GA, 30.1 weeks ± 4.4 [range, 21.7-40 weeks]). GAM results showed that lower FS and lower spatial resolution led to overestimations in selected brain regions of subcortical volumes and cortical morphological measurements. Only the peak cortical thickness in developmental trajectories was significantly influenced by the effects of FS and R. Notably, ComBat-GAM harmonization effectively removed site effects while preserving developmental patterns. CONCLUSION Our findings pinpointed the key acquisition factors in in-utero fetal brain MRI and underscored the necessity of data harmonization when pooling multisite data for fetal brain morphology investigations. KEY POINTS Question How do specific site MRI acquisition factors affect fetal brain imaging? Finding Lower FS and spatial resolution overestimated subcortical volumes and cortical measurements. Cortical thickness in developmental trajectories was influenced by FS and in-plane resolution. Clinical relevance This study provides important guidelines for the fetal MRI community when scanning fetal brains and underscores the necessity of data harmonization of cross-center fetal studies.
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Affiliation(s)
- Xinyi Xu
- Department of Biomedical Engineering, College of Biomedical Engineering & Instrument Science, Zhejiang University, Hangzhou, China
| | - Cong Sun
- Department of Radiology, Beijing Hospital, National Center of Gerontology, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, Beijing, China
| | - Hong Yu
- Dalian Municipal Women and Children's Medical Center (Group), Dalian, China
| | - Guohui Yan
- Department of Radiology, Women's Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Qingqing Zhu
- Department of Radiology, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Xianglei Kong
- Department of Radiology, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Yibin Pan
- Department of Obstetrics and Gynecology, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, China
- Key Laboratory of Reproductive Dysfunction Management of Zhejiang Province, Zhejiang Provincial Clinical Research Center for Obstetrics and Gynecology, Hangzhou, China
| | - Haoan Xu
- Department of Biomedical Engineering, College of Biomedical Engineering & Instrument Science, Zhejiang University, Hangzhou, China
| | - Tianshu Zheng
- Department of Biomedical Engineering, College of Biomedical Engineering & Instrument Science, Zhejiang University, Hangzhou, China
| | - Chi Zhou
- Department of Biomedical Engineering, College of Biomedical Engineering & Instrument Science, Zhejiang University, Hangzhou, China
| | - Yutian Wang
- Department of Biomedical Engineering, College of Biomedical Engineering & Instrument Science, Zhejiang University, Hangzhou, China
| | - Jiaxin Xiao
- Department of Biomedical Engineering, College of Biomedical Engineering & Instrument Science, Zhejiang University, Hangzhou, China
- School of Biomedical Engineering & Imaging Sciences, Faculty of Life Sciences and Medicine, King's College London, London, UK
| | - Ruike Chen
- Department of Biomedical Engineering, College of Biomedical Engineering & Instrument Science, Zhejiang University, Hangzhou, China
| | - Mingyang Li
- Department of Biomedical Engineering, College of Biomedical Engineering & Instrument Science, Zhejiang University, Hangzhou, China
| | - Songying Zhang
- Department of Obstetrics and Gynecology, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, China
- Key Laboratory of Reproductive Dysfunction Management of Zhejiang Province, Zhejiang Provincial Clinical Research Center for Obstetrics and Gynecology, Hangzhou, China
| | - Hongjie Hu
- Department of Radiology, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, China.
| | - Yu Zou
- Department of Radiology, Women's Hospital, Zhejiang University School of Medicine, Hangzhou, China.
| | - Jingshi Wang
- Dalian Municipal Women and Children's Medical Center (Group), Dalian, China.
| | - Guangbin Wang
- Department of Radiology, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, China.
| | - Dan Wu
- Department of Biomedical Engineering, College of Biomedical Engineering & Instrument Science, Zhejiang University, Hangzhou, China.
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Xu H, Shi W, Sun J, Zheng T, Xu X, Sun C, Yi S, Wang G, Wu D. A motion assessment method for reference stack selection in fetal brain MRI reconstruction based on tensor rank approximation. NMR IN BIOMEDICINE 2024:e5248. [PMID: 39231762 DOI: 10.1002/nbm.5248] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/31/2024] [Revised: 07/12/2024] [Accepted: 08/08/2024] [Indexed: 09/06/2024]
Abstract
Slice-to-volume registration and super-resolution reconstruction are commonly used to generate 3D volumes of the fetal brain from 2D stacks of slices acquired in multiple orientations. A critical initial step in this pipeline is to select one stack with the minimum motion among all input stacks as a reference for registration. An accurate and unbiased motion assessment (MA) is thus crucial for successful selection. Here, we presented an MA method that determines the minimum motion stack based on 3D low-rank approximation using CANDECOMP/PARAFAC (CP) decomposition. Compared to the current 2D singular value decomposition (SVD) based method that requires flattening stacks into matrices to obtain ranks, in which the spatial information is lost, the CP-based method can factorize 3D stack into low-rank and sparse components in a computationally efficient manner. The difference between the original stack and its low-rank approximation was proposed as the motion indicator. Experiments on linearly and randomly simulated motion illustrated that CP demonstrated higher sensitivity in detecting small motion with a lower baseline bias, and achieved a higher assessment accuracy of 95.45% in identifying the minimum motion stack, compared to the SVD-based method with 58.18%. CP also showed superior motion assessment capabilities in real-data evaluations. Additionally, combining CP with the existing SRR-SVR pipeline significantly improved 3D volume reconstruction. The results indicated that our proposed CP showed superior performance compared to SVD-based methods with higher sensitivity to motion, assessment accuracy, and lower baseline bias, and can be used as a prior step to improve fetal brain reconstruction.
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Affiliation(s)
- Haoan Xu
- Key Laboratory for Biomedical Engineering of Ministry of Education, Department of Biomedical Engineering, College of Biomedical Engineering & Instrument Science, Zhejiang University, Hangzhou, China
| | - Wen Shi
- Key Laboratory for Biomedical Engineering of Ministry of Education, Department of Biomedical Engineering, College of Biomedical Engineering & Instrument Science, Zhejiang University, Hangzhou, China
- Department of Biomedical Engineering, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
| | - Jiwei Sun
- Key Laboratory for Biomedical Engineering of Ministry of Education, Department of Biomedical Engineering, College of Biomedical Engineering & Instrument Science, Zhejiang University, Hangzhou, China
| | - Tianshu Zheng
- Key Laboratory for Biomedical Engineering of Ministry of Education, Department of Biomedical Engineering, College of Biomedical Engineering & Instrument Science, Zhejiang University, Hangzhou, China
| | - Xinyi Xu
- Key Laboratory for Biomedical Engineering of Ministry of Education, Department of Biomedical Engineering, College of Biomedical Engineering & Instrument Science, Zhejiang University, Hangzhou, China
| | - Cong Sun
- Department of Radiology, Beijing Hospital, National Center of Gerontology, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, Beijing, China
| | - Sun Yi
- MR Collaboration, Siemens Healthcare China, Shanghai, China
| | - Guangbin Wang
- Department of Radiology, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, Shandong, China
| | - Dan Wu
- Key Laboratory for Biomedical Engineering of Ministry of Education, Department of Biomedical Engineering, College of Biomedical Engineering & Instrument Science, Zhejiang University, Hangzhou, China
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Desrosiers J, Caron-Desrochers L, René A, Gaudet I, Pincivy A, Paquette N, Gallagher A. Functional connectivity development in the prenatal and neonatal stages measured by functional magnetic resonance imaging: A systematic review. Neurosci Biobehav Rev 2024; 163:105778. [PMID: 38936564 DOI: 10.1016/j.neubiorev.2024.105778] [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: 12/07/2023] [Revised: 04/28/2024] [Accepted: 06/17/2024] [Indexed: 06/29/2024]
Abstract
The prenatal and neonatal periods are two of the most important developmental stages of the human brain. It is therefore crucial to understand normal brain development and how early connections are established during these periods, in order to advance the state of knowledge on altered brain development and eventually identify early brain markers of neurodevelopmental disorders and diseases. In this systematic review (Prospero ID: CRD42024511365), we compiled resting state functional magnetic resonance imaging (fMRI) studies in healthy fetuses and neonates, in order to outline the main characteristics of typical development of the functional brain connectivity during the prenatal and neonatal periods. A systematic search of five databases identified a total of 12 573 articles. Of those, 28 articles met pre-established selection criteria based determined by the authors after surveying and compiling the major limitations reported within the literature. Inclusion criteria were: (1) resting state studies; (2) presentation of original results; (3) use of fMRI with minimum one Tesla; (4) a population ranging from 20 weeks of GA to term birth (around 37-42 weeks of PMA); (5) singleton pregnancy with normal development (absence of any complications known to alter brain development). Exclusion criteria were: (1) preterm studies; (2) post-mortem studies; (3) clinical or pathological studies; (4) twin studies; (5) papers with a sole focus on methodology (i.e. focused on tool and analysis development); (6) volumetric studies; (7) activation map studies; (8) cortical analysis studies; (9) conference papers. A risk of bias assessment was also done to evaluate each article's methodological rigor. 1877 participants were included across all the reviewed articles. Results consistently revealed a developmental gradient of increasing functional brain connectivity from posterior to anterior regions and from proximal-to-distal regions. A decrease in local small-world organization shortly after birth was also observed; small-world characteristics were present in fetuses and newborns, but appeared weaker in the latter group. Also, the posterior-to-anterior gradient could be associated with earlier development of the sensorimotor networks in the posterior regions while more complex higher-order networks (e.g. attention-related) mature later in the anterior regions. The main limitations of this systematic review stem from the inherent limitations of functional imaging in fetuses, mainly: unevenly distributed populations and limited sample sizes; fetal movements in the womb and other imaging obstacles; and a large voxel resolution when imaging a small brain. Another limitation specific to this review is the relatively small number of included articles compared to very a large search result, which may have led to relevant articles having been overlooked.
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Affiliation(s)
- Jérémi Desrosiers
- Neurodevelopmental Optical Imaging Laboratory (LIONLAB), Sainte-Justine University Hospital Research Center, Montreal, QC, Canada; School of Psychoeducation, University of Montreal, QC, Canada
| | - Laura Caron-Desrochers
- Neurodevelopmental Optical Imaging Laboratory (LIONLAB), Sainte-Justine University Hospital Research Center, Montreal, QC, Canada; Department of Psychology, University of Montreal, QC, Canada
| | - Andréanne René
- Neurodevelopmental Optical Imaging Laboratory (LIONLAB), Sainte-Justine University Hospital Research Center, Montreal, QC, Canada; Department of Psychology, University of Montreal, QC, Canada
| | - Isabelle Gaudet
- Neurodevelopmental Optical Imaging Laboratory (LIONLAB), Sainte-Justine University Hospital Research Center, Montreal, QC, Canada; Department of Health Sciences, Université du Québec à Chicoutimi, QC, Canada
| | - Alix Pincivy
- Sainte-Justine University Health Center and Research Center Libraries, Montreal, QC, Canada
| | - Natacha Paquette
- Neurodevelopmental Optical Imaging Laboratory (LIONLAB), Sainte-Justine University Hospital Research Center, Montreal, QC, Canada; Department of Psychology, University of Montreal, QC, Canada
| | - Anne Gallagher
- Neurodevelopmental Optical Imaging Laboratory (LIONLAB), Sainte-Justine University Hospital Research Center, Montreal, QC, Canada; Department of Psychology, University of Montreal, QC, Canada.
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5
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Loomis-Goltl EI, Power SJ, Neuberger I, Barhaghi K, Kotlarek KJ. Examining Craniofacial and Velopharyngeal Structures in Premature Infants: A Window Into the Womb. J Craniofac Surg 2024:00001665-990000000-01711. [PMID: 38864619 DOI: 10.1097/scs.0000000000010390] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/06/2024] [Accepted: 05/09/2024] [Indexed: 06/13/2024] Open
Abstract
BACKGROUND Very little is known about how the velopharynx and levator veli palatini muscle develop in utero. The purpose of this study was to describe craniofacial, velopharyngeal, and levator veli palatini dimensions in a group of infants born prematurely and imaged before 40 weeks gestation. METHODS A retrospective, descriptive study design was utilized to examine the MRI scans of 6 infants less than 40 weeks' gestation. Imaging was initially completed for medically necessity and pulled from patients' charts retrospectively for the purpose of this study. Craniofacial, velopharyngeal, and levator veli palatini dimensions were analyzed. RESULTS All linear measures were consistently shorter across all variable categories. While effective VP ratio was less favorable for speech in infants under 40 weeks' gestation, angle measures such as LVP angle of origin, NSB angle, SNA angle, and SNB angle were relatively unchanged. CONCLUSIONS Linear craniofacial, VP, and LVP variables tend to be smaller in infants under 40 weeks' gestation than those reported within the first 6 months of life while angulation is relatively similar. Future research in this area may be relevant to better diagnosis of craniofacial conditions in utero.
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Affiliation(s)
| | | | - Ilana Neuberger
- University of Colorado School of Medicine
- Children's Hospital Colorado, Aurora, CO
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6
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van der Beek JN, Schenk JP, Morosi C, Watson TA, Coma A, Graf N, Chowdhury T, Ramírez-Villar GL, Spreafico F, Welter N, Dzhuma K, van Tinteren H, de Krijger RR, van den Heuvel-Eibrink MM, Littooij AS. Diagnostic magnetic resonance imaging characteristics of congenital mesoblastic nephroma: a retrospective multi-center International Society of Pediatric Oncology-Renal Tumor Study Group (SIOP-RTSG) radiology panel study. Pediatr Radiol 2024; 54:965-976. [PMID: 38609702 PMCID: PMC11111520 DOI: 10.1007/s00247-024-05918-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/06/2023] [Revised: 03/20/2024] [Accepted: 03/21/2024] [Indexed: 04/14/2024]
Abstract
BACKGROUND Congenital mesoblastic nephroma is the most common solid renal tumor in neonates. Therefore, patients <3 months of age are advised to undergo upfront nephrectomy, whereas invasive procedures at diagnosis in patients ≥3 months of age are discouraged by the International Society of Pediatric Oncology-Renal Tumor Study Group (SIOP-RTSG). Nevertheless, discriminating congenital mesoblastic nephroma, especially from the more common Wilms tumor, solely based on imaging remains difficult. Recently, magnetic resonance imaging (MRI) has become the preferred modality. Studies focusing on MRI characteristics of congenital mesoblastic nephroma are limited. OBJECTIVE This study aims to identify diagnostic MRI characteristics of congenital mesoblastic nephroma in the largest series of patients to date. MATERIALS AND METHODS In this retrospective multicenter study, five SIOP-RTSG national review radiologists identified 52 diagnostic MRIs of histologically proven congenital mesoblastic nephromas. MRI was performed following SIOP-RTSG protocols, while radiologists assessed their national cases using a validated case report form. RESULTS Patients (24/52 classic, 11/52 cellular, and 15/52 mixed type congenital mesoblastic nephroma, 2/52 unknown) had a median age of 1 month (range 1 day-3 months). Classic type congenital mesoblastic nephroma appeared homogeneous with a lack of hemorrhage, necrosis and/or cysts, showing a concentric ring sign in 14 (58.3%) patients. Cellular and mixed type congenital mesoblastic nephroma appeared more heterogeneous and were larger (311.6 and 174.2 cm3, respectively, versus 41.0 cm3 for the classic type (P<0.001)). All cases were predominantly T2-weighted isointense and T1-weighted hypointense, and mean overall apparent diffusion coefficient values ranged from 1.05-1.10×10-3 mm2/s. CONCLUSION This retrospective international collaborative study showed classic type congenital mesoblastic nephroma predominantly presented as a homogeneous T2-weighted isointense mass with a typical concentric ring sign, whereas the cellular type appeared more heterogeneous. Future studies may use identified MRI characteristic of congenital mesoblastic nephroma for validation and for exploring the discriminative non-invasive value of MRI, especially from Wilms tumor.
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Affiliation(s)
- Justine N van der Beek
- Department of Radiology and Nuclear Medicine, University Medical Center Utrecht/Wilhelmina Children's Hospital, Utrecht University, Heidelberglaan 100, 3584 CX, Utrecht, The Netherlands.
- Princess Máxima Center for Pediatric Oncology, Utrecht, The Netherlands.
| | - Jens-Peter Schenk
- Clinic of Diagnostic and Interventional Radiology, Division of Pediatric Radiology, Heidelberg University Hospital, Heidelberg, Germany
| | - Carlo Morosi
- Department of Radiology, Fondazione IRCCS Istituto Nazionale dei Tumori, Milan, Italy
| | - Tom A Watson
- Department of Paediatric Radiology, Great Ormond Street Hospital for Children NHS Foundation Trust, London, UK
| | - Ana Coma
- Department of Pediatric Radiology, Hospital Vall d'Hebron, Barcelona, Spain
| | - Norbert Graf
- Department of Pediatric Oncology & Hematology, Saarland University Medical Center and Saarland University Faculty of Medicine, Homburg, Germany
| | - Tanzina Chowdhury
- Department of Haematology and Oncology, Great Ormond Street Hospital for Children NHS Foundation Trust, London, UK
| | - Gema L Ramírez-Villar
- Department of Paediatric Oncology, Hospital Universitario Virgen del Rocío, Seville, Spain
| | - Filippo Spreafico
- Pediatric Oncology Unit, Department of Medical Oncology and Hematology, Fondazione IRCCS Istituto Nazionale dei Tumori, Milan, Italy
| | - Nils Welter
- Department of Pediatric Oncology & Hematology, Saarland University Medical Center and Saarland University Faculty of Medicine, Homburg, Germany
| | - Kristina Dzhuma
- Developmental Biology and Cancer Department, University College London Great Ormond Street Institute of Child Health, London, UK
- Department of Paediatric Urology, Great Ormond Street Hospital for Children NHS Foundation Trust, London, UK
| | - Harm van Tinteren
- Princess Máxima Center for Pediatric Oncology, Utrecht, The Netherlands
| | - Ronald R de Krijger
- Princess Máxima Center for Pediatric Oncology, Utrecht, The Netherlands
- Department of Pathology, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Marry M van den Heuvel-Eibrink
- Princess Máxima Center for Pediatric Oncology, Utrecht, The Netherlands
- Division of Child Health, Wilhelmina Children's Hospital, Utrecht University, Utrecht, The Netherlands
| | - Annemieke S Littooij
- Department of Radiology and Nuclear Medicine, University Medical Center Utrecht/Wilhelmina Children's Hospital, Utrecht University, Heidelberglaan 100, 3584 CX, Utrecht, The Netherlands
- Princess Máxima Center for Pediatric Oncology, Utrecht, The Netherlands
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Feng Z, Zhou R, Xia W, Wang S, Liu Y, Huang Z, Gan H. PDFF-CNN: An attention-guided dynamic multi-orientation feature fusion method for gestational age prediction on imbalanced fetal brain MRI dataset. Med Phys 2024; 51:3480-3494. [PMID: 38043088 DOI: 10.1002/mp.16875] [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: 08/06/2023] [Revised: 11/02/2023] [Accepted: 11/19/2023] [Indexed: 12/05/2023] Open
Abstract
BACKGROUND Fetal brain magnetic resonance imaging (MRI)-based gestational age prediction has been widely used to characterize normal fetal brain development and diagnose congenital brain malformations. PURPOSE The uncertainty of fetal position and external interference leads to variable localization and direction of the fetal brain. In addition, pregnant women typically concentrate on receiving MRI scans during the fetal anomaly scanning week, leading to an imbalanced distribution of fetal brain MRI data. The above-mentioned problems pose great challenges for deep learning-based fetal brain MRI gestational age prediction. METHODS In this study, a pyramid squeeze attention (PSA)-guided dynamic feature fusion CNN (PDFF-CNN) is proposed to robustly predict gestational ages from fetal brain MRI images on an imbalanced dataset. PDFF-CNN contains four components: transformation module, feature extraction module, dynamic feature fusion module, and balanced mean square error (MSE) loss. The transformation and feature extraction modules are employed by using the PSA to learn multiscale and multi-orientation feature representations in a parallel weight-sharing Siamese network. The dynamic feature fusion module automatically learns the weights of feature vectors generated in the feature extraction module to dynamically fuse multiscale and multi-orientation brain sulci and gyri features. Considering the fact of the imbalanced dataset, the balanced MSE loss is used to mitigate the negative impact of imbalanced data distribution on gestational age prediction performance. RESULTS Evaluated on an imbalanced fetal brain MRI dataset of 1327 routine clinical T2-weighted MRI images from 157 subjects, PDFF-CNN achieved promising gestational age prediction performance with an overall mean absolute error of 0.848 weeks and anR 2 $R^2$ of 0.904. Furthermore, the attention activation maps of PDFF-CNN were derived, which revealed regional features that contributed to gestational age prediction at each gestational stage. CONCLUSIONS These results suggest that the proposed PDFF-CNN might have broad clinical applicability in guiding treatment interventions and delivery planning, which has the potential to be helpful with prenatal diagnosis.
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Affiliation(s)
- Ziteng Feng
- School of Computer Science, Hubei University of Technology, Wuhan, China
| | - Ran Zhou
- School of Computer Science, Hubei University of Technology, Wuhan, China
| | - Wei Xia
- Wuhan Children's Hospital (Wuhan Maternal and Child Healthcare Hospital), Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Siru Wang
- School of Computer Science, Hubei University of Technology, Wuhan, China
| | - Yang Liu
- School of Computer Science, Hubei University of Technology, Wuhan, China
| | - Zhongwei Huang
- School of Computer Science, Hubei University of Technology, Wuhan, China
| | - Haitao Gan
- School of Computer Science, Hubei University of Technology, Wuhan, China
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8
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Zhang W, Zhang X, Li L, Liao L, Zhao F, Zhong T, Pei Y, Xu X, Yang C, Zhang H, Li G. A joint brain extraction and image quality assessment framework for fetal brain MRI slices. Neuroimage 2024; 290:120560. [PMID: 38431181 DOI: 10.1016/j.neuroimage.2024.120560] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/13/2023] [Revised: 02/26/2024] [Accepted: 02/27/2024] [Indexed: 03/05/2024] Open
Abstract
Brain extraction and image quality assessment are two fundamental steps in fetal brain magnetic resonance imaging (MRI) 3D reconstruction and quantification. However, the randomness of fetal position and orientation, the variability of fetal brain morphology, maternal organs around the fetus, and the scarcity of data samples, all add excessive noise and impose a great challenge to automated brain extraction and quality assessment of fetal MRI slices. Conventionally, brain extraction and quality assessment are typically performed independently. However, both of them focus on the brain image representation, so they can be jointly optimized to ensure the network learns more effective features and avoid overfitting. To this end, we propose a novel two-stage dual-task deep learning framework with a brain localization stage and a dual-task stage for joint brain extraction and quality assessment of fetal MRI slices. Specifically, the dual-task module compactly contains a feature extraction module, a quality assessment head and a segmentation head with feature fusion for simultaneous brain extraction and quality assessment. Besides, a transformer architecture is introduced into the feature extraction module and the segmentation head. We utilize a multi-step training strategy to guarantee a stable and successful training of all modules. Finally, we validate our method by a 5-fold cross-validation and ablation study on a dataset with fetal brain MRI slices in different qualities, and perform a cross-dataset validation in addition. Experiments show that the proposed framework achieves very promising performance.
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Affiliation(s)
- Wenhao Zhang
- School of Electronic and Information Engineering, South China University of Technology, Guangzhou, China
| | - Xin Zhang
- School of Electronic and Information Engineering, South China University of Technology, Guangzhou, China.
| | - Lingyi Li
- School of Electronic and Information Engineering, South China University of Technology, Guangzhou, China
| | - Lufan Liao
- School of Electronic and Information Engineering, South China University of Technology, Guangzhou, China
| | - Fenqiang Zhao
- Department of Radiology and BRIC, University of North Carolina at Chapel Hill, USA
| | - Tao Zhong
- Department of Radiology and BRIC, University of North Carolina at Chapel Hill, USA
| | - Yuchen Pei
- Department of Radiology and BRIC, University of North Carolina at Chapel Hill, USA
| | - Xiangmin Xu
- School of Electronic and Information Engineering, South China University of Technology, Guangzhou, China
| | - Chaoxiang Yang
- Department of Radiology, Guangdong Women and Children Hospital, Guangzhou, China
| | - He Zhang
- Department of Radiology, Obstetrics and Gynecology Hospital, Fudan University, Shanghai, China.
| | - Gang Li
- Department of Radiology and BRIC, University of North Carolina at Chapel Hill, USA.
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Roy P, Sah V, Deb N, Jaiswal V. Navigating the path of TOF- A Literature review unveiling maternal-fetal dynamics, treatment strategies and psychological dimensions. Dis Mon 2024; 70:101659. [PMID: 37951837 DOI: 10.1016/j.disamonth.2023.101659] [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] [Indexed: 11/14/2023]
Abstract
Tetralogy of Fallot (TOF) is a complex congenital heart defect that poses unique challenges for both mothers and their unborn children. This comprehensive review, aims to provide a holistic exploration of the maternal-fetal dynamics, treatment strategies, and psychological dimensions involved in navigating the path of TOF during pregnancy. It delves into the physiological changes that occur during pregnancy in TOF patients, including pulmonary regurgitation, right ventricular hypertrophy, and the overriding aorta. By understanding these dynamics, healthcare professionals can tailor treatment strategies to optimize maternal and fetal outcomes. The review further investigates the treatment strategies employed in managing TOF during pregnancy, encompassing medical interventions, cardiac monitoring, and multidisciplinary care. It explores the role of advanced imaging techniques, such as echocardiography and cardiac magnetic resonance imaging, in assessing TOF severity and guiding treatment decisions. The psychological factors influencing maternal adaptation, coping strategies, and the long-term implications on the child's psychological development are also examined. The integration of multidisciplinary approaches, including cardiac care, psychosocial support, and mental health interventions, can orchestrate a harmonious symphony of maternal-fetal well-being in the challenging journey of TOF pregnancies. Future research endeavours should continue to explore these dimensions, further refining treatment strategies and enhancing the understanding of TOF pregnancies for improved outcomes.
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Affiliation(s)
- Poulami Roy
- Department of Medicine, North Bengal Medical College and Hospital, India
| | - Viraj Sah
- Seth Gordhandas Sunderdas Medical College and King Edward Memorial Hospital, Mumbai
| | - Novonil Deb
- Department of Medicine, North Bengal Medical College and Hospital, India.
| | - Vikash Jaiswal
- Department of Cardiovascular Research, Larkin Community Hospital, South Miami, FL, USA
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10
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Hussain NM, O'Halloran M, McDermott B, Elahi MA. Fetal monitoring technologies for the detection of intrapartum hypoxia - challenges and opportunities. Biomed Phys Eng Express 2024; 10:022002. [PMID: 38118183 DOI: 10.1088/2057-1976/ad17a6] [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: 05/13/2023] [Accepted: 12/20/2023] [Indexed: 12/22/2023]
Abstract
Intrapartum fetal hypoxia is related to long-term morbidity and mortality of the fetus and the mother. Fetal surveillance is extremely important to minimize the adverse outcomes arising from fetal hypoxia during labour. Several methods have been used in current clinical practice to monitor fetal well-being. For instance, biophysical technologies including cardiotocography, ST-analysis adjunct to cardiotocography, and Doppler ultrasound are used for intrapartum fetal monitoring. However, these technologies result in a high false-positive rate and increased obstetric interventions during labour. Alternatively, biochemical-based technologies including fetal scalp blood sampling and fetal pulse oximetry are used to identify metabolic acidosis and oxygen deprivation resulting from fetal hypoxia. These technologies neither improve clinical outcomes nor reduce unnecessary interventions during labour. Also, there is a need to link the physiological changes during fetal hypoxia to fetal monitoring technologies. The objective of this article is to assess the clinical background of fetal hypoxia and to review existing monitoring technologies for the detection and monitoring of fetal hypoxia. A comprehensive review has been made to predict fetal hypoxia using computational and machine-learning algorithms. The detection of more specific biomarkers or new sensing technologies is also reviewed which may help in the enhancement of the reliability of continuous fetal monitoring and may result in the accurate detection of intrapartum fetal hypoxia.
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Affiliation(s)
- Nadia Muhammad Hussain
- Discipline of Electrical & Electronic Engineering, University of Galway, Ireland
- Translational Medical Device Lab, Lambe Institute for Translational Research, University Hospital Galway, Ireland
| | - Martin O'Halloran
- Discipline of Electrical & Electronic Engineering, University of Galway, Ireland
- Translational Medical Device Lab, Lambe Institute for Translational Research, University Hospital Galway, Ireland
| | - Barry McDermott
- Translational Medical Device Lab, Lambe Institute for Translational Research, University Hospital Galway, Ireland
- College of Medicine, Nursing & Health Sciences, University of Galway, Ireland
| | - Muhammad Adnan Elahi
- Discipline of Electrical & Electronic Engineering, University of Galway, Ireland
- Translational Medical Device Lab, Lambe Institute for Translational Research, University Hospital Galway, Ireland
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11
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Maralani PJ, Pai V, Ertl-Wagner BB. Safety of Magnetic Resonance Imaging in Pregnancy. RADIOLOGIE (HEIDELBERG, GERMANY) 2023; 63:34-40. [PMID: 37747489 DOI: 10.1007/s00117-023-01207-7] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Accepted: 08/24/2023] [Indexed: 09/26/2023]
Abstract
Magnetic resonance imaging is being increasingly used to diagnose and follow up a variety of medical conditions in pregnancy, both for maternal and fetal indications. However, limited data regarding its safe use in pregnancy may be a source of anxiety and avoidance for both patients and their healthcare providers. In this review, we critically discuss the main safety concerns of Magnetic Resonance Imaging (MRI) in pregnancy including energy deposition, acoustic noise, and use of contrast agents, supported by data from animal and human studies. Use of maternal sedatives and concerns related to occupational exposure in pregnant personnel are also addressed. Exposure to gadolinium-based contrast agents and sedation for MRI during pregnancy should be avoided whenever feasible.
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Affiliation(s)
- Pejman Jabehdar Maralani
- Department of Medical Imaging, Sunnybrook Health Sciences Centre, Bayview Avenue, Room AG270C, 2075, Toronto, Ontario, Canada.
| | - Vivek Pai
- Department of Medical Imaging, University of Toronto, The Hospital for Sick Children, 555 University Ave, M5G 1X8, Toronto, ON, Canada
| | - Birgit B Ertl-Wagner
- Department of Medical Imaging, University of Toronto, The Hospital for Sick Children, 555 University Ave, M5G 1X8, Toronto, ON, Canada
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12
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Vahedifard F, Ai HA, Supanich MP, Marathu KK, Liu X, Kocak M, Ansari SM, Akyuz M, Adepoju JO, Adler S, Byrd S. Automatic Ventriculomegaly Detection in Fetal Brain MRI: A Step-by-Step Deep Learning Model for Novel 2D-3D Linear Measurements. Diagnostics (Basel) 2023; 13:2355. [PMID: 37510099 PMCID: PMC10378043 DOI: 10.3390/diagnostics13142355] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/15/2023] [Revised: 07/07/2023] [Accepted: 07/09/2023] [Indexed: 07/30/2023] Open
Abstract
In this study, we developed an automated workflow using a deep learning model (DL) to measure the lateral ventricle linearly in fetal brain MRI, which are subsequently classified into normal or ventriculomegaly, defined as a diameter wider than 10 mm at the level of the thalamus and choroid plexus. To accomplish this, we first trained a UNet-based deep learning model to segment the brain of a fetus into seven different tissue categories using a public dataset (FeTA 2022) consisting of fetal T2-weighted images. Then, an automatic workflow was developed to perform lateral ventricle measurement at the level of the thalamus and choroid plexus. The test dataset included 22 cases of normal and abnormal T2-weighted fetal brain MRIs. Measurements performed by our AI model were compared with manual measurements performed by a general radiologist and a neuroradiologist. The AI model correctly classified 95% of fetal brain MRI cases into normal or ventriculomegaly. It could measure the lateral ventricle diameter in 95% of cases with less than a 1.7 mm error. The average difference between measurements was 0.90 mm in AI vs. general radiologists and 0.82 mm in AI vs. neuroradiologists, which are comparable to the difference between the two radiologists, 0.51 mm. In addition, the AI model also enabled the researchers to create 3D-reconstructed images, which better represent real anatomy than 2D images. When a manual measurement is performed, it could also provide both the right and left ventricles in just one cut, instead of two. The measurement difference between the general radiologist and the algorithm (p = 0.9827), and between the neuroradiologist and the algorithm (p = 0.2378), was not statistically significant. In contrast, the difference between general radiologists vs. neuroradiologists was statistically significant (p = 0.0043). To the best of our knowledge, this is the first study that performs 2D linear measurement of ventriculomegaly with a 3D model based on an artificial intelligence approach. The paper presents a step-by-step approach for designing an AI model based on several radiological criteria. Overall, this study showed that AI can automatically calculate the lateral ventricle in fetal brain MRIs and accurately classify them as abnormal or normal.
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Affiliation(s)
- Farzan Vahedifard
- Department of Diagnostic Radiology and Nuclear Medicine, Rush University Medical Center, Rush Medical College, Chicago, IL 60612, USA
| | - H Asher Ai
- Division for Diagnostic Medical Physics, Department of Radiology and Nuclear Medicine, Rush University Medical Center, Rush Medical College, Chicago, IL 60612, USA
| | - Mark P Supanich
- Division for Diagnostic Medical Physics, Department of Radiology and Nuclear Medicine, Rush University Medical Center, Rush Medical College, Chicago, IL 60612, USA
| | - Kranthi K Marathu
- Department of Diagnostic Radiology and Nuclear Medicine, Rush University Medical Center, Rush Medical College, Chicago, IL 60612, USA
| | - Xuchu Liu
- Department of Diagnostic Radiology and Nuclear Medicine, Rush University Medical Center, Rush Medical College, Chicago, IL 60612, USA
| | - Mehmet Kocak
- Department of Diagnostic Radiology and Nuclear Medicine, Rush University Medical Center, Rush Medical College, Chicago, IL 60612, USA
| | - Shehbaz M Ansari
- Department of Diagnostic Radiology and Nuclear Medicine, Rush University Medical Center, Rush Medical College, Chicago, IL 60612, USA
| | - Melih Akyuz
- Department of Diagnostic Radiology and Nuclear Medicine, Rush University Medical Center, Rush Medical College, Chicago, IL 60612, USA
| | - Jubril O Adepoju
- Department of Diagnostic Radiology and Nuclear Medicine, Rush University Medical Center, Rush Medical College, Chicago, IL 60612, USA
| | - Seth Adler
- Department of Diagnostic Radiology and Nuclear Medicine, Rush University Medical Center, Rush Medical College, Chicago, IL 60612, USA
| | - Sharon Byrd
- Department of Diagnostic Radiology and Nuclear Medicine, Rush University Medical Center, Rush Medical College, Chicago, IL 60612, USA
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13
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Chandrasekhar P, Rangasami R, Andrew C, Paarthipan N. Establishing and Comparing the Normal apparent Diffusion Coefficient Values of Fetal Organs and Placenta Using 1.5 Tesla and 3.0 T MRI at Various Gestational Age. Ethiop J Health Sci 2023; 33:621-630. [PMID: 38784210 PMCID: PMC11111180 DOI: 10.4314/ejhs.v33i4.8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/27/2023] [Accepted: 04/04/2023] [Indexed: 05/25/2024] Open
Abstract
Background Diffusion-weighted imaging (DWI) is the random Brownian motion of water molecules within a tissue voxel. The apparent diffusion coefficient (ADC) is a quantitative parameter calculated from the DWI that directly reflects the mobility of water molecules in biological tissues. The objective of this study was to establish and compare the normal reference ADC values of fetal organs and the placenta using 1.5 T and 3.0 T MRI at various gestational ages. Methods This was a retrospective and prospective observational study. This study included one hundred and three (103) singleton pregnancies for each magnetic field strength. Diffusion-weighted imaging was performed using single-shot spin-echo-planar imaging (EPI) in the axial plane of the fetal head-trunk with a slice thickness of 4mm and diffusion gradient values of b = 0 and b = 700-800 s/mm2. Results The mean ADC values of cerebral WM areas were significantly higher than the deep grey areas in the brain. The white-matter regions, lung, and placenta showed a positive and significant correlation with increasing gestational age in both field strengths. A statistically weak negative correlation was observed between increasing gestational age and ADC measurements obtained in the thalamus, cerebellum, pons, and kidney. Conclusion This study gives the reference values for both 1.5T and 3T MRI of vital organs. The current study shows that diffusion-weighted MRI can offer a promising technique to evaluate the structural development of fetal organs and can potentially act as a biomarker for predicting the functionality of the fetal organs in abnormalities.
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Affiliation(s)
- Priyanka Chandrasekhar
- Department of Radiology, Sri Ramachandra Institute of Higher Education and Research, Chennai-600116, India
| | - Rajeswaran Rangasami
- Department of Radiology, Sri Ramachandra Institute of Higher Education and Research, Chennai-600116, India
| | - Chitra Andrew
- Department of Fetal Medicine,Sri Ramachandra Institute of Higher Education and Research, Chennai-600116, India
| | - N Paarthipan
- Department of Radiology, Saveetha Medical College and Hospital,Chennai-602105, India
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14
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Brady D, Schlatterer SD, Whitehead MT. Fetal brain MRI: neurometrics, typical diagnoses, and resolving common dilemmas. Br J Radiol 2023; 96:20211019. [PMID: 35604645 PMCID: PMC10321264 DOI: 10.1259/bjr.20211019] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2021] [Revised: 04/29/2022] [Accepted: 05/11/2022] [Indexed: 01/13/2023] Open
Abstract
This review presents a practical approach to imaging the fetal brain by MRI. Herein, we demonstrate how to measure brain structures and fluid spaces, and discuss the importance of comparing measurements to normative biometric references at a corresponding gestational age. We present some common imaging dilemmas of the technical aspects of fetal MRI with regard to typical regions of abnormality including the cerebrum, the ventricular system, and the posterior fossa, and discuss how to resolve them.
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15
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Ponrartana S, Nguyen HN, Cui SX, Tian Y, Kumar P, Wood JC, Nayak KS. Low-field 0.55 T MRI evaluation of the fetus. Pediatr Radiol 2023; 53:1469-1475. [PMID: 36882594 PMCID: PMC10276075 DOI: 10.1007/s00247-023-05604-x] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/25/2022] [Revised: 12/28/2022] [Accepted: 01/12/2023] [Indexed: 03/09/2023]
Abstract
Fetal magnetic resonance imaging (MRI) is an important adjunct modality for the evaluation of fetal abnormalities. Recently, low-field MRI systems at 0.55 Tesla have become available which can produce images on par with 1.5 Tesla systems but with lower power deposition, acoustic noise, and artifact. In this article, we describe a technical innovation using low-field MRI to perform diagnostic quality fetal MRI.
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Affiliation(s)
- Skorn Ponrartana
- Department of Radiology, Children's Hospital Los Angeles, Los Angeles, CA, USA.
| | - HaiThuy N Nguyen
- Department of Radiology, Children's Hospital Los Angeles, Los Angeles, CA, USA
| | - Sophia X Cui
- Siemens Medical Solutions, USA, Inc, Los Angeles, CA, USA
| | - Ye Tian
- Department of Electrical and Computer Engineering, University of Southern California, Los Angeles, CA, USA
| | - Prakash Kumar
- Department of Electrical and Computer Engineering, University of Southern California, Los Angeles, CA, USA
| | - John C Wood
- Department of Radiology, Children's Hospital Los Angeles, Los Angeles, CA, USA
- Division of Pediatric Cardiology, Children's Hospital Los Angeles, Los Angeles, CA, USA
| | - Krishna S Nayak
- Department of Electrical and Computer Engineering, University of Southern California, Los Angeles, CA, USA
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16
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Eisenmenger LB, Peret A, Roberts GS, Spahic A, Tang C, Kuner AD, Grayev AM, Field AS, Rowley HA, Kennedy TA. Focused Abbreviated Survey MRI Protocols for Brain and Spine Imaging. Radiographics 2023; 43:e220147. [PMID: 37167089 PMCID: PMC10262597 DOI: 10.1148/rg.220147] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/14/2022] [Revised: 10/12/2022] [Accepted: 10/18/2022] [Indexed: 05/13/2023]
Abstract
There has been extensive growth in both the technical development and the clinical applications of MRI, establishing this modality as one of the most powerful diagnostic imaging tools. However, long examination and image interpretation times still limit the application of MRI, especially in emergent clinical settings. Rapid and abbreviated MRI protocols have been developed as alternatives to standard MRI, with reduced imaging times, and in some cases limited numbers of sequences, to more efficiently answer specific clinical questions. A group of rapid MRI protocols used at the authors' institution, referred to as FAST (focused abbreviated survey techniques), are designed to include or exclude emergent or urgent conditions or screen for specific entities. These FAST protocols provide adequate diagnostic image quality with use of accelerated approaches to produce imaging studies faster than traditional methods. FAST protocols have become critical diagnostic screening tools at the authors' institution, allowing confident and efficient confirmation or exclusion of actionable findings. The techniques commonly used to reduce imaging times, the imaging protocols used at the authors' institution, and future directions in FAST imaging are reviewed to provide a practical and comprehensive overview of FAST MRI for practicing neuroradiologists. ©RSNA, 2023 Quiz questions for this article are available in the supplemental material.
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Affiliation(s)
| | | | - Grant S. Roberts
- From the Departments of Radiology (L.B.E., A.P., A.D.K., A.M.G.,
A.S.F., H.A.R., T.A.K.) and Medical Physics (G.S.R., A.S., C.T.), University of
Wisconsin School of Medicine and Public Health, 600 Highland Ave, Madison, WI
53792-3252
| | - Alma Spahic
- From the Departments of Radiology (L.B.E., A.P., A.D.K., A.M.G.,
A.S.F., H.A.R., T.A.K.) and Medical Physics (G.S.R., A.S., C.T.), University of
Wisconsin School of Medicine and Public Health, 600 Highland Ave, Madison, WI
53792-3252
| | - Chenwei Tang
- From the Departments of Radiology (L.B.E., A.P., A.D.K., A.M.G.,
A.S.F., H.A.R., T.A.K.) and Medical Physics (G.S.R., A.S., C.T.), University of
Wisconsin School of Medicine and Public Health, 600 Highland Ave, Madison, WI
53792-3252
| | - Anthony D. Kuner
- From the Departments of Radiology (L.B.E., A.P., A.D.K., A.M.G.,
A.S.F., H.A.R., T.A.K.) and Medical Physics (G.S.R., A.S., C.T.), University of
Wisconsin School of Medicine and Public Health, 600 Highland Ave, Madison, WI
53792-3252
| | - Allison M. Grayev
- From the Departments of Radiology (L.B.E., A.P., A.D.K., A.M.G.,
A.S.F., H.A.R., T.A.K.) and Medical Physics (G.S.R., A.S., C.T.), University of
Wisconsin School of Medicine and Public Health, 600 Highland Ave, Madison, WI
53792-3252
| | - Aaron S. Field
- From the Departments of Radiology (L.B.E., A.P., A.D.K., A.M.G.,
A.S.F., H.A.R., T.A.K.) and Medical Physics (G.S.R., A.S., C.T.), University of
Wisconsin School of Medicine and Public Health, 600 Highland Ave, Madison, WI
53792-3252
| | - Howard A. Rowley
- From the Departments of Radiology (L.B.E., A.P., A.D.K., A.M.G.,
A.S.F., H.A.R., T.A.K.) and Medical Physics (G.S.R., A.S., C.T.), University of
Wisconsin School of Medicine and Public Health, 600 Highland Ave, Madison, WI
53792-3252
| | - Tabassum A. Kennedy
- From the Departments of Radiology (L.B.E., A.P., A.D.K., A.M.G.,
A.S.F., H.A.R., T.A.K.) and Medical Physics (G.S.R., A.S., C.T.), University of
Wisconsin School of Medicine and Public Health, 600 Highland Ave, Madison, WI
53792-3252
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17
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Xu J, Moyer D, Gagoski B, Iglesias JE, Grant PE, Golland P, Adalsteinsson E. NeSVoR: Implicit Neural Representation for Slice-to-Volume Reconstruction in MRI. IEEE TRANSACTIONS ON MEDICAL IMAGING 2023; 42:1707-1719. [PMID: 37018704 PMCID: PMC10287191 DOI: 10.1109/tmi.2023.3236216] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/02/2023]
Abstract
Reconstructing 3D MR volumes from multiple motion-corrupted stacks of 2D slices has shown promise in imaging of moving subjects, e. g., fetal MRI. However, existing slice-to-volume reconstruction methods are time-consuming, especially when a high-resolution volume is desired. Moreover, they are still vulnerable to severe subject motion and when image artifacts are present in acquired slices. In this work, we present NeSVoR, a resolution-agnostic slice-to-volume reconstruction method, which models the underlying volume as a continuous function of spatial coordinates with implicit neural representation. To improve robustness to subject motion and other image artifacts, we adopt a continuous and comprehensive slice acquisition model that takes into account rigid inter-slice motion, point spread function, and bias fields. NeSVoR also estimates pixel-wise and slice-wise variances of image noise and enables removal of outliers during reconstruction and visualization of uncertainty. Extensive experiments are performed on both simulated and in vivo data to evaluate the proposed method. Results show that NeSVoR achieves state-of-the-art reconstruction quality while providing two to ten-fold acceleration in reconstruction times over the state-of-the-art algorithms.
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18
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Faruk Topaloğlu Ö, Koplay M, Kılınçer A, Örgül G, Sedat Durmaz M. Quantitative measurements and morphological evaluation of fetal cardiovascular structures with fetal cardiac MRI. Eur J Radiol 2023; 163:110828. [PMID: 37059007 DOI: 10.1016/j.ejrad.2023.110828] [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: 01/11/2023] [Revised: 03/17/2023] [Accepted: 04/04/2023] [Indexed: 04/16/2023]
Abstract
PURPOSE Fetal cardiac magnetic resonance imaging (FCMR) can be used as an imaging modality in fetal cardiovascular evaluation as studied in recent years. We aimed to evaluate cardiovascular morphology using FCMR and to observe the development of cardiovascular structures according to gestational age (GA) in pregnant women. METHOD In our prospective study, 120 pregnant women between 19 and 37 weeks of gestation in whom absence of cardiac anomaly could not be excluded by ultrasonography (US) or, who were referred to us for magnetic resonance imaging (MRI) for suspected non-cardiovascular system pathology, were included. According to the axis of the fetal heart, axial, coronal, and sagittal multiplanar steady-state free precession (SSFP) and 'real time' untriggered SSFP sequence, respectively, were obtained. The morphology of the cardiovascular structures and their relationships with each other were evaluated, and their sizes were measured. RESULTS Seven cases (6.3%) contained motion artefacts that did not allow the assessment and measurement of cardiovascular morphology, and three (2.9%) cases with cardiac pathology in the analysed images were excluded from the study. The study included a total of 100 cases. Cardiac chamber diameter, heart diameter, heart length, heart area, thoracic diameter, and thoracic area were measured in all fetuses. The diameters of the aorta ascendens (Aa), aortic isthmus (Ai), aorta descendens (Ad), main pulmonary artery (MPA), ductus arteriosus (DA, superior vena cava (SVC), and inferior vena cava (IVC) were measured in all fetuses. The left pulmonary artery (LPA) was visualised in 89 patients (89%). The right PA (RPA) was visualised in 99 (99%) cases. Four pulmonary veins (PVs) were seen in 49 (49%) cases, three in 33 (33%), and two in 18 (18%). High correlation values were found for all diameter measurements performed with GW. CONCLUSION In cases where US cannot achieve adequate image quality, FCMR can contribute to diagnosis. The very short acquisition time and parallel imaging technique with the SSFP sequence allow for adequate image quality without maternal or fetal sedation.
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Affiliation(s)
| | - Mustafa Koplay
- Department of Radiology, Selcuk University, Faculty of Medicine, Konya, Turkey
| | - Abidin Kılınçer
- Department of Radiology, Selcuk University, Faculty of Medicine, Konya, Turkey
| | - Gökçen Örgül
- Department of Obstetrics and Gynecology, Selcuk University, Faculty of Medicine, Konya, Turkey
| | - Mehmet Sedat Durmaz
- Department of Radiology, Selcuk University, Faculty of Medicine, Konya, Turkey
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19
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Emam D, Aertsen M, Van der Veeken L, Fidon L, Patkee P, Kyriakopoulou V, De Catte L, Russo F, Demaerel P, Vercauteren T, Rutherford M, Deprest J. Longitudinal MRI Evaluation of Brain Development in Fetuses with Congenital Diaphragmatic Hernia around the Time of Fetal Endotracheal Occlusion. AJNR Am J Neuroradiol 2023; 44:205-211. [PMID: 36657946 PMCID: PMC9891331 DOI: 10.3174/ajnr.a7760] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/28/2022] [Accepted: 12/10/2022] [Indexed: 01/21/2023]
Abstract
BACKGROUND AND PURPOSE Congenital diaphragmatic hernia is associated with high mortality and morbidity, including evidence suggesting neurodevelopmental comorbidities after birth. The aim of this study was to document longitudinal changes in brain biometry and the cortical folding pattern in fetuses with congenital diaphragmatic hernia compared with healthy fetuses. MATERIALS AND METHODS This is a retrospective cohort study including fetuses with isolated congenital diaphragmatic hernia between January 2007 and May 2019, with at least 2 MR imaging examinations. For controls, we used images from fetuses who underwent MR imaging for an unrelated condition that did not compromise fetal brain development and fetuses from healthy pregnant women. Biometric measurements and 3D segmentations of brain structures were used as well as qualitative and quantitative grading of the supratentorial brain. Brain development was correlated with disease-severity markers. RESULTS Forty-two fetuses were included, with a mean gestational age at first MR imaging of 28.0 (SD, 2.1) weeks and 33.2 (SD, 1.3) weeks at the second imaging. The mean gestational age in controls was 30.7 (SD, 4.2) weeks. At 28 weeks, fetuses with congenital diaphragmatic hernia had abnormal qualitative and quantitative maturation, more extra-axial fluid, and larger total skull volume. By 33 weeks, qualitative grading scores were still abnormal, but quantitative scoring was in the normal range. In contrast, the extra-axial fluid volume remained abnormal with increased ventricular volume. Normal brain parenchymal volumes were found. CONCLUSIONS Brain development in fetuses with congenital diaphragmatic hernia around 28 weeks appears to be delayed. This feature is less prominent at 33 weeks. At this stage, there was also an increase in ventricular and extra-axial space volume.
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Affiliation(s)
- D Emam
- From the Department of Development and Regeneration (D.E., L.V.d.V., L.D.C., F.R., J.D.), Cluster Woman and Child, Group Biomedical Sciences, KU Leuven University of Leuven, Leuven, Belgium
- Department Obstetrics and Gynaecology (D.E., L.F.), Faculty of Medicine, Tanta University, Tanta, Egypt
| | - M Aertsen
- Department of Imaging and Pathology (M.A., P.D.), Clinical Department of Radiology, University Hospitals, KU Leuven, Leuven, Belgium
| | - L Van der Veeken
- From the Department of Development and Regeneration (D.E., L.V.d.V., L.D.C., F.R., J.D.), Cluster Woman and Child, Group Biomedical Sciences, KU Leuven University of Leuven, Leuven, Belgium
- Clinical Department Obstetrics and Gynaecology (L.V.d.V., L.D.C., F.R., J.D.), University Hospitals Leuven, Leuven, Belgium
| | - L Fidon
- Department Obstetrics and Gynaecology (D.E., L.F.), Faculty of Medicine, Tanta University, Tanta, Egypt
- Division of Imaging Sciences and Biomedical Engineering, Perinatal Imaging and Health and School of Biomedical Engineering and Imaging Sciences (L.F., T.V., J.D.), King's College London, King's Health Partners, St. Thomas' Hospital, London, UK
| | - P Patkee
- Centre for the Developing Brain (P.P., V.K., M.R., J.D.)
| | | | - L De Catte
- From the Department of Development and Regeneration (D.E., L.V.d.V., L.D.C., F.R., J.D.), Cluster Woman and Child, Group Biomedical Sciences, KU Leuven University of Leuven, Leuven, Belgium
- Clinical Department Obstetrics and Gynaecology (L.V.d.V., L.D.C., F.R., J.D.), University Hospitals Leuven, Leuven, Belgium
| | - F Russo
- From the Department of Development and Regeneration (D.E., L.V.d.V., L.D.C., F.R., J.D.), Cluster Woman and Child, Group Biomedical Sciences, KU Leuven University of Leuven, Leuven, Belgium
- Clinical Department Obstetrics and Gynaecology (L.V.d.V., L.D.C., F.R., J.D.), University Hospitals Leuven, Leuven, Belgium
| | - P Demaerel
- Department of Imaging and Pathology (M.A., P.D.), Clinical Department of Radiology, University Hospitals, KU Leuven, Leuven, Belgium
| | - T Vercauteren
- Division of Imaging Sciences and Biomedical Engineering, Perinatal Imaging and Health and School of Biomedical Engineering and Imaging Sciences (L.F., T.V., J.D.), King's College London, King's Health Partners, St. Thomas' Hospital, London, UK
| | - M Rutherford
- Centre for the Developing Brain (P.P., V.K., M.R., J.D.)
| | - J Deprest
- From the Department of Development and Regeneration (D.E., L.V.d.V., L.D.C., F.R., J.D.), Cluster Woman and Child, Group Biomedical Sciences, KU Leuven University of Leuven, Leuven, Belgium
- Clinical Department Obstetrics and Gynaecology (L.V.d.V., L.D.C., F.R., J.D.), University Hospitals Leuven, Leuven, Belgium
- Centre for the Developing Brain (P.P., V.K., M.R., J.D.)
- Division of Imaging Sciences and Biomedical Engineering, Perinatal Imaging and Health and School of Biomedical Engineering and Imaging Sciences (L.F., T.V., J.D.), King's College London, King's Health Partners, St. Thomas' Hospital, London, UK
- Institute for Women's Health (J.D.), University College London, London, UK
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20
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Fet-Net Algorithm for Automatic Detection of Fetal Orientation in Fetal MRI. Bioengineering (Basel) 2023; 10:bioengineering10020140. [PMID: 36829634 PMCID: PMC9952178 DOI: 10.3390/bioengineering10020140] [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: 12/20/2022] [Revised: 01/06/2023] [Accepted: 01/13/2023] [Indexed: 01/22/2023] Open
Abstract
Identifying fetal orientation is essential for determining the mode of delivery and for sequence planning in fetal magnetic resonance imaging (MRI). This manuscript describes a deep learning algorithm named Fet-Net, composed of convolutional neural networks (CNNs), which allows for the automatic detection of fetal orientation from a two-dimensional (2D) MRI slice. The architecture consists of four convolutional layers, which feed into a simple artificial neural network. Compared with eleven other prominent CNNs (different versions of ResNet, VGG, Xception, and Inception), Fet-Net has fewer architectural layers and parameters. From 144 3D MRI datasets indicative of vertex, breech, oblique and transverse fetal orientations, 6120 2D MRI slices were extracted to train, validate and test Fet-Net. Despite its simpler architecture, Fet-Net demonstrated an average accuracy and F1 score of 97.68% and a loss of 0.06828 on the 6120 2D MRI slices during a 5-fold cross-validation experiment. This architecture outperformed all eleven prominent architectures (p < 0.05). An ablation study proved each component's statistical significance and contribution to Fet-Net's performance. Fet-Net demonstrated robustness in classification accuracy even when noise was introduced to the images, outperforming eight of the 11 prominent architectures. Fet-Net's ability to automatically detect fetal orientation can profoundly decrease the time required for fetal MRI acquisition.
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21
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Imaging fetal anatomy. Semin Cell Dev Biol 2022; 131:78-92. [PMID: 35282997 DOI: 10.1016/j.semcdb.2022.02.023] [Citation(s) in RCA: 17] [Impact Index Per Article: 8.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/22/2021] [Revised: 02/23/2022] [Accepted: 02/23/2022] [Indexed: 02/07/2023]
Abstract
Due to advancements in ultrasound techniques, the focus of antenatal ultrasound screening is moving towards the first trimester of pregnancy. The early first trimester however remains in part, a 'black box', due to the size of the developing embryo and the limitations of contemporary scanning techniques. Therefore there is a need for images of early anatomical developmental to improve our understanding of this area. By using new imaging techniques, we can not only obtain better images to further our knowledge of early embryonic development, but clear images of embryonic and fetal development can also be used in training for e.g. sonographers and fetal surgeons, or to educate parents expecting a child with a fetal anomaly. The aim of this review is to provide an overview of the past, present and future techniques used to capture images of the developing human embryo and fetus and provide the reader newest insights in upcoming and promising imaging techniques. The reader is taken from the earliest drawings of da Vinci, along the advancements in the fields of in utero ultrasound and MR imaging techniques towards high-resolution ex utero imaging using Micro-CT and ultra-high field MRI. Finally, a future perspective is given about the use of artificial intelligence in ultrasound and new potential imaging techniques such as synchrotron radiation-based CT to increase our knowledge regarding human development.
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22
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The role of ultrasound and MRI in diagnosing of obstetrics cardiac disorders: A systematic review. JOURNAL OF RADIATION RESEARCH AND APPLIED SCIENCES 2022. [DOI: 10.1016/j.jrras.2022.06.007] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/18/2022]
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23
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Tang X, Bai G, Wang H, Guo F, Yin H. A comparison of the accuracy of fetal magnetic resonance imaging and ultrasonography for the diagnosis of fetal congenital malformations of the spine and spinal cord. Prenat Diagn 2022; 42:1295-1302. [PMID: 35808906 DOI: 10.1002/pd.6209] [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: 11/17/2021] [Revised: 06/30/2022] [Accepted: 07/04/2022] [Indexed: 11/08/2022]
Abstract
PURPOSE To determine the diagnostic value of fetal magnetic resonance imaging (MRI) for congenital spine/spinal cord malformations. METHODS This single-center retrospective study included 120 cases of fetal spine/spinal cord abnormalities detected using fetal ultrasonography (US) and further examined by fetal MRI between 2016 and 2020. Cases were divided into three groups (congenital spine, spinal cord, and spine + spinal cord malformations) based on US assessment. We analyzed the accuracy of fetal US and MRI relative to postnatal imaging. RESULTS The diagnostic accuracy of fetal MRI for fetal spinal cord, spine, and spine + spinal cord malformations was 86.2% (25/29), 89.4% (42/47), and 86.3% (38/44), respectively, and the corresponding rates for fetal US were 51.7% (15/29), 87.2% (41/47), and 68.2% (30/44). The diagnostic accuracy did not differ between fetal MRI and US for congenital spine malformations (P > 0.05); for congenital spinal cord malformations and congenital spine+spinal cord malformations, the diagnostic accuracy was significantly higher for fetal MRI than for fetal US (P < 0.05). CONCLUSIONS Fetal MRI is effective in the assessment of congenital spine/spinal cord malformations. It can yield information that supplements US findings, especially for congenital spinal cord malformations, and can improve the accuracy of fetal diagnosis. This article is protected by copyright. All rights reserved.
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Affiliation(s)
- Xing Tang
- Department of Radiology, Xijing Hospital, Fourth Military Medical University, Xi'an, Shaanxi, PR China
| | - Guoyan Bai
- Department of Clinical Laboratory, Shaanxi Provincial People's Hospital, Xi'an, Shaanxi, PR China
| | - Hong Wang
- Department of Radiology, Xijing Hospital, Fourth Military Medical University, Xi'an, Shaanxi, PR China
| | - Fan Guo
- Department of Radiology, Xijing Hospital, Fourth Military Medical University, Xi'an, Shaanxi, PR China
| | - Hong Yin
- Department of Radiology, Xijing Hospital, Fourth Military Medical University, Xi'an, Shaanxi, PR China
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24
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Attention-guided deep learning for gestational age prediction using fetal brain MRI. Sci Rep 2022; 12:1408. [PMID: 35082346 PMCID: PMC8791965 DOI: 10.1038/s41598-022-05468-5] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/03/2021] [Accepted: 01/05/2022] [Indexed: 12/18/2022] Open
Abstract
Magnetic resonance imaging offers unrivaled visualization of the fetal brain, forming the basis for establishing age-specific morphologic milestones. However, gauging age-appropriate neural development remains a difficult task due to the constantly changing appearance of the fetal brain, variable image quality, and frequent motion artifacts. Here we present an end-to-end, attention-guided deep learning model that predicts gestational age with R2 score of 0.945, mean absolute error of 6.7 days, and concordance correlation coefficient of 0.970. The convolutional neural network was trained on a heterogeneous dataset of 741 developmentally normal fetal brain images ranging from 19 to 39 weeks in gestational age. We also demonstrate model performance and generalizability using independent datasets from four academic institutions across the U.S. and Turkey with R2 scores of 0.81–0.90 after minimal fine-tuning. The proposed regression algorithm provides an automated machine-enabled tool with the potential to better characterize in utero neurodevelopment and guide real-time gestational age estimation after the first trimester.
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25
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Liao Y, Li X, Jia F, Ye Z, Ning G, Liu S, Li P, Fu C, Li Q, Wang S, Zhang H, Qu H. Optimization of the image contrast for the developing fetal brain using 3D radial VIBE sequence in 3 T magnetic resonance imaging. BMC Med Imaging 2022; 22:11. [PMID: 35057733 PMCID: PMC8780316 DOI: 10.1186/s12880-022-00737-1] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/14/2021] [Accepted: 01/13/2022] [Indexed: 11/18/2022] Open
Abstract
BACKGROUND Faster and motion robust magnetic resonance imaging (MRI) sequences are desirable in fetal brain MRI. T1-weighted images are essential for evaluating fetal brain development. We optimized the radial volumetric interpolated breath-hold examination (VIBE) sequence for qualitative T1-weighted images of the fetal brain with improved image contrast and reduced motion sensitivity. MATERIALS AND METHODS This was an institutional review board-approved prospective study. Thirty-five pregnant subjects underwent fetal brain scan at 3 Tesla MRI. T1-weighted images were acquired using a 3D radial VIBE sequence with flip angles of 6º, 9º, 12º, and 15º. T1-weighted images of Cartesian VIBE sequence were acquired in three of the subjects. Qualitative assessments including image quality and motion artifact severity were evaluated. The image contrast ratio between gray and white matter were measured. Interobserver reliability and intraobserver repeatability were assessed using intraclass correlation coefficient (ICC). RESULTS Interobserver reliability and intraobserver repeatability universally revealed almost perfect agreement (ICC > 0.800). Significant differences in image quality were detected in basal ganglia (P = 0.023), central sulcus (P = 0.028), myelination (P = 0.007) and gray matter (P = 0.023) among radial VIBE with flip angles 6º, 9º, 12º, 15º. Image quality at the 9º flip angle in radial VIBE was generally better than flip angle of 15º. Radial VIBE sequence with 9º flip angle of gray matter was significantly different by gestational age (GA) before and after 28 weeks (P = 0.036). Quantified image contrast was significantly different among different flip angles, consistent with qualitative analysis of image quality. CONCLUSIONS Three-dimensional radial VIBE with 9º flip angle provides optimal, stable T1-weighted images of the fetal brain. Fetal brain structure and development can be evaluated using high-quality images obtained using this angle. However, different scanners will achieve different TRs and so the FA should be re-optimized each time a new protocol is employed.
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Affiliation(s)
- Yi Liao
- Department of Radiology, West China Second University Hospital of Sichuan University, Chengdu, Sichuan, People's Republic of China
- Key Laboratory of Birth Defects and Related Diseases of Women and Children (Sichuan University), Ministry of Education, West China Second University Hospital, Sichuan University, Chengdu, Sichuan, People's Republic of China
| | - Xuesheng Li
- Department of Radiology, West China Second University Hospital of Sichuan University, Chengdu, Sichuan, People's Republic of China
- Key Laboratory of Birth Defects and Related Diseases of Women and Children (Sichuan University), Ministry of Education, West China Second University Hospital, Sichuan University, Chengdu, Sichuan, People's Republic of China
| | - Fenglin Jia
- Department of Radiology, West China Second University Hospital of Sichuan University, Chengdu, Sichuan, People's Republic of China
- Key Laboratory of Birth Defects and Related Diseases of Women and Children (Sichuan University), Ministry of Education, West China Second University Hospital, Sichuan University, Chengdu, Sichuan, People's Republic of China
| | - Zhijun Ye
- Department of Radiology, West China Second University Hospital of Sichuan University, Chengdu, Sichuan, People's Republic of China
- Key Laboratory of Birth Defects and Related Diseases of Women and Children (Sichuan University), Ministry of Education, West China Second University Hospital, Sichuan University, Chengdu, Sichuan, People's Republic of China
| | - Gang Ning
- Department of Radiology, West China Second University Hospital of Sichuan University, Chengdu, Sichuan, People's Republic of China
- Key Laboratory of Birth Defects and Related Diseases of Women and Children (Sichuan University), Ministry of Education, West China Second University Hospital, Sichuan University, Chengdu, Sichuan, People's Republic of China
| | - Sai Liu
- Department of Radiology, West China Second University Hospital of Sichuan University, Chengdu, Sichuan, People's Republic of China
- Key Laboratory of Birth Defects and Related Diseases of Women and Children (Sichuan University), Ministry of Education, West China Second University Hospital, Sichuan University, Chengdu, Sichuan, People's Republic of China
| | - Pei Li
- Department of Radiology, West China Second University Hospital of Sichuan University, Chengdu, Sichuan, People's Republic of China
- Key Laboratory of Birth Defects and Related Diseases of Women and Children (Sichuan University), Ministry of Education, West China Second University Hospital, Sichuan University, Chengdu, Sichuan, People's Republic of China
| | - Chuan Fu
- Department of Radiology, West China Second University Hospital of Sichuan University, Chengdu, Sichuan, People's Republic of China
- Key Laboratory of Birth Defects and Related Diseases of Women and Children (Sichuan University), Ministry of Education, West China Second University Hospital, Sichuan University, Chengdu, Sichuan, People's Republic of China
| | - Qing Li
- MR Collaborations, Siemens Healthineers, Shanghai, People's Republic of China
| | - Shaoyu Wang
- MR Scientific Marketing, Siemens Healthineers, Shanghai, People's Republic of China
| | - Huapeng Zhang
- MR Application, Xi'an Branch of Siemens Healthineers, Shanxi, People's Republic of China
| | - Haibo Qu
- Department of Radiology, West China Second University Hospital of Sichuan University, Chengdu, Sichuan, People's Republic of China.
- Key Laboratory of Birth Defects and Related Diseases of Women and Children (Sichuan University), Ministry of Education, West China Second University Hospital, Sichuan University, Chengdu, Sichuan, People's Republic of China.
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Liu T, Al-Kzayer LFY, Sarsam SN, Chen L, Saeed RM, Ali KH, Nakazawa Y. Cellular congenital mesoblastic nephroma detected by prenatal MRI: a case report and literature review. Transl Pediatr 2022; 11:163-173. [PMID: 35242663 PMCID: PMC8825936 DOI: 10.21037/tp-21-289] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/22/2021] [Accepted: 11/01/2021] [Indexed: 11/06/2022] Open
Abstract
Congenital mesoblastic nephroma (CMN) is a rare tumor, yet it is the most frequently diagnosed renal neoplasm in the first 3 months of life. CMN reports with prenatal magnetic resonance imaging (MRI) are scarce. Our aims were to describe a case with fetal MR imaging along with other findings, and to review the literature concerned with prenatal MRI detection of CMN. Upon routine ultrasound (US) examination of a 36-week pregnant woman, a fetal abdominal mass was disclosed. Prenatal MRI revealed a large, well-circumscribed renal mass of solid and cystic components, not invading the adjacent tissues, but compressing normal renal parenchyma of the lower pole of the left kidney. Thus, a low malignant renal tumor was considered. After Cesarean delivery, imaging including US and computerized tomography (CT) scan was performed on the apparently healthy boy and verified the prenatal MRI finding. Accordingly, left nephrectomy was performed at the age of 12 days. The pathology confirmed CT results of the solid and cystic components of the mass, in addition to the necrotic and hemorrhagic constitution. Cellular CMN was diagnosed, and ETV6 gene rearrangement was demonstrated by FISH analysis. No recurrence was detected within the 40 months follow-up after the operation. Our report described a rare and seldomly detected renal tumor in utero with the aid of MRI and reviewed the few related reports in the literature in which MRI was performed prenatally. This report also highlights the need for prenatal MRI as a complementary tool to US in cases with suspected fetal renal mass and recommends its use for carefully managing the possible risks during the perinatal period.
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Affiliation(s)
- Tingting Liu
- Department of Pediatric Hematology/Oncology, Xinhua Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, China
| | | | - Shamil Naji Sarsam
- Department of Radiology, Ibn Al-Nafees Hospital, Manama, Kingdom of Bahrain
| | - Lei Chen
- Department of Pathology, Xinhua Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, China
| | - Raghad M Saeed
- Department of Pediatric Oncology, Children Welfare Teaching Hospital, Baghdad Medical City, Baghdad, Iraq
| | - Kenan Hussien Ali
- Department of Family Medicine, Baghdad University, College of Medicine, Baghdad, Iraq
| | - Yozo Nakazawa
- Department of Pediatrics, Shinshu University School of Medicine, Matsumoto, Nagano, Japan
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Amodeo I, Borzani I, Raffaeli G, Persico N, Amelio GS, Gulden S, Colnaghi M, Villamor E, Mosca F, Cavallaro G. The role of magnetic resonance imaging in the diagnosis and prognostic evaluation of fetuses with congenital diaphragmatic hernia. Eur J Pediatr 2022; 181:3243-3257. [PMID: 35794403 PMCID: PMC9395465 DOI: 10.1007/s00431-022-04540-6] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/26/2022] [Accepted: 06/23/2022] [Indexed: 11/04/2022]
Abstract
UNLABELLED In recent years, magnetic resonance imaging (MRI) has largely increased our knowledge and predictive accuracy of congenital diaphragmatic hernia (CDH) in the fetus. Thanks to its technical advantages, better anatomical definition, and superiority in fetal lung volume estimation, fetal MRI has been demonstrated to be superior to 2D and 3D ultrasound alone in CDH diagnosis and outcome prediction. This is of crucial importance for prenatal counseling, risk stratification, and decision-making approach. Furthermore, several quantitative and qualitative parameters can be evaluated simultaneously, which have been associated with survival, postnatal course severity, and long-term morbidity. CONCLUSION Fetal MRI will further strengthen its role in the near future, but it is necessary to reach a consensus on indications, methodology, and data interpretation. In addition, it is required data integration from different imaging modalities and clinical courses, especially for predicting postnatal pulmonary hypertension. This would lead to a comprehensive prognostic assessment. WHAT IS KNOWN • MRI plays a key role in evaluating the fetal lung in patients with CDH. • Prognostic assessment of CDH is challenging, and advanced imaging is crucial for a complete prenatal assessment and counseling. WHAT IS NEW • Fetal MRI has strengthened its role over ultrasound due to its technical advantages, better anatomical definition, superior fetal lung volume estimation, and outcome prediction. • Imaging and clinical data integration is the most desirable strategy and may provide new MRI applications and future research opportunities.
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Affiliation(s)
- Ilaria Amodeo
- grid.414818.00000 0004 1757 8749Neonatal Intensive Care Unit, Fondazione IRCCS Ca’ Granda Ospedale Maggiore Policlinico, Via Della Commenda 12, 20122 Milan, Italy
| | - Irene Borzani
- grid.414818.00000 0004 1757 8749Pediatric Radiology Unit, Fondazione IRCCS Ca’ Granda Ospedale Maggiore Policlinico, Milan, Italy
| | - Genny Raffaeli
- grid.414818.00000 0004 1757 8749Neonatal Intensive Care Unit, Fondazione IRCCS Ca’ Granda Ospedale Maggiore Policlinico, Via Della Commenda 12, 20122 Milan, Italy ,grid.4708.b0000 0004 1757 2822Department of Clinical Sciences and Community Health, Università Degli Studi Di Milano, Milan, Italy
| | - Nicola Persico
- grid.4708.b0000 0004 1757 2822Department of Clinical Sciences and Community Health, Università Degli Studi Di Milano, Milan, Italy ,grid.414818.00000 0004 1757 8749Department of Obstetrics and Gynecology, Fondazione IRCCS Ca’ Granda, Ospedale Maggiore Policlinico, Milan, Italy
| | - Giacomo Simeone Amelio
- grid.414818.00000 0004 1757 8749Neonatal Intensive Care Unit, Fondazione IRCCS Ca’ Granda Ospedale Maggiore Policlinico, Via Della Commenda 12, 20122 Milan, Italy
| | - Silvia Gulden
- grid.414818.00000 0004 1757 8749Neonatal Intensive Care Unit, Fondazione IRCCS Ca’ Granda Ospedale Maggiore Policlinico, Via Della Commenda 12, 20122 Milan, Italy
| | - Mariarosa Colnaghi
- grid.414818.00000 0004 1757 8749Neonatal Intensive Care Unit, Fondazione IRCCS Ca’ Granda Ospedale Maggiore Policlinico, Via Della Commenda 12, 20122 Milan, Italy
| | - Eduardo Villamor
- grid.412966.e0000 0004 0480 1382Department of Pediatrics, School for Oncology and Reproduction (GROW), Maastricht University Medical Center, University of Maastricht, MUMC+), Maastricht, the Netherlands
| | - Fabio Mosca
- grid.414818.00000 0004 1757 8749Neonatal Intensive Care Unit, Fondazione IRCCS Ca’ Granda Ospedale Maggiore Policlinico, Via Della Commenda 12, 20122 Milan, Italy ,grid.4708.b0000 0004 1757 2822Department of Clinical Sciences and Community Health, Università Degli Studi Di Milano, Milan, Italy
| | - Giacomo Cavallaro
- Neonatal Intensive Care Unit, Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Via Della Commenda 12, 20122, Milan, Italy.
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Ex utero intrapartum technique (EXIT): Indications, procedure methods and materno-fetal complications - A literature review. J Gynecol Obstet Hum Reprod 2021; 51:102252. [PMID: 34638008 DOI: 10.1016/j.jogoh.2021.102252] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/09/2021] [Revised: 09/24/2021] [Accepted: 10/06/2021] [Indexed: 12/23/2022]
Abstract
A congenital malformation of the head, neck or thorax can lead to upper airway compression with a risk of asphyxia or neonatal death. To secure and protect the upper airway, the Ex Utero Intrapartum Therapy (EXIT) procedure has been developed. The procedure allows delivery of the fetus via a hysterotomy while relying on the placenta as the organ of respiration for the fetus prior to clamping of the umbilical cord. A high level of expertise is necessary for successful completion of the EXIT procedure, which is not void of maternal and fetal risks. In this literature review, we present the indications, procedure methods and materno-fetal complications associated with the EXIT procedure.
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29
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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. MEDICAL IMAGE COMPUTING AND COMPUTER-ASSISTED INTERVENTION : MICCAI ... INTERNATIONAL CONFERENCE ON MEDICAL IMAGE COMPUTING AND COMPUTER-ASSISTED INTERVENTION 2021; 12907:197-206. [PMID: 37103468 PMCID: PMC10129053 DOI: 10.1007/978-3-030-87234-2_19] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [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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30
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Hoffmann M, Abaci Turk E, Gagoski B, Morgan L, Wighton P, Tisdall MD, Reuter M, Adalsteinsson E, Grant PE, Wald LL, van der Kouwe AJW. Rapid head-pose detection for automated slice prescription of fetal-brain MRI. INTERNATIONAL JOURNAL OF IMAGING SYSTEMS AND TECHNOLOGY 2021; 31:1136-1154. [PMID: 34421216 PMCID: PMC8372849 DOI: 10.1002/ima.22563] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 08/28/2020] [Revised: 01/29/2021] [Accepted: 02/09/2021] [Indexed: 06/13/2023]
Abstract
In fetal-brain MRI, head-pose changes between prescription and acquisition present a challenge to obtaining the standard sagittal, coronal and axial views essential to clinical assessment. As motion limits acquisitions to thick slices that preclude retrospective resampling, technologists repeat ~55-second stack-of-slices scans (HASTE) with incrementally reoriented field of view numerous times, deducing the head pose from previous stacks. To address this inefficient workflow, we propose a robust head-pose detection algorithm using full-uterus scout scans (EPI) which take ~5 seconds to acquire. Our ~2-second procedure automatically locates the fetal brain and eyes, which we derive from maximally stable extremal regions (MSERs). The success rate of the method exceeds 94% in the third trimester, outperforming a trained technologist by up to 20%. The pipeline may be used to automatically orient the anatomical sequence, removing the need to estimate the head pose from 2D views and reducing delays during which motion can occur.
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Affiliation(s)
- Malte Hoffmann
- Department of Radiology, Massachusetts General HospitalBostonMassachusettsUSA
- Department of RadiologyHarvard Medical SchoolBostonMassachusettsUSA
| | - Esra Abaci Turk
- Fetal‐Neonatal Neuroimaging and Developmental Science Center, Boston Children's HospitalBostonMassachusettsUSA
- Electrical Engineering and Computer ScienceMassachusetts Institute of TechnologyCambridgeMassachusettsUSA
| | - Borjan Gagoski
- Department of RadiologyHarvard Medical SchoolBostonMassachusettsUSA
- Fetal‐Neonatal Neuroimaging and Developmental Science Center, Boston Children's HospitalBostonMassachusettsUSA
| | - Leah Morgan
- Department of Radiology, Massachusetts General HospitalBostonMassachusettsUSA
| | - Paul Wighton
- Department of Radiology, Massachusetts General HospitalBostonMassachusettsUSA
| | - Matthew Dylan Tisdall
- Radiology, Perelman School of MedicineUniversity of PennsylvaniaPhiladelphiaPennsylvaniaUSA
| | - Martin Reuter
- Department of Radiology, Massachusetts General HospitalBostonMassachusettsUSA
- Department of RadiologyHarvard Medical SchoolBostonMassachusettsUSA
- German Center for Neurodegenerative DiseasesBonnGermany
| | - Elfar Adalsteinsson
- Electrical Engineering and Computer ScienceMassachusetts Institute of TechnologyCambridgeMassachusettsUSA
- Institute for Medical Engineering and ScienceMassachusetts Institute of TechnologyCambridgeMassachusettsUSA
| | - Patricia Ellen Grant
- Department of RadiologyHarvard Medical SchoolBostonMassachusettsUSA
- Fetal‐Neonatal Neuroimaging and Developmental Science Center, Boston Children's HospitalBostonMassachusettsUSA
| | - Lawrence L. Wald
- Department of Radiology, Massachusetts General HospitalBostonMassachusettsUSA
- Department of RadiologyHarvard Medical SchoolBostonMassachusettsUSA
| | - André J. W. van der Kouwe
- Department of Radiology, Massachusetts General HospitalBostonMassachusettsUSA
- Department of RadiologyHarvard Medical SchoolBostonMassachusettsUSA
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Lee FT, Seed M, Sun L, Marini D. Fetal brain issues in congenital heart disease. Transl Pediatr 2021; 10:2182-2196. [PMID: 34584890 PMCID: PMC8429876 DOI: 10.21037/tp-20-224] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/04/2020] [Accepted: 08/27/2020] [Indexed: 12/17/2022] Open
Abstract
Following the improvements in the clinical management of patients with congenital heart disease (CHD) and their increased survival, neurodevelopmental outcome has become an emerging priority in pediatric cardiology. Large-scale efforts have been made to protect the brain during the postnatal, surgical, and postoperative period; however, the presence of brain immaturity and injury at birth suggests in utero and peripartum disturbances. Over the past decade, there has been considerable interest and investigations on fetal brain growth in the setting of CHD. Advancements in fetal brain imaging have identified abnormal brain development in fetuses with CHD from the macrostructural (brain volumes and cortical folding) down to the microstructural (biochemistry and water diffusivity) scale, with more severe forms of CHD showing worse disturbances and brain abnormalities starting as early as the first trimester. Anomalies in common genetic developmental pathways and diminished cerebral substrate delivery secondary to altered cardiovascular physiology are the forefront hypotheses, but other factors such as impaired placental function and maternal psychological stress have surfaced as important contributors to fetal brain immaturity in CHD. The characterization and timing of fetal brain disturbances and their associated mechanisms are important steps for determining preventative prenatal interventions, which may provide a stronger foundation for the developing brain during childhood.
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Affiliation(s)
- Fu-Tsuen Lee
- Department of Physiology, Faculty of Medicine, University of Toronto, Toronto, Canada.,Division of Cardiology, Department of Paediatrics, Hospital for Sick Children, University of Toronto, Toronto, Canada
| | - Mike Seed
- Division of Cardiology, Department of Paediatrics, Hospital for Sick Children, University of Toronto, Toronto, Canada.,Department of Diagnostic Imaging, Hospital for Sick Children, University of Toronto, Toronto, Canada
| | - Liqun Sun
- Division of Cardiology, Department of Paediatrics, Hospital for Sick Children, University of Toronto, Toronto, Canada
| | - Davide Marini
- Division of Cardiology, Department of Paediatrics, Hospital for Sick Children, University of Toronto, Toronto, Canada
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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: 0.7] [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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Lu Q. Editorial for "Data Quality Assessment for Super-Resolution Fetal Brain MR Imaging: A Retrospective 1.5 T Study". J Magn Reson Imaging 2021; 54:1361-1362. [PMID: 33982827 DOI: 10.1002/jmri.27699] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/03/2021] [Accepted: 05/05/2021] [Indexed: 11/10/2022] Open
Affiliation(s)
- Quin Lu
- Philips Healthcare North America, San Francisco, California, USA
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Rubert N, Bardo DME, Vaughn J, Cornejo P, Goncalves LF. Data Quality Assessment for Super-Resolution Fetal Brain MR Imaging: A Retrospective 1.5 T Study. J Magn Reson Imaging 2021; 54:1349-1360. [PMID: 33949725 DOI: 10.1002/jmri.27665] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/09/2021] [Revised: 04/12/2021] [Accepted: 04/13/2021] [Indexed: 11/05/2022] Open
Abstract
BACKGROUND Super-resolution is a promising technique to create isotropic image volumes from stacks of two-dimensional (2D) motion-corrupted images in fetal magnetic resonance imaging (MRI). PURPOSE To determine an acquisition quality metric and correlate that metric with radiologist perception of three-dimensional (3D) image quality. STUDY TYPE Retrospective. SUBJECTS Eighty-seven patients, mean gestational age 29 ± 6 weeks. FIELD STRENGTH/SEQUENCE 1.5 T/2D fast spin-echo. ASSESSMENT Four radiologists (L.G., D.M.E.B., P.C., and J.V.; 31, 21, 7, and 7 years' experience, respectively) graded reconstructions on a 0 to 4 scale for overall appearance and visibility of specific anatomy. During reconstruction, slices were labeled as inliers based on correlation between a simulated vs. actual acquisition. The fraction of brain voxels in inlier slicers vs. total brain voxels was measured for each acquisition. STATISTICAL TESTS Paired sample t test, Pearson's correlation, intra-class correlation. RESULTS The average brain mask inlier fraction for all acquisitions was 0.8. There was a statistically significant correlation (0.71) between overall reconstruction appearance and number of acquisitions with inlier fraction above 0.73. There was low correlation (0.21, P = 0.05) between the number of acquisitions used in the reconstruction and overall score when no data quality measure was considered. Similar results were found for ratings of specific anatomy. Statistically significant differences in overall perception of image quality were found when using three vs. four, four vs. five, and three vs. five high-quality acquisitions in the reconstruction. Five high-quality acquisitions were sufficient to yield an average radiologist rating of 3.59 out of 4.0 for overall image quality. DATA CONCLUSION Reconstruction quality can be reliably predicted using the brain mask inlier fraction. Real-time super-resolution protocols could exploit this to terminate acquisition when enough high-quality acquisitions have been collected. To achieve consistent 3D image quality it may be necessary to acquire more than five scans to compensate for severely motion-corrupted acquisitions. LEVEL OF EVIDENCE 3 TECHNICAL EFFICACY: 1.
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Affiliation(s)
- Nicholas Rubert
- Department of Radiology, Phoenix Children's Hospital, Phoenix, Arizona, USA
| | - Dianna M E Bardo
- Department of Radiology, Phoenix Children's Hospital, Phoenix, Arizona, USA.,Departments of Radiology and Child Health, University of Arizona, Phoenix, Arizona, USA.,Department of Radiology, Mayo Clinic, Scottsdale, Arizona, USA.,Department of Radiology, Creighton University, Phoenix, Arizona, USA.,Department of Neuroradiology, Barrows Neurological Institute, Phoenix, Arizona, USA
| | - Jennifer Vaughn
- Department of Radiology, Phoenix Children's Hospital, Phoenix, Arizona, USA.,Departments of Radiology and Child Health, University of Arizona, Phoenix, Arizona, USA.,Department of Radiology, Creighton University, Phoenix, Arizona, USA.,Department of Neuroradiology, Barrows Neurological Institute, Phoenix, Arizona, USA
| | - Patricia Cornejo
- Department of Radiology, Phoenix Children's Hospital, Phoenix, Arizona, USA.,Departments of Radiology and Child Health, University of Arizona, Phoenix, Arizona, USA.,Department of Radiology, Mayo Clinic, Scottsdale, Arizona, USA.,Department of Radiology, Creighton University, Phoenix, Arizona, USA.,Department of Neuroradiology, Barrows Neurological Institute, Phoenix, Arizona, USA
| | - Luis F Goncalves
- Department of Radiology, Phoenix Children's Hospital, Phoenix, Arizona, USA.,Departments of Radiology and Child Health, University of Arizona, Phoenix, Arizona, USA
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Hoffmann M, Moyer DC, Zhang L, Golland P, Gagoski B, Grant PE, van der Kouwe AJ. Learning-based automatic field-of-view positioning for fetal-brain MRI. PROCEEDINGS OF THE INTERNATIONAL SOCIETY FOR MAGNETIC RESONANCE IN MEDICINE ... SCIENTIFIC MEETING AND EXHIBITION. INTERNATIONAL SOCIETY FOR MAGNETIC RESONANCE IN MEDICINE. SCIENTIFIC MEETING AND EXHIBITION 2021; 29:1362. [PMID: 36284600 PMCID: PMC9592155] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Grants] [Subscribe] [Scholar Register] [Indexed: 06/16/2023]
Affiliation(s)
- Malte Hoffmann
- Department of Radiology, Harvard Medical School, Boston, MA, United States
- Department of Radiology, Massachusetts General Hospital, Boston, MA, United States
| | - Daniel C Moyer
- Computer Science and Artificial Intelligence Laboratory, MIT, Cambridge, MA, United States
| | - Lawrence Zhang
- Computer Science and Artificial Intelligence Laboratory, MIT, Cambridge, MA, United States
| | - Polina Golland
- Computer Science and Artificial Intelligence Laboratory, MIT, Cambridge, MA, United States
| | - Borjan Gagoski
- Department of Radiology, Harvard Medical School, Boston, MA, United States
- Fetal-Neonatal Neuroimaging and Developmental Science Center, Boston Children's Hospital, Boston, MA, United States
| | - P Ellen Grant
- Department of Radiology, Harvard Medical School, Boston, MA, United States
- Fetal-Neonatal Neuroimaging and Developmental Science Center, Boston Children's Hospital, Boston, MA, United States
| | - André Jw van der Kouwe
- Department of Radiology, Harvard Medical School, Boston, MA, United States
- Department of Radiology, Massachusetts General Hospital, Boston, MA, United States
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Largent A, Kapse K, Barnett SD, De Asis-Cruz J, Whitehead M, Murnick J, Zhao L, Andersen N, Quistorff J, Lopez C, Limperopoulos C. Image Quality Assessment of Fetal Brain MRI Using Multi-Instance Deep Learning Methods. J Magn Reson Imaging 2021; 54:818-829. [PMID: 33891778 DOI: 10.1002/jmri.27649] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/22/2020] [Revised: 04/09/2021] [Accepted: 04/12/2021] [Indexed: 11/06/2022] Open
Abstract
BACKGROUND Due to random motion of fetuses and maternal respirations, image quality of fetal brain MRIs varies considerably. To address this issue, visual inspection of the images is performed during acquisition phase and after 3D-reconstruction, and the images are re-acquired if they are deemed to be of insufficient quality. However, this process is time-consuming and subjective. Multi-instance (MI) deep learning methods (DLMs) may perform this task automatically. PURPOSE To propose an MI count-based DLM (MI-CB-DLM), an MI vote-based DLM (MI-VB-DLM), and an MI feature-embedding DLM (MI-FE-DLM) for automatic assessment of 3D fetal-brain MR image quality. To quantify influence of fetal gestational age (GA) on DLM performance. STUDY TYPE Retrospective. SUBJECTS Two hundred and seventy-one MR exams from 211 fetuses (mean GA ± SD = 30.9 ± 5.5 weeks). FIELD STRENGTH/SEQUENCE T2 -weighted single-shot fast spin-echo acquired at 1.5 T. ASSESSMENT The T2 -weighted images were reconstructed in 3D. Then, two fetal neuroradiologists, a clinical neuroscientist, and a fetal MRI technician independently labeled the reconstructed images as 1 or 0 based on image quality (1 = high; 0 = low). These labels were fused and served as ground truth. The proposed DLMs were trained and evaluated using three repeated 10-fold cross-validations (training and validation sets of 244 and 27 scans). To quantify GA influence, this variable was included as an input of the DLMs. STATISTICAL TESTS DLM performance was evaluated using precision, recall, F-score, accuracy, and AUC values. RESULTS Precision, recall, F-score, accuracy, and AUC averaged over the three cross validations were 0.85 ± 0.01, 0.85 ± 0.01, 0.85 ± 0.01, 0.85 ± 0.01, 0.93 ± 0.01, for MI-CB-DLM (without GA); 0.75 ± 0.03, 0.75 ± 0.03, 0.75 ± 0.03, 0.75 ± 0.03, 0.81 ± 0.03, for MI-VB-DLM (without GA); 0.81 ± 0.01, 0.81 ± 0.01, 0.81 ± 0.01, 0.81 ± 0.01, 0.89 ± 0.01, for MI-FE-DLM (without GA); and 0.86 ± 0.01, 0.86 ± 0.01, 0.86 ± 0.01, 0.86 ± 0.01, 0.93 ± 0.01, for MI-CB-DLM with GA. DATA CONCLUSION MI-CB-DLM performed better than other DLMs. Including GA as an input of MI-CB-DLM improved its performance. MI-CB-DLM may potentially be used to objectively and rapidly assess fetal MR image quality. EVIDENCE LEVEL 4 TECHNICAL EFFICACY: Stage 3.
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Affiliation(s)
- Axel Largent
- Developing Brain Institute, Division of Diagnostic Imaging and Radiology, Children's National Hospital, Washington, District of Columbia, USA
| | - Kushal Kapse
- Developing Brain Institute, Division of Diagnostic Imaging and Radiology, Children's National Hospital, Washington, District of Columbia, USA
| | - Scott D Barnett
- Developing Brain Institute, Division of Diagnostic Imaging and Radiology, Children's National Hospital, Washington, District of Columbia, USA
| | - Josepheen De Asis-Cruz
- Developing Brain Institute, Division of Diagnostic Imaging and Radiology, Children's National Hospital, Washington, District of Columbia, USA
| | - Matthew Whitehead
- Developing Brain Institute, Division of Diagnostic Imaging and Radiology, Children's National Hospital, Washington, District of Columbia, USA.,Department of Neurology, Children's National Hospital, Washington, District of Columbia, USA
| | - Jonathan Murnick
- Developing Brain Institute, Division of Diagnostic Imaging and Radiology, Children's National Hospital, Washington, District of Columbia, USA
| | - Li Zhao
- Developing Brain Institute, Division of Diagnostic Imaging and Radiology, Children's National Hospital, Washington, District of Columbia, USA
| | - Nicole Andersen
- Developing Brain Institute, Division of Diagnostic Imaging and Radiology, Children's National Hospital, Washington, District of Columbia, USA
| | - Jessica Quistorff
- Developing Brain Institute, Division of Diagnostic Imaging and Radiology, Children's National Hospital, Washington, District of Columbia, USA
| | - Catherine Lopez
- Developing Brain Institute, Division of Diagnostic Imaging and Radiology, Children's National Hospital, Washington, District of Columbia, USA
| | - Catherine Limperopoulos
- Developing Brain Institute, Division of Diagnostic Imaging and Radiology, Children's National Hospital, Washington, District of Columbia, USA.,Department of Radiology, Pediatrics, George Washington University, Washington, District of Columbia, USA.,Neurology School of Medicine and Health Sciences, George Washington University, Washington, District of Columbia, USA
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37
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Jensen KK, Oh KY, Patel N, Narasimhan ER, Ku AS, Sohaey R. Fetal Hepatomegaly: Causes and Associations. Radiographics 2021; 40:589-604. [PMID: 32125959 DOI: 10.1148/rg.2020190114] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/28/2023]
Abstract
Fetal hepatomegaly is associated with significant fetal morbidity and mortality. However, hepatomegaly might be overlooked when numerous other fetal anomalies are present, or it might not be noticed when it is an isolated entity. As the largest solid organ in the abdomen, the liver can be seen well with US or MRI, and the normal imaging characteristics are well described. The length of the fetal liver, which can be used to identify hepatomegaly, can be determined by measuring the liver from the diaphragm to the tip of the right lobe in the sagittal plane. Fetal hepatomegaly is seen with infection, transient abnormal myelopoiesis, liver storage and deposition diseases, some syndromes, large liver tumors, biliary atresia, and anemia. Some of these diagnoses are treatable during the fetal period. Attention to the associated findings and specific hepatic and nonhepatic imaging characteristics can help facilitate more accurate diagnoses and appropriate patient counseling.©RSNA, 2020.
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Affiliation(s)
- Kyle K Jensen
- From the Department of Diagnostic Radiology, Oregon Health & Science University, 3181 SW Sam Jackson Park Rd, L-340, Portland, OR 97239
| | - Karen Y Oh
- From the Department of Diagnostic Radiology, Oregon Health & Science University, 3181 SW Sam Jackson Park Rd, L-340, Portland, OR 97239
| | - Neel Patel
- From the Department of Diagnostic Radiology, Oregon Health & Science University, 3181 SW Sam Jackson Park Rd, L-340, Portland, OR 97239
| | - Evan R Narasimhan
- From the Department of Diagnostic Radiology, Oregon Health & Science University, 3181 SW Sam Jackson Park Rd, L-340, Portland, OR 97239
| | - Alexei S Ku
- From the Department of Diagnostic Radiology, Oregon Health & Science University, 3181 SW Sam Jackson Park Rd, L-340, Portland, OR 97239
| | - Roya Sohaey
- From the Department of Diagnostic Radiology, Oregon Health & Science University, 3181 SW Sam Jackson Park Rd, L-340, Portland, OR 97239
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38
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Sun L, Lee FT, van Amerom JFP, Freud L, Jaeggi E, Macgowan CK, Seed M. Update on fetal cardiovascular magnetic resonance and utility in congenital heart disease. JOURNAL OF CONGENITAL CARDIOLOGY 2021. [DOI: 10.1186/s40949-021-00059-x] [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
Congenital heart disease (CHD) is the most common birth defect, affecting approximately eight per thousand newborns. Between one and two neonates per thousand have congenital cardiac lesions that require immediate post-natal treatment to stabilize the circulation, and the management of these patients in particular has been greatly enhanced by prenatal detection. The antenatal diagnosis of CHD has been made possible through the development of fetal echocardiography, which provides excellent visualization of cardiac anatomy and physiology and is widely available. However, late gestational fetal echocardiographic imaging can be hampered by suboptimal sonographic windows, particularly in the setting of oligohydramnios or adverse maternal body habitus.
Main body
Recent advances in fetal cardiovascular magnetic resonance (CMR) technology now provide a feasible alternative that could be helpful when echocardiography is inconclusive or limited. Fetal CMR has also been used to study fetal circulatory physiology in human fetuses with CHD, providing new insights into how these common anatomical abnormalities impact the distribution of blood flow and oxygen across the fetal circulation. In combination with conventional fetal and neonatal magnetic resonance imaging (MRI) techniques, fetal CMR can be used to explore the relationship between abnormal cardiovascular physiology and fetal development. Similarly, fetal CMR has been successfully applied in large animal models of the human fetal circulation, aiding in the evaluation of experimental interventions aimed at improving in utero development. With the advent of accelerated image acquisition techniques, post-processing approaches to correcting motion artifacts and commercial MRI compatible cardiotocography units for acquiring gated fetal cardiac imaging, an increasing number of CMR methods including angiography, ventricular volumetry, and the quantification of vessel blood flow and oxygen content are now possible.
Conclusion
Fetal CMR has reached an exciting stage whereby it may now be used to enhance the assessment of cardiac morphology and fetal hemodynamics in the setting of prenatal CHD.
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Soewondo W, Kusumaningrum S, Putro PS, Indriyani I, Maryetty IP, Rosati A, Yuliantara EE. The use of FIESTA sequence MRI in successful management of abdominal pregnancy. Clin Imaging 2021; 77:117-121. [PMID: 33667944 DOI: 10.1016/j.clinimag.2021.01.005] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/31/2020] [Revised: 12/30/2020] [Accepted: 01/06/2021] [Indexed: 11/19/2022]
Abstract
Identification of fetal location and its relations to abdominal organs is extremely important in reducing fetal and maternal morbidity in rare cases of abdominal pregnancy. Ultrasound examination is inadequate for helping to successfully manage such cases. In this case report, FIESTA sequence MRI is used to provide high-resolution, better contrast, and higher signal-to-noise ratio fetal and abdominal images. A case of advanced abdominal pregnancy with a live fetus is reported. The surgery was conducted successfully on 34 weeks of gestation.
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Affiliation(s)
- Widiastuti Soewondo
- Department of Radiology, Dr. Moewardi Public Hospital, Faculty of Medicine, Universitas Sebelas Maret, Surakarta, Indonesia.
| | - Sulistyani Kusumaningrum
- Department of Radiology, Dr. Moewardi Public Hospital, Faculty of Medicine, Universitas Sebelas Maret, Surakarta, Indonesia
| | - Prasetyo Sarwono Putro
- Department of Radiology, Dr. Moewardi Public Hospital, Faculty of Medicine, Universitas Sebelas Maret, Surakarta, Indonesia
| | - Ifada Indriyani
- Department of Radiology, Dr. Moewardi Public Hospital, Faculty of Medicine, Universitas Sebelas Maret, Surakarta, Indonesia
| | - Ida Prista Maryetty
- Department of Radiology, Dr. Moewardi Public Hospital, Faculty of Medicine, Universitas Sebelas Maret, Surakarta, Indonesia
| | - Ari Rosati
- Department of Radiology, Dr. Moewardi Public Hospital, Faculty of Medicine, Universitas Sebelas Maret, Surakarta, Indonesia
| | - Eric Edwin Yuliantara
- Department of Obstetrics, Dr. Moewardi Public Hospital, Faculty of Medicine, Universitas Sebelas Maret, Surakarta, Indonesia
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40
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Advances in the prenatal investigation of the fetus using MRI. GINECOLOGIA.RO 2021. [DOI: 10.26416/gine.32.2.2021.5007] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/08/2022] Open
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Knoop MS, Groot ER, Dudink J. Current ideas about the roles of rapid eye movement and non-rapid eye movement sleep in brain development. Acta Paediatr 2021; 110:36-44. [PMID: 32673435 PMCID: PMC7818400 DOI: 10.1111/apa.15485] [Citation(s) in RCA: 33] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/22/2020] [Accepted: 07/13/2020] [Indexed: 12/22/2022]
Abstract
Understanding the links between sleep and brain development is important, as rapid eye movement (REM) sleep and non-REM (NREM) sleep seem to contribute to different aspects of brain maturation. If children have sleep problems, REM sleep and NREM sleep are likely to have different consequences for their developing brain, depending on their age. We highlight important discoveries from human and animal research on the role sleep plays in brain development. A hypothetical model is presented to explain the dynamic relationship of REM sleep and NREM sleep with different processes of brain maturation, with implications for current neonatal care and future research.
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Affiliation(s)
- Marit S. Knoop
- Department of Neonatology Wilhelmina Children's Hospital University Medical Center Utrecht Utrecht The Netherlands
| | - Eline R. Groot
- Department of Neonatology Wilhelmina Children's Hospital University Medical Center Utrecht Utrecht The Netherlands
| | - Jeroen Dudink
- Department of Neonatology Wilhelmina Children's Hospital University Medical Center Utrecht Utrecht The Netherlands
- Brain Center Rudolf Magnus University Medical Center Utrecht Utrecht The Netherlands
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Coblentz AC, Teixeira SR, Mirsky DM, Johnson AM, Feygin T, Victoria T. How to read a fetal magnetic resonance image 101. Pediatr Radiol 2020; 50:1810-1829. [PMID: 33252751 DOI: 10.1007/s00247-020-04768-0] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/21/2020] [Revised: 05/22/2020] [Accepted: 07/01/2020] [Indexed: 12/18/2022]
Abstract
Accurate antenatal diagnosis is essential for planning appropriate pregnancy management and improving perinatal outcomes. The provision of information vital for prognostication is a crucial component of prenatal imaging, and this can be enhanced by the use of fetal MRI. Image acquisition, interpretation and reporting of a fetal MR study can be daunting to the individual who has encountered few or none of these examinations. This article provides the radiology trainee with a general approach to interpreting a fetal MRI. The authors review the added value of prenatal MRI in the overall assessment of fetal wellbeing, discuss MRI protocols and techniques, and review the normal appearance of maternal and fetal anatomy. The paper concludes with a sample template for structured reporting, to serve as a checklist and guideline for reporting radiologists.
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Affiliation(s)
- Ailish C Coblentz
- Radiology Department, The Children's Hospital of Philadelphia, 34th Street and Civic Center Boulevard, Philadelphia, PA, 10104, USA
| | - Sara R Teixeira
- Radiology Department, The Children's Hospital of Philadelphia, 34th Street and Civic Center Boulevard, Philadelphia, PA, 10104, USA
| | - David M Mirsky
- Neuroradiology Department, Children's Hospital of Colorado, Aurora, CO, USA
| | - Ann M Johnson
- Radiology Department, The Children's Hospital of Philadelphia, 34th Street and Civic Center Boulevard, Philadelphia, PA, 10104, USA
| | - Tamara Feygin
- Radiology Department, The Children's Hospital of Philadelphia, 34th Street and Civic Center Boulevard, Philadelphia, PA, 10104, USA
| | - Teresa Victoria
- Radiology Department, The Children's Hospital of Philadelphia, 34th Street and Civic Center Boulevard, Philadelphia, PA, 10104, USA.
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Russo C, Nastro A, Cicala D, De Liso M, Covelli EM, Cinalli G. Neuroimaging in tuberous sclerosis complex. Childs Nerv Syst 2020; 36:2497-2509. [PMID: 32519125 DOI: 10.1007/s00381-020-04705-4] [Citation(s) in RCA: 18] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/13/2020] [Accepted: 05/25/2020] [Indexed: 01/26/2023]
Abstract
INTRODUCTION Tuberous sclerosis complex (TSC) is a rare autosomal dominant disorder affecting multiple systems, due to inactivating mutations of TSC1 or TSC2 mTOR pathway genes. Neurological manifestations are observed in about 95% cases, representing the most frequent cause of morbidity and one of the most common causes of mortality. BACKGROUND Neuroimaging is crucial for early diagnosis, monitoring, and management of these patients. While computed tomography is generally used as first-line investigation at emergency department, magnetic resonance imaging is the reference method to define central nervous system involvement and investigate subtle pathophysiological alterations in TSC patients. PURPOSE Here, we review the state-of-the-art knowledge in TSC brain imaging, describing conventional findings and depicting the role of advanced techniques in providing new insights on the disease, also offering an overview on future perspectives of neuroimaging applications for a better understanding of disease pathophysiology.
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Affiliation(s)
- Camilla Russo
- Department of Pediatric Neurosciences, Pediatric Neuroradiology Unit, Santobono-Pausilipon Children's Hospital, Naples, Italy.,Department of Electrical Engineering and Information Technology (DIETI), University of Naples "Federico II", Naples, Italy
| | - Anna Nastro
- Department of Pediatric Neurosciences, Pediatric Neuroradiology Unit, Santobono-Pausilipon Children's Hospital, Naples, Italy
| | - Domenico Cicala
- Department of Pediatric Neurosciences, Pediatric Neuroradiology Unit, Santobono-Pausilipon Children's Hospital, Naples, Italy
| | - Maria De Liso
- Department of Pediatric Neurosciences, Pediatric Neuroradiology Unit, Santobono-Pausilipon Children's Hospital, Naples, Italy
| | - Eugenio Maria Covelli
- Department of Pediatric Neurosciences, Pediatric Neuroradiology Unit, Santobono-Pausilipon Children's Hospital, Naples, Italy
| | - Giuseppe Cinalli
- Department of Pediatric Neurosciences, Pediatric Neurosurgery Unit, Santobono-Pausilipon Children's Hospital, Via Mario Fiore n. 6, 80129, Naples, Italy.
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Bhat R, Al-Samarraie M, Nada A, Leiva-Salinas C, Whitehead M, Mahdi E. Spotlight on the pediatric eye: a pictorial review of orbital anatomy and congenital orbital pathologies. Neuroradiol J 2020; 34:21-32. [PMID: 32865127 DOI: 10.1177/1971400920949232] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/08/2023] Open
Abstract
Orbital lesions in the pediatric population vary from adults in terms of their presentation, unique pathology, and imaging characteristics. The prompt and accurate diagnosis of these lesions is imperative to prevent serious consequences in terms of visual impairment and disfigurement. Along with dedicated ophthalmologic examination, imaging is instrumental in characterizing these lesions, both for accurate diagnosis and subsequent management. In our pictorial essay, we provide a basic review of orbital embryology, anatomy, and congenital orbital pathologies, with emphasis on radiological findings.
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Affiliation(s)
- Roopa Bhat
- Department of Radiology, University of Missouri Health Care, USA
| | | | - Ayman Nada
- Department of Radiology, University of Missouri Health Care, USA
| | | | - Matthew Whitehead
- Diagnostic Imaging and Radiology, Children's National Health Systems, USA.,George Washington University Hospital, USA
| | - Eman Mahdi
- Department of Radiology, University of Missouri Health Care, USA
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45
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Gupta S, Mohi JK, Gambhir P, Mohi MK. Prenatal diagnosis of congenital anomalies of genito-urinary system on fetal magnetic resonance imaging. THE EGYPTIAN JOURNAL OF RADIOLOGY AND NUCLEAR MEDICINE 2020. [DOI: 10.1186/s43055-020-00278-z] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/26/2022] Open
Abstract
Abstract
Background
The aim of this study is to elucidate the spectrum of commonly encountered anomalies affecting fetal genito-urinary system (GUS) on fetal MRI and examine its utility in providing better morphological information resulting in improved diagnostic accuracy and in detecting additional malformations. The study also aims to highlight the promising role of fetal MRI in the detection and characterization of renal fusion anomalies like the horseshoe kidney or developmental abnormalities such as renal agenesis/ectopia.
Results
The mean age of study participants was 29 years ± 3 years. The gestation age of pregnant mothers ranged from 18 weeks and 1 day to 39 weeks and 0 day. Amniotic fluid was reduced or absent in 41% (N = 13) and normal in 59% (N = 18) of participating mothers. Overall, urinary obstruction was the commonest anomaly encountered (29%) followed by the multicystic dysplastic kidney (MCDK) (22%). Bilateral renal disease was seen in all mothers having features of anhydramnios {B/L MCDK (N = 3), autosomal recessive polycystic kidney disease (ARPKD) (N = 2), posterior urethral valves (PUV) (N = 2), B/L renal agenesis (N = 3), and megacystis (N = 1)}. Fusion anomalies (horseshoe kidney) and rotation anomaly (malrotation) were detected in one case each. Additional extrarenal findings were seen on fetal MRI in 35% (N = 11) cases.
Conclusions
Fetal MRI improves diagnostic accuracy in anomalies affecting the fetal kidney and genito-urinary systems by better morphological delineation. It has the ability to detect additional extra-renal malformations and perform a more accurate assessment of associated pulmonary hypoplasia. The diffusion-weighted sequence is particularly useful in confirming the diagnosis of renal agenesis/ectopia.
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46
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Dong SZ, Zhu M, Ji H, Ren JY, Liu K. Fetal cardiac MRI: a single center experience over 14-years on the potential utility as an adjunct to fetal technically inadequate echocardiography. Sci Rep 2020; 10:12373. [PMID: 32704065 PMCID: PMC7378840 DOI: 10.1038/s41598-020-69375-3] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2020] [Accepted: 07/07/2020] [Indexed: 12/26/2022] Open
Abstract
Unlike ultrasound (US) imaging, foetal magnetic resonance imaging (MRI) is not significantly limited by maternal obesity, oligohydramnios, uterine myoma, twins, and foetal lie, which impair US visualization of the foetus. The present study aimed to introduce our foetal cardiac MRI scanning technology and over 14-years of experience on the potential utility of foetal cardiac MRI examination as an adjunct to foetal technically inadequate echocardiography (Echo). This retrospective review included 1,573 pregnant women [1,619 foetuses (46 twins)] referred for a foetal cardiac MRI because of technically limited Echo. Foetal cardiac MRI was performed using two 1.5 T units. Among the 1,619 foetuses referred for cardiac MRI, 1,379 (85.2%) cases were followed up using postnatal imaging and/or surgery, 240 (14.8%), including three twins, had no follow-up confirmation because of pregnancy termination without autopsy or loss to follow-up. The results of the present study indicated that foetal cardiac MRI examinations can be a useful adjunct to foetal echocardiography when the technical limitations of echocardiography make it inadequate for diagnosis.
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Affiliation(s)
- Su-Zhen Dong
- Department of Radiology, Shanghai Children's Medical Center, Shanghai Jiaotong University School of Medicine, Shanghai, 200127, China.
| | - Ming Zhu
- Department of Radiology, Shanghai Children's Medical Center, Shanghai Jiaotong University School of Medicine, Shanghai, 200127, China.
| | - Hui Ji
- Department of Radiology, Shanghai Children's Medical Center, Shanghai Jiaotong University School of Medicine, Shanghai, 200127, China
| | - Jing-Ya Ren
- Department of Radiology, Shanghai Children's Medical Center, Shanghai Jiaotong University School of Medicine, Shanghai, 200127, China
| | - Ke Liu
- Department of Radiology, Shanghai Children's Medical Center, Shanghai Jiaotong University School of Medicine, Shanghai, 200127, China
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47
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Rohanizadegan M, Tracy S, Galarreta CI, Poorvu T, Buchmiller TL, Bird LM, Estroff JA, Tan WH. Genetic diagnoses and associated anomalies in fetuses prenatally diagnosed with esophageal atresia. Am J Med Genet A 2020; 182:1890-1895. [PMID: 32573094 DOI: 10.1002/ajmg.a.61639] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/13/2020] [Revised: 04/12/2020] [Accepted: 05/04/2020] [Indexed: 12/28/2022]
Abstract
Esophageal atresia (EA) is a congenital anomaly occurring in 2.3 per 10,000 live births. Due to advances in prenatal imaging, EA is more readily diagnosed, but data on the associated genetic diagnoses, other anomalies, and postnatal outcome for fetuses diagnosed prenatally with EA are scarce. We collected data from two academic medical centers (n = 61). Our data included fetuses with suspected EA on prenatal imaging that was confirmed postnatally and had at least one genetic test. In our cohort of 61 cases, 29 (49%) were born prematurely and 19% of those born alive died in the first 9 years of life. The most commonly associated birth defects were cardiac anomalies (67%) and spine anomalies (50%). A diagnosis was made in 61% of the cases; the most common diagnoses were vertebral defects, anal atresia, cardiac anomalies, tracheoesophageal fistula with esophageal atresia, radial or renal dysplasia, and limb anomalies association (43%, although 12% met only 2 of the criteria), trisomy 21 (5%), and CHARGE syndrome (5%). Our findings suggest that most fetuses with prenatally diagnosed EA have one or more additional major anomaly that warrants a more comprehensive clinical genetics evaluation. Fetuses diagnosed prenatally appear to represent a cohort with a worse outcome.
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Affiliation(s)
- Mersedeh Rohanizadegan
- Division of Genetics and Genomics, Boston Children's Hospital, Harvard Medical School, Boston, Massachusetts, USA
| | - Sarah Tracy
- Department of Surgery, Boston Children's Hospital, Harvard Medical School, Boston, Massachusetts, USA
| | - Carolina I Galarreta
- Department of Pediatrics, University of California, San Diego, California, USA
- Division of Genetics/Dysmorphology, Rady Children's Hospital San Diego, San Diego, California, USA
| | - Tabitha Poorvu
- Division of Genetics and Genomics, Boston Children's Hospital, Harvard Medical School, Boston, Massachusetts, USA
- Maternal Fetal Care Center, Boston Children's Hospital, Boston, Massachusetts, USA
| | - Terry L Buchmiller
- Department of Surgery, Boston Children's Hospital, Harvard Medical School, Boston, Massachusetts, USA
- Maternal Fetal Care Center, Boston Children's Hospital, Boston, Massachusetts, USA
| | - Lynne M Bird
- Department of Pediatrics, University of California, San Diego, California, USA
- Division of Genetics/Dysmorphology, Rady Children's Hospital San Diego, San Diego, California, USA
| | - Judy A Estroff
- Maternal Fetal Care Center, Boston Children's Hospital, Boston, Massachusetts, USA
- Department of Radiology, Boston Children's Hospital, Harvard Medical School, Boston, Massachusetts, USA
| | - Wen-Hann Tan
- Division of Genetics and Genomics, Boston Children's Hospital, Harvard Medical School, Boston, Massachusetts, USA
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48
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Goldman-Yassen AE, Goodrich JT, Miller TS, Farinhas JM. Preoperative Evaluation of Craniopagus Twins: Anatomy, Imaging Techniques, and Surgical Management. AJNR Am J Neuroradiol 2020; 41:951-959. [PMID: 32439641 DOI: 10.3174/ajnr.a6571] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/06/2019] [Accepted: 02/10/2020] [Indexed: 11/07/2022]
Abstract
Craniopagus twins are a rare congenital malformation in which twins are conjoined at the head. Although there is high prenatal and postnatal mortality for craniopagus twins, successful separation has become more common due to advances in neuroimaging, neuroanesthesia, and neurosurgical techniques. Joined brain tissue, shared arteries and veins, and defects in the skull and dura make surgery technically challenging, and neuroimaging plays an important role in preoperative planning. Drawing on our experience from consultation for multiple successful separations of craniopagus twins, we discuss what radiologists need to know about the anatomy, classification, imaging techniques, and surgical management of craniopagus twins.
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Affiliation(s)
- A E Goldman-Yassen
- From the Department of Radiology (A.E.G.-Y.), Children's Hospital of Philadelphia, Philadelphia, Pennsylvania .,Departments of Radiology (A.E.G.-Y., J.M.F.)
| | - J T Goodrich
- Neurosurgery (J.T.G.), Montefiore Medical Center, Bronx, New York
| | - T S Miller
- Department of Radiology (T.S.M.), Stamford Hospital, Stamford, Connecticut
| | - J M Farinhas
- Departments of Radiology (A.E.G.-Y., J.M.F.).,Department of Radiology (J.M.F.), Moffitt Cancer Center Tampa, Florida
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Tanacan A, Ozgen B, Fadiloglu E, Unal C, Oguz KK, Beksac MS. Prenatal diagnosis of central nervous system abnormalities: Neurosonography versus fetal magnetic resonance imaging. Eur J Obstet Gynecol Reprod Biol 2020; 250:195-202. [PMID: 32460228 DOI: 10.1016/j.ejogrb.2020.05.013] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/11/2020] [Revised: 04/30/2020] [Accepted: 05/07/2020] [Indexed: 12/12/2022]
Abstract
OBJECTIVE To share our experience in diagnosis of congenital central nervous system (CNS) abnormalities by fetal magnetic resonance imaging (MRI). STUDY DESIGN This study consisted of 110 pregnancies. Neurosonography (NS) findings were compared with MRI results. Anomalies were categorized into 10 groups: 1) Corpus callosum (CC) and cavum septum pellucidum (CSP) anomalies, 2) Neural tube defects (NTD), 3) Posterior fossa anomalies (PFA), 4) Primary ventriculomegaly (PVM), 5) Microcephaly, 6) Macrocephaly, 7) Periventricular leukomalacia (PVL), 8) Craniosynostosis, 9) Intracranial hemorrhage (ICH) and 10) Lumbosacral teratoma. Demographic features, clinical characteristics and perinatal outcomes of the study subjects were evaluated. RESULTS Gestational weeks for NS and for MRI were 25.5 and 26.5 weeks, respectively. Fourteen (12.7%) pregnancies were terminated. PVM (n = 36, 32.7%), CC and CSP anomalies (n = 29, 26.3%), PFA (n = 11, 10%) and NTD (n = 11, 10%) were the most common fetal MRI indications. There were no statistically significant differences between the accuracy of fetal NS and fetal MRI for CC and CSP anomalies, NTDs, PFA and PVM (p = 0.09, 0.43, 0.45 and 0.23, respectively). However, fetal MRI was more accurate for the detection of normal anatomic findings in cases with suspected microcephaly, macrocephaly and craniosynostosis in NS when pooled together (p = 0.007). Furthermore, MRI also seemed to be advantageous in CC & CSP anomalies though it was not validated by statistical measures. No statistically significant difference was found for diagnostic performance of NS and MRI according to gestational week (p = 0.27). CONCLUSION Fetal MRI in addition to NS may improve diagnostic accuracy in pregnancies with congenital CNS abnormalities.
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Affiliation(s)
- Atakan Tanacan
- Division of Perinatology, Department of Obstetrics and Gynecology, Hacettepe University, Ankara, Turkey.
| | - Burce Ozgen
- Department of Radiology, Hacettepe University, Ankara, Turkey
| | - Erdem Fadiloglu
- Division of Perinatology, Department of Obstetrics and Gynecology, Hacettepe University, Ankara, Turkey
| | - Canan Unal
- Division of Perinatology, Department of Obstetrics and Gynecology, Hacettepe University, Ankara, Turkey
| | | | - Mehmet Sinan Beksac
- Division of Perinatology, Department of Obstetrics and Gynecology, Hacettepe University, Ankara, Turkey
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Raafat RME, Abdelrahman TM, Hafez MAF. The prevalence and the adding value of fetal MRI imaging in midline cerebral anomalies. THE EGYPTIAN JOURNAL OF RADIOLOGY AND NUCLEAR MEDICINE 2020. [DOI: 10.1186/s43055-020-0146-0] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022] Open
Abstract
Abstract
Background
Foetal MR imaging is widely accepted as an adjunct to foetal ultrasonography; however, there are many controversies regarding its importance and indications. Therefore, this study aimed to evaluate foetuses with different midline cerebral abnormalities, to determine the prevalence of these anomalies, to define the role of foetal MRI, and to compare MRI and ultrasound (US) result with postnatal MRI findings. Seventy-eight pregnant women who had foetuses with CNS abnormalities detected by sonogram were included. Foetuses with midline anomalies were selected and evaluated by anomaly scan foetal US, pre- and postnatal MRI.
Results
Midline brain anomalies were found in 47.4% of foetuses with brain anomalies. Holoprosencephaly was found in 24.3% of midline anomaly foetuses, corpus callosum abnormalities (ACC) were detected in 40.5%, midline intracranial mass lesions in 2.7%, and midline posterior fossa anomalies in 32.4%. An agreement between MRI and US in the main diagnosis was in 56.76% of cases; MRI added information to US findings in 43.2% of cases, and US added information to MRI findings in 8.1% of cases.
Conclusion
In evaluating midline cerebral anomalies, US and MRI are complementary techniques. US is the primary survey, and MRI can add additional information and/or change the main diagnosis.
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