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Meng H, Luo ZL, Shen Y, Liu QQ, Li MZ, Gao YM. Accurate prenatal diagnosis of coarctation of the aorta by 3-step echocardiographic diagnostic protocol. BMC Pediatr 2024; 24:552. [PMID: 39192246 DOI: 10.1186/s12887-024-04851-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/28/2022] [Accepted: 05/22/2024] [Indexed: 08/29/2024] Open
Abstract
BACKGROUND Coarctation of the aorta (CoA) is the most common undiagnosed congenital heart defect during prenatal screening. High false positive and false negative rates seriously affect prenatal consultation and postnatal management. The objective of the study was to assess the utility of various measurements to predict prenatal CoA and to derive a diagnostic algorithm. METHODS One hundred and fifty-four fetuses with suspected CoA who presented at Fuwai Hospital between December 2017 and August 2021 were enrolled and divided into confirmed CoA cases (n = 47) and false positive cases (n = 107), according to their postnatal outcomes. The transverse aortic arch, isthmus, and descending aorta were measured in the long-axis view of the aortic arch. The angle between the transverse aortic arch (TAO) and the descending aortic arch (DAO) was defined as the TAO-DAO angle and measured in the long axis or sagittal view. Based on the database in GE Voluson E10 and the formula (Z = [Formula: see text]), the standard score (Z-score) of the dimensions of the aorta were calculated in relation to the gestational age. The main echocardiographic indices were combined to design a 3-step diagnostic protocol. The TAO-DAO angle was used as the first step in the diagnostic model. The diameter of the transverse arch and the Z-score of the isthmus were the second step. The third-step indices included a Z-score of the transverse arch, diameter of the isthmus, distance from the left subclavian artery (LSA) to left common carotid artery (LCCA), the ratio of isthmus diameter and LSA diameter and ratio of the distances (the distance between the LSA and LCCA to the distance between the right innominate artery and LCCA). The receiver operating characteristic (ROC) curve determined the predictive capability of each diagnostic parameter, and the kappa test determined the diagnostic accuracy of the proposed model. RESULTS The cases with confirmed CoA had thinner transverse arches (1.92 ± 0.32 mm vs. 3.06 ± 0.67 mm, P = 0.0001), lower Z-scores of the isthmus (-8.97 ± 1.45 vs. -5.65 ± 1.60, P = 0.0001), smaller TAO-DAO angles (105.54 ± 11.51° vs. 125.29 ± 8.97°, P = 0.0001) and larger distance between the LSA and LCCA (4.45 ± 1.75 mm vs. 2.74 ± 1.07 mm, P = 0.0001) than the false positive cases. The area under the curve (AUC) was 0.947 (95% CI 0.91-0.98) for the TAO-DAO angle ≤ 115.75°, 0.942 (95% CI 0.91-0.98) for the transverse arch diameter ≤ 2.31 mm, 0.937 (95% CI 0.90-0.98) for the Z-score of the isthmus ≤ -7.5, and 0.975 (95% CI 0.95-1.00) for the 3-step diagnostic protocol with 97.8% sensitivity and 97.2% specificity. The kappa test showed that the model's diagnostic accuracy was consistent with postnatal outcomes (kappa value 0.936, P = 0.0001). CONCLUSIONS The 3-step diagnostic protocol included the three most useful measurements and the additional indices with appropriate cut-off values. The algorithm is useful for the detection of aortic coarctation in fetuses with a high degree of accuracy. TRIAL REGISTRATION Retrospectively registered.
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Affiliation(s)
- Hong Meng
- Department of Echocardiography, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, 167 Beilishi Rd, Xicheng District, Beijing, 100037, P. R. China.
| | - Zhi-Ling Luo
- Department of Echocardiography, Fuwai Yunnan Cardiovascular Hospital Kunming, Kunming, 650102, China
| | - Yan Shen
- Department of Echocardiography, Fuwai Yunnan Cardiovascular Hospital Kunming, Kunming, 650102, China
| | - Qian-Qian Liu
- Department of Echocardiography, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, 167 Beilishi Rd, Xicheng District, Beijing, 100037, P. R. China
| | - Mu-Zi Li
- Department of Echocardiography, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, 167 Beilishi Rd, Xicheng District, Beijing, 100037, P. R. China
| | - Yi-Ming Gao
- Department of Echocardiography, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, 167 Beilishi Rd, Xicheng District, Beijing, 100037, P. R. China
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Taksøe-Vester CA, Mikolaj K, Petersen OBB, Vejlstrup NG, Christensen AN, Feragen A, Nielsen M, Svendsen MBS, Tolsgaard MG. Role of artificial-intelligence-assisted automated cardiac biometrics in prenatal screening for coarctation of aorta. ULTRASOUND IN OBSTETRICS & GYNECOLOGY : THE OFFICIAL JOURNAL OF THE INTERNATIONAL SOCIETY OF ULTRASOUND IN OBSTETRICS AND GYNECOLOGY 2024; 64:36-43. [PMID: 38339776 DOI: 10.1002/uog.27608] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/01/2023] [Revised: 01/31/2024] [Accepted: 01/31/2024] [Indexed: 02/12/2024]
Abstract
OBJECTIVE Although remarkable strides have been made in fetal medicine and the prenatal diagnosis of congenital heart disease, around 60% of newborns with isolated coarctation of the aorta (CoA) are not identified prior to birth. The prenatal detection of CoA has been shown to have a notable impact on survival rates of affected infants. To this end, implementation of artificial intelligence (AI) in fetal ultrasound may represent a groundbreaking advance. We aimed to investigate whether the use of automated cardiac biometric measurements with AI during the 18-22-week anomaly scan would enhance the identification of fetuses that are at risk of developing CoA. METHODS We developed an AI model capable of identifying standard cardiac planes and conducting automated cardiac biometric measurements. Our data consisted of pregnancy ultrasound image and outcome data spanning from 2008 to 2018 and collected from four distinct regions in Denmark. Cases with a postnatal diagnosis of CoA were paired with healthy controls in a ratio of 1:100 and matched for gestational age within 2 days. Cardiac biometrics obtained from the four-chamber and three-vessel views were included in a logistic regression-based prediction model. To assess its predictive capabilities, we assessed sensitivity and specificity on receiver-operating-characteristics (ROC) curves. RESULTS At the 18-22-week scan, the right ventricle (RV) area and length, left ventricle (LV) diameter and the ratios of RV/LV areas and main pulmonary artery/ascending aorta diameters showed significant differences, with Z-scores above 0.7, when comparing subjects with a postnatal diagnosis of CoA (n = 73) and healthy controls (n = 7300). Using logistic regression and backward feature selection, our prediction model had an area under the ROC curve of 0.96 and a specificity of 88.9% at a sensitivity of 90.4%. CONCLUSIONS The integration of AI technology with automated cardiac biometric measurements obtained during the 18-22-week anomaly scan has the potential to enhance substantially the performance of screening for fetal CoA and subsequently the detection rate of CoA. Future research should clarify how AI technology can be used to aid in the screening and detection of congenital heart anomalies to improve neonatal outcomes. © 2024 The Authors. Ultrasound in Obstetrics & Gynecology published by John Wiley & Sons Ltd on behalf of International Society of Ultrasound in Obstetrics and Gynecology.
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Affiliation(s)
- C A Taksøe-Vester
- Department of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
- Center of Fetal Medicine, Department of Gynecology, Fertility and Obstetrics, Copenhagen University Hospital, Rigshospitalet, Copenhagen, Denmark
- Copenhagen Academy of Medical Education and Simulation (CAMES), Rigshospitalet, Copenhagen, Denmark
| | - K Mikolaj
- Technical University of Denmark, Lyngby, Denmark
| | - O B B Petersen
- Department of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
- Center of Fetal Medicine, Department of Gynecology, Fertility and Obstetrics, Copenhagen University Hospital, Rigshospitalet, Copenhagen, Denmark
| | - N G Vejlstrup
- Department of Cardiology, Copenhagen University Hospital, Rigshospitalet, Copenhagen, Denmark
| | | | - A Feragen
- Technical University of Denmark, Lyngby, Denmark
| | - M Nielsen
- Department of Computer Science, University of Copenhagen, Copenhagen, Denmark
| | - M B S Svendsen
- Copenhagen Academy of Medical Education and Simulation (CAMES), Rigshospitalet, Copenhagen, Denmark
| | - M G Tolsgaard
- Department of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
- Center of Fetal Medicine, Department of Gynecology, Fertility and Obstetrics, Copenhagen University Hospital, Rigshospitalet, Copenhagen, Denmark
- Copenhagen Academy of Medical Education and Simulation (CAMES), Rigshospitalet, Copenhagen, Denmark
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Villalaín C, D'Antonio F, Flacco ME, Gómez-Montes E, Herraiz I, Deiros-Bronte L, Maskatia SA, Phillips AA, Contro E, Fricke K, Bhawna A, Beattie MJ, Moon-Grady AJ, Durand I, Slodki M, Respondek-Liberska M, Patel C, Kawamura H, Rizzo G, Pagani G, Galindo A. Diagnostic accuracy of prenatal ultrasound in coarctation of aorta: systematic review and individual participant data meta-analysis. ULTRASOUND IN OBSTETRICS & GYNECOLOGY : THE OFFICIAL JOURNAL OF THE INTERNATIONAL SOCIETY OF ULTRASOUND IN OBSTETRICS AND GYNECOLOGY 2024; 63:446-456. [PMID: 38197327 DOI: 10.1002/uog.27576] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/20/2023] [Revised: 12/24/2023] [Accepted: 12/28/2023] [Indexed: 01/11/2024]
Abstract
OBJECTIVE To determine the diagnostic accuracy of prenatal ultrasound in detecting coarctation of the aorta (CoA). METHODS An individual participant data meta-analysis was performed to report on the strength of association and diagnostic accuracy of different ultrasound signs in detecting CoA prenatally. MEDLINE, EMBASE and CINAHL were searched for studies published between January 2000 and November 2021. Inclusion criteria were fetuses with suspected isolated CoA, defined as ventricular and/or great vessel disproportion with right dominance on ultrasound assessment. Individual participant-level data were obtained by two leading teams. PRISMA-IPD and PRISMA-DTA guidelines were used for extracting data, and the QUADAS-2 tool was used for assessing quality and applicability. The reference standard was CoA, defined as narrowing of the aortic arch, diagnosed after birth. The most commonly evaluated parameters on ultrasound, both in B-mode and on Doppler, constituted the index test. Summary estimates of sensitivity, specificity, diagnostic odds ratio (DOR) and likelihood ratios were computed using the hierarchical summary receiver-operating-characteristics model. RESULTS The initial search yielded 72 studies, of which 25 met the inclusion criteria. Seventeen studies (640 fetuses) were included. On random-effects logistic regression analysis, tricuspid valve/mitral valve diameter ratio > 1.4 and > 1.6, aortic isthmus/arterial duct diameter ratio < 0.7, hypoplastic aortic arch (all P < 0.001), aortic isthmus diameter Z-score of < -2 in the sagittal (P = 0.003) and three-vessel-and-trachea (P < 0.001) views, pulmonary artery/ascending aorta diameter ratio > 1.4 (P = 0.048) and bidirectional flow at the foramen ovale (P = 0.012) were independently associated with CoA. Redundant foramen ovale was inversely associated with CoA (P = 0.037). Regarding diagnostic accuracy, tricuspid valve/mitral valve diameter ratio > 1.4 had a sensitivity of 72.6% (95% CI, 48.2-88.3%), specificity of 65.4% (95% CI, 46.9-80.2%) and DOR of 5.02 (95% CI, 1.82-13.9). The sensitivity and specificity values were, respectively, 75.0% (95% CI, 61.1-86.0%) and 39.7% (95% CI, 27.0-53.4%) for pulmonary artery/ascending aorta diameter ratio > 1.4, 47.8% (95% CI, 14.6-83.0%) and 87.6% (95% CI, 27.3-99.3%) for aortic isthmus diameter Z-score of < -2 in the sagittal view and 74.1% (95% CI, 58.0-85.6%) and 62.0% (95% CI, 41.6-78.9%) for aortic isthmus diameter Z-score of < -2 in the three-vessel-and-trachea view. Hypoplastic aortic arch had a sensitivity of 70.0% (95% CI, 42.0-88.6%), specificity of 91.3% (95% CI, 78.6-96.8%) and DOR of 24.9 (95% CI, 6.18-100). The diagnostic yield of prenatal ultrasound in detecting CoA did not change significantly when considering multiple categorical parameters. Five of the 11 evaluated continuous parameters were independently associated with CoA (all P < 0.001) but all had low-to-moderate diagnostic yield. CONCLUSIONS Several prenatal ultrasound parameters are associated with an increased risk for postnatal CoA. However, diagnostic accuracy is only moderate, even when combinations of parameters are considered. © 2024 The Authors. Ultrasound in Obstetrics & Gynecology published by John Wiley & Sons Ltd on behalf of International Society of Ultrasound in Obstetrics and Gynecology.
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Affiliation(s)
- C Villalaín
- Fetal Medicine Unit, Department of Obstetrics and Gynecology, Hospital Universitario 12 de Octubre, Complutense University, Madrid, Spain
- Instituto de Investigación del Hospital 12 de Octubre (imas12), Madrid, Spain
- Primary Care Interventions to Prevent Maternal and Child Chronic Diseases of Perinatal and Developmental Origin (RICORS network), RD21/0012/0024, Madrid, Spain
| | - F D'Antonio
- Department of Obstetrics and Gynaecology, University of Chieti, Chieti, Italy
| | - M E Flacco
- Department of Environmental and Preventive Sciences, University of Ferrara, Ferrara, Italy
| | - E Gómez-Montes
- Fetal Medicine Unit, Department of Obstetrics and Gynecology, Hospital Universitario 12 de Octubre, Complutense University, Madrid, Spain
- Instituto de Investigación del Hospital 12 de Octubre (imas12), Madrid, Spain
- Primary Care Interventions to Prevent Maternal and Child Chronic Diseases of Perinatal and Developmental Origin (RICORS network), RD21/0012/0024, Madrid, Spain
| | - I Herraiz
- Fetal Medicine Unit, Department of Obstetrics and Gynecology, Hospital Universitario 12 de Octubre, Complutense University, Madrid, Spain
- Instituto de Investigación del Hospital 12 de Octubre (imas12), Madrid, Spain
- Primary Care Interventions to Prevent Maternal and Child Chronic Diseases of Perinatal and Developmental Origin (RICORS network), RD21/0012/0024, Madrid, Spain
| | - L Deiros-Bronte
- Department of Pediatric Cardiology, La Paz Children's Hospital, Madrid, Spain
| | - S A Maskatia
- Division of Pediatric Cardiology, Stanford University School of Medicine, Palo Alto, CA, USA
| | - A A Phillips
- Division of Pediatric Cardiology, Stanford University School of Medicine, Palo Alto, CA, USA
| | - E Contro
- Department of Obstetrics and Gynecology, Fetal Medicine Unit, S. Orsola University Hospital, Bologna, Italy
| | - K Fricke
- Department of Clinical Sciences Lund, Pediatric Cardiology, Lund University, Skane University Hospital, Lund, Sweden
| | - A Bhawna
- Department of Pediatrics, University of Washington School of Medicine, Seattle Children's Hospital, Seattle, WA, USA
| | - M J Beattie
- Division of Pediatric Cardiology, University of California San Francisco, San Francisco, CA, USA
| | - A J Moon-Grady
- Division of Pediatric Cardiology, University of California San Francisco, San Francisco, CA, USA
| | - I Durand
- Department of Pediatrics, Rouen University Hospital, Rouen, France
| | - M Slodki
- Medicine Faculty, Mazovian University in Plock, Plock, Poland
- Department of Prenatal Cardiology, Polish Mother's Memorial Hospital Research Institute in Lodz, Lodz, Poland
| | - M Respondek-Liberska
- Department for Diagnosis and Prevention of Congenital Malformations, Medical University of Lodz, Lodz, Poland
- Fetal Cardiology Department Polish Mother's Memorial Hospital, Lodz, Poland
| | - C Patel
- Children's Hospital of Philadelphia, Philadelphia, PA, USA
| | - H Kawamura
- Department of Maternal Fetal Medicine, Osaka Women's and Children's Hospital, Osaka, Japan
| | - G Rizzo
- Department of Obstetrics and Gynecology, Fondazione Policinico Tor Vergata, Università di Roma Tor Vergata, Rome, Italy
| | - G Pagani
- Department of Obstetrics and Gynecology, ASST-Papa Giovanni XXIII, Maternal Fetal Medicine Unit, Bergamo, Italy
| | - A Galindo
- Fetal Medicine Unit, Department of Obstetrics and Gynecology, Hospital Universitario 12 de Octubre, Complutense University, Madrid, Spain
- Instituto de Investigación del Hospital 12 de Octubre (imas12), Madrid, Spain
- Primary Care Interventions to Prevent Maternal and Child Chronic Diseases of Perinatal and Developmental Origin (RICORS network), RD21/0012/0024, Madrid, Spain
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Hermida U, van Poppel MPM, Lloyd DFA, Steinweg JK, Vigneswaran TV, Simpson JM, Razavi R, De Vecchi A, Pushparajah K, Lamata P. Learning the Hidden Signature of Fetal Arch Anatomy: a Three-Dimensional Shape Analysis in Suspected Coarctation of the Aorta. J Cardiovasc Transl Res 2023; 16:738-747. [PMID: 36301513 PMCID: PMC10299929 DOI: 10.1007/s12265-022-10335-9] [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: 06/09/2022] [Accepted: 10/13/2022] [Indexed: 10/31/2022]
Abstract
Neonatal coarctation of the aorta (CoA) is a common congenital heart defect. Its antenatal diagnosis remains challenging, and its pathophysiology is poorly understood. We present a novel statistical shape modeling (SSM) pipeline to study the role and predictive value of arch shape in CoA in utero. Cardiac magnetic resonance imaging (CMR) data of 112 fetuses with suspected CoA was acquired and motion-corrected to three-dimensional volumes. Centerlines from fetal arches were extracted and used to build a statistical shape model capturing relevant anatomical variations. A linear discriminant analysis was used to find the optimal axis between CoA and false positive cases. The CoA shape risk score classified cases with an area under the curve of 0.907. We demonstrate the feasibility of applying a SSM pipeline to three-dimensional fetal CMR data while providing novel insights into the anatomical determinants of CoA and the relevance of in utero arch anatomy for antenatal diagnosis of CoA.
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Affiliation(s)
- Uxio Hermida
- Department of Biomedical Engineering, School of Biomedical Engineering and Imaging Sciences, King's College London, St Thomas' Hospital, 5Th Floor Becket House, 1 Lambeth Palace Road, London, SE1 7EH, UK
| | - Milou P M van Poppel
- Department of Cardiovascular Imaging, School of Biomedical Engineering and Imaging Sciences, King's College London, St Thomas' Hospital, London, SE1 7EH, UK
| | - David F A Lloyd
- Department of Perinatal Imaging, School of Biomedical Engineering and Imaging Sciences, King's College London, St Thomas' Hospital, London, SE1 7EH, UK
- Department of Congenital Heart Disease, Evelina London Children's Hospital, London, SE1 7EH, UK
| | - Johannes K Steinweg
- Department of Cardiovascular Imaging, School of Biomedical Engineering and Imaging Sciences, King's College London, St Thomas' Hospital, London, SE1 7EH, UK
| | - Trisha V Vigneswaran
- Department of Congenital Heart Disease, Evelina London Children's Hospital, London, SE1 7EH, UK
- Harris Birthright Centre, Fetal Medicine Research Institute, King's College Hospital, London, UK
| | - John M Simpson
- Department of Congenital Heart Disease, Evelina London Children's Hospital, London, SE1 7EH, UK
- Harris Birthright Centre, Fetal Medicine Research Institute, King's College Hospital, London, UK
| | - Reza Razavi
- Department of Cardiovascular Imaging, School of Biomedical Engineering and Imaging Sciences, King's College London, St Thomas' Hospital, London, SE1 7EH, UK
- Department of Congenital Heart Disease, Evelina London Children's Hospital, London, SE1 7EH, UK
| | - Adelaide De Vecchi
- Department of Biomedical Engineering, School of Biomedical Engineering and Imaging Sciences, King's College London, St Thomas' Hospital, 5Th Floor Becket House, 1 Lambeth Palace Road, London, SE1 7EH, UK
| | - Kuberan Pushparajah
- Department of Cardiovascular Imaging, School of Biomedical Engineering and Imaging Sciences, King's College London, St Thomas' Hospital, London, SE1 7EH, UK
- Department of Congenital Heart Disease, Evelina London Children's Hospital, London, SE1 7EH, UK
| | - Pablo Lamata
- Department of Biomedical Engineering, School of Biomedical Engineering and Imaging Sciences, King's College London, St Thomas' Hospital, 5Th Floor Becket House, 1 Lambeth Palace Road, London, SE1 7EH, UK.
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Sun J, Starc J, Stevens RM. Challenges of prenatal diagnosis of fetal hypoplastic aortic arch and predication of the need for intervention. J Card Surg 2022; 37:3711-3712. [PMID: 36047368 DOI: 10.1111/jocs.16837] [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: 07/07/2022] [Revised: 07/31/2022] [Accepted: 08/02/2022] [Indexed: 11/30/2022]
Abstract
Prenatal diagnosis of hypoplastic aortic arch and coarctation of aorta is still challenging and remains one of the most difficult cardiac defects to diagnose. The results reveal a significant improvement of prenatal diagnosis of hypoplastic arch and coarctation of aorta. The data also shows the significant overlapping of fetal aortic isthmus z score between the infants who need the arch procedure and those who do not.
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Affiliation(s)
- Jie Sun
- St. Christopher's Hospital for Children, Drexel University College of Medicine, Philadelphia, Pennsylvania, USA
| | - James Starc
- St. Christopher's Hospital for Children, Drexel University College of Medicine, Philadelphia, Pennsylvania, USA
| | - Randy M Stevens
- St. Christopher's Hospital for Children, Drexel University College of Medicine, Philadelphia, Pennsylvania, USA
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