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Merhar SL, Bann CM, Mack N, Newman JE, Limperopoulos C, Ambalavanan N, Davis JM, DeMauro SB, Lorch S, Wilson-Costello DE, Peralta-Carcelan M, Parlberg LM, Poindexter BB, Kapse K, Kline-Fath B, Murnick J. Prenatal Opioid Exposure is Associated with Punctate White Matter Lesions in Term Newborns. J Pediatr 2025:114669. [PMID: 40414418 DOI: 10.1016/j.jpeds.2025.114669] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/20/2025] [Revised: 05/05/2025] [Accepted: 05/19/2025] [Indexed: 05/27/2025]
Abstract
OBJECTIVE To assess whether prenatal opioid exposure is associated with punctate white matter lesions (PWML) on brain magnetic resonance imaging (MRI) in a large prospective cohort of term newborns. STUDY DESIGN Newborns ≥37 weeks' gestation with prenatal opioid exposure and unexposed controls underwent brain MRI at 0-1 months of age in the prospective observational Outcomes of Babies with Opioid Exposure (OBOE) study. Exposure status was based on maternal self-report and/or maternal or neonatal toxicology screening. MRIs were scored by two pediatric neuroradiologists masked to exposure. Multinomial logistic regression was used to compute odds ratios for PWML by opioid exposure, adjusting for various confounders. RESULTS Opioid-exposed newborns (n=165) had lower birth weight and smaller head circumference and were more likely to have mothers who smoked, were positive for hepatitis C, and had limited education than unexposed neonates (n=94). 27% of exposed newborns had 1 or more PWML compared with 13% of unexposed newborns (P = .031). After adjusting for covariates, opioid exposure was associated with higher odds of PWML (adjusted odds ratio [aOR] 2.68, 95% CI 1.07-6.72, P = .04), with methadone exposure worse than buprenorphine and other opioids (aOR 3.25, 95% CI 1.21-8.75, P=.02). CONCLUSIONS Prenatal opioid exposure is associated with an increased risk of PWML in newborns, with methadone exposure significantly worse than buprenorphine. As PWML are associated with adverse neurologic outcomes in other populations, follow-up will evaluate if these lesions significantly impact neurodevelopmental outcomes.
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Affiliation(s)
- Stephanie L Merhar
- Perinatal Institute, Division of Neonatology, Cincinnati Children's Hospital Medical Center, Cincinnati, OH; Department of Pediatrics, University of Cincinnati, Cincinnati, OH
| | | | - Nicole Mack
- RTI International, Research Triangle Park, NC
| | | | | | | | | | - Sara B DeMauro
- Children's Hospital of Philadelphia, Philadelphia, PA; University of Pennsylvania, Philadelphia, PA
| | - Scott Lorch
- Children's Hospital of Philadelphia, Philadelphia, PA; University of Pennsylvania, Philadelphia, PA
| | | | | | | | | | | | - Beth Kline-Fath
- Department of Radiology, Cincinnati Children's Hospital Medical Center, Cincinnati, OH
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López‐Guerrero N, Alcauter S. Developmental Trajectories and Differences in Functional Brain Network Properties of Preterm and At-Term Neonates. Hum Brain Mapp 2025; 46:e70126. [PMID: 39815687 PMCID: PMC11735747 DOI: 10.1002/hbm.70126] [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: 01/29/2024] [Revised: 12/10/2024] [Accepted: 12/23/2024] [Indexed: 01/18/2025] Open
Abstract
Premature infants, born before 37 weeks of gestation can have alterations in neurodevelopment and cognition, even when no anatomical lesions are evident. Resting-state functional neuroimaging of naturally sleeping babies has shown altered connectivity patterns, but there is limited evidence on the developmental trajectories of functional organization in preterm neonates. By using a large dataset from the developing Human Connectome Project, we explored the differences in graph theory properties between at-term (n = 332) and preterm (n = 115) neonates at term-equivalent age, considering the age subgroups proposed by the World Health Organization for premature birth. Leveraging the longitudinal follow-up for some preterm participants, we characterized the developmental trajectories for preterm and at-term neonates, for this purpose linear, quadratic, and log-linear mixed models were constructed with gestational age at scan as an independent fixed-effect variable and random effects were added for the intercept and subject ID. Significance was defined at p < 0.05, and the model with the lowest Akaike Information Criterion (AIC) was selected as the best model. We found significant differences between groups in connectivity strength, clustering coefficient, characteristic path length and global efficiency. Specifically, at term-equivalent ages, higher connectivity, clustering coefficient and efficiency are identified for neonates born at later postmenstrual ages. Similarly, the characteristic path length showed the inverse pattern. These results were consistent for a variety of connectivity thresholds at both the global (whole brain) and local level (brain regions). The brain regions with the greatest differences between groups include primary sensory and motor regions and the precuneus which may relate to the risk factors for sensorimotor and behavioral deficits associated with premature birth. Our results also show non-linear developmental trajectories for premature neonates, but decreased integration and segregation even at term-equivalent age. Overall, our results confirm altered functional connectivity, integration and segregation properties of the premature brain despite showing rapid maturation after birth.
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Affiliation(s)
- N. López‐Guerrero
- Instituto de NeurobiologíaUniversidad Nacional Autónoma de MéxicoQuerétaroMexico
| | - Sarael Alcauter
- Instituto de NeurobiologíaUniversidad Nacional Autónoma de MéxicoQuerétaroMexico
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Sullivan G, Quigley AJ, Choi S, Teed R, Blesa Cabez M, Vaher K, Corrigan A, Stoye DQ, Thrippleton MJ, Bastin M, Boardman JP. Brain 3T magnetic resonance imaging in neonates: features and incidental findings from a research cohort enriched for preterm birth. Arch Dis Child Fetal Neonatal Ed 2024; 110:85-90. [PMID: 38960453 PMCID: PMC11672019 DOI: 10.1136/archdischild-2024-326960] [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: 02/02/2024] [Accepted: 06/18/2024] [Indexed: 07/05/2024]
Abstract
BACKGROUND AND OBJECTIVES The survival rate and patterns of brain injury after very preterm birth are evolving with changes in clinical practices. Additionally, incidental findings can present legal, ethical and practical considerations. Here, we report MRI features and incidental findings from a large, contemporary research cohort of very preterm infants and term controls. METHODS 288 infants had 3T MRI at term-equivalent age: 187 infants born <32 weeks without major parenchymal lesions, and 101 term-born controls. T1-weighted, T2-weighted and susceptibility-weighted imaging were used to classify white and grey matter injury according to a structured system, and incidental findings described. RESULTS Preterm infants: 34 (18%) had white matter injury and 4 (2%) had grey matter injury. 51 (27%) infants had evidence of intracranial haemorrhage and 34 (18%) had punctate white matter lesions (PWMLs). Incidental findings were detected in 12 (6%) preterm infants. Term infants: no term infants had white or grey matter injury. Incidental findings were detected in 35 (35%); these included intracranial haemorrhage in 22 (22%), periventricular pseudocysts in 5 (5%) and PWMLs in 4 (4%) infants. From the whole cohort, 10 (3%) infants required referral to specialist services. CONCLUSIONS One-fifth of very preterm infants without major parenchymal lesions have white or grey matter abnormalities at term-equivalent age. Incidental findings are seen in 6% of preterm and 35% of term infants. Overall, 3% of infants undergoing MRI for research require follow-up due to incidental findings. These data should help inform consent procedures for research and assist service planning for centres using 3T neonatal brain MRI for clinical purposes.
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Affiliation(s)
- Gemma Sullivan
- The University of Edinburgh Centre for Clinical Brain Sciences, Edinburgh, UK
| | - Alan J Quigley
- Radiology, Royal Hospital for Children and Young People, Edinburgh, UK
| | - Samantha Choi
- Radiology, Royal Hospital for Children and Young People, Edinburgh, UK
| | - Rory Teed
- The University of Edinburgh MRC Centre for Reproductive Health, Edinburgh, UK
| | - Manuel Blesa Cabez
- The University of Edinburgh Centre for Clinical Brain Sciences, Edinburgh, UK
- The University of Edinburgh MRC Centre for Reproductive Health, Edinburgh, UK
| | - Kadi Vaher
- The University of Edinburgh Centre for Clinical Brain Sciences, Edinburgh, UK
- The University of Edinburgh MRC Centre for Reproductive Health, Edinburgh, UK
| | - Amy Corrigan
- The University of Edinburgh MRC Centre for Reproductive Health, Edinburgh, UK
| | - David Q Stoye
- The University of Edinburgh MRC Centre for Reproductive Health, Edinburgh, UK
| | - Michael J Thrippleton
- The University of Edinburgh Centre for Clinical Brain Sciences, Edinburgh, UK
- The University of Edinburgh Edinburgh Imaging Facility, Edinburgh, UK
| | - Mark Bastin
- The University of Edinburgh Centre for Clinical Brain Sciences, Edinburgh, UK
- The University of Edinburgh Edinburgh Imaging Facility, Edinburgh, UK
| | - James P Boardman
- The University of Edinburgh Centre for Clinical Brain Sciences, Edinburgh, UK
- The University of Edinburgh MRC Centre for Reproductive Health, Edinburgh, UK
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Di Pasquo E, Contro E, Labadini C, Dall'Asta A, Volpe N, Larcher L, Vettor L, Piemonti L, Ormitti F, Ghi T. Visualization of caudothalamic groove at expert fetal neurosonography. ULTRASOUND IN OBSTETRICS & GYNECOLOGY : THE OFFICIAL JOURNAL OF THE INTERNATIONAL SOCIETY OF ULTRASOUND IN OBSTETRICS AND GYNECOLOGY 2024; 64:785-791. [PMID: 38764195 DOI: 10.1002/uog.27699] [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: 02/04/2024] [Revised: 04/02/2024] [Accepted: 05/06/2024] [Indexed: 05/21/2024]
Abstract
OBJECTIVES To describe the sonographic features of the caudothalamic groove in the third trimester of pregnancy in a group of structurally normal fetuses and to report a small series of cases with abnormal appearance of the caudothalamic groove at antenatal cranial ultrasound. METHODS This was an observational study conducted at two fetal medicine referral units in Italy. A non-consecutive cohort of pregnant women with a singleton non-anomalous pregnancy were recruited prospectively and underwent three-dimensional (3D) ultrasound assessment of the fetal brain at 28-32 weeks' gestation. At offline analysis, the ultrasound volumes were adjusted in the multiplanar mode, according to a standardized methodology, until the caudothalamic groove was visible in the parasagittal plane. To evaluate interobserver agreement, two operators were asked independently to indicate if the caudothalamic groove was visible unilaterally or bilaterally on each volume and Cohen's kappa (κ) coefficient was calculated. The digital archives of the two centers were also searched retrospectively to retrieve cases with abnormal findings at the level of the caudothalamic groove on antenatal cranial ultrasound that were confirmed postnatally. RESULTS A total of 180 non-consecutive cases were included. At offline analysis of the 3D ultrasound volumes, the caudothalamic groove was identified in the parasagittal plane by both operators at least unilaterally in 176 (97.8%) cases and bilaterally in 174 (96.7%) cases. The κ-coefficient for the agreement between the two independent operators in recognizing the caudothalamic groove was 0.89 and 0.83 for one and both hemispheres, respectively. The retrospective search of our archives yielded five cases with an abnormal appearance of the caudothalamic groove at antenatal cranial ultrasound, including two cases of hemorrhage and three cases of cyst. CONCLUSIONS The caudothalamic groove is consistently seen in normal fetuses on multiplanar neurosonography in the third trimester, and abnormal findings in this region may be detected antenatally. © 2024 International Society of Ultrasound in Obstetrics and Gynecology.
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Affiliation(s)
- E Di Pasquo
- Unit of Obstetrics and Gynecology, University Hospital of Parma, Parma, Italy
| | - E Contro
- Unit of Obstetrics and Gynecology, Department of Medicine and Surgery, S. Orsola University Hospital of Bologna, IRCCS AOUB, Bologna, Italy
| | - C Labadini
- Unit of Obstetrics and Gynecology, Department of Medicine and Surgery, University of Parma, Parma, Italy
| | - A Dall'Asta
- Unit of Obstetrics and Gynecology, University Hospital of Parma, Parma, Italy
- Unit of Obstetrics and Gynecology, Department of Medicine and Surgery, University of Parma, Parma, Italy
| | - N Volpe
- Unit of Obstetrics and Gynecology, University Hospital of Parma, Parma, Italy
| | - L Larcher
- Unit of Obstetrics and Gynecology, Department of Medicine and Surgery, S. Orsola University Hospital of Bologna, IRCCS AOUB, Bologna, Italy
| | - L Vettor
- Unit of Obstetrics and Gynecology, Department of Medicine and Surgery, S. Orsola University Hospital of Bologna, IRCCS AOUB, Bologna, Italy
| | - L Piemonti
- Unit of Obstetrics and Gynecology, Department of Medicine and Surgery, S. Orsola University Hospital of Bologna, IRCCS AOUB, Bologna, Italy
| | - F Ormitti
- Department of Radiology, University Hospital of Parma, Parma, Italy
| | - T Ghi
- Unit of Obstetrics and Gynecology, University Hospital of Parma, Parma, Italy
- Unit of Obstetrics and Gynecology, Department of Medicine and Surgery, University of Parma, Parma, Italy
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Shin HI, Lee NM, Kim SM, Hwang H, Choi G, Han DH, Kim DK. The association between ventricle ratio in preterm infants and motor developmental delay. Dev Neurosci 2024:000540754. [PMID: 39222619 DOI: 10.1159/000540754] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/12/2024] [Accepted: 07/29/2024] [Indexed: 09/04/2024] Open
Abstract
Introduction Early prediction and timely intervention are particularly essential for high-risk preterm infants. Brain magnetic resonance imaging (BMRI) is frequently used alongside functional evaluations to improve predictions of developmental outcomes. This study aimed to assess voxel-based brain volumetry in extremely preterm infants using BMRI at term equivalent age (TEA) and investigate its association with developmental outcomes. Methods From March 2016 to December 2019, high-risk preterm infants (birth weight < 1500g or gestational age < 32 weeks) with BMRI at TEA and follow-up developmental data assessed by Bayley-III were included. For BMRI volumetry, manual tracing and segmentation were performed on T1-weighted scans, and after smoothing, voxels were calculated for each brain segment. Forty-seven subjects were enrolled and categorized into typical/delayed motor groups Results Results revealed a significant difference in ventricle size and ventricle ratio in BMRI at TEA between the groups. Even after controlling for other factors that could influence developmental outcomes, ventricle ratio emerged as a robust, single predictor for future motor development. Conclusion This study suggests the potential clinical utility of BMRI volumetry in predicting motor development outcomes.
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Damien J, Vannasing P, Tremblay J, Petitpas L, Marandyuk B, Balasingam T, El Jalbout R, Paquette N, Donofrio G, Birca A, Gallagher A, Pinchefsky EF. Relationship between EEG spectral power and dysglycemia with neurodevelopmental outcomes after neonatal encephalopathy. Clin Neurophysiol 2024; 163:160-173. [PMID: 38754181 DOI: 10.1016/j.clinph.2024.03.029] [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: 10/06/2023] [Revised: 02/28/2024] [Accepted: 03/23/2024] [Indexed: 05/18/2024]
Abstract
OBJECTIVE We investigated how electroencephalography (EEG) quantitative measures and dysglycemia relate to neurodevelopmental outcomes following neonatal encephalopathy (NE). METHODS This retrospective study included 90 neonates with encephalopathy who received therapeutic hypothermia. EEG absolute spectral power was calculated during post-rewarming and 2-month follow-up. Measures of dysglycemia (hypoglycemia, hyperglycemia, and glycemic lability) and glucose variability were computed for the first 48 h of life. We evaluated the ability of EEG and glucose measures to predict neurodevelopmental outcomes at ≥ 18 months, using logistic regressions (with area under the receiver operating characteristic [AUROC] curves). RESULTS The post-rewarming global delta power (average all electrodes), hyperglycemia and glycemic lability predicted moderate/severe neurodevelopmental outcome separately (AUROC = 0.8, 95%CI [0.7,0.9], p < .001) and even more so when combined (AUROC = 0.9, 95%CI [0.8,0.9], p < .001). After adjusting for NE severity and magnetic resonance imaging (MRI) brain injury, only global delta power remained significantly associated with moderate/severe neurodevelopmental outcome (odds ratio [OR] = 0.9, 95%CI [0.8,1.0], p = .04), gross motor delay (OR = 0.9, 95%CI [0.8,1.0], p = .04), global developmental delay (OR = 0.9, 95%CI [0.8,1.0], p = .04), and auditory deficits (OR = 0.9, 95%CI [0.8,1.0], p = .03). CONCLUSIONS In NE, global delta power post-rewarming was predictive of outcomes at ≥ 18 months. SIGNIFICANCE EEG markers post-rewarming can aid prediction of neurodevelopmental outcomes following NE.
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Affiliation(s)
- Janie Damien
- Neurodevelopmental Optical Imaging Laboratory (LION Lab), Sainte-Justine University Hospital Centre, Montreal, QC, Canada; Research Centre, Sainte-Justine University Hospital Centre, Montreal, QC, Canada; Department of Psychology, University of Montreal, Montreal, QC, Canada.
| | - Phetsamone Vannasing
- Neurodevelopmental Optical Imaging Laboratory (LION Lab), Sainte-Justine University Hospital Centre, Montreal, QC, Canada; Research Centre, Sainte-Justine University Hospital Centre, Montreal, QC, Canada.
| | - Julie Tremblay
- Neurodevelopmental Optical Imaging Laboratory (LION Lab), Sainte-Justine University Hospital Centre, Montreal, QC, Canada; Research Centre, Sainte-Justine University Hospital Centre, Montreal, QC, Canada.
| | - Laurence Petitpas
- Neurodevelopmental Optical Imaging Laboratory (LION Lab), Sainte-Justine University Hospital Centre, Montreal, QC, Canada; Research Centre, Sainte-Justine University Hospital Centre, Montreal, QC, Canada; Department of Psychology, University of Montreal, Montreal, QC, Canada.
| | - Bohdana Marandyuk
- Research Centre, Sainte-Justine University Hospital Centre, Montreal, QC, Canada.
| | - Thameya Balasingam
- Research Centre, Sainte-Justine University Hospital Centre, Montreal, QC, Canada.
| | - Ramy El Jalbout
- Department of Radiology, Sainte-Justine University Hospital Centre, Montreal, QC, Canada.
| | - Natacha Paquette
- Neurodevelopmental Optical Imaging Laboratory (LION Lab), Sainte-Justine University Hospital Centre, Montreal, QC, Canada; Research Centre, Sainte-Justine University Hospital Centre, Montreal, QC, Canada; Department of Psychology, University of Montreal, Montreal, QC, Canada.
| | - Gianluca Donofrio
- Department of Neurosciences Rehabilitation, Ophthalmology, Genetics, Maternal and Child Health (DiNOGMI), University of Genoa, Via Gerolamo Gaslini 5, 16147 Genoa, Italy; Service of Neurology, Department of Pediatrics, Sainte-Justine University Hospital Centre, Montreal, QC, Canada.
| | - Ala Birca
- Research Centre, Sainte-Justine University Hospital Centre, Montreal, QC, Canada; Service of Neurology, Department of Pediatrics, Sainte-Justine University Hospital Centre, Montreal, QC, Canada
| | - Anne Gallagher
- Neurodevelopmental Optical Imaging Laboratory (LION Lab), Sainte-Justine University Hospital Centre, Montreal, QC, Canada; Research Centre, Sainte-Justine University Hospital Centre, Montreal, QC, Canada; Department of Psychology, University of Montreal, Montreal, QC, Canada.
| | - Elana F Pinchefsky
- Research Centre, Sainte-Justine University Hospital Centre, Montreal, QC, Canada; Service of Neurology, Department of Pediatrics, Sainte-Justine University Hospital Centre, Montreal, QC, Canada.
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Xie Q, Liao YH, He WJ, Wang GQ. Incidence and clinical analysis of asymptomatic intracranial hemorrhage in neonates with cerebral hypoxic-ischaemic risk based on multisequence MR images. Sci Rep 2024; 14:14721. [PMID: 38926428 PMCID: PMC11208507 DOI: 10.1038/s41598-024-62473-6] [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: 11/11/2023] [Accepted: 05/17/2024] [Indexed: 06/28/2024] Open
Abstract
The incidence and clinical distribution of intracranial haemorrhage (ICH) in neonates at risk of cerebral hypoxia-ischaemia have not been reported in specific studies. Based on conventional magnetic resonance imaging (MRI) versus susceptibility weighted imaging (SWI), this study aimed to analyse the occurrence of asymptomatic ICH in newborns with or without risk of cerebral hypoxia-ischaemia and to accumulate objective data for clinical evaluations of high-risk neonates and corresponding response strategies. 317 newborns were included. MRI revealed that the overall incidence of ICH was 59.31%. The most common subtype was intracranial extracerebral haemorrhage (ICECH) which included subarachnoid haemorrhage (SAH) and subdural haemorrhage (SDH). ICECH accounted for 92.02% of ICH. The positive detection rate of ICECH by SWI was significantly higher than that by T1WI. The incidence of total ICH, ICECH and SAH was greater among children who were delivered vaginally than among those who underwent caesarean delivery. Asymptomatic neonatal ICH may be a common complication of the neonatal birth process, and SWI may improve the detection rate. Transvaginal delivery and a weight greater than 2500 g were associated with a high incidence of ICECH in neonates. The impact of neonatal cerebral hypoxia-ischaemia risk factors on the occurrence of asymptomatic ICH may be negligible.
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Affiliation(s)
- Qi Xie
- Department of Medical Imaging in Nansha, Guangzhou First People's Hospital, School of Medicine, South China University of Technology, Guangzhou, 511457, China.
| | - Yan-Hui Liao
- Department of Medical Imaging in Nansha, Guangzhou First People's Hospital, School of Medicine, South China University of Technology, Guangzhou, 511457, China
- Department of Nuclear Medicine, Meizhou People's Hospital, Meizhou, 514031, Guangdong, China
| | - Wen-Juan He
- Department of Medical Imaging in Nansha, Guangzhou First People's Hospital, School of Medicine, South China University of Technology, Guangzhou, 511457, China
| | - Gui-Qin Wang
- Medical Record Department in Nansha, Guangzhou First People's Hospital, School of Medicine, South China University of Technology, Guangzhou, 511457, China
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Bahl R, Hotton E, Crofts J, Draycott T. Assisted vaginal birth in 21st century: current practice and new innovations. Am J Obstet Gynecol 2024; 230:S917-S931. [PMID: 38462263 DOI: 10.1016/j.ajog.2022.12.305] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/31/2022] [Revised: 12/12/2022] [Accepted: 12/14/2022] [Indexed: 03/12/2024]
Abstract
Assisted vaginal birth rates are falling globally with rising cesarean delivery rates. Cesarean delivery is not without consequence, particularly when carried out in the second stage of labor. Cesarean delivery in the second stage is not entirely protective against pelvic floor morbidity and can lead to serious complications in a subsequent pregnancy. It should be acknowledged that the likelihood of morbidity for mother and baby associated with cesarean delivery increases with advancing labor and is greater than spontaneous vaginal birth, irrespective of the method of operative birth in the second stage of labor. In this article, we argue that assisted vaginal birth is a skilled and safe option that should always be considered and be available as an option for women who need assistance in the second stage of labor. Selecting the most appropriate mode of birth at full dilatation requires accurate clinical assessment, supported decision-making, and personalized care with consideration for the woman's preferences. Achieving vaginal birth with the primary instrument is more likely with forceps than with vacuum extraction (risk ratio, 0.58; 95% confidence interval, 0.39-0.88). Midcavity forceps are associated with a greater incidence of obstetric anal sphincter injury (odds ratio, 1.83; 95% confidence interval, 1.32-2.55) but no difference in neonatal Apgar score or umbilical artery pH. The risk for adverse outcomes is minimized when the procedure is conducted by a skilled accoucheur who selects the most appropriate instrument likely to achieve vaginal birth with the primary instrument. Anticipation of potential complications and dynamic decision-making are just as important as the technique for safe instrument use. Good communication with the woman and the birthing partner is vital and there are various recommendations on how to achieve this. There have been recent developments (such as OdonAssist) in device innovation, training, and strategies for implementation at a scale that can provide opportunities for both improved outcomes and reinvigoration of an essential skill that can save mothers' and babies' lives across the world.
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Affiliation(s)
- Rachna Bahl
- Department of Obstetrics and Gynaecology, University Hospitals Bristol National Health Service Trust, Bristol, United Kingdom; Royal College of Obstetricians and Gynaecologists, London, United Kingdom.
| | | | - Joanna Crofts
- Department of Obstetrics and Gynaecology, North Bristol National Health Service Trust, Bristol, United Kingdom
| | - Tim Draycott
- Royal College of Obstetricians and Gynaecologists, London, United Kingdom; Department of Obstetrics and Gynaecology, North Bristol National Health Service Trust, Bristol, United Kingdom
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Wu YW, Monsell SE, Glass HC, Wisnowski JL, Mathur AM, McKinstry RC, Bluml S, Gonzalez FF, Comstock BA, Heagerty PJ, Juul SE. How well does neonatal neuroimaging correlate with neurodevelopmental outcomes in infants with hypoxic-ischemic encephalopathy? Pediatr Res 2023; 94:1018-1025. [PMID: 36859442 PMCID: PMC10444609 DOI: 10.1038/s41390-023-02510-8] [Citation(s) in RCA: 24] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/04/2022] [Revised: 01/19/2023] [Accepted: 01/22/2023] [Indexed: 03/03/2023]
Abstract
BACKGROUND In newborns with hypoxic-ischemic encephalopathy (HIE), the correlation between neonatal neuroimaging and the degree of neurodevelopmental impairment (NDI) is unclear. METHODS Infants with HIE enrolled in a randomized controlled trial underwent neonatal MRI/MR spectroscopy (MRS) using a harmonized protocol at 4-6 days of age. The severity of brain injury was measured with a validated scoring system. Using proportional odds regression, we calculated adjusted odds ratios (aOR) for the associations between MRI/MRS measures of injury and primary ordinal outcome (i.e., normal, mild NDI, moderate NDI, severe NDI, or death) at age 2 years. RESULTS Of 451 infants with MRI/MRS at a median age of 5 days (IQR 4.5-5.8), outcomes were normal (51%); mild (12%), moderate (14%), severe NDI (13%); or death (9%). MRI injury score (aOR 1.06, 95% CI 1.05, 1.07), severe brain injury (aOR 39.6, 95% CI 16.4, 95.6), and MRS lactate/n-acetylaspartate (NAA) ratio (aOR 1.6, 95% CI 1.4,1.8) were associated with worse primary outcomes. Infants with mild/moderate MRI brain injury had similar BSID-III cognitive, language, and motor scores as infants with no injury. CONCLUSION In the absence of severe injury, brain MRI/MRS does not accurately discriminate the degree of NDI. Given diagnostic uncertainty, families need to be counseled regarding a range of possible neurodevelopmental outcomes. IMPACT Half of all infants with hypoxic-ischemic encephalopathy (HIE) enrolled in a large clinical trial either died or had neurodevelopmental impairment at age 2 years despite receiving therapeutic hypothermia. Severe brain injury and a global pattern of brain injury on MRI were both strongly associated with death or neurodevelopmental impairment. Infants with mild or moderate brain injury had similar mean BSID-III cognitive, language, and motor scores as infants with no brain injury on MRI. Given the prognostic uncertainty of brain MRI among infants with less severe degrees of brain injury, families should be counseled regarding a range of possible neurodevelopmental outcomes.
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Affiliation(s)
- Yvonne W Wu
- Department of Neurology, University of California San Francisco, San Francisco, CA, USA.
- Department of Pediatrics, University of California San Francisco, San Francisco, CA, USA.
| | - Sarah E Monsell
- Department of Biostatistics, University of Washington, Seattle, WA, USA
| | - Hannah C Glass
- Department of Neurology, University of California San Francisco, San Francisco, CA, USA
- Department of Pediatrics, University of California San Francisco, San Francisco, CA, USA
- Department of Epidemiology, University of California San Francisco, San Francisco, CA, USA
| | - Jessica L Wisnowski
- Department of Radiology, Children's Hospital Los Angeles, Los Angeles, CA, USA
- Department of Pediatrics, Children's Hospital Los Angeles, Los Angeles, CA, USA
| | - Amit M Mathur
- Department of Pediatrics, Saint Louis University School of Medicine, St. Louis, MO, USA
| | - Robert C McKinstry
- Mallinckrodt Institute of Radiology, Washington Univ School of Medicine, St. Louis, MO, USA
| | - Stefan Bluml
- Department of Radiology, Children's Hospital Los Angeles, Los Angeles, CA, USA
- Department of Radiology, University of Southern CA Keck School of Medicine, Los Angeles, CA, USA
| | - Fernando F Gonzalez
- Department of Pediatrics, University of California San Francisco, San Francisco, CA, USA
| | - Bryan A Comstock
- Department of Biostatistics, University of Washington, Seattle, WA, USA
| | | | - Sandra E Juul
- Department of Pediatrics, University of Washington School of Medicine, Seattle, WA, USA
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Fukami-Gartner A, Baburamani AA, Dimitrova R, Patkee PA, Ojinaga-Alfageme O, Bonthrone AF, Cromb D, Uus AU, Counsell SJ, Hajnal JV, O’Muircheartaigh J, Rutherford MA. Comprehensive volumetric phenotyping of the neonatal brain in Down syndrome. Cereb Cortex 2023; 33:8921-8941. [PMID: 37254801 PMCID: PMC10350827 DOI: 10.1093/cercor/bhad171] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/17/2023] [Revised: 04/28/2023] [Accepted: 04/29/2023] [Indexed: 06/01/2023] Open
Abstract
Down syndrome (DS) is the most common genetic cause of intellectual disability with a wide range of neurodevelopmental outcomes. To date, there have been very few in vivo neuroimaging studies of the neonatal brain in DS. In this study we used a cross-sectional sample of 493 preterm- to term-born control neonates from the developing Human Connectome Project to perform normative modeling of regional brain tissue volumes from 32 to 46 weeks postmenstrual age, accounting for sex and age variables. Deviation from the normative mean was quantified in 25 neonates with DS with postnatally confirmed karyotypes from the Early Brain Imaging in DS study. Here, we provide the first comprehensive volumetric phenotyping of the neonatal brain in DS, which is characterized by significantly reduced whole brain, cerebral white matter, and cerebellar volumes; reduced relative frontal and occipital lobar volumes, in contrast with enlarged relative temporal and parietal lobar volumes; enlarged relative deep gray matter volume (particularly the lentiform nuclei); and enlargement of the lateral ventricles, amongst other features. In future, the ability to assess phenotypic severity at the neonatal stage may help guide early interventions and, ultimately, help improve neurodevelopmental outcomes in children with DS.
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Affiliation(s)
- Abi Fukami-Gartner
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King’s College London, St. Thomas’ Hospital, London SE1 7EH, United Kingdom
- MRC Centre for Neurodevelopmental Disorders, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London SE1 1UL, United Kingdom
| | - Ana A Baburamani
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King’s College London, St. Thomas’ Hospital, London SE1 7EH, United Kingdom
| | - Ralica Dimitrova
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King’s College London, St. Thomas’ Hospital, London SE1 7EH, United Kingdom
- Department of Forensic and Neurodevelopmental Science, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London SE5 8AF, United Kingdom
| | - Prachi A Patkee
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King’s College London, St. Thomas’ Hospital, London SE1 7EH, United Kingdom
| | - Olatz Ojinaga-Alfageme
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King’s College London, St. Thomas’ Hospital, London SE1 7EH, United Kingdom
- Centre for Brain and Cognitive Development, Birkbeck, University of London, London WC1E 7HX, United Kingdom
| | - Alexandra F Bonthrone
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King’s College London, St. Thomas’ Hospital, London SE1 7EH, United Kingdom
| | - Daniel Cromb
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King’s College London, St. Thomas’ Hospital, London SE1 7EH, United Kingdom
| | - Alena U Uus
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King’s College London, St. Thomas’ Hospital, London SE1 7EH, United Kingdom
- Department of Biomedical Engineering, School of Biomedical Engineering and Imaging Sciences, King’s College London, London SE1 7EH, United Kingdom
| | - Serena J Counsell
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King’s College London, St. Thomas’ Hospital, London SE1 7EH, United Kingdom
| | - Joseph V Hajnal
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King’s College London, St. Thomas’ Hospital, London SE1 7EH, United Kingdom
- Department of Biomedical Engineering, School of Biomedical Engineering and Imaging Sciences, King’s College London, London SE1 7EH, United Kingdom
| | - Jonathan O’Muircheartaigh
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King’s College London, St. Thomas’ Hospital, London SE1 7EH, United Kingdom
- MRC Centre for Neurodevelopmental Disorders, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London SE1 1UL, United Kingdom
- Department of Forensic and Neurodevelopmental Science, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London SE5 8AF, United Kingdom
| | - Mary A Rutherford
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King’s College London, St. Thomas’ Hospital, London SE1 7EH, United Kingdom
- MRC Centre for Neurodevelopmental Disorders, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London SE1 1UL, United Kingdom
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11
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Thiim KR, Garvey AA, Singh E, Walsh B, Inder TE, El-Dib M. Brain Injury in Infants Evaluated for, But Not Treated with, Therapeutic Hypothermia. J Pediatr 2023; 253:304-309. [PMID: 36179889 DOI: 10.1016/j.jpeds.2022.09.027] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/01/2022] [Revised: 09/15/2022] [Accepted: 09/22/2022] [Indexed: 11/30/2022]
Abstract
Defining neonatal encephalopathy clinically to qualify for therapeutic hypothermia is challenging. This study examines magnetic resonance imaging outcomes of 39 infants who were evaluated and not cooled using criteria inclusive of mild encephalopathy. Infants evaluated for therapeutic hypothermia are at risk for brain injury and may benefit from neuroimaging and follow-up.
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Affiliation(s)
- Kirsten R Thiim
- Department of Pediatric Newborn Medicine, Brigham and Women's Hospital, Boston, MA
| | - Aisling A Garvey
- Department of Pediatric Newborn Medicine, Brigham and Women's Hospital, Boston, MA; INFANT Research Centre, University College Cork, Cork, Ireland; Department of Paediatrics and Child Health, University College Cork, Cork, Ireland; Harvard Medical School, Boston, MA
| | - Elizabeth Singh
- Department of Pediatric Newborn Medicine, Brigham and Women's Hospital, Boston, MA
| | - Brian Walsh
- Department of Pediatric Newborn Medicine, Brigham and Women's Hospital, Boston, MA; INFANT Research Centre, University College Cork, Cork, Ireland; Department of Paediatrics and Child Health, University College Cork, Cork, Ireland; Department of Neonatology, Cork University Maternity Hospital, Cork, Ireland
| | - Terrie E Inder
- Department of Pediatric Newborn Medicine, Brigham and Women's Hospital, Boston, MA; Harvard Medical School, Boston, MA
| | - Mohamed El-Dib
- Department of Pediatric Newborn Medicine, Brigham and Women's Hospital, Boston, MA; Harvard Medical School, Boston, MA.
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12
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Kular S, Holmes H, Hart A, Griffiths P, Connolly D. Evaluation of the Prevalence of Punctate White Matter Lesions in a Healthy Volunteer Neonatal Population. AJNR Am J Neuroradiol 2022; 43:1210-1213. [PMID: 35863781 PMCID: PMC9575410 DOI: 10.3174/ajnr.a7578] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/17/2022] [Accepted: 05/24/2022] [Indexed: 11/07/2022]
Abstract
Hypoxic-ischemic injury is the most common cause of neonatal encephalopathy. T1-weighted punctate white matter lesions have been described in hypoxic-ischemic injury. We have reviewed a healthy volunteer neonatal population to assess the prevalence of punctate white matter lesions in neonates with no clinical signs of hypoxic-ischemic injury. Fifty-two subjects were scanned on a neonatal-specific 3T MR imaging scanner. Twelve patients were excluded due to the lack of T1-weighted imaging, leaving a total of 40 patients (35 term, 5 preterm) assessed in the study. One had a solitary T1-punctate white matter lesion. We concluded that solitary punctate white matter lesions have a low prevalence in healthy neonates.
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Affiliation(s)
- S Kular
- From the Departments of Neuroradiology (S.K., H.H., P.G., D.C.)
| | - H Holmes
- From the Departments of Neuroradiology (S.K., H.H., P.G., D.C.)
| | - A Hart
- Neurology (A.H.), Sheffield Children's Hospital, Sheffield, UK
| | - P Griffiths
- From the Departments of Neuroradiology (S.K., H.H., P.G., D.C.)
| | - D Connolly
- From the Departments of Neuroradiology (S.K., H.H., P.G., D.C.)
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13
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Mahdi Z, Marandyuk B, Desnous B, Liet AS, Chowdhury RA, Birca V, Décarie JC, Tremblay S, Lodygensky GA, Birca A, Pinchefsky EF, Dehaes M. Opioid analgesia and temperature regulation are associated with EEG background activity and MRI outcomes in neonates with mild-to-moderate hypoxic-ischemic encephalopathy undergoing therapeutic hypothermia. Eur J Paediatr Neurol 2022; 39:11-18. [PMID: 35598572 DOI: 10.1016/j.ejpn.2022.04.001] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/17/2021] [Revised: 02/23/2022] [Accepted: 04/09/2022] [Indexed: 11/17/2022]
Abstract
BACKGROUND Therapeutic hypothermia (TH) without sedation may lead to discomfort, which may be associated with adverse consequences in neonates with hypoxic-ischemic encephalopathy (HIE). The aim of this study was to assess the association between level of exposure to opioids and temperature, with electroencephalography (EEG) background activity post-TH and magnetic resonance imaging (MRI) brain injury in neonates with HIE. METHODS Thirty-one neonates with mild-to-moderate HIE who underwent TH were identified. MRIs were reviewed for presence of brain injury. Quantitative EEG background features including EEG discontinuity index and spectral power densities were calculated during rewarming and post-rewarming periods. Dose of opioids administered during TH and temperatures were collected from the medical charts. Multivariable linear and logistic regression analyses were conducted to assess the associations between cumulative dose of opioids and temperature with EEG background and MRI while adjusting for markers of HIE severity. RESULTS Higher opioid doses (β = -0.21, p = 0.02) and reduced skin temperature (β = 0.14, p < 0.01) were associated with lower EEG discontinuity index recorded post-TH. Higher opioid doses (β = 0.75, p = 0.01) and reduced skin temperature (β = -0.39, p = 0.02) were also associated with higher EEG Delta power post-TH. MRI brain injury was observed in 14 patients (45%). In adjusted regression analyses, higher opioid doses (OR = 0.00; 95%CI: 0-0.19; p = 0.01), reduced skin temperature (OR = 41.19; 95%CI: 2.27-747.86; p = 0.01) and reduced cooling device output temperature (OR = 1.91; 95%CI: 1.05-3.48; p = 0.04) showed an association with lower odds of brain injury. CONCLUSIONS Higher level of exposure to opioids and reduced skin temperature during TH in mild-to-moderate HIE were associated with improved EEG background activity post-TH. Moreover, higher exposure to opioids, reduced skin temperature and reduced device output temperature were associated with lower odds of brain injury on MRI.
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Affiliation(s)
- Zamzam Mahdi
- Research Centre, Sainte-Justine University Hospital Center, 3175 Chemin de la Cote-Sainte-Catherine, Montreal, QC, H3T 1C5, Canada
| | - Bohdana Marandyuk
- Research Centre, Sainte-Justine University Hospital Center, 3175 Chemin de la Cote-Sainte-Catherine, Montreal, QC, H3T 1C5, Canada
| | - Beatrice Desnous
- Research Centre, Sainte-Justine University Hospital Center, 3175 Chemin de la Cote-Sainte-Catherine, Montreal, QC, H3T 1C5, Canada; Division of Neurology, Department of Neuroscience, University of Montreal and Sainte-Justine University Hospital Center, 3175 Chemin de la Cote-Sainte-Catherine, Monteal, QC, H3T 1C5, Canada
| | - Anne-Sophie Liet
- Research Centre, Sainte-Justine University Hospital Center, 3175 Chemin de la Cote-Sainte-Catherine, Montreal, QC, H3T 1C5, Canada
| | - Rasheda Arman Chowdhury
- Research Centre, Sainte-Justine University Hospital Center, 3175 Chemin de la Cote-Sainte-Catherine, Montreal, QC, H3T 1C5, Canada; Institute of Biomedical Engineering, University of Montreal, 2900 Edouard Montpetit Blvd, Montreal, QC, H3T 1A4, Canada
| | - Veronica Birca
- Research Centre, Sainte-Justine University Hospital Center, 3175 Chemin de la Cote-Sainte-Catherine, Montreal, QC, H3T 1C5, Canada
| | - Jean-Claude Décarie
- Department of Radiology, Radio-oncology and Nuclear Medicine, University of Montreal, 2900 Edouard Montpetit Blvd, Montreal, QC, H3T 1A4, Canada
| | - Sophie Tremblay
- Research Centre, Sainte-Justine University Hospital Center, 3175 Chemin de la Cote-Sainte-Catherine, Montreal, QC, H3T 1C5, Canada; Division of Neonatology, Department of Pediatrics, University of Montreal and Sainte-Justine University Hospital Center, 3175 Chemin de la Cote-Sainte-Catherine, Montreal, QC, H3T 1C5, Canada
| | - Gregory Anton Lodygensky
- Research Centre, Sainte-Justine University Hospital Center, 3175 Chemin de la Cote-Sainte-Catherine, Montreal, QC, H3T 1C5, Canada; Division of Neonatology, Department of Pediatrics, University of Montreal and Sainte-Justine University Hospital Center, 3175 Chemin de la Cote-Sainte-Catherine, Montreal, QC, H3T 1C5, Canada
| | - Ala Birca
- Research Centre, Sainte-Justine University Hospital Center, 3175 Chemin de la Cote-Sainte-Catherine, Montreal, QC, H3T 1C5, Canada; Division of Neurology, Department of Neuroscience, University of Montreal and Sainte-Justine University Hospital Center, 3175 Chemin de la Cote-Sainte-Catherine, Monteal, QC, H3T 1C5, Canada
| | - Elana F Pinchefsky
- Research Centre, Sainte-Justine University Hospital Center, 3175 Chemin de la Cote-Sainte-Catherine, Montreal, QC, H3T 1C5, Canada; Division of Neurology, Department of Neuroscience, University of Montreal and Sainte-Justine University Hospital Center, 3175 Chemin de la Cote-Sainte-Catherine, Monteal, QC, H3T 1C5, Canada
| | - Mathieu Dehaes
- Research Centre, Sainte-Justine University Hospital Center, 3175 Chemin de la Cote-Sainte-Catherine, Montreal, QC, H3T 1C5, Canada; Institute of Biomedical Engineering, University of Montreal, 2900 Edouard Montpetit Blvd, Montreal, QC, H3T 1A4, Canada; Department of Radiology, Radio-oncology and Nuclear Medicine, University of Montreal, 2900 Edouard Montpetit Blvd, Montreal, QC, H3T 1A4, Canada.
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14
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Edwards AD, Rueckert D, Smith SM, Abo Seada S, Alansary A, Almalbis J, Allsop J, Andersson J, Arichi T, Arulkumaran S, Bastiani M, Batalle D, Baxter L, Bozek J, Braithwaite E, Brandon J, Carney O, Chew A, Christiaens D, Chung R, Colford K, Cordero-Grande L, Counsell SJ, Cullen H, Cupitt J, Curtis C, Davidson A, Deprez M, Dillon L, Dimitrakopoulou K, Dimitrova R, Duff E, Falconer S, Farahibozorg SR, Fitzgibbon SP, Gao J, Gaspar A, Harper N, Harrison SJ, Hughes EJ, Hutter J, Jenkinson M, Jbabdi S, Jones E, Karolis V, Kyriakopoulou V, Lenz G, Makropoulos A, Malik S, Mason L, Mortari F, Nosarti C, Nunes RG, O’Keeffe C, O’Muircheartaigh J, Patel H, Passerat-Palmbach J, Pietsch M, Price AN, Robinson EC, Rutherford MA, Schuh A, Sotiropoulos S, Steinweg J, Teixeira RPAG, Tenev T, Tournier JD, Tusor N, Uus A, Vecchiato K, Williams LZJ, Wright R, Wurie J, Hajnal JV. The Developing Human Connectome Project Neonatal Data Release. Front Neurosci 2022; 16:886772. [PMID: 35677357 PMCID: PMC9169090 DOI: 10.3389/fnins.2022.886772] [Citation(s) in RCA: 67] [Impact Index Per Article: 22.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/28/2022] [Accepted: 04/19/2022] [Indexed: 11/24/2022] Open
Abstract
The Developing Human Connectome Project has created a large open science resource which provides researchers with data for investigating typical and atypical brain development across the perinatal period. It has collected 1228 multimodal magnetic resonance imaging (MRI) brain datasets from 1173 fetal and/or neonatal participants, together with collateral demographic, clinical, family, neurocognitive and genomic data from 1173 participants, together with collateral demographic, clinical, family, neurocognitive and genomic data. All subjects were studied in utero and/or soon after birth on a single MRI scanner using specially developed scanning sequences which included novel motion-tolerant imaging methods. Imaging data are complemented by rich demographic, clinical, neurodevelopmental, and genomic information. The project is now releasing a large set of neonatal data; fetal data will be described and released separately. This release includes scans from 783 infants of whom: 583 were healthy infants born at term; as well as preterm infants; and infants at high risk of atypical neurocognitive development. Many infants were imaged more than once to provide longitudinal data, and the total number of datasets being released is 887. We now describe the dHCP image acquisition and processing protocols, summarize the available imaging and collateral data, and provide information on how the data can be accessed.
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Affiliation(s)
- A. David Edwards
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King’s College London, London, United Kingdom
- MRC Centre for Neurodevelopmental Disorders, King’s College London, London, United Kingdom
| | - Daniel Rueckert
- Biomedical Image Analysis Group, Department of Computing, Imperial College London, London, United Kingdom
- Institute for AI and Informatics in Medicine, Klinikum Rechts der Isar, Technical University of Munich, Munich, Germany
| | - Stephen M. Smith
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom
| | - Samy Abo Seada
- Biomedical Engineering Department, School of Biomedical Engineering & Imaging Sciences, King’s College London, London, United Kingdom
| | - Amir Alansary
- Biomedical Image Analysis Group, Department of Computing, Imperial College London, London, United Kingdom
| | - Jennifer Almalbis
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King’s College London, London, United Kingdom
| | - Joanna Allsop
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King’s College London, London, United Kingdom
| | - Jesper Andersson
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom
| | - Tomoki Arichi
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King’s College London, London, United Kingdom
- MRC Centre for Neurodevelopmental Disorders, King’s College London, London, United Kingdom
| | - Sophie Arulkumaran
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King’s College London, London, United Kingdom
| | - Matteo Bastiani
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom
- Sir Peter Mansfield Imaging Centre, Mental Health and Clinical Neurosciences, School of Medicine, University of Nottingham, Nottingham, United Kingdom
| | - Dafnis Batalle
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King’s College London, London, United Kingdom
- Department of Forensic and Neurodevelopmental Sciences, Institute of Psychiatry, Psychology & Neuroscience, King’s College London, London, United Kingdom
| | - Luke Baxter
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom
| | - Jelena Bozek
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom
- Faculty of Electrical Engineering and Computing, University of Zagreb, Zagreb, Croatia
| | - Eleanor Braithwaite
- Centre for Brain and Cognitive Development, Department of Psychological Sciences, Birkbeck, University of London, London, United Kingdom
| | - Jacqueline Brandon
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King’s College London, London, United Kingdom
| | - Olivia Carney
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King’s College London, London, United Kingdom
| | - Andrew Chew
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King’s College London, London, United Kingdom
| | - Daan Christiaens
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King’s College London, London, United Kingdom
- Department of Electrical Engineering, ESAT/PSI, KU Leuven, Leuven, Belgium
| | - Raymond Chung
- BioResource Centre, NIHR Biomedical Research Centre, South London and Maudsley NHS Trust, London, United Kingdom
| | - Kathleen Colford
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King’s College London, London, United Kingdom
| | - Lucilio Cordero-Grande
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King’s College London, London, United Kingdom
- Biomedical Image Technologies, ETSI Telecomunicación, Universidad Politécnica de Madrid and CIBER-BBN, Madrid, Spain
| | - Serena J. Counsell
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King’s College London, London, United Kingdom
| | - Harriet Cullen
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King’s College London, London, United Kingdom
- Department of Medical and Molecular Genetics, School of Basic and Medical Biosciences, King’s College London, London, United Kingdom
| | - John Cupitt
- Biomedical Image Analysis Group, Department of Computing, Imperial College London, London, United Kingdom
| | - Charles Curtis
- BioResource Centre, NIHR Biomedical Research Centre, South London and Maudsley NHS Trust, London, United Kingdom
| | - Alice Davidson
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King’s College London, London, United Kingdom
| | - Maria Deprez
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King’s College London, London, United Kingdom
- Biomedical Engineering Department, School of Biomedical Engineering & Imaging Sciences, King’s College London, London, United Kingdom
| | - Louise Dillon
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King’s College London, London, United Kingdom
| | - Konstantina Dimitrakopoulou
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King’s College London, London, United Kingdom
- Translational Bioinformatics Platform, NIHR Biomedical Research Centre, Guy’s and St. Thomas’ NHS Foundation Trust and King’s College London, London, United Kingdom
| | - Ralica Dimitrova
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King’s College London, London, United Kingdom
- Department of Forensic and Neurodevelopmental Sciences, Institute of Psychiatry, Psychology & Neuroscience, King’s College London, London, United Kingdom
| | - Eugene Duff
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom
| | - Shona Falconer
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King’s College London, London, United Kingdom
| | - Seyedeh-Rezvan Farahibozorg
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom
| | - Sean P. Fitzgibbon
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom
| | - Jianliang Gao
- Biomedical Image Analysis Group, Department of Computing, Imperial College London, London, United Kingdom
| | - Andreia Gaspar
- Institute for Systems and Robotics (ISR-Lisboa)/LaRSyS, Department of Bioengineering, Instituto Superior Técnico, Universidade de Lisboa, Lisbon, Portugal
| | - Nicholas Harper
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King’s College London, London, United Kingdom
| | - Sam J. Harrison
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom
| | - Emer J. Hughes
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King’s College London, London, United Kingdom
| | - Jana Hutter
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King’s College London, London, United Kingdom
- Biomedical Engineering Department, School of Biomedical Engineering & Imaging Sciences, King’s College London, London, United Kingdom
| | - Mark Jenkinson
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom
| | - Saad Jbabdi
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom
| | - Emily Jones
- Centre for Brain and Cognitive Development, Department of Psychological Sciences, Birkbeck, University of London, London, United Kingdom
| | - Vyacheslav Karolis
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King’s College London, London, United Kingdom
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom
| | - Vanessa Kyriakopoulou
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King’s College London, London, United Kingdom
| | - Gregor Lenz
- Biomedical Image Analysis Group, Department of Computing, Imperial College London, London, United Kingdom
| | - Antonios Makropoulos
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King’s College London, London, United Kingdom
- Biomedical Image Analysis Group, Department of Computing, Imperial College London, London, United Kingdom
| | - Shaihan Malik
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King’s College London, London, United Kingdom
- Biomedical Engineering Department, School of Biomedical Engineering & Imaging Sciences, King’s College London, London, United Kingdom
| | - Luke Mason
- Centre for Brain and Cognitive Development, Department of Psychological Sciences, Birkbeck, University of London, London, United Kingdom
| | - Filippo Mortari
- Biomedical Image Analysis Group, Department of Computing, Imperial College London, London, United Kingdom
| | - Chiara Nosarti
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King’s College London, London, United Kingdom
- Department of Child and Adolescent Psychiatry, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, United Kingdom
| | - Rita G. Nunes
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King’s College London, London, United Kingdom
- Institute for Systems and Robotics (ISR-Lisboa)/LaRSyS, Department of Bioengineering, Instituto Superior Técnico, Universidade de Lisboa, Lisbon, Portugal
| | - Camilla O’Keeffe
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King’s College London, London, United Kingdom
| | - Jonathan O’Muircheartaigh
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King’s College London, London, United Kingdom
- MRC Centre for Neurodevelopmental Disorders, King’s College London, London, United Kingdom
- Department of Forensic and Neurodevelopmental Sciences, Institute of Psychiatry, Psychology & Neuroscience, King’s College London, London, United Kingdom
| | - Hamel Patel
- BioResource Centre, NIHR Biomedical Research Centre, South London and Maudsley NHS Trust, London, United Kingdom
| | - Jonathan Passerat-Palmbach
- Biomedical Image Analysis Group, Department of Computing, Imperial College London, London, United Kingdom
| | - Maximillian Pietsch
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King’s College London, London, United Kingdom
- Department of Forensic and Neurodevelopmental Sciences, Institute of Psychiatry, Psychology & Neuroscience, King’s College London, London, United Kingdom
| | - Anthony N. Price
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King’s College London, London, United Kingdom
- Biomedical Engineering Department, School of Biomedical Engineering & Imaging Sciences, King’s College London, London, United Kingdom
| | - Emma C. Robinson
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King’s College London, London, United Kingdom
- Biomedical Engineering Department, School of Biomedical Engineering & Imaging Sciences, King’s College London, London, United Kingdom
| | - Mary A. Rutherford
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King’s College London, London, United Kingdom
| | - Andreas Schuh
- Biomedical Image Analysis Group, Department of Computing, Imperial College London, London, United Kingdom
| | - Stamatios Sotiropoulos
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom
- Sir Peter Mansfield Imaging Centre, Mental Health and Clinical Neurosciences, School of Medicine, University of Nottingham, Nottingham, United Kingdom
| | - Johannes Steinweg
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King’s College London, London, United Kingdom
| | - Rui Pedro Azeredo Gomes Teixeira
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King’s College London, London, United Kingdom
- Biomedical Engineering Department, School of Biomedical Engineering & Imaging Sciences, King’s College London, London, United Kingdom
| | - Tencho Tenev
- Biomedical Image Analysis Group, Department of Computing, Imperial College London, London, United Kingdom
| | - Jacques-Donald Tournier
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King’s College London, London, United Kingdom
- Biomedical Engineering Department, School of Biomedical Engineering & Imaging Sciences, King’s College London, London, United Kingdom
| | - Nora Tusor
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King’s College London, London, United Kingdom
| | - Alena Uus
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King’s College London, London, United Kingdom
- Biomedical Engineering Department, School of Biomedical Engineering & Imaging Sciences, King’s College London, London, United Kingdom
| | - Katy Vecchiato
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King’s College London, London, United Kingdom
| | - Logan Z. J. Williams
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King’s College London, London, United Kingdom
| | - Robert Wright
- Biomedical Image Analysis Group, Department of Computing, Imperial College London, London, United Kingdom
| | - Julia Wurie
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King’s College London, London, United Kingdom
| | - Joseph V. Hajnal
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King’s College London, London, United Kingdom
- Biomedical Engineering Department, School of Biomedical Engineering & Imaging Sciences, King’s College London, London, United Kingdom
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15
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Hendrix CL, Thomason ME. A survey of protocols from 54 infant and toddler neuroimaging research labs. Dev Cogn Neurosci 2022; 54:101060. [PMID: 35033971 PMCID: PMC8762357 DOI: 10.1016/j.dcn.2022.101060] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/13/2021] [Revised: 12/20/2021] [Accepted: 01/09/2022] [Indexed: 01/13/2023] Open
Abstract
Infant and toddler MRI enables unprecedented insight into the developing brain. However, consensus about optimal data collection practices is lacking, which slows growth of the field and impedes replication efforts. The goal of this study was to collect systematic data across a large number of infant/toddler research laboratories to better understand preferred practices. Survey data addressed MRI acquisition strategies, scan success rates, visit preparations, scanning protocols, accommodations for families, study design, and policies regarding incidental findings. Respondents had on average 8 years' experience in early life neuroimaging and represented more than fifty research laboratories. Areas of consensus across labs included higher success rates among newborns compared to older infants or toddlers, high rates of data loss across age groups, endorsement of multiple layers of hearing protection, and age-specific scan preparation and participant accommodation. Researchers remain divided on decisions in longitudinal study design and practices regarding incidental findings. This study summarizes practices honed over years of work by a large collection of scientists, which may serve as an important resource for those new to the field. The ability to reference data about best practices facilitates future harmonization, data sharing, and reproducibility, all of which advance this important frontier in developmental science.
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Affiliation(s)
- Cassandra L Hendrix
- Department of Child and Adolescent Psychiatry, New York University Medical Center, New York, NY, USA.
| | - Moriah E Thomason
- Department of Child and Adolescent Psychiatry, New York University Medical Center, New York, NY, USA; Department of Population Health, New York University Medical Center, New York, NY, USA; Neuroscience Institute, New York University Medical Center, New York, NY, USA
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16
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Korom M, Camacho MC, Filippi CA, Licandro R, Moore LA, Dufford A, Zöllei L, Graham AM, Spann M, Howell B, Shultz S, Scheinost D. Dear reviewers: Responses to common reviewer critiques about infant neuroimaging studies. Dev Cogn Neurosci 2022; 53:101055. [PMID: 34974250 PMCID: PMC8733260 DOI: 10.1016/j.dcn.2021.101055] [Citation(s) in RCA: 24] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/15/2021] [Revised: 11/28/2021] [Accepted: 12/26/2021] [Indexed: 01/07/2023] Open
Abstract
The field of adult neuroimaging relies on well-established principles in research design, imaging sequences, processing pipelines, as well as safety and data collection protocols. The field of infant magnetic resonance imaging, by comparison, is a young field with tremendous scientific potential but continuously evolving standards. The present article aims to initiate a constructive dialog between researchers who grapple with the challenges and inherent limitations of a nascent field and reviewers who evaluate their work. We address 20 questions that researchers commonly receive from research ethics boards, grant, and manuscript reviewers related to infant neuroimaging data collection, safety protocols, study planning, imaging sequences, decisions related to software and hardware, and data processing and sharing, while acknowledging both the accomplishments of the field and areas of much needed future advancements. This article reflects the cumulative knowledge of experts in the FIT'NG community and can act as a resource for both researchers and reviewers alike seeking a deeper understanding of the standards and tradeoffs involved in infant neuroimaging.
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Affiliation(s)
- Marta Korom
- Department of Psychological and Brain Sciences, University of Delaware, Newark, DE, USA.
| | - M Catalina Camacho
- Division of Biology and Biomedical Sciences (Neurosciences), Washington University School of Medicine, St. Louis, MO, USA.
| | - Courtney A Filippi
- Emotion and Development Branch, National Institute of Mental Health, Bethesda, MD, USA
| | - Roxane Licandro
- Institute of Visual Computing and Human-Centered Technology, Computer Vision Lab, TU Wien, Vienna, Austria; Department of Biomedical Imaging and Image-guided Therapy, Computational Imaging Research, Medical University of Vienna, Vienna, Austria
| | - Lucille A Moore
- Department of Psychiatry, Oregon Health and Science University, Portland, OR, USA
| | - Alexander Dufford
- Department of Radiology & Biomedical Imaging, Yale School of Medicine, New Haven, CT, USA
| | - Lilla Zöllei
- A.A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Boston, MA, USA
| | - Alice M Graham
- Department of Psychiatry, Oregon Health and Science University, Portland, OR, USA
| | - Marisa Spann
- Department of Psychiatry, Columbia University Irving Medical Center, New York, NY, USA
| | - Brittany Howell
- Fralin Biomedical Research Institute at Virginia Tech Carilion, Department of Human Development and Family Science, Virginia Polytechnic Institute and State University, Roanoke, VA, USA
| | - Sarah Shultz
- Division of Autism & Department of Pediatrics, Emory University School of Medicine, Atlanta, GA, USA; Marcus Autism Center, Children's Healthcare of Atlanta, Atlanta, GA, USA.
| | - Dustin Scheinost
- Department of Radiology & Biomedical Imaging, Yale School of Medicine, New Haven, CT, USA.
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17
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Efficient Claustrum Segmentation in T2-weighted Neonatal Brain MRI Using Transfer Learning from Adult Scans. Clin Neuroradiol 2022; 32:665-676. [PMID: 35072752 PMCID: PMC9424135 DOI: 10.1007/s00062-021-01137-8] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/11/2021] [Accepted: 12/25/2021] [Indexed: 11/03/2022]
Abstract
Abstract
Purpose
Intrauterine claustrum and subplate neuron development have been suggested to overlap. As premature birth typically impairs subplate neuron development, neonatal claustrum might indicate a specific prematurity impact; however, claustrum identification usually relies on expert knowledge due to its intricate structure. We established automated claustrum segmentation in newborns.
Methods
We applied a deep learning-based algorithm for segmenting the claustrum in 558 T2-weighted neonatal brain MRI of the developing Human Connectome Project (dHCP) with transfer learning from claustrum segmentation in T1-weighted scans of adults. The model was trained and evaluated on 30 manual bilateral claustrum annotations in neonates.
Results
With only 20 annotated scans, the model yielded median volumetric similarity, robust Hausdorff distance and Dice score of 95.9%, 1.12 mm and 80.0%, respectively, representing an excellent agreement between the automatic and manual segmentations. In comparison with interrater reliability, the model achieved significantly superior volumetric similarity (p = 0.047) and Dice score (p < 0.005) indicating stable high-quality performance. Furthermore, the effectiveness of the transfer learning technique was demonstrated in comparison with nontransfer learning. The model can achieve satisfactory segmentation with only 12 annotated scans. Finally, the model’s applicability was verified on 528 scans and revealed reliable segmentations in 97.4%.
Conclusion
The developed fast and accurate automated segmentation has great potential in large-scale study cohorts and to facilitate MRI-based connectome research of the neonatal claustrum. The easy to use models and codes are made publicly available.
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