Mingyang Li¹, Xinyi Xu¹, Zuozhen Cao¹, Ruike Chen¹, Ruoke Zhao¹, Zhiyong Zhao¹, and Dan Wu^1
1College of Biomedical Engineering & Instrument Science, Zhejiang University, Zhejiang, China

Keywords: Gray Matter, Multimodal, parcellation, morphometric similarity, atlas

In this work, we aimed to generate a comprehensive parcellation of the human neonatal cortex based on multi-modal MRI features. We collected the dataset from the developing human connectome project and estimated ten different MRI features to calculate the similarity between different locations in the neonatal cortex. We developed an automated algorithm based on gradient of the integrated similarity map to generate parcellations at different resolutions. We also provided a manual parcellation based on the multimodal similarity for higher anatomical interpretability. The present work may facilitate structural-functional connectome analysis in early brain development.

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MinJung Jang^1,2 and Zungho Zun^1
1Department of Radiology, Weill Cornell Medicine, New York, NY, United States, ²Department of Biomedical Engineering, Ulsan National Institute of Science and Techonology, Ulsan, Korea, Republic of

Keywords: Fetal, Fetus

Reliable fetal brain anatomical imaging is critical to identify structural brain abnormalities early in utero. Fetal brain imaging with increased spatial resolution may provide more details but is limited by a large acquisition matrix size with a long readout time. Here, we demonstrate high-resolution fetal brain imaging using a reduced field-of-view with outer volume suppression. The performance of outer volume suppression pulse was evaluated in simulations and phantom/in vivo experiments. High-resolution imaging with reduced field-of-view demonstrated improved image quality than conventional imaging without visible blurring or aliasing artifacts.

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Bossmat Yehuda^1,2, Aviad Rabinowich, MD^1,3,4, Dafi Surani¹, Yair Wexler⁵, Netanell avisdris^1,6, Ori Ben-Zvi¹, Bella Spector^1,6, Leo Joskowicz⁶, Liat Ben-Sira, MD^1,3, Elka Miller, MD⁷, and Dafna Ben Bashat^1,2,4
1Sagol Brain Institute, Tel Aviv Sourasky Medical Center, Tel Aviv, Israel, ²Sagol School of Neuroscience, Tel Aviv University, Tel Aviv, Israel, ³Department of Radiology, Tel Aviv Sourasky Medical Center, Tel Aviv, Israel, ⁴Sackler Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel, ⁵School of Neurobiology, Biochemistry and Biophysics, Faculty of Life Sciences, Tel Aviv University, Tel Aviv, Israel, ⁶School of Computer Science and Engineering, The Hebrew University of Jerusalem, Jerusalem, Israel, ⁷CHEO Medical Imaging, University of Ottawa, Ottawa, ON, Canada

Keywords: Fetal, Neuro, gyrification

Current clinical assessment of fetal brain gyrification is performed manually and subjectively.  Previous studies that suggested methods for quantitative assessment of fetal brain gyrification were based on 3D reconstruction. In this study we propose an automatic method for quantifying the gyrification from routinely acquired 2D clinical data. We calculate five different gyrification indices for both the right and left hemispheres. We present developmental curves of 134 control fetuses in a wide range of GA (18-37 weeks) and demonstrate differences between control fetuses and fetuses with malformation of cortical development: five with lissencephaly and 13 with polymicrogyria.

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Aviad Rabinowich^1,2,3, Netanell Avisdris^1,4, Ayala Zilberman^2,5, Sapir Lazar^2,6, Daphna Link-Sourani¹, Jacky Herzlich^2,7, Bella Specktor-Fadida⁴, Leo Joskowicz⁴, Gustavo Malinger^2,5, Liat Ben Sira^2,6, Liran Hiersch^2,5, and Dafna Ben Bashat^1,2,8
1Sagol Brain Institute, Tel Aviv Sourasky Medical Center, Tel Aviv, Israel, ²Sackler Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel, ³Department of Radiology, Tel Aviv Soursaky Medical Center, Tel Aviv, Israel, ⁴School of Computer Science and Engineering, The Hebrew University of Jerusalem, Jerusalem, Israel, ⁵Department of Obstetrics and Gynecology, Lis Hospital for Women, Tel Aviv Sourasky Medical Center, Tel Aviv, Israel, ⁶Department of Radiology, Tel Aviv Sourasky Medical Center, Tel Aviv, Israel, ⁷Neonatal Intensive Care Unit, Dana Dwek Children's Hospital, Tel Aviv Sourasky Medical Center, Tel Aviv, Israel, ⁸Sagol School of Neuroscience, Tel Aviv University, Tel Aviv, Israel

Keywords: Fetal, Fetus, Fetal growth restriction

Adipose tissue (AT, i.e., fat) deposition is reduced in undernourished growth-restricted fetuses (FGR) and may correlate with disease severity. Previous studies showed reduced AT using mainly linear sonographic measurements of the subcutaneous fat. We demonstrate the use of a two-point Dixon sequence for whole-body subcutaneous AT. The fat content of 64 fetuses (37 appropriate for gestation age [AGA], 18 FGR, and 9 small for gestational age) was measured using three adiposity parameters. We demonstrated third-trimester AT accretion in AGA fetuses and reduced AT in FGR. This study is the first to demonstrate whole-fetus subcutaneous AT changes in FGR.  

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Kathleen Elizabeth Colford¹, Daniel Cromb¹, Zoe Hesketh¹, Tom Finck^1,2, Ayse Ceren-Tanritanir^1,3, Serena Counsell¹, and Mary Rutherford^1,4
1Centre for the Developing Brain, School of Biomedical Engineering & Imaging Sciences, Kings College London, London, United Kingdom, ²Department of Diagnostic and Interventional Neuroradiology, Klinikum rechts der Isar der Technischen Universität München, Munich, Germany, ³Guys and St. Thomas’s NHS Foundation Trust, London, United Kingdom, ⁴MRC Centre for Neurodevelopmental Disorders, King’s College London, London, United Kingdom

Keywords: Fetal, Data Analysis, Maternal BMI, Signal to Noise Ratio

We assessed  SNR (signal-to-noise-ratio) against elevated maternal BMI in fetal brain/body MRI imaging to examine if SNR decreases both objectively/subjectively, and if MRI could be an alternative imaging modality in prenatal care. Spearman’s Correlation-Rank coefficient was used to identify relationships between SNR measurements in ROI’s and maternal BMI. There’s a negative downward trend between maternal BMI and SNR seen for all fetal ROIs (particularly in regions more susceptible to SNR); subjective assessment didn’t identify any association between BMI and image quality. Our results suggest that MRI is a viable alternative to ultrasound in pregnant women with elevated BMI.

Cai Xianyun¹, Chen Xin¹, Jinxia Zhu², and Guangbin Wang^1
1Shandong Provincial Hospital Affiliated to Shandong First Medical University, jinan, China, ²MR Collaboration, Siemens Healthineers Ltd, Beijing, China. Email: jinxia.zhu@siemens-healthineers.com, beijing, China

Keywords: Fetal, Normal development

Imaging the anatomy of the spine and its relevant pathology is clinically important for the early identification of spinal malformations and anomalous osseous development. our study applied MRI-based “black-bone” sequence to elucidate the growth dynamics of vertebrae ossification center in utero fetuses in second-third trimester. We found that the fetal vertebrae were correlated with gestational age and follow a certain formula, providing the existing literature with completely novel quantitative data.

Xin Zhang¹, Fan Wu¹, Zhaoji Chen¹, Yuchao Li¹, Zhenqing Liu¹, Chenxin Xie¹, and Hongsheng Liu^1
1Department of Diagnostic Radiology, Guangzhou Women and Children's Medical Center, Guangzhou Medical University，Guangdong Provincial Clinical Research Center for Child Health, 510623, China, Guangzhou, China

Keywords: Fetal, Brain, Fetal MRI; Isolated ventriculomegaly

The lateral ventricle is closely related to the occipital lobe anatomically. We found changes in cortical volume and white matter volume in isolated fetuses ventriculomegaly. This study will address whether occipital and occipital gyrus volumes differ in IVM and investigate the developmental pattern of the occipital lobe with increasing gestational age investigate. This study will help to provide the research basis for the study the neurodevelopment in IVM fetuses.

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Tommaso Ciceri^1,2, Letizia Squarcina³, Adele Ferro⁴, Florian Montano⁵, Alessandra Bertoldo^2,6, Nicola Persico⁷, Simona Boito⁷, Fabio Maria Triulzi^3,8, Giorgio Conte⁸, Paolo Brambilla^3,4, and Denis Peruzzo^5
1NeuroImaging, IRCCS Eugenio Medea, Bosisio Parini (LC), Italy, ²Department of Information Engineering, University of Padua, Padova, Italy, ³Pathophysiology and Transplantation, University of Milan, Milano, Italy, ⁴Neurosciences and Mental Health, Fondazione IRCCS Ca’ Granda Ospedale Maggiore Policlinico, Milano, Italy, ⁵NeuroImaging Lab, IRCCS Eugenio Medea, Bosisio Parini (LC), Italy, ⁶Neuroscience Center, University of Padua, Padova, Italy, ⁷Department of Woman, Child and Newborn, Fondazione IRCCS Ca’ Granda Ospedale Maggiore Policlinico, Milano, Italy, ⁸Services and Preventive Medicine, Fondazione IRCCS Ca’ Granda Ospedale Maggiore Policlinico, Milano, Italy

Keywords: Fetal, Brain, Neurodevelopment, Biometry, Image Reconstruction

In this study, we characterized the geometric reliability of the Super-Resolution (SR) images reconstructed via NiftyMIC and MIALSRTK toolkits over a common clinical fetal MR dataset (20-21 weeks of gestation). We compare 15 biometric measures derived from the acquired 2D images with those derived from the SR brain volumes. Furthermore, we examined two different acquisition sequences (TSE Vs. b-FFE) to evaluate which of them lead to more reliable measures and high-resolution reconstructions. Our findings strengthen the adoption of SR toolkits for fetal brain reconstructions to perform biometry evaluations, suggesting to use TSE sequences.

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Shaihan J Malik^1,2,3, Raphael Tomi-Tricot^2,4, Philippa Bridgen^2,5, Anthony N Price^3,5, Megan Quirke⁵, Daniel V Cromb³, Paul Cawley^3,5, Enrico De Vita^2,3, Jonathan O’Muircheartaigh^3,6, Serena J Counsell³, Sharon Giles^2,5, Mary Rutherford³, A. David Edwards^3,5,6, Joseph V Hajnal^1,2,3, and Tomoki Arichi^3,5,6
1Biomedical Engineering Department, School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom, ²London Collaborative Ultrahigh field System (LoCUS), King's College London, London, United Kingdom, ³Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom, ⁴MR Research Collaborations, Siemens Healthcare Limited, Frimley, United Kingdom, ⁵Guy's and St. Thomas' NHS Foundation Trust, London, United Kingdom, ⁶Centre for Neurodevelopmental Disorders, King's College London, London, United Kingdom

Keywords: Neonatal, Relaxometry

T₁ and T₂ measurements were made in 8 neonates (median age 42+1 weeks) scanned on a 7 Tesla MRI system, using inversion recovery and spin echo methods respectively. The aim of this study is to help to establish expected ranges, to prepare for systematic relaxometry studies, and to identify optimal operating points for imaging neonates at ultra-high field. Region of interest measurements show strong age dependence of T₁, and some variation in T₂ (particularly in frontal white matter). The measured T₁ times are longer than in adults at 7T, and also longer than in neonates imaged on lower field systems.

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Stephanie A Giza¹, Simran Sethi¹, Genevieve Eastabrook^2,3, Barbra de Vrijer^2,3, and Charles A McKenzie^1,3
1Medical Biophysics, University of Western Ontario, London, ON, Canada, ²Obstetrics and Gynaecology, University of Western Ontario, London, ON, Canada, ³Maternal, Fetal and Newborn Health, Children's Health Research Institute, London, ON, Canada

Keywords: Fetal, Fat

Fat fractions in fetal adipose tissue vary across gestation and across different regions of the body, and can be measured by chemical shift encoded MRI which provides accurate measurements of fat fraction above 10%. The assessment of lower fat fractions can be improved by increasing flip angle, but this introduces T1 bias. We demonstrated that this T1 bias can be corrected using fetal adipose tissue water and lipid T1 values, preserving accuracy of the fat fraction measurement while simultaneously improving its precision in fetal adipose tissue.

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Emily Peacock¹, Paponrad Tontivuthikul², Joanna Chappell¹, Nada Mufti^1,2, Janina Schellenberg², Michael Ebner¹, Sebastien Ourselin^1,3, Anna David^2,4,5, Rosalind Aughwane², and Andrew Melbourne^1,2,3
1School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom, ²Elizabeth Garrett Anderson Institute for Women's Health, University College London, London, United Kingdom, ³Department of Medical Physics and Biomedical Engineering, University College London, London, United Kingdom, ⁴University Hospital KU Leuven, Leuven, Belgium, ⁵5NIHR University College London Hospitals Biomedical Research Centre, London, United Kingdom

Keywords: Image Reconstruction, Brain, Fetus, Machine Learning

State-of-the-art machine learning algorithms were applied to create MRI 3D super-resolution reconstructions of fetal brains to analyse brain development in fetal growth restriction. Reconstructions were segmented into the grey matter, white matter, deep grey matter, cerebellum and brainstem, and volumetric and cortical surface data was extracted. We found that the five brain regions segmented were significantly smaller in the FGR cohort than in controls, and that this effect was linked to feto-placental blood oxygen saturation. FGR fetuses showed evidence of brain sparing from MRI and ultrasound measurements and preservation of tissue relationships, such as the grey:white matter ratio.

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Xiaoxu Na¹, Aline Andres^2,3,4, Charles M. Glasier¹, Jayne Bellando², Haitao Chen^5,6,7, Wei Gao^5,6, and Xiawei Ou^1,2,3,4
1Radiology, University of Arkansas for Medical Sciences, Little Rock, AR, United States, ²Pediatrics, University of Arkansas for Medical Sciences, Little Rock, AR, United States, ³Arkansas Children’s Nutrition Center, Little Rock, AR, United States, ⁴Arkansas Children’s Research Institute, Little Rock, AR, United States, ⁵Biomedical Sciences and Imaging, Cedars Sinai Medical Center, Los Angeles, CA, United States, ⁶Biomedical Imaging Research Institute, Cedars Sinai Medical Center, Los Angeles, CA, United States, ⁷Bioengineering, University of California at Los Angeles, Los Angeles, CA, United States

Keywords: Neonatal, fMRI (resting state)

This study reports associations between maternal depression symptoms during pregnancy and neonatal brain functional connectivity. The mothers self-rated their depression symptoms during pregnancy using Beck Depression Inventory-II, and their newborns underwent a brain MRI examination including structural 3D T1-weighted images and resting-state fMRI for functional connectivity measurements. Most participants scored in the minimal range for depressive symptoms. Significant negative associations between maternal depression symptoms at ~36 weeks of pregnancy and newborn functional connectivity were observed in multiple brain regions/networks, indicating a negative influence of antenatal depression symptoms on neonatal brain functional development even in women with low symptoms of depression.

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Tomoki Arichi^1,2,3, Philippa Bridgen^2,4, Raphael Tomi-Tricot^1,4,5, Daniel Cromb¹, Paul Cawley^1,2, Megan Quirke^1,2, Anthony N Price^1,2, Enrico De Vita^1,4, Jonathan O'Muircheartaigh^1,3, Serena J Counsell¹, A David Edwards^1,3, Joseph V Hajnal^1,4, and Shaihan Malik^1,4
1Department of Perinatal Imaging, Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom, ²Guy's and St Thomas' NHS Foundation Trust, London, United Kingdom, ³MRC Centre for Neurodevelopmental Disorders, King's College London, London, United Kingdom, ⁴London Collaborative Ultra high field System (LoCUS), Kings College London, London, United Kingdom, ⁵MR Research Collaborations, Siemens Healthcare Limited, Frimley, United Kingdom

Keywords: Neonatal, fMRI (resting state)

Acquiring BOLD fMRI data at ultra-high field offers marked gains in sensitivity and spatial specificity including within cortical layers and distinct subcortical nuclei. We describe the first pilot data demonstrating feasibility of characterizing resting state networks in the neonatal brain using a 7 Tesla system. In 3 neonates imaged at full term, we show that in addition to the canonical networks seen at standard field strengths, ultra-high field fMRI enables network delineation with higher spatial specificity, including better localization to the cortex and with definition of individual networks corresponding to distinct anatomical regions and tissues.    

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Caroline Magnain¹, Robin Haynes², Jean Augustinack¹, Hannah Kinney², and Lilla Zollei^1
1MGH, Boston, MA, United States, ²BCH, Boston, MA, United States

Keywords: Neonatal, Multimodal, postmortem, brain development

The core lesion of SIDS is a set of medullar nuclei with abnormalities correlated with sudden infant death syndrome (SIDS). We performed ex vivo whole brain and brainstem MRI, optical coherence tomography and histology at an unprecedented spatial resolution on a postmortem infant brain to investigate the structural properties of the caudal medulla. In our image processing pipeline, we register all image modalities into the same coordinate system along with a rich set of segmentation labels. Such multimodal construction helps us validate imaging findings at various resolution levels and will serve as prior information in automated segmentation solutions.

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Enrico De Vita^1,2,3, Maria Yanez-Lopez⁴, Anthony N Price^2,5, Philippa Bridgen^3,6, Shaihan Malik^2,3, Megan Quirke^2,6,7, Raphael Tomi-Tricot^3,7,8, Mary A Rutherford², Joseph V Hajnal^2,3,7, and Tomoki Arichi^2,6,9
1MR Physics group, Radiology Department, Great Ormond Street Hospital, London, United Kingdom, ²Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King’s College London, London, United Kingdom, ³London Collaborative Ultra high field System (LoCUS), King’s College London, London, United Kingdom, ⁴MR Physics Group, Department of Medical Physics and Clinical Engineering, Swansea Bay University Health Board, Swansea, United Kingdom, ⁵MR Physics, Guys and St Thomas’ NHS Foundation Trust, London, United Kingdom, ⁶Guys and St Thomas’ NHS Foundation Trust, London, United Kingdom, ⁷Biomedical Engineering Department, School of Biomedical Engineering and Imaging Sciences, King’s College London, London, United Kingdom, ⁸MR Research Collaborations, Siemens Healthcare Limited, Frimley, United Kingdom, ⁹MRC Centre for Neurodevelopmental Disorders, King’s College London, London, United Kingdom

Keywords: Neonatal, Spectroscopy, 7T, ultra-high field

We present 1H-MRS results from a pilot cohort of newborn infants, acquired on a 7T system. Whilst a customised approach is required for patient preparation and sequence calibrations, our preliminary data points to highly improved sensitivity and data quality at ultra-high field compared to typical spectra from adults at the same field or newborn infants at lower field strengths. We also report initial estimates of T1 and T2 for the main metabolites in the neonatal brain at 7T.

Yihan Wu¹, Lana Vasung¹, Davood Karimi¹, and Ali Gholipour^1
1Harvard Medical School & Boston Children's Hospital, Boston, MA, United States

Keywords: Neonatal, Data Analysis

This study analyzed the development of brain's structural connectivity during the perinatal period using the diffusion MRI data of 263 subjects from the dHCP dataset. We used anatomically constrained probabilistic tractography to reconstruct structural connectomes. We computed connectivity metrics to assess network integration and segregation and tested for the effects of postmenstrual age (PMA), premature birth, and gender. Results showed increasing network integration and segregation with PMA in the range 29 to 45 weeks. Premature birth and male gender were associated with significantly lower rates of increase in global efficiency.

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Alexandra De Silvestro^1,2,3, Giancarlo Natalucci⁴, Maria Feldmann^3,5, Cornelia Hagmann^3,6, Thi Dao Nguyen⁴, Seline Coraj⁴, Beatrice Latal^3,5, Walter Knirsch^1,3, and Ruth Tuura^2,3
1Pediatric Cardiology, Pediatric Heart Center, Department of Surgery, University Children's Hospital Zurich, Zurich, Switzerland, ²Center for MR-Research, University Children's Hospital Zurich, Zurich, Switzerland, ³Children's Research Center, University Children's Hospital Zurich, Zurich, Switzerland, ⁴Department of Neonatology, University Hospital Zurich, Zurich, Switzerland, ⁵Child Development Center, University Children's Hospital Zurich, Zurich, Switzerland, ⁶Department of Neonatology and Pediatric Intensive Care, University Children's Hospital Zurich, Zurich, Switzerland

Keywords: Neonatal, Arterial spin labelling

We aimed to compare cerebral perfusion in neonates with severe congenital heart disease (CHD) and healthy controls using arterial spin labeling magnetic resonance imaging. Sixty-seven scans of CHD patients and 23 scans of controls were analyzed (postmenstrual age at scan 41.6±1.8 and 41.9±2.1 weeks, respectively). As in healthy neonates, cerebral perfusion in CHD patients increased with age. Whereas age-adjusted whole brain perfusion was similar to controls, redistribution of regional perfusion was detected in CHD patients. Furthermore, the presence of a systemic-to-pulmonary shunt was associated with cerebral hypoperfusion. Effects of cerebral perfusion alterations on neurodevelopment need to be further assessed.

Yihan Wu¹, Ruolin Li¹, Yifan Shuai¹, Zhiyong Zhao¹, and Dan Wu^1
1Key Laboratory for Biomedical Engineering of Ministry of Education, Department of Biomedical Engineering, College of Biomedical Engineering & Instrument Science, Zhejiang University, Hangzhou, China

Keywords: Neonatal, fMRI (resting state)

The present study aimed to explore functional connectivity changes with anatomical distance in neonatal brain by using the second dHCP resting-state fMRI dataset. We calculated distance-dependent functional connectivity density (FCD) maps to test for the effect of age, preterm-birth, and gender. Results found that the FCD in neonatal brains showed distance-dependent changes with PMA, in which the short- and long-range FCD changes were associated with maternal environment and postnatal experience, respectively. Moreover, the preterm- and term-born infants showed different patterns in short- and long-range FCD. These findings suggested distance-dependent changes in functional connectivity in neonatal brain during early development.

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Yael Zaffrani-Reznikov¹, Onur Afacan², Sila Kurugol², Simon Warfield², and Moti Freiman^1
1Technion, Haifa, Israel, ²Boston Children's Hospital, Boston, MA, United States

Keywords: Fetal, Diffusion/other diffusion imaging techniques, fetal imaging

Quantitative analysis of fetal lung Diffusion Weighted MRI (DWI) data shows potential in providing quantitative imaging biomarkers for assessing fetal lung maturation. However, fetal motion during the acquisition impairs the accuracy and robustness of the analysis. We introduce qDWI-morph, an unsupervised deep-neural network architecture for motion correction and quantitative DWI (qDWI) analysis. We simultaneously estimate the qDWI parameters and the motion model by minimizing a bio-physically-informed loss. The qDWI-morph achieved an improved correlation between qDWI parameters in the fetal lung with the gestational age (R-squared=0.32) over baseline analysis without motion correction (R-squared=0.13) and our network with registration loss solely (R-squared=0.28).

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Ruoke Zhao¹, Xinyi Xu¹, Zhiyong Zhao¹, Mingyang Li¹, Ruike Chen¹, Yao Shen¹, Cong Sun², Guangbin Wang³, and Dan Wu^1
1College of Biomedical Engineering & Instrument Science, Zhejiang University, Hangzhou, China, ²Department of Radiology, Beijing Hospital, National Center of Gerontology, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, Beijing, China, ³Department of Radiology, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, China

Keywords: Fetal, Brain Connectivity

The fetal brain morphological network is important for us to understand early brain organization but has not characterized previously. In the study, we constructed fetal individual morphometric similarity networks using multiple cortical features based on in utero MRI data. The results demonstrated the decline of morphological symmetry between hemispheres during development. The morphological similarity between the limbic regions and other regions significantly increased while the similarity between the parieto-occipital regions and other regions significantly decreased. Small world organizations appeared as early as 22 weeks, and the network topology developed towards more integrated and less segregated during fetal period.