Haotian Li¹, Guohui Yan², Wanrong Luo¹, Tingting Liu¹, Yan Wang¹, Yi Zhang¹, Li Zhao³, Catherine Limperopoulos³, Yu Zou², 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, Zhejiang, China, ²Department of Radiology, Women's Hospital,School of Medicine,Zhejiang University, Hangzhou, Zhejiang, China, ³Diagnostic Imaging and Radiology, Children's National Medical Center, Washington, DC, WA, United States

Fetal brain MRI has become an important tool for in-utero assessment of brain development and disorders. Here we proposed an automated pipeline with fetal brain segmentation, super-resolution reconstruction, and fetal brain atlasing to quantitatively map in-utero fetal brain development in a Chinese population. We designed a U-net CNN implemented for automatic fetal brain segmentation, which showed superior segmentation accuracy compared with conventional methods. We then generated a Chinese fetal brain atlas, using an iterative linear and nonlinear registration method. Based on the 4D spatiotemporal atlas, we characterized the three-dimensional morphological evolution of the fetal brain between 23-36 weeks of gestation.

Maximilian Pietsch^1,2, Daan Christiaens^2,3, Jana Hutter^1,2, Lucilio Cordero-Grande^1,2, Anthony N. Price^1,2, Emer Hughes², David Edwards², Joseph V. Hajnal^1,2, Serena J. Counsell², and J-Donald Tournier^1,2
1Biomedical Engineering Department, School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom, ²Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom, ³Department of Electrical Engineering (ESAT/PSI), KU Leuven, Leuven, Belgium

Mapping tissue maturation in the fetal brain with diffusion MRI requires modelling transient processes in early brain development. In this work, we extend a data-driven multi-component framework introduced for modelling neonatal brain development to fetal data of the developing Human Connectome Project (dHCP). To this end, we build weekly templates ranging from 23 to 37 weeks gestational age that consist of one fluid and two orientationally-resolved tissue components. The orientation-resolved components exhibit marked spatial patterns and temporal trajectories, and demonstrate pronounced microstructural changes with gestational age.

Paolo Bosco¹, Simona Fiori², Rosa Pasquariello¹, Elena Scaffei^2,3, Michela Tosetti¹, and Laura Biagi^1
1Laboratory of Medical Physics and Magnetic Resonance, IRCCS Stella Maris Foundation, Pisa, Italy, ²Department of Developmental Neuroscience, IRCCS Stella Maris Foundation, Pisa, Italy, ³Department of Clinical and Experimental Medicine, University of Pisa, Pisa, Italy

Natural sleep brain MRI (nsMRI) up to 6 months of life to support early diagnosis in term and preterm infants at high risk for cerebral palsy and other developmental disorders is still far from clinical practice, due to unproven feasibility and quality. We extracted some measures of quality (signal to noise ratio, contrast to noise ratio in a cohort of 23 and 53 infants who underwent sedation or natural sleep brain MR respectively. Most of the quality measures extracted across different MR modalities did not differ between nsMRI and sedation MRI (sMRI) suggesting the feasibility of nsMRI at younger ages.

Gian Franco Piredda^1,2,3, Tom Hilbert^1,2,3, Baptiste Morel^4,5, Clovis Tauber⁴, Jean Philippe Cottier⁴, Lars Lauer⁶, Jean-Philippe Thiran^2,3, Bénédicte Maréchal^1,2,3, and Tobias Kober^1,2,3
1Advanced Clinical Imaging Technology, Siemens Healthcare AG, Lausanne, Switzerland, ²Department of Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland, ³LTS5, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland, ⁴UMR 1253, iBrain, Université de Tours, Inserm, Tours, France, ⁵Pediatric Radiology Department, Clocheville Hospital, CHRU of Tours, Tours, France, ⁶SHS DI MR SIP, Siemens Healthcare GmbH, Erlangen, Germany

The sensitivity of T₁ mapping towards brain maturation during the first years of life was shown in previous studies. This work investigates whether this sensitivity is high enough that age of young subjects can be directly estimate from T₁ relaxometry, which in turn enables to determine the developmental stage of the subject’s brain. A random forest regression was employed to estimate subjects’ age based on median T₁ values of different brain regions. Good correlation (r=0.95) was found between actual and predicted ages, and proof-of-concept results in a patient showed the potential of the proposed framework to detect developmental delays.

James Timothy Grist¹, Stephanie Timothy Withey¹, Lesley MacPherson², Adam Oates³, Stephen Timothy Powell¹, Jan Novak⁴, Laurence Abernethy⁵, Barry Pizer⁶, Ricahrd Grundy⁷, Simon Bailey⁸, Dipayan Mitra⁸, Theodoros N Arvantis⁹, Dorothee P. Auer⁷, and Andrew C Peet^1
1University of Birmingham, Birmingham, United Kingdom, ²Birmingham Women's and CHildren's NHS foundation trust, Birmingham, United Kingdom, ³Birmingham Women's and Children's NHS foundation trust, Birmingham, United Kingdom, ⁴Aston University, Birmingham, United Kingdom, ⁵Alder Hey Children's NHS foundation trust, Liverpool, United Kingdom, ⁶Institute of Translation Medicine, University of Liverpool, Liverpool, United Kingdom, ⁷University of Nottingham, Nottingham, United Kingdom, ⁸Royal Victoria Infirmary, Newcastle, United Kingdom, ⁹University of Warwick, Warwick, United Kingdom

This study focuses on the combination of diffusion and perfusion imaging with advanced machine learning to predict survival in a cohort of paediatric brain tumours. Results show two novel subgroups with significantly different survival. These results will aid in clinical decision making and therapeutic studies. 

Matteo Maspero^1,2, Laura G Bentvelzen^1,2, Mark H F Savenije^1,2, Enrica Seravalli¹, Geert O R Janssens^1,3, Cornelis A T van den Berg^1,2, and Marielle E P Philippens^1
1Radiotherapy, UMC Utrecht, Utrecht, Netherlands, ²Computational imaging group for MR diagnostic & therapy, UMC Utrecht, Utrecht, Netherlands, ³Paediatric Oncology, Princess Maxima Center, Utrecht, Netherlands

The feasibility of radiotherapy dose calculations for brain tumours from MRI acquired with a heterogeneous set of acquisition protocols on paediatric patients was investigated using a combination of networks trained on orthogonal planes to estimate the uncertainty of the generated sCT.

Apurva Shah¹, Apoorva Safai¹, Veeramani Preethish Kumar², Atchayaram Nalini², Jitender Saini³, and Madhura Ingalhalikar^1
1Symbiosis Center for Medical Image Analysis, Symbiosis International University, Pune, India, ²Department of Neurology, National Institute of Mental Health and Neurosciences, Bengaluru, India, ³Department of Radiology, National Institute of Mental Health and Neurosciences, Bengaluru, India

Duchenne Muscular Dystrophy (DMD) is a genetic neuromuscular disorder, characterized by muscle weakness and cognitive deficits due to mutation in DMD gene. Dp140+ and Dp140- are DMD subtypes derived based on promoter site of isoform Dp140 in DMD gene. Our work investigated the structural connectivity in DMD and its sub-types and demonstrated widespread and global reduction in connectivity across whole brain in DMD compared to controls. Higher dysconnectivity was observed in Dp140- subtype especially in cerebellar and frontal regions compared to Dp140+ implying that the promotor site of Dp140 isoform plays a crucial role in terms of impaired information processing.

Jitender Saini¹, Veeramani Preethish Kumar², Apurva Shah³, Manoj Kumar⁴, Madhura Ingalhalikar⁵, and Nalini Atchayaram ^2
1Nueroimaging and Interventional Radiology, National Institute of Mental Health and, Bangalore, India, ²Neurology, National Institute of Mental Health and, Bangalore, India, ³3Symbiosis Centre for Medical Image Analysis, Symbiosis International University, Pune, India, ⁴Neuroimaging and Interventional Radiology, National Institute of Mental Health and, Bangalore, India, ⁵Symbiosis Centre for Medical Image Analysis, Symbiosis International University, Pune, India

Duchenne muscular dystrophy (DMD), a genetically inherited X-linked neuromuscular disorder characterised by progressive muscle weakness and significant non-motor manifestations like poor IQ, and neuropsychiatric illnesses. In this study, we evaluate white matter (WM) abnormalities in DMD patients using diffusion tensor imaging (DTI). We observed widespread WM changes in DMD patients and the presence of distal mutation was associated with poor clinical and neuropsychological profile with severe and spatially more WM abnormalities.  

Alister J Bates¹, Nara S Higano¹, Andreas Schuh², Andrew Hahn³, Katie J Carey³, Sean B Fain³, Paul Kingma⁴, and Jason C Woods^1
1Center for Pulmonary Imaging, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, United States, ²Biomedical Image Analysis Group, Imperial College London, London, United Kingdom, ³Biomedical Engineering, University of Wisconsin-Madison, Madison, WI, United States, ⁴Bronchopulmonary Dysplasia (BPD) Center, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, United States

Neonatal lung disease is often related to premature birth or congenital abnormalities. Structural MRI has been performed in these patients but does not indicate which lung regions perform gas exchange. Registered respiratory gated ultra-short echo-time proton MRI can produce lung ventilation maps in neonates throughout the respiratory cycle. This technique showed clear differences between a control subject and 2 patients with lung disease in terms of ventilation efficiency (inhaled air per milliliter of lung), spatial and temporal ventilation homogeneity. Further differences were shown post-surgical intervention, demonstrating the method and as a potential means to assess treatment efficacy.

Konstantinos G. Zeimpekis¹, Florian Wiesinger², Gaspar Delso², Julia Geiger³, and Christian Kellenberger^4
1Nuclear Medicine, University Hospital Zurich, Zurich, Switzerland, ²GE Healthcare, Chicago, IL, United States, ³University Children's Hospital Zurich, Zurich, Switzerland, ⁴Radiology, University Children's Hospital Zurich, Zurich, Switzerland

3D ultrashort echo-time Cones is tested against PROPELLER for lung density detection in paediatric cases on two cohorts: patients with morphologically normal lungs and patients with Cystic Fibrosis. Cones seems to be able to detect lung density based on lung-to-background signal intensities ratio (LBR) while PROPELLER fails to show any correlation. Cones is able to show the lung anteroposterior gravity gradient as well. There was no difference between Cones LBR of controls and CF while pixel-intensity histogram analysis of Cones slices seem to differentiate pathological from normal lung. Qualitatively, lung constrast decreases with increasing age.

Xiaodong Zhong¹, Houchun H Hu², Tess Armstrong^3,4, Marcel D Nickel⁵, Stephan A.R. Kannengiesser⁵, Vibhas Deshpande⁶, Berthold Kiefer⁵, and Holden H Wu^3,4
1MR R&D Collaborations, Siemens Healthcare, Los Angeles, CA, United States, ²Department of Radiology, Nationwide Children's Hospital, Columbus, OH, United States, ³Department of Radiological Sciences, University of California Los Angeles, Los Angeles, CA, United States, ⁴Department of Physics and Biology in Medicine, University of California Los Angeles, Los Angeles, CA, United States, ⁵MR Application Predevelopment, Siemens Healthcare GmbH, Erlangen, Germany, ⁶MR R&D Collaborations, Siemens Healthcare, Austin, TX, United States

Liver fat and iron quantification is of growing interest. However, it is challenging and sometimes impossible to perform breath-hold MRI acquisitions in children. Using a breath-hold 3D Cartesian method as reference, a self-gating free-breathing 3D stack-of-radial liver R₂^* quantification technique was evaluated. Results showed that the free-breathing stack-of-radial technique accurately quantified fat even without self-gating, while free-breathing R₂^* quantification had biases caused by respiratory motion and self-gating was necessary for accurate R₂^* quantification in pediatric subjects. This technique has potential for accurate and efficient free-breathing quantification of both liver fat and iron in pediatric patients.

Sevgi Gokce Kafali^1,2, Tess Armstrong¹, Shu-Fu Shih^1,2, Joseph L Holtrop³, Robert S Venick⁴, Shahnaz Ghahremani¹, Bradley D. Bolster Jr⁵, Claudia M. Hillenbrand³, Kara L. Calkins⁴, and Holden H. Wu^1,2
1Radiological Sciences, University of California, Los Angeles, Los Angeles, CA, United States, ²Bioengineering, University of California, Los Angeles, Los Angeles, CA, United States, ³Diagnostic Imaging, St. Jude Children’s Research Hospital, Memphis, TN, United States, ⁴Pediatrics, University of California, Los Angeles, Los Angeles, CA, United States, ⁵Siemens Medical Solutions, Salt Lake City, UT, United States

Hepatic stiffness measured by magnetic resonance elastography (MRE) is a biomarker that correlates with histopathological staging of liver fibrosis. Conventional Cartesian gradient-echo MRE requires breath-holding (BH), which may be inconsistent and challenging for children. Free-breathing (FB) MRE based on radial acquisition is a promising solution to this problem. In this study, we investigated the agreement in hepatic stiffness values from BH-MRE and FB-MRE, as well as repeatability, in healthy children and pediatric patients at 3T. Bland-Altman analysis showed a high level of agreement between BH-MRE and FB-MRE, and repeatability analysis showed similar performance for BH-MRE and FB-MRE. 

Hayfa Sharif^1,2, Nichola Abrehart¹, Caroline Hoad^1,3, Kathryn Murray^1,3, Alan Perkins^1,4, Penny Gowland³, Robin Spiller¹, Roy Harris¹, Sian Kirkham⁵, Sabarinathan Loganathan⁵, Michalis Papadopoulos⁵, Young Persons Advisory Group (YPAG)⁶, David Devadason⁵, and Luca Marciani^1
1Nottingham Digestive Diseases Centre and NIHR Nottingham Biomedical Research Centre, University of Nottingham, Nottingham, United Kingdom, ²Clinical Radiology, Amiri Hospital, Ministry Of Health, Civil Service Commission, Kuwait, ³Sir Peter Mansfield Imaging Centre, School of Physics and Astronomy, University of Nottingham, Nottingham, United Kingdom, ⁴Medical Physics and Clinical Engineering, Nottingham University Hospitals, Queen’s Medical Centre, Nottingham, United Kingdom, ⁵Nottingham Children’s Hospital, Nottingham University Hospitals NHS Trust, Queen’s Medical Centre, Nottingham, United Kingdom, ⁶NUH YPAG, Nottingham University Hospitals NHS Trust, Nottingham, United Kingdom

We developed a new MRI mini-capsule marker device to measure whole gut transit (WGTT) in pediatric constipation to overcome image quality and ionizing radiation limitations of current X-ray methods. Thirty five healthy children and 16 patients with constipation were asked to swallow a number of mini-capsules and imaged, following a common X-ray radiopaque marker protocol. The capsules were imaged successfully in the colon. WGTT was calculated from the capsules count and was significantly longer in the patients compared to the controls. The study also showed excellent feasibility and safety of using the new device and methods in children with constipation.

Yao Sui^1,2, Onur Afacan^1,2, Ali Gholipour^1,2, and Simon Keith Warfield^1,2
1Harvard Medical School, Boston, MA, United States, ²Boston Children's Hospital, Boston, MA, United States

Motion monitoring has shown helpful in MRI, particularly in long acquisitions such as 2D echo-planar imaging for fMRI. The most widely-used motion monitoring for fMRI relies on volume-to-volume registration (VVR). However, motion happens at the slice level, and VVR is insufficiently sensitive to intra-volume motion. In this work, we present the first slice-by-slice self-navigated motion monitoring system for MRI via a real-time slice-to-volume registration (SVR) algorithm. Extensive experiments demonstrated that our approach provides accurate motion measurements, and allows adaptive acquisition that ensures sufficient amount of data, while not acquiring data in excess, leading to improved data quality and reduced costs.

Emi Niisato¹, Yung-Chieh Chen², Shojen Cheng², Yi-Hsin Wang², Wei Liu³, Daniel Nicolas Splitthoff⁴, and Cheng-Yu Chen^2
1Siemens Healthcare Limited, Taipei, Taiwan, ²Department of Medical Imaging, Taipei Medical University Hospital, Taipei, Taiwan, ³Siemens Shenzhen Magnetic Resonance Ltd, Shenzhen, China, ⁴Siemens Healthineers AG, Erlangen, Germany

Pediatric magnetic resonance imaging (MRI) needs extra care since patients cannot remain still for long in the MRI bore. Therefore, scans should be performed as quickly as possible. Our study investigated the role of fast T1 3D Magnetization Prepared Rapid Acquisition Gradient Echo (MPRAGE) scans using wave-controlled aliasing with parallel imaging (wave-CAIPI) in pediatric patients. We presented that scan times were shortened significantly, and images had fewer motion artifacts compared with conventional MPRAGE images. We further evaluated contrast-to-noise ratios (CNRs) in five cerebellar areas and saw no significant differences between the conventional and wave-CAIPI MPRAGE images.