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Journal articleMunroe PB, Addison S, Abrams DJ, et al., 2018,
Postmortem genetic testing for cardiac ion channelopathies in stillbirths
, Circulation: Cardiovascular Genetics, Vol: 11, ISSN: 1942-325XBackgroundAlthough stillbirth is a significant health problem worldwide, the definitive cause of death remains elusive in many cases, despite detailed autopsy. In this study of partly explained and unexplained stillbirths, we used next-generation sequencing to examine an extended panel of 35 candidate genes known to be associated with ion channel disorders and sudden cardiac death.Methods and ResultsWe examined tissue from 242 stillbirths (≥22 weeks), including those where no definite cause of death could be confirmed after a full autopsy. We obtained high-quality DNA from 70 cases, which were then sequenced for a custom panel of 35 genes, 12 for inherited long- and short-QT syndrome genes (LQT1-LQT12 and SQT1-3), and 23 additional candidate genes derived from genome-wide association studies. We examined the functional significance of a selected variant by patch-clamp electrophysiological recording. No predicted damaging variants were identified in KCNQ1 (LQT1) or KCNH2 (LQT2). A rare putative pathogenic variant was found in KCNJ2(LQT7) in 1 case, and several novel variants of uncertain significance were observed. The KCNJ2 variant (p. R40Q), when assessed by whole-cell patch clamp, affected the function of the channel. There was no significant evidence of enrichment of rare predicted damaging variants within any of the candidate genes.ConclusionsAlthough a causative link is unclear, 1 putative pathogenic and variants of uncertain significance variant resulting in cardiac channelopathies was identified in some cases of otherwise unexplained stillbirth, and these variants may have a role in fetal demise.
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Conference paperDong S, Gao Z, Sun S, et al., 2018,
Holistic and deep feature pyramids for saliency detection
Saliency detection has been increasingly gaining research interest in recent years since many computer vision applications need to derive object attentions from images in the first steps. Multi-scale awareness of the saliency detector becomes essential to find thin and small attention regions as well as keeping high-level semantics. In this paper, we propose a novel holistic and deep feature pyramid neural network architecture that can leverage multi-scale semantics in feature encoding stage and saliency region prediction (decoding) stage. In the encoding stage, we exploit multi-scale and pyramidal hierarchy of feature maps via the densely connected network with variable-size dilated convolutions as well as a pyramid pooling. In the decoding stage, we fuse multi-level feature maps via up-sampling and convolution. In addition, we utilize the multi-level deep supervision via plugging in loss functions at every feature fusion level. Multi-loss supervision regularizes weights searching space among different tasks minimizing over-fitting and enhances gradient signal during backpropagation, and thus enables us training the network from scratch. This architecture builds an inherent multi-level semantic pyramidal feature maps at different scales and enhances model's capability in the saliency detection task. We validated our approach on six benchmark datasets and compared with eleven state-of-the-art methods. The results demonstrated that the design effectiveness and our approach outperformed the compared methods.
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Conference paperLi M, Dong S, Zhang K, et al., 2018,
Deep Learning intra-image and inter-images features for Co-saliency detection
In this paper, we propose a novel deep end-to-end co-saliency detection approach to extract common salient objects from images group. The existing approaches rely heavily on manually designed metrics to characterize co-saliency. However, these methods are so subjective and not flexible enough that leads to poor generalization ability. Furthermore, most approaches separate the process of single image features and group images features extraction, which ignore the correlation between these two features that can promote the model performance. The proposed approach solves these two problems by multistage representation to extract features based on high-spatial resolution CNN. In addition, we utilize the modified CAE to explore the learnable consistency. Finally, the intra-image contrast and the inter-images consistency are fused to generate the final co-saliency maps automatically among group images by multistage learning. Experiment results demonstrate the effectiveness and superiority of our approach beyond the state-of-the-art methods.
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Working paperOlliverre N, Yang G, Slabaugh G, et al., 2018,
Generating Magnetic Resonance Spectroscopy Imaging Data of Brain Tumours from Linear, Non-linear and Deep Learning Models
, Publisher: SPRINGER INTERNATIONAL PUBLISHING AG- Author Web Link
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- Citations: 5
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Conference paperSoltaninejad M, Zhang L, Lambrou T, et al., 2018,
MRI Brain Tumor Segmentation and Patient Survival Prediction Using Random Forests and Fully Convolutional Networks
, 3rd International Workshop on Brain-Lesion (BrainLes) held jointly at the Conference on Medical Image Computing for Computer Assisted Intervention (MICCAI), Publisher: SPRINGER INTERNATIONAL PUBLISHING AG, Pages: 204-215, ISSN: 0302-9743- Cite
- Citations: 45
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Journal articleLally PJ, Montaldo P, Oliveira V, et al., 2017,
Residual brain injury after early discontinuation of cooling therapy in mild neonatal encephalopathy
, Archives of Disease in Childhood. Fetal and Neonatal Edition, Pages: F383-F387, ISSN: 1359-2998We examined the brain injury and neurodevelopmental outcomes in a prospective cohort of 10 babies with mild encephalopathy who had early cessation of cooling therapy. All babies had MRI and spectroscopy within 2 weeks after birth and neurodevelopmental assessment at 2 years. Cooling was prematurely discontinued at a median age of 9 hours (IQR 5–13) due to rapid clinical improvement. Five (50%) had injury on MRI or spectroscopy, and two (20%) had an abnormal neurodevelopmental outcome at 2 years. Premature cessation of cooling therapy in babies with mild neonatal encephalopathy does not exclude residual brain injury and adverse long-term neurodevelopmental outcomes. This study refers to babies recruited into the MARBLE study (NCT01309711, pre-results stage).
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Journal articleLally PJ, Montaldo P, Oliveira V, et al., 2017,
Residual brain injury after early discontinuation of cooling therapy in mild neonatal encephalopathy
, Archives of Disease in Childhood. Fetal and Neonatal Edition, Vol: 103, Pages: F383-F387, ISSN: 1359-2998We examined the brain injury and neurodevelopmental outcomes in a prospective cohort of 10 babies with mild encephalopathy who had early cessation of cooling therapy. All babies had MRI and spectroscopy within 2 weeks after birth and neurodevelopmental assessment at 2 years. Cooling was prematurely discontinued at a median age of 9 hours (IQR 5-13) due to rapid clinical improvement. Five (50%) had injury on MRI or spectroscopy, and two (20%) had an abnormal neurodevelopmental outcome at 2 years. Premature cessation of cooling therapy in babies with mild neonatal encephalopathy does not exclude residual brain injury and adverse long-term neurodevelopmental outcomes. This study refers to babies recruited into the MARBLE study (NCT01309711, pre-results stage).
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Journal articleForte E, Aiello M, Inglese M, et al., 2017,
Coronary artery aneurysms detected by computed tomography coronary angiography
, EUROPEAN HEART JOURNAL-CARDIOVASCULAR IMAGING, Vol: 18, Pages: 1229-1235, ISSN: 2047-2404- Author Web Link
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- Citations: 18
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Journal articleAlfaro-Almagro F, Jenkinson M, Bangerter NK, et al., 2017,
Image processing and Quality Control for the first 10,000 brain imaging datasets from UK Biobank.
, NeuroImage, Vol: 166, Pages: 400-424, ISSN: 1053-8119UK Biobank is a large-scale prospective epidemiological study with all data accessible to researchers worldwide. It is currently in the process of bringing back 100,000 of the original participants for brain, heart and body MRI, carotid ultrasound and low-dose bone/fat x-ray. The brain imaging component covers 6 modalities (T1, T2 FLAIR, susceptibility weighted MRI, Resting fMRI, Task fMRI and Diffusion MRI). Raw and processed data from the first 10,000 imaged subjects has recently been released for general research access. To help convert this data into useful summary information we have developed an automated processing and QC (Quality Control) pipeline that is available for use by other researchers. In this paper we describe the pipeline in detail, following a brief overview of UK Biobank brain imaging and the acquisition protocol. We also describe several quantitative investigations carried out as part of the development of both the imaging protocol and the processing pipeline.
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Journal articleGrech-Sollars M, Vaqas B, Thompson G, et al., 2017,
An MRS- and PET-guided biopsy tool for intraoperative neuronavigational systems.
, J Neurosurg, Vol: 127, Pages: 812-818OBJECTIVE Glioma heterogeneity and the limitations of conventional structural MRI for identifying aggressive tumor components can limit the reliability of stereotactic biopsy and, hence, tumor characterization, which is a hurdle for developing and selecting effective treatment strategies. In vivo MR spectroscopy (MRS) and PET enable noninvasive imaging of cellular metabolism relevant to proliferation and can detect regions of more highly active tumor. Here, the authors integrated presurgical PET and MRS with intraoperative neuronavigation to guide surgical biopsy and tumor sampling of brain gliomas with the aim of improving intraoperative tumor-tissue characterization and imaging biomarker validation. METHODS A novel intraoperative neuronavigation tool was developed as part of a study that aimed to sample high-choline tumor components identified by multivoxel MRS and 18F-methylcholine PET-CT. Spatially coregistered PET and MRS data were integrated into structural data sets and loaded onto an intraoperative neuronavigation system. High and low choline uptake/metabolite regions were represented as color-coded hollow spheres for targeted stereotactic biopsy and tumor sampling. RESULTS The neurosurgeons found the 3D spherical targets readily identifiable on the interactive neuronavigation system. In one case, areas of high mitotic activity were identified on the basis of high 18F-methylcholine uptake and elevated choline ratios found with MRS in an otherwise low-grade tumor, which revealed the possible use of this technique for tumor characterization. CONCLUSIONS These PET and MRI data can be combined and represented usefully for the surgeon in neuronavigation systems. This method enables neurosurgeons to sample tumor regions based on physiological and molecular imaging markers. The technique was applied for characterizing choline metabolism using MRS and 18F PET; however, this approach provides proof of principle for using different radionuclide tracers and other MRI m
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For enquiries about the MRI Physics Collective, please contact:
Mary Finnegan
Senior MR Physicist at the Imperial College Healthcare NHS Trust
Pete Lally
Assistant Professor in Magnetic Resonance (MR) Physics at Imperial College
Jan Sedlacik
MR Physicist at the Robert Steiner MR Unit, Hammersmith Hospital Campus