Intraoperative Organ Motion Models with an Ensemble of Conditional Generative Adversarial Networks

In this paper, we describe how a patient-specific, ultrasound-probe-induced prostate motion model can be directly generated from a single preoperative MR image. Our motion model allows for sampling from the conditional distribution of dense displacement fields, is encoded by a generative neural network conditioned on a medical image, and accepts random noise as additional input. The generative network is trained by a minimax optimisation with a second discriminative neural network, tasked to distinguish generated samples from training motion data. In this work, we propose that 1) jointly optimising a third conditioning neural network that pre-processes the input image, can effectively extract patient-specific features for conditioning; and 2) combining multiple generative models trained separately with heuristically pre-disjointed training data sets can adequately mitigate the problem of mode collapse. Trained with diagnostic T2-weighted MR images from 143 real patients and 73,216 3D dense displacement fields from finite element simulations of intraoperative prostate motion due to transrectal ultrasound probe pressure, the proposed models produced physically-plausible patient-specific motion of prostate glands. The ability to capture biomechanically simulated motion was evaluated using two errors representing generalisability and specificity of the model. The median values, calculated from a 10-fold cross-validation, were 2.8+/-0.3 mm and 1.7+/-0.1 mm, respectively. We conclude that the introduced approach demonstrates the feasibility of applying state-of-the-art machine learning algorithms to generate organ motion models from patient images, and shows significant promise for future research.Comment: Accepted to MICCAI 201

Time for change: a new training programme for morpho-molecular pathologists?

The evolution of cellular pathology as a specialty has always been driven by technological developments and the clinical relevance of incorporating novel investigations into diagnostic practice. In recent years, the molecular characterisation of cancer has become of crucial relevance in patient treatment both for predictive testing and subclassification of certain tumours. Much of this has become possible due to the availability of next-generation sequencing technologies and the whole-genome sequencing of tumours is now being rolled out into clinical practice in England via the 100 000 Genome Project. The effective integration of cellular pathology reporting and genomic characterisation is crucial to ensure the morphological and genomic data are interpreted in the relevant context, though despite this, in many UK centres molecular testing is entirely detached from cellular pathology departments. The CM-Path initiative recognises there is a genomics knowledge and skills gap within cellular pathology that needs to be bridged through an upskilling of the current workforce and a redesign of pathology training. Bridging this gap will allow the development of an integrated 'morphomolecular pathology' specialty, which can maintain the relevance of cellular pathology at the centre of cancer patient management and allow the pathology community to continue to be a major influence in cancer discovery as well as playing a driving role in the delivery of precision medicine approaches. Here, several alternative models of pathology training, designed to address this challenge, are presented and appraised

Adversarial Deformation Regularization for Training Image Registration Neural Networks

We describe an adversarial learning approach to constrain convolutional neural network training for image registration, replacing heuristic smoothness measures of displacement fields often used in these tasks. Using minimally-invasive prostate cancer intervention as an example application, we demonstrate the feasibility of utilizing biomechanical simulations to regularize a weakly-supervised anatomical-label-driven registration network for aligning pre-procedural magnetic resonance (MR) and 3D intra-procedural transrectal ultrasound (TRUS) images. A discriminator network is optimized to distinguish the registration-predicted displacement fields from the motion data simulated by finite element analysis. During training, the registration network simultaneously aims to maximize similarity between anatomical labels that drives image alignment and to minimize an adversarial generator loss that measures divergence between the predicted- and simulated deformation. The end-to-end trained network enables efficient and fully-automated registration that only requires an MR and TRUS image pair as input, without anatomical labels or simulated data during inference. 108 pairs of labelled MR and TRUS images from 76 prostate cancer patients and 71,500 nonlinear finite-element simulations from 143 different patients were used for this study. We show that, with only gland segmentation as training labels, the proposed method can help predict physically plausible deformation without any other smoothness penalty. Based on cross-validation experiments using 834 pairs of independent validation landmarks, the proposed adversarial-regularized registration achieved a target registration error of 6.3 mm that is significantly lower than those from several other regularization methods.Comment: Accepted to MICCAI 201

Label-driven weakly-supervised learning for multimodal deformable image registration

Spatially aligning medical images from different modalities remains a challenging task, especially for intraoperative applications that require fast and robust algorithms. We propose a weakly-supervised, label-driven formulation for learning 3D voxel correspondence from higher-level label correspondence, thereby bypassing classical intensity-based image similarity measures. During training, a convolutional neural network is optimised by outputting a dense displacement field (DDF) that warps a set of available anatomical labels from the moving image to match their corresponding counterparts in the fixed image. These label pairs, including solid organs, ducts, vessels, point landmarks and other ad hoc structures, are only required at training time and can be spatially aligned by minimising a cross-entropy function of the warped moving label and the fixed label. During inference, the trained network takes a new image pair to predict an optimal DDF, resulting in a fully-automatic, label-free, real-time and deformable registration. For interventional applications where large global transformation prevails, we also propose a neural network architecture to jointly optimise the global- and local displacements. Experiment results are presented based on cross-validating registrations of 111 pairs of T2-weighted magnetic resonance images and 3D transrectal ultrasound images from prostate cancer patients with a total of over 4000 anatomical labels, yielding a median target registration error of 4.2 mm on landmark centroids and a median Dice of 0.88 on prostate glands.Comment: Accepted to ISBI 201

Label-free Screening of Biochemical Changes in Macrophage-like Cells Following MoS2 Exposure Using Raman Micro-spectroscopy

The emergence of large scale production techniques for 2D particulate materials has dramatically increased their applications potential. Understanding the interactions of biological cells with such particulate material is therefore of paramount importance, both for toxicological assessment and potential biomedical applications. Conventional in-vitro cytological assays commonly record only a single colorimetric end-point, and do not provide an in-depth analysis of how such materials are uptaken and processed within cells. To demonstrate its potential as an alternative, label free approach, confocal Raman micro-spectroscopy has been used to profile the cellular response of macrophage-like immune cells as a result of exposure to a sub-lethal dose of particulate MoS2, as an example novel 2D material. Particles were seen to be uptaken and trafficked in sub-cellular vesicles, and this sensitive technique allows differences in the biochemical composition of the vesicles to be assessed and monitored as a function of time. Untreated macrophage-like cells contain lipidic vesicles which are found to be relatively rich in the membrane lipid sphingomyelin, key to the process of cell membrane regeneration. After exposure to MoS2, the particulate material is seen to be invaginated in similar vesicles, the most prominent of which now, however, have spectroscopic signatures which are dominated by those of phosphatidyl family lipids, consistent with the phagocytotic pathway. The lipidic content of cells is seen to increase at all time-points (4, 24 and 72 h). although vesicles composed of sphingomyelin become more prominent again following a prolonged incubation of 72 h to a sub-lethal dose of MoS2, as the immune cell has processed the particulate material and initiates recovery to a normal/untreated state. This study reveals Raman micro-spectroscopy is an effective method for monitoring cellular responses and evolution of organelle compositions in response to MoS2 exposure. The additional benefit of using this technique is that cells can be monitored as a function of time, while it can also be used for screening other micro/nano materials for toxicology and/or establishing cell responses

In-vitro Localisation and Degradation of Few-layer MoS2 Submicrometric Plates in Human Macrophage-like Cells: a Label Free Raman Micro-spectroscopic Study

Monitoring the uptake, micro-environment and fate of micro or nano scaled particulate materials in cells is of paramount importance for the emerging fields of toxicology and medicine. Such particulate materials are known to interfere with colorimetric assays and many such assays record only a single end-point. Therefore, there is a need for a label-free, cost effective technique with little or no inference from the particulate materials. Raman micro-spectroscopy was used to simultaneously interrogate the integrity of few-layer MoS2 submicrometric plates in human macrophage-like cells, in-vitro, as well as the biochemical characteristics of the local micro-environment in which they are encompassed. Firstly, the degradation profile of MoS2 plates induced by hydrogen peroxidase was established using UV-Vis absorption and Raman micro-spectroscopy. Raman micro-spectroscopic maps interrogated all aspects of the cell, including the nucleus, cytoplasm and perinuclear region, and the location/distribution of MoS2 was monitored as a function of time (4, 24 and 72 h). Whereas only pristine MoS2 was detectable after 4 and 72 periods, degradation in-vitro was confirmed following a 24 h incubation. Analysis of the MoS2 micro-environments revealed the presence of both phosphatidyl lipidic vesicles and enzymatic regions containing lysozyme, the former being most associated with the MoS2 degradation. There was an increase and saturation of cytosolic neutral lipids detected following a 24 h incubation with MoS2, which reduces following a prolonged incubation of 72 h. This study reveals that macrophage-like cells perform degradation of the material in-vitro within lipidic vesicles subsequent to phagocytosis, which manifest as an increase in the production of lipid bodies as a mechanism of defense following exposure to industrial grade MoS2

Sensory nerve transfers in the upper limb after peripheral nerve injury:a scoping review

Nerve transfer for motor nerve paralysis is an established technique for treating complex nerve injuries. However, nerve transfer for sensory reconstruction has not been widely used, and published research on this topic is limited compared to motor nerve transfer. The indications and outcomes of nerve transfer for the restoration of sensory function remain unproven. This scoping review examines the indications, outcomes and complications of sensory nerve transfer. In total, 22 studies were included; the major finding is that distal sensory nerve transfers are more successful than proximal ones in succeeding protective sensation. Although the risk of extension of the sensory deficit with donor site loss and morbidity from neuromas remain a barrier to wider adoption, these complications were not reported in the review. Further, the scarcity of studies and small patient series limit the ability to determine sensory nerve transfer success. However, sensory restoration remains an opportunity for surgeons to pursue.</p

Sensory nerve transfers in the upper limb after peripheral nerve injury:a scoping review

Nerve transfer for motor nerve paralysis is an established technique for treating complex nerve injuries. However, nerve transfer for sensory reconstruction has not been widely used, and published research on this topic is limited compared to motor nerve transfer. The indications and outcomes of nerve transfer for the restoration of sensory function remain unproven. This scoping review examines the indications, outcomes and complications of sensory nerve transfer. In total, 22 studies were included; the major finding is that distal sensory nerve transfers are more successful than proximal ones in succeeding protective sensation. Although the risk of extension of the sensory deficit with donor site loss and morbidity from neuromas remain a barrier to wider adoption, these complications were not reported in the review. Further, the scarcity of studies and small patient series limit the ability to determine sensory nerve transfer success. However, sensory restoration remains an opportunity for surgeons to pursue.</p

A direct-to-drive neural data acquisition system

Driven by the increasing channel count of neural probes, there is much effort being directed to creating increasingly scalable electrophysiology data acquisition (DAQ) systems. However, all such systems still rely on personal computers for data storage, and thus are limited by the bandwidth and cost of the computers, especially as the scale of recording increases. Here we present a novel architecture in which a digital processor receives data from an analog-to-digital converter, and writes that data directly to hard drives, without the need for a personal computer to serve as an intermediary in the DAQ process. This minimalist architecture may support exceptionally high data throughput, without incurring costs to support unnecessary hardware and overhead associated with personal computers, thus facilitating scaling of electrophysiological recording in the future.National Institutes of Health (U.S.) (Grant 1DP1NS087724)National Institutes of Health (U.S.) (Grant 1R01DA029639)National Institutes of Health (U.S.) (Grant 1R01NS067199)National Institutes of Health (U.S.) (Grant 2R44NS070453)National Institutes of Health (U.S.) (Grant R43MH101943)New York Stem Cell FoundationPaul Allen FoundationMassachusetts Institute of Technology. Media LaboratoryGoogle (Firm)United States. Defense Advanced Research Projects Agency (HR0011-14-2-0004)Hertz Foundation (Myhrvold Family Fellowship

Periconceptional environment predicts leukocyte telomere length in a cross-sectional study of 7-9 year old rural Gambian children

Early life exposures are important predictors of adult disease risk. Although the underlying mechanisms are largely unknown, telomere maintenance may be involved. This study investigated the relationship between seasonal differences in parental exposures at time of conception and leukocyte telomere length (LTL) in their offspring. LTL was measured in two cohorts of children aged 2 yrs (N = 487) and 7–9 yrs (N = 218). The association between date of conception and LTL was examined using Fourier regression models, adjusted for age, sex, leukocyte cell composition, and other potential confounders. We observed an effect of season in the older children in all models [likelihood ratio test (LRT) χ²2 = 7.1, p = 0.03; fully adjusted model]. LTL was greatest in children conceived in September (in the rainy season), and smallest in those conceived in March (in the dry season), with an effect size (LTL peak–nadir) of 0.60 z-scores. No effect of season was evident in the younger children (LRT χ²2 = 0.87, p = 0.65). The different results obtained for the two cohorts may reflect a delayed effect of season of conception on postnatal telomere maintenance. Alternatively, they may be explained by unmeasured differences in early life exposures, or the increased telomere attrition rate during infancy