The shoulder relies heavily on coordinated muscle activity for normal function owing to its limited osseous constraint. However, previous studies have failed to examine the sophisticated ...interrelationship between all muscles. It is essential for these normal relationships to be defined as a basis for understanding pathology. Therefore, the primary aim of the study was to investigate shoulder inter-muscular coordination during different planes of shoulder elevation. Twenty healthy subjects were included. Electromyography was recorded from 14 shoulder girdle muscles as subjects performed shoulder flexion, scapula plane elevation, abduction and extension. Cross-correlation was used to examine the coordination between different muscles and muscle groups. Significantly higher coordination existed between the rotator cuff and deltoid muscle groups during the initial (Pearson Correlation Coefficient (PCC) = 0.79) and final (PCC = 0.74) stages of shoulder elevation compared to the mid-range (PCC = 0.34) (p = 0.020-0.035). Coordination between the deltoid and a functional adducting group comprising the latissimus dorsi and teres major was particularly high (PCC = 0.89) during early shoulder elevation. The destabilising force of the deltoid, during the initial stage of shoulder elevation, is balanced by the coordinated activity of the rotator cuff, latissimus dorsi and teres major. Stability requirements are lower during the mid-range of elevation. At the end-range of movement the demand for muscular stability again increases and higher coordination is seen between the deltoid and rotator cuff muscle groups. It is proposed that by appreciating the sophistication of normal shoulder function targeted evidence-based rehabilitation strategies for conditions such as subacromial impingement syndrome or shoulder instability can be developed.
Vascularisation is a key feature of cancer growth, invasion and metastasis. To better understand the governing biophysical processes and their relative importance, it is instructive to develop ...physiologically representative mathematical models with which to compare to experimental data. Previous studies have successfully applied this approach to test the effect of various biochemical factors on tumour growth and angiogenesis. However, these models do not account for the experimentally observed dependency of angiogenic network evolution on growth-induced solid stresses. This work introduces two novel features: the effects of hapto- and mechanotaxis on vessel sprouting, and mechano-sensitive dynamic vascular remodelling. The proposed three-dimensional, multiscale, in-silico model of dynamically coupled angiogenic tumour growth is specified to in-vivo and in-vitro data, chosen, where possible, to provide a physiologically consistent description. The model is then validated against in-vivo data from murine mammary carcinomas, with particular focus placed on identifying the influence of mechanical factors. Crucially, we find that it is necessary to include hapto- and mechanotaxis to recapitulate observed time-varying spatial distributions of angiogenic vasculature.
Mounting evidence suggests that neuronal activity influences myelination, potentially allowing for experience-driven modulation of neural circuitry. The degree to which neuronal activity is capable ...of regulating myelination at the individual axon level is unclear. Here we demonstrate that stimulation of somatosensory axons in the mouse brain increases proliferation and differentiation of oligodendrocyte progenitor cells (OPCs) within the underlying white matter. Stimulated axons display an increased probability of being myelinated compared to neighboring non-stimulated axons, in addition to being ensheathed with thicker myelin. Conversely, attenuating neuronal firing reduces axonal myelination in a selective activity-dependent manner. Our findings reveal that the process of selecting axons for myelination is strongly influenced by the relative activity of individual axons within a population. These observed cellular changes are consistent with the emerging concept that adaptive myelination is a key mechanism for the fine-tuning of neuronal circuitry in the mammalian CNS.
Surgical treatment for early-stage breast carcinoma primarily necessitates breast conserving therapy (BCT), where the tumour is removed while preserving the breast shape. To date, there have been ...very few attempts to develop accurate and efficient computational tools that could be used in the clinical environment for pre-operative planning and oncoplastic breast surgery assessment. Moreover, from the breast cancer research perspective, there has been very little effort to model complex mechano-biological processes involved in wound healing. We address this by providing an integrated numerical framework that can simulate the therapeutic effects of BCT over the extended period of treatment and recovery. A validated, three-dimensional, multiscale finite element procedure that simulates breast tissue deformations and physiological wound healing is presented. In the proposed methodology, a partitioned, continuum-based mathematical model for tissue recovery and angiogenesis, and breast tissue deformation is considered. The effectiveness and accuracy of the proposed numerical scheme is illustrated through patient-specific representative examples. Wound repair and contraction numerical analyses of real MRI-derived breast geometries are investigated, and the final predictions of the breast shape are validated against post-operative follow-up optical surface scans from four patients. Mean (standard deviation) breast surface distance errors in millimetres of 3.1 (±3.1), 3.2 (±2.4), 2.8 (±2.7) and 4.1 (±3.3) were obtained, demonstrating the ability of the surgical simulation tool to predict, pre-operatively, the outcome of BCT to clinically useful accuracy.
We present an in-silico model of avascular poroelastic tumour growth coupled with a multiscale biphasic description of the tumour-host environment. The model is specified to in-vitro data, ...facilitating biophysically realistic simulations of tumour spheroid growth into a dense collagen hydrogel. We use the model to first confirm that passive mechanical remodelling of collagen fibres at the tumour boundary is driven by solid stress, and not fluid pressure. The model is then used to demonstrate the influence of collagen microstructure on peritumoural permeability and interstitial fluid flow. Our model suggests that at the tumour periphery, remodelling causes the peritumoural stroma to become more permeable in the circumferential than radial direction, and the interstitial fluid velocity is found to be dependent on initial collagen alignment. Finally we show that solid stresses are negatively correlated with peritumoural permeability, and positively correlated with interstitial fluid velocity. These results point to a heterogeneous, microstructure-dependent force environment at the tumour-peritumoural stroma interface.
Abstract A large number of algorithms have been developed to perform non-rigid registration and it is a tool commonly used in medical image analysis. The free-form deformation algorithm is a ...well-established technique, but is extremely time consuming. In this paper we present a parallel-friendly formulation of the algorithm suitable for graphics processing unit execution. Using our approach we perform registration of T1-weighted MR images in less than 1 min and show the same level of accuracy as a classical serial implementation when performing segmentation propagation. This technology could be of significant utility in time-critical applications such as image-guided interventions, or in the processing of large data sets.
•Work undertaken at CMIC, UCL from 2005 to 2015 on the topic of image guided interventions and image guided therapy, with reference to earlier work at CISG, Guy’s Hospital, KCL.•Shows how a ...hierarchical approach to computational anatomy in image guided interventions was developed.•Illustrated with applications in guiding neurosurgery, detection of colon cancer, planning breast cancer surgery, guiding prostate cancer interventions and image directed lung radiotherapy.
This paper describes work at CMIC, UCL from 2005 to 2015 combining clinical imaging and computational models applied to cancer detection and image guided interventions. In particular it shows how we have developed a hierarchical approach to multiscale computational anatomy for image guided interventions. Display omitted
This short paper describes the development of the UCL Centre for Medical Image Computing (CMIC) from 2006 to 2016, together with reference to historical developments of the Computational Imaging sciences Group (CISG) at Guy’s Hospital. Key early work in automated image registration led to developments in image guided surgery and improved cancer diagnosis and therapy. The work is illustrated with examples from neurosurgery, laparoscopic liver and gastric surgery, diagnosis and treatment of prostate cancer and breast cancer, and image guided radiotherapy for lung cancer.
Mutual information (MI) registration including spatial information has been shown to perform better than the traditional MI measures for certain nonrigid registration tasks. In this work, we first ...provide new insight to problems of the MI-based registration and propose to use the spatially encoded mutual information (SEMI) to tackle these problems. To encode spatial information, we propose a hierarchical weighting scheme to differentiate the contribution of sample points to a set of entropy measures, which are associated to spatial variable values. By using free-form deformations (FFDs) as the transformation model, we can first define the spatial variable using the set of FFD control points, and then propose a local ascent optimization scheme for nonrigid SEMI registration. The proposed SEMI registration can improve the registration accuracy in the nonrigid cases where the traditional MI is challenged due to intensity distortion, contrast enhancement, or different imaging modalities. It also has a similar computation complexity to the registration using traditional MI measures, improving up to two orders of magnitude of computation time compared to the traditional schemes. We validate our algorithms using phantom brain MRI, simulated dynamic contrast enhanced mangetic resonance imaging (MRI) of the liver, and in vivo cardiac MRI. The results show that the SEMI registration significantly outperforms the traditional MI registration.
Surrogate-driven respiratory motion models relate the motion of the internal anatomy to easily acquired respiratory surrogate signals, such as the motion of the skin surface. They are usually built ...by first using image registration to determine the motion from a number of dynamic images, and then fitting a correspondence model relating the motion to the surrogate signals. In this paper we present a generalized framework that unifies the image registration and correspondence model fitting into a single optimization. This allows the use of 'partial' imaging data, such as individual slices, projections, or k-space data, where it would not be possible to determine the motion from an individual frame of data. Motion compensated image reconstruction can also be incorporated using an iterative approach, so that both the motion and a motion-free image can be estimated from the partial image data. The framework has been applied to real 4DCT, Cine CT, multi-slice CT, and multi-slice MR data, as well as simulated datasets from a computer phantom. This includes the use of a super-resolution reconstruction method for the multi-slice MR data. Good results were obtained for all datasets, including quantitative results for the 4DCT and phantom datasets where the ground truth motion was known or could be estimated.
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