Lumbar Spine Location in Fluoroscopic Images by Evidence Gathering

Low back pain (LBP) is a very common problem and lumbar segmental instability is one of the causes. It is important to investigate lumbar spine movement in order to understand instability better and as an aid to diagnosis. Digital videofluoroscopy provides a method of quantifying the motion of individual vertebrae, but due to the relatively poor image quality, it is difficult and time consuming to locate landmarks manually, from which the kinematics can be calculated. Some semi-automatic approaches have already been developed but these are still time consuming and require some manual interaction. In this paper we apply the Hough transform (HT) to locate the lumbar spinal segments automatically. The HT is a powerful tool in computer vision and it has good performance in noise and partial occlusion. A recent arbitrary shape representation avoids problems inherent with tabular representations in the generalised HT (GHT) by describing shapes using a continuous formulation. The target shape is described by a set of Fourier descriptors, which vote in an accumulator space from which the object parameters of translation (including the x and y direction), rotation and scale can be determined. At present, this algorithm has been applied to the images of lumbar spine, and has been shown to provide satisfactory results. Further work will concentrate on reducing the computational time for real-time application, and on approaches to refine information at the apices, given initialisation by the new HT method

Automatic Lumbar Vertebrae Segmentation in Fluoroscopic Images via Optimised Concurrent Hough Transform

Low back pain is a very common problem in the industrialised countries and its associated cost is enormous. Diagnosis of the underlying causes can be extremely difficult. Many studies have focused on mechanical disorders of the spine. Digital videofluoroscopy (DVF) was widely used to obtain images for motion studies. This can provide motion sequences of the lumbar spine, but the images obtained often suffer due to noise, exacerbated by the very low radiation dosage. Thus determining vertebrae position within the image sequence presents a considerable challenge. In this paper, we show how our new approach can automatically detect the positions and borders of vertebrae concurrently, relieving many of the problems experienced in other approaches. First, we use phase congruency to relieve difficulty associated with threshold selection in edge detection of the illumination variant DVF images. Then, our new Hough transform approach is applied to determine the moving vertebrae, concurrently. We include optimisation via a genetic algorithm as without it the extraction of moving multiple vertebrae is computationally daunting. Our results show that this new approach can indeed provide extractions of position and rotation which appear to be of sufficient quality to aid therapy and diagnosis of spinal disorders

A novel experimental technique and its application to study the effects of particle density and flow submergence on bed particle saltation

This research was sponsored by EPSRC grant EP/G056404/1 which is greatly appreciated.Peer reviewedPublisher PD

The fluctuation energy balance in non-suspended fluid-mediated particle transport

Here we compare two extreme regimes of non-suspended fluid-mediated particle transport, transport in light and heavy fluids ("saltation" and "bedload", respectively), regarding their particle fluctuation energy balance. From direct numerical simulations, we surprisingly find that the ratio between collisional and fluid drag dissipation of fluctuation energy is significantly larger in saltation than in bedload, even though the contribution of interparticle collisions to transport of momentum and energy is much smaller in saltation due to the low concentration of particles in the transport layer. We conclude that the much higher frequency of high-energy particle-bed impacts ("splash") in saltation is the cause for this counter-intuitive behavior. Moreover, from a comparison of these simulations to Particle Tracking Velocimetry measurements which we performed in a wind tunnel under steady transport of fine and coarse sand, we find that turbulent fluctuations of the flow produce particle fluctuation energy at an unexpectedly high rate in saltation even under conditions for which the effects of turbulence are usually believed to be small

Bed load sediment transport and morphological evolution in a degrading uniform sediment channel under unsteady flow hydrographs

Flume experiments are conducted to investigate the intrinsic links between time-varying bed load transport properties for uniform sediments and bed surface morphology under unsteady hydrograph flows, in the absence of upstream sediment supply. These conditions are representative of regulated river reaches (e.g. downstream of a dam) that are subject to natural flood discharges or managed water releases, resulting in net degradation of the river bed. The results demonstrate that the hydrograph magnitude and unsteadiness have significant impacts on sediment transport rates and yields, as well as hysteresis patterns and yield ratios generated during the rising and falling limbs. A new hydrograph descriptor combining the influence of total water work and unsteadiness on bed load transport is shown to delineate these hysteresis patterns and yield ratios, whilst correlating strongly with overall sediment yields. This provides an important parametric link between unsteady hydrograph flow conditions, bed load transport and bed surface degradation under imposed zero sediment feed conditions. As such, maximum bed erosion depths and the longitudinal bed degradation profiles along the flume, are strongly dependent on the magnitude of this new hydrograph descriptor. Similarly, non-equilibrium bed forms generated along the flume indicate that formative conditions for alternate bars, mixed bar/dunes or dunes are defined reasonably well by an existing morphological model and the new hydrograph descriptor. These findings provide a new framework for improved predictive capabilities for sediment transport and morphodynamic response in regulated rivers to natural or imposed unsteady flows, while their wider application to graded sediments are also considered

Bone-Induced Expression of Integrin β3 Enables Targeted Nanotherapy of Breast Cancer Metastases

Bone metastases occur in approximately 70% of metastatic breast cancer patients, often leading to skeletal injuries. Current treatments are mainly palliative and underscore the unmet clinical need for improved therapies. In this study, we provide preclinical evidence for an antimetastatic therapy based on targeting integrin β3 (β3), which is selectively induced on breast cancer cells in bone by the local bone microenvironment. In a preclinical model of breast cancer, β3 was strongly expressed on bone metastatic cancer cells, but not primary mammary tumors or visceral metastases. In tumor tissue from breast cancer patients, β3 was significantly elevated on bone metastases relative to primary tumors from the same patient (n = 42). Mechanistic investigations revealed that TGFβ signaling through SMAD2/SMAD3 was necessary for breast cancer induction of β3 within the bone. Using a micelle-based nanoparticle therapy that recognizes integrin αvβ3 (αvβ3-MPs of ∼12.5 nm), we demonstrated specific localization to breast cancer bone metastases in mice. Using this system for targeted delivery of the chemotherapeutic docetaxel, we showed that bone tumor burden could be reduced significantly with less bone destruction and less hepatotoxicity compared with equimolar doses of free docetaxel. Furthermore, mice treated with αvβ3-MP-docetaxel exhibited a significant decrease in bone-residing tumor cell proliferation compared with free docetaxel. Taken together, our results offer preclinical proof of concept for a method to enhance delivery of chemotherapeutics to breast cancer cells within the bone by exploiting their selective expression of integrin αvβ3 at that metastatic site

Observations of bedforms on a dissipative macrotidal beach

NERC NE/H004262/1 and NE/H02543X/1 DRIB

The Relationship Between Ambient Atmospheric Fine Particulate Matter (PM2.5) and Glaucoma in a Large Community Cohort.

Purpose: Glaucoma is more common in urban populations than in others. Ninety percent of the world's population are exposed to air pollution above World Health Organization (WHO) recommended limits. Few studies have examined the association between air pollution and glaucoma. Methods: Questionnaire data, ophthalmic measures, and ambient residential area air quality data for 111,370 UK Biobank participants were analyzed. Particulate matter with an aerodynamic diameter < 2.5 μm (PM2.5) was selected as the air quality exposure of interest. Eye measures included self-reported glaucoma, intraocular pressure (IOP), and average thickness of macular ganglion cell-inner plexiform layer (GCIPL) across nine Early Treatment Diabetic Retinopathy Study (ETDRS) retinal subfields as obtained from spectral-domain optical coherence tomography. We examined the associations of PM2.5 concentration with self-reported glaucoma, IOP, and GCIPL. Results: Participants resident in areas with higher PM2.5 concentration were more likely to report a diagnosis of glaucoma (odds ratio = 1.06, 95% confidence interval [CI] = 1.01-1.12, per interquartile range [IQR] increase P = 0.02). Higher PM2.5 concentration was also associated with thinner GCIPL (β = -0.56 μm, 95% CI = -0.63 to -0.49, per IQR increase, P = 1.2 × 10-53). A dose-response relationship was observed between higher levels of PM2.5 and thinner GCIPL (P < 0.001). There was no clinically relevant relationship between PM2.5 concentration and IOP. Conclusions: Greater exposure to PM2.5 is associated with both self-reported glaucoma and adverse structural characteristics of the disease. The absence of an association between PM2.5 and IOP suggests the relationship may occur through a non-pressure-dependent mechanism, possibly neurotoxic and/or vascular effects