Investigating the Validity of Soft Tissue Signs on Lateral Ankle X-Ray to Aid Diagnosis of Achilles Tendon Rupture in the Emergency Department

AimsTo investigate the diagnostic validity of four radiological soft tissue signs Kager's sign (K), disruption to the tendon (D), loss of parallelism (P) and fusiform swelling of the tendon (F) on a lateral ankle x-ray to aid Achilles tendon rupture diagnosis.MethodsWe retrospectively identified two groups of patients; Group A consisted of patients with an Achilles tendon rupture and Group B included patients with a clinically intact Achilles tendon but with a lateral ankle ligament sprain. Three clinicians independently reviewed all patients' x-rays for each of the radiological features under investigation to determine whether a rupture was present or not. Inter-rater and Intra-rater reliability were calculated using the Kappa coefficient (Kc.) To determine the predicted value of the signs sensitivity, specificity, positive predicted values and negative predicted values were calculated.Results85 patients x-rays were included in this study; Group A n = 47, Group B n = 38. The most valid radiological sign appeared to be loss of parallelism (sensitivity 70%, specificity 97%, kappa 0.55-0.58).ConclusionClinicians reviewing a lateral ankle x-ray of a patient with an acute ankle injury should review the x-ray for loss of parallelism between the tendon and skin; identification of this radiological sign may alert the clinician to the possible diagnosis of a ruptured Achilles tendon. Reviewing this may reduce the number of missed Achilles ruptures

Comparative Dosimetric Analysis and Normal Tissue Complication Probability Modelling of Four-Dimensional Computed Tomography Planning Scans Within the UK NeoSCOPE Trial

Neoadjuvant chemoradiotherapy for resectable oesophageal cancer improves overall survival compared to surgery alone but is associated with increased toxicity. NeoSCOPE is a trial of two different nCRT regimens for resectable oesophageal and was the first multi-centre trial in the UK to incorporate 4D-CT into the radiotherapy planning. Using NeoSCOPE 4D-CT cases, we undertook a dosimetric comparison study of 3D-CT versus 4D-CT plans comparing target volume coverage and dose to organs at risk. We used established normal tissue complication probability (NTCP) models to evaluate the potential toxicity reduction of using 4D-CT plans in oesophageal cancer. Our work shows that incorporating 4D-CT into treatment planning may significantly reduce the toxicity burden from this treatment

On gradual regime switching models: A generalisation of Hamilton's method of time-series analysis.

The class of Markov Switching time series models, introduced by Professor James Hamilton, is nearly twenty years old. Despite this, relatively little work has been done on allowing gradual transitions between the regimes of the model. Almost all of the published work relates to modelling a transition between two regression lines rather than incorporating it into a time series model. We decided to approach the problem from two directions. First, we wanted to look at Filtered Telegraph signals (Filtered Markov processes) and consider their suitability for time series analysis. Secondly, we wished to extend the existing Regime Switching models to allow a gradual transition between regimes. In our work on the Filtered Markov process we present a method for obtaining moments for a signal with any number of regimes, rather than the usual two. This enables us to find the stationary, transient and conditional moments of the signal. We include an expression for the covariance of two observations from a signal, obtained using the conditional moments. While considering how to fit a Filtered Markov process we identify several new methods that can be used for estimating the parameters of a sample from the Beta distribution where the observations have been contaminated by noise. We also include extensive tables of the percentiles of the estimators for each of the methods. We also present a new algorithm that utilises the Filtered Markov process to generate random Beta variates. Finally we take a more practical approach, introducing some simple models that, while useful in their own right, could also be used to bridge the gap between the two-regime Markov switching model and the Filtered Markov process. These Ladder models are then applied to several data sets to explore the problems faced by gradual switching models and collect evidence of their suitability