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Aim: This study was conducted to assess the predictive value of coagulation abnormalities in determining disease severity and prognosis of acute pancreatitis (AP). Methods: Patients of AP and 25 healthy volunteers were included in this prospective observational study. The final outcomes were disease severity assessed by Computed Tomography Severity Index, Acute Physiological Assessment and Chronic Health Evaluation-II, presence of organ failure and mortality. Prothrombin time (PT), partial thromboplastin time (PTT), thrombin time (TT), fibrinogen, antithrombin-III (AT-III), protein-C, and proteinS levels were assessed on day 0, 3 and 7 of admission. Results: Of the 38 patients included, 13 died. Mean PT and TT were similar between patients and controls on any given day. PTT showed elevation on day 3 and 7 (p=0.001) compared to controls, although fibrinogen and D-dimer were significantly higher in patients on all days. Protein C and AT-III were significantly lower in patients and more so in non survivors ((p=0.001)) than controls. Multiple logistic regression analysis revealed D-dimer levels >400-800 ng/ml and AT-III level of <71% at admission were associated with high mortality (OR 11.2, AUROC 0.70 and OR 16.6, AUROC 0.82 respectively) as well as predicted organ failure. Conclusion: Serum D-dimer and antithrombin-III levels can be used to assess disease severity and predict outcome of patients with acute pancreatitis.

A number of analysis tools have been developed for the estimation of brain atrophy using MRI. Since brain atrophy is being increasingly used as a marker of disease progression in many neuro-degenerative diseases such as Multiple Sclerosis and Alzheimer's disease, the validation of these tools is an important task. However, this is complex, in the real scenario, due to the absence of gold standards for comparison. In order to create gold standards, we first propose an approach for the realistic simulation of brain tissue loss that relies on the estimation of a topology preserving B-spline based deformation fields. Using these gold standards, an evaluation of the performance of three standard brain atrophy estimation methods (SIENA, SIENAX and BSI-UCD), on the basis of their robustness to various sources of error (bias-field inhomogeneity, noise, geometrical distortions, interpolation artefacts and presence of lesions), is presented. Our evaluation shows that, in general, bias-field inhomogeneity and noise lead to larger errors in the estimated atrophy than geometrical distortions and interpolation artefacts. Experiments on 18 different anatomical models of the brain after simulating whole brain atrophies in the range of 0.2-1.5% indicate that, in the presence of bias-field inhomogeneity and noise, a mean error of 0.64+/-0.53%,4.00+/-2.41% and 1.79+/-0.97% may be expected in the atrophy estimated by SIENA, SIENAX and BSI-UCD, respectively.