Pretreatment prognostic value of dynamic contrast-enhanced magnetic resonance imaging vascular, texture, shape, and size parameters compared with traditional survival indicators obtained from locally advanced breast cancer patients

Objectives: The aim of this study was to determine if associations exist between pretreatment dynamic contrast-enhanced (DCE) magnetic resonance imaging (MRI)-based metrics (vascular kinetics, texture, shape, size) and survival intervals. Furthermore, the aim of this study was to compare the prognostic value of DCE-MRI parameters against traditional pretreatment survival indicators. Materials and Methods: A retrospective study was undertaken. Approval had previously been granted for the retrospective use of such data, and the need for informed consent was waived. Prognostic value of pretreatment DCE-MRI parameters and clinical data was assessed via Cox proportional hazards models. The variables retained by the final overall survival Cox proportional hazards model were utilized to stratify risk of death within 5 years. Results: One hundred twelve subjects were entered into the analysis. Regarding disease-free survival-negative estrogen receptor status, T3 or higher clinical tumor stage, large ( > 9.8 cm 3 ) MR tumor volume, higher 95th percentile ( > 79%) percentage enhancement, and reduced ( > 0.22) circularity represented the retained model variables. Similar results were noted for the overall survival with negative estrogen receptor status, T3 or higher clinical tumor stage, and large ( > 9.8 cm 3 ) MR tumor volume, again all been retained by the model in addition to higher ( > 0.71) 25th percentile area under the enhancement curve. Accuracy of risk stratification based on either traditional (59%) or DCEMRI (65%) survival indicators performed to a similar level. However, combined traditional and MR risk stratification resulted in the highest accuracy (86%). Conclusions: Multivariate survival analysis has revealed thatmodel-retained DCEMRI variables provide independent prognostic information complementing traditional survival indicators and as such could help to appropriately stratify treatment

Locality and exponential error reduction in numerical lattice gauge theory

In non-abelian gauge theories without matter fields, expectation values of large Wilson loops and loop correlation functions are difficult to compute through numerical simulation, because the signal-to-noise ratio is very rapidly decaying for increasing loop sizes. Using a multilevel scheme that exploits the locality of the theory, we show that the statistical errors in such calculations can be exponentially reduced. We explicitly demonstrate this in the SU(3) theory, for the case of the Polyakov loop correlation function, where the efficiency of the simulation is improved by many orders of magnitude when the area bounded by the loops exceeds 1 fm^2.Comment: Plain TeX source, 18 pages, figures include