MRI-based contrast clearance analysis shows high differentiation accuracy between radiation-induced reactions and progressive disease after cranial radiotherapy

BACKGROUND: Pseudoprogression (PsP) or radiation necrosis (RN) may frequently occur after cranial radiotherapy and show a similar imaging pattern compared with progressive disease (PD). We aimed to evaluate the diagnostic accuracy of magnetic resonance imaging-based contrast clearance analysis (CCA) in this clinical setting. PATIENTS AND METHODS: Patients with equivocal imaging findings after cranial radiotherapy were consecutively included into this monocentric prospective study. CCA was carried out by software-based automated subtraction of imaging features in late versus early T1-weighted sequences after contrast agent application. Two experienced neuroradiologists evaluated CCA with respect to PsP/RN and PD being blinded for histological findings. The radiological assessment was compared with the histopathological results, and its accuracy was calculated statistically. RESULTS: A total of 33 patients were included; 16 (48.5%) were treated because of a primary brain tumor (BT), and 17 (51.1%) because of a secondary BT. In one patient, CCA was technically infeasible. The accuracy of CCA in predicting the histological result was 0.84 [95% confidence interval (CI) 0.67-0.95; one-sided P = 0.051; n = 32]. Sensitivity and specificity of CCA were 0.93 (95% CI 0.66-1.00) and 0.78 (95% CI 0.52-0.94), respectively. The accuracy in patients with secondary BTs was 0.94 (95% CI 0.71-1.00) and nonsignificantly higher compared with patients with primary BT with an accuracy of 0.73 (95% CI 0.45-0.92), P = 0.16. CONCLUSIONS: In this study, CCA was a highly accurate, easy, and helpful method for distinguishing PsP or RN from PD after cranial radiotherapy, especially in patients with secondary tumors after radiosurgical treatment

IFIP WG 13.2 workshop on user experience and user-centered development processes

\u3cp\u3eThis workshop focusses on the interplay of user experience (UX) and user-centered development processes of interactive systems. It is organized by the IFIP Working Group 13.2 on Human-Centered Software Methodologies. It is proposed as a follow-up activity started at an interactive session organized at HCSE 2014. Our ultimate goal is bringing together researchers and practitioners to discuss real-life case studies featuring success and/or failure stories of development processes that take into account UX as an important dimension for the interactive system at concern. Based on these discussions, we expect to deepen the understanding of problems and challenges when dealing with UX in the software development process.\u3c/p\u3

Quantification of Hv1-induced proton translocation by a lipid-coupled Oregon Green 488-based assay

Passive proton translocation across membranes through proton channels is generally measured with assays that allow a qualitative detection of the H+-transfer. However, if a quantitative and time-resolved analysis is required, new methods have to be developed. Here, we report on the quantification of pH changes induced by the voltage-dependent proton channel Hv1 using the commercially available pH-sensitive fluorophore Oregon Green 488-DHPE (OG488-DHPE). We successfully expressed and isolated Hv1 from Escherichia coli and reconstituted the protein in large unilamellar vesicles. Reconstitution was verified by surface enhanced infrared absorption (SEIRA) spectroscopy and proton activity was measured by a standard 9-amino-6-chloro-2-methoxyacridine assay. The quantitative OG488-DHPE assay demonstrated that the proton translocation rate of reconstituted Hv1 is much smaller than those reported in cellular systems. The OG488-DHPE assay further enabled us to quantify the KD-value of the Hv1-inhibitor 2-guanidinobenzimidazole, which matches well with that found in cellular experiments. Our results clearly demonstrate the applicability of the developed in vitro assay to measure proton translocation in a quantitative fashion; the assay allows to screen for new inhibitors and to determine their characteristic parameters. Graphical abstract ᅟ