Treatment with (90)Y- and (177)Lu-DOTATOC in patients with metastatic neuroendocrine tumors

BACKGROUND: Treatment with (90)Y- or (177)Lu-DOTATOC has recently been introduced in the palliative treatment of somatostatin receptor-expressing neuroendocrine tumors (NETs). The aim of the study was to present clinical experience with (90)Y- and (177)Lu-DOTATOC therapy in the management of NET. METHODS: To prove suitability for treatment each patient underwent scanning with (111)In-DTPAOC or (68)Ga-DOTATOC positron emission tomography/computed tomography. All patients received [(90)Y-DOTATOC] as initial treatment. In case of disease relapse the treatment was repeated. To avoid side effects of repeated [(90)Y] applications, a switch to [(177)Lu-DOTATOC] was carried out. Clinical, biochemical, and radioimaging responses were documented. RESULTS: Twenty patients with metastatic nonresectable NETs (15 pancreas NETs, 2 midgut NETs, 1 gastrinoma, 1 paraganglioma, 1 NET of unknown primary origin) were included. In 8 patients the treatment was repeated more than once (mean, 3 times; range, 2-5 times). After [(90)Y] treatment moderate toxicity was observed in 8 patients. No serious adverse events were documentable. After restaging, a partial remission was found in 5 patients, stable disease in 11 patients, and tumor progression in 4 patients. CONCLUSIONS: Peptide receptor-targeted radionuclide therapy is a promising, safe, and feasible approach in the palliative therapy of patients with NET.

Mobility and Bandwidth Prediction as a Service in Virtualized LTE Systems

Recently telecommunication industry benefits from infrastructure sharing, one of the most fundamental enablers of cloud computing, leading to emergence of the Mobile Virtual Network Operator (MVNO) concept. The most momentous intents by this approach are the support of on-demand provisioning and elasticity of virtualized mobile network components, based on data traffic load. To realize it, during operation and management procedures, the virtualized services need be triggered in order to scale-up/down or scale-out/in an instance. In this paper we propose an architecture called MOBaaS (Mobility and Bandwidth Availability Prediction as a Service), comprising two algorithms in order to predict user(s) mobility and network link bandwidth availability, that can be implemented in cloud based mobile network structure and can be used as a support service by any other virtualized mobile network services. MOBaaS can provide prediction information in order to generate required triggers for on-demand deploying, provisioning, disposing of virtualized network components. This information can be used for self-adaptation procedures and optimal network function configuration during run-time operation, as well. Through the preliminary experiments with the prototype implementation on the OpenStack platform, we evaluated and confirmed the feasibility and the effectiveness of the prediction algorithms and the proposed architecture.