Lexicographic optimization-based planning for stereotactic radiosurgery of brain metastases.

AIM: To validate a fully-automated lexicographic optimization-planning system (mCycle, Elekta) for single-(SL) and multiple-(ML, up to 4 metastases) lesions in intracranial stereotactic radiosurgery (SRS, 21 Gy, single fraction). METHODS: A pre-determined priority list, Wish-List (WL), represents a dialogue between planner and clinician, establishing strict constraints and pursuing objectives. In order to satisfy the clinical protocol without manual intervention, four patients were required to tweak and fine-tune each WL (SLp, MLp) for coplanar arcs. Thirty-five testing plans (20 SLp, 15 MLp) were automatically re-planned (mCP). Automatic and manual plans were compared including dose constraints, conformality, modulation complexity score (MCS), delivery time, and local gamma analysis (2%/2 mm). To ensure plan clinical acceptability, two radiation oncologists conducted an independent blind plan choice. RESULTS: Each WL-tuning took 3 days. Estimated median manual plans and mCP calculation time were 8 and 3 h, respectively. Significant increases in SLp and MLp target coverage and conformity were registered. mCP showed a not significant and clinically acceptable higher median brain V12Gy. SLp registered a -5.8% MU decrease with comparable median delivery time (MP 2.0 min, mCP 1.9 min) while MLp showed a +9.8% MU increase and longer delivery time (MP 3.5 min, mCP 4.4 min). mCP MCS resulted significantly higher without affecting gamma passing rates. At blind choice, mCP were preferred in the majority of cases. CONCLUSIONS: Lexicographic optimization produced acceptable SRS plans with coplanar arcs significantly reducing the overall planning time in cases with up to 4 brain metastases. These planning improvements suggest further investigations by setting high-quality non-coplanar arc plans as a reference.

Graphene Oxide Membranes for Trace Hydrocarbon Contaminant Removal from Aqueous Solution.

The aim of this paper is to shed light on the application of graphene oxide (GO) membranes for the selective removal of benzene, toluene, and xylene (BTX) from wastewater. These molecules are present in traces in the water produced from oil and gas plants and are treated now with complex filtration systems. GO membranes are obtained by a simple, fast, and scalable method. The focus of this work is to prove the possibility of employing GO membranes for the filtration of organic contaminants present in traces in oil and gas wastewater, which has never been reported. The stability of GO membranes is analyzed in water solutions with different pH and salinity. Details of the membrane preparation are provided, resulting in a crucial step to achieve a good filtration performance. Material characterization techniques such as electron microscopy, x-ray diffraction, and infrared spectroscopy are employed to study the physical and chemical structure of GO membranes, while gas chromatography, UV-visible spectroscopy, and gravimetric techniques allow the quantification of their filtration performance. An impressive rejection of about 90% was achieved for 1 ppm of toluene and other pollutants in water, demonstrating the excellent performance of GO membranes in the oil and gas field.