While nanocrystalline diamond is quickly becoming one of the most widely studied nanomaterials, achieving a large fraction of diamond nanoparticles in a polymer coating has been an unresolved problem. In this work, polymer nano- and microfibers containing high loadings of 5 nm diamond particles (up to 80 wt % in polyacrylonitrile and 40% in polyamide 11) have been demonstrated using electrospun nanofibers as a delivery vehicle. The electrospun nanofibers with a high load of nanodiamond in the polymers were fused into thin transparent films, which had high mechanical properties; an improvement of 4 times for the Young's modulus and 2 times for the hardness was observed already at 20% nanodiamond in polyamide 11. These films can provide UV protection and scratch resistance to a variety of surfaces, especially in applications where a combination of mechanical, thermal, and dielectric properties is required.

BackgroundTo evaluate a knowledge based planning model for RapidPlan (RP) generated for advanced head and neck cancer (HNC) patient treatments, as well its ability to possibly improve the clinical plan quality. The stability of the model was assessed also for a different beam geometry, different dose fractionation and different management of bilateral structures (parotids).MethodsDosimetric and geometric data from plans of 83 patients presenting HNC were selected for the model training. All the plans used volumetric modulated arc therapy (VMAT, RapidArc) to treat two targets at dose levels of 69.96 and 54.45 Gy in 33 fractions with simultaneous integrated boost. Two models were generated, the first separating the ipsi- and contra-lateral parotids, while the second associating the two parotids to a single structure for training. The optimization objectives were adjusted to the final model to better translate the institutional planning and dosimetric strategies and trade-offs. The models were validated on 20 HNC patients, comparing the RP generated plans and the clinical plans. RP generated plans were also compared between the clinical beam arrangement and a simpler geometry, as well as for a different fractionation scheme.ResultsRP improved significantly the clinical plan quality, with a reduction of 2 Gy, 5 Gy, and 10 Gy of the mean parotid, oral cavity and laryngeal doses, respectively. A simpler beam geometry was deteriorating the plan quality, but in a small amount, keeping a significant improvement relative to the clinical plan. The two models, with one or two parotid structures, showed very similar results. NTCP evaluations indicated the possibility of improving (NTCP decreasing of about 7%) the toxicity profile when using the RP solution.ConclusionsThe HNC RP model showed improved plan quality and planning stability for beam geometry and fractionation. An adequate choice of the objectives in the model is necessary for the trade-offs strategies.

For optimal setting applied in the algorithm configuration phase, the agreement of Acuros calculations with measurements could achieve the 3% for MLC-defined fields as small as 0.5 × 0.5 cm. Similar agreement was found for AAA for fields as small as 1 × 1 cm.

A systematic study of the PTW microDiamond (MD) output factors (OF) is reported, aimed at clarifying its response in small fields and investigating its suitability for small field reference dosimetry. Ten MDs were calibrated under Co irradiation. OF measurements were performed in 6 MV photon beams by a CyberKnife M6, a Varian DHX and an Elekta Synergy linacs. Two PTW silicon diodes E (Si-D) were used for comparison. The results obtained by the MDs were evaluated in terms of absorbed dose to water determination in reference conditions and OF measurements, and compared to the results reported in the recent literature. To this purpose, the Monte Carlo (MC) beam-quality correction factor, [Formula: see text], was calculated for the MD, and the small field output correction factors, [Formula: see text], were calculated for both the MD and the Si-D by two different research groups. An empirical function was also derived, providing output correction factors within 0.5% from the MC values calculated for all of the three linacs. A high reproducibility of the dosimetric properties was observed among the ten MDs. The experimental [Formula: see text] values are in agreement within 1% with the MC calculated ones. Output correction factors within  +0.7% and  -1.4% were obtained down to field sizes as narrow as 5 mm. The resulting MD and Si-D field factors are in agreement within 0.2% in the case of CyberKnife measurements and 1.6% in the other cases. This latter higher spread of the data was demonstrated to be due to a lower reproducibility of small beam sizes defined by jaws or multi leaf collimators. The results of the present study demonstrate the reproducibility of the MD response and provide a validation of the MC modelling of this device. In principle, accurate reference dosimetry is thus feasible by using the microDiamond dosimeter for field sizes down to 5 mm.

PurposeTo determine if the performance of a knowledge based RapidPlan (RP) planning model could be improved with an iterative learning process, i.e. if plans generated by an RP model could be used as new input to re-train the model and achieve better performance.MethodsClinical VMAT plans from 83 patients presenting with head and neck cancer were selected to train an RP model, CL-1. With this model, new plans on the same patients were generated, and subsequently used as input to train a novel model, CL-2. Both models were validated on a cohort of 20 patients and dosimetric results compared. Another set of 83 plans was realised on the same patients with different planning criteria, by using a simple template with no attempt to manually improve the plan quality. Those plans were employed to train another model, TP-1. The differences between the plans generated by CL-1 and TP-1 for the validation cohort of patients were compared with respect to the differences between the original plans used to build the two models.ResultsThe CL-2 model presented an improvement relative to CL-1, with higher R2 values and better regression plots. The mean doses to parallel organs decreased with CL-2, while D1% to serial organs increased (but not significantly). The different models CL-1 and TP-1 were able to yield plans according to each original strategy.ConclusionA refined RP model allowed the generation of plans with improved quality, mostly for parallel organs at risk and, possibly, also the intrinsic model quality.

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PurposeTo appraise the ability of a radiomics signature to predict clinical outcome after stereotactic body radiation therapy (SBRT) for pancreas carcinoma.MethodsA cohort of 100 patients was included in this retrospective, single institution analysis. Radiomics texture features were extracted from computed tomography (CT) images obtained for the clinical target volume. The cohort of patients was randomly divided into two separate groups for the training (60 patients) and validation (40 patients). Cox regression models were built to predict overall survival and local control. The significant predictors at univariate analysis were included in a multivariate model. The quality of the models was appraised by means of area under the curve and concordance index.ResultsA clinical-radiomic signature associated with Overall Survival (OS) was found significant in both training and validation sets (p = 0.01 and 0.05 and concordance index 0.73 and 0.75 respectively). Similarly, a signature was found for Local Control (LC) with p = 0.007 and 0.004 and concordance index 0.69 and 0.75. In the low risk group, the median OS and LC in the validation group were 14.4 and 28.6 months while in the high-risk group were 9.0 and 17.5 months respectively.ConclusionA CT based radiomic signature was identified which correlate with OS and LC after SBRT and allowed to identify low and high-risk groups of patients.