To identify key dosimetric parameters that have close associations with tumor treatment response and body weight change in SFRT treatments with a large range of spatial-fractionation scale at dose rates of several Gy/min. Methods Six study arms using uniform tumor radiation, half-tumor radiation, 2mm beam array radiation, 0.3mm minibeam radiation, and an untreated arm were used. All treatments were delivered on a 320kV x-ray irradiator. Forty-two female Fischer 344 rats with fibrosarcoma tumor allografts were used. Dosimetric parameters studied are peak dose and width, valley dose and width, peak-to-valley-dose-ratio (PVDR), volumetric average dose, percentage volume directly irradiated, and tumor-and normal-tissue EUD. Animal survival, tumor volume change, and body weight change (indicative of treatment toxicity) are tested for association with the dosimetric parameters using linear regression and Cox Proportional Hazards models. Results The dosimetric parameters most closely associated with tumor response are tumor EUD (R 2 = 0.7923, F-stat = 15.26*; z-test =-4.07***), valley (minimum) dose (R 2 = 0.7636, Fstat = 12.92*; z-test =-4.338***), and percentage tumor directly irradiated (R 2 = 0.7153, Fstat = 10.05*; z-test =-3.837***) per the linear regression and Cox Proportional Hazards models, respectively. Tumor response is linearly proportional to valley (minimum) doses

Background The electronic cigarette industry is growing, with youth using e-cigarettes at higher rates than they are using cigarettes, and retail and online sales projected to reach $10 billion in 2017. Minimal regulation of the production and marketing of e-cigarettes exists to date, which has allowed companies to promote unsupported claims. We assessed the shipping, product features and packaging of a wide variety of e-cigarettes purchased online by adults and youth. Methods The most popular internet e-cigarette vendors were identified from a larger study of internet tobacco vendors. Between August 2013 and June 2014, adults made 56 purchase attempts from online vendors, and youth made 98 attempts. Packages received were assessed for exterior and internal packaging features, including product information, health warnings and additional materials. Results We analysed a total of 125 orders featuring 86 unique brands of e-cigarettes. The contents were rarely indicated on package exteriors. Product information came with just 60% of orders and just 38.4% included an instruction manual. Only 44.6% of products included a health warning, and some had unsupported claims, such as lack of secondhand smoke exposure. Additionally, some products were leaking e-liquid and battery fluid on arrival. Conclusions A large variety of e-cigarette products are manufactured and marketed to consumers. Many products do not include instructions for use, and unsupported claims are being presented to consumers. Effective federal regulation of the manufacturing, packaging, product information and health claims surrounding e-cigarettes is necessary to ensure consumers are presented with accurate e-cigarette use information.

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2728 Abstract 29 Purpose: To identify key dosimetric parameters that have close associations with tumor treatment 30 response and body weight change in SFRT treatments with a large range of spatial-fractionation 31 scale at dose rates of several Gy/min. 32 Methods: Six study arms using uniform tumor radiation, half-tumor radiation, 2mm beam array 33 radiation, 0.3mm minibeam radiation, and an untreated arm were used. All treatments were 34 delivered on a 320kV x-ray irradiator. Forty-two female Fischer 344 rats with fibrosarcoma tumor 35 allografts were used. Dosimetric parameters studied are peak dose and width, valley dose and 36 width, peak-to-valley-dose-ratio, volumetric average dose, percentage volume directly irradiated, 37 and tumor-and normal-tissue EUD. Animal survival, tumor volume change, and body weight 38 change (indicative of treatment toxicity) are tested for association with the dosimetric parameters 39 using linear regression and Cox Proportional Hazards models.

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