EP-1349: Long term results of a phase I-II study of moderate hypofractionated IGRT in prostate cancer

Pregnant women diagnosed with gestational diabetes mellitus subjected to diet (GDMd) that do not reach normal glycaemia are passed to insulin therapy (GDMi). GDMd associates with increased human cationic amino acid transporter 1 (hCAT-1)-mediated transport of L-arginine and nitric oxide synthase (NOS) activity in foetoplacental vasculature, a phenomenon reversed by exogenous insulin. Whether insulin therapy results in reversal of the GDMd effect on the foetoplacental vasculature is unknown. We assayed whether insulin therapy normalizes GDMd-associated foetoplacental endothelial dysfunction. Primary cultures of human umbilical vein endothelial cells (HUVECs) from GDMi pregnancies were used to assay L-arginine transport kinetics, NOS activity, p44/42mapk and protein kinase B/Akt activation, and umbilical vein rings reactivity. HUVECs from GDMi or GDMd show increased hCAT-1 expression and maximal transport capacity, NOS activity, and eNOS, and p44/42mapk, but not Akt activator phosphorylation. Dilation in response to insulin or calcitonin-gene related peptide was impaired in umbilical vein rings from GDMi and GDMd pregnancies. Incubation of HUVECs in vitro with insulin (1 nmol/L) restored hCAT-1 and eNOS expression and activity, and eNOS and p44/42mapk activator phosphorylation. Thus, maternal insulin therapy does not seem to reverse GDMd-associated alterations in human foetoplacental vasculature.Fondo Nacional de Desarrollo Científico y Tecnológico Chileno 1150377 , 1150344 , 11150083Servicio de Salud de Medicina Oriente de Chile 1938–2016Marie Curie International Research 295185 - EULAMDIM

Stochastic inverse modeling of transient laboratory-scale three-dimensional two-phase core flooding scenarios

We develop a comprehensive and efficient workflow for a stochastic assessment of key parameters governing two-phase flow conditions associated with core-scale experiments. We rely on original and detailed datasets collected on a Berea sandstone sample. These capture the temporal evolution of pressure drop across the core and three-dimensional maps of phase saturations (determined via X-ray CT) in oil- and brine-displacement flooding scenarios characterized by diverse brine/oil viscosity contrasts. Such experiments are used as a test-bed for the proposed stochastic model calibration strategy. The latter is structured across three main steps: (i) a preliminary calibration, aimed at identifying a behavioral region of the model parameter space; (ii) a Global Sensitivity Analysis (GSA), geared towards identification of the relative importance of model parameters on observed model outputs and assessment of non-influential parameters to reduce dimensionality of the parameter space; and (iii) a stochastic inverse modeling procedure. The latter is based on a differential-evolution genetic algorithm to efficiently explore the reduced parameter space stemming from the GSA. It enables one to obtain a probabilistic description of the relevant model parameters through their frequency distributions conditional on the detailed type of information collected. Coupling GSA with a stochastic parameter estimation approach based on a genetic algorithm of the type we consider enables streamlining the procedure and effectively cope with the considerable computational efforts linked to the two-phase scenario considered. Results show a remarkable agreement with experimental data and imbue us with confidence on the potential of the approach to embed the type of rich datasets considered towards model parameter estimation fully including uncertainty

Acute kidney injury and acute kidney disease in high-dose cisplatin-treated head and neck cancer

Background: In locally advanced head and neck squamous cell carcinoma (LA-SCCHN) at least 200mg/m2 (standard dose 300 mg/m2) of cisplatin concomitant with radiotherapy represents the standard of care, both in postoperative and conservative settings. Nevertheless, high dose administration every 3 weeks is often replaced with low dose weekly cisplatin to avoid toxicities like kidney injury, though often failing to reach the therapeutic dose. Our aim was to investigate the incidence of renal impairment in the real-life setting, integrating high dose cisplatin with adequate supportive therapy, and to explore both Acute Kidney Injury (AKI) and Acute Kidney Disease (AKD), a recently described clinical renal syndrome that encompasses functional alterations of the kidney lasting fewer than 3 months. Methods: One hundred and nine consecutive patients affected by LA-SCCHN and treated with at least a cumulative dosage of 200 mg/m2 of cisplatin concomitant with radiotherapy were enrolled in this prospective observational study. Results: AKI was reported in 12.8% of patients, 50% of whom were stage 1 (KDIGO criteria), while 25.7% of the cohort developed AKD. Patients with baseline estimated Glomerular Filtration Rate (eGFR) < 90 ml/min showed a higher incidence of AKD (36.2% vs 17.7%). Hypertension, baseline eGFR, and therapy with Renin-angiotensin-aldosterone system inhibitors proved to be significant factors associated with both AKI and AKD. Conclusion: AKI and AKD are not rare complications of high-dose cisplatin, but an appropriate prevention strategy and accurate monitoring of patients during treatment could lead to a reduction of the burden of these conditions

Stochastic inverse modeling of transient laboratory-scale three-dimensional two-phase core flooding scenarios

We develop a comprehensive and efficient workflow for a stochastic assessment of key parameters governing two-phase flow conditions associated with core-scale experiments. We rely on original and detailed datasets collected on a Berea sandstone sample. These capture the temporal evolution of pressure drop across the core and three-dimensional maps of phase saturations (determined via X-ray CT) in oil- and brine-displacement flooding scenarios characterized by diverse brine/oil viscosity contrasts. Such experiments are used as a test-bed for the proposed stochastic model calibration strategy. The latter is structured across three main steps: (i) a preliminary calibration, aimed at identifying a behavioral region of the model parameter space; (ii) a Global Sensitivity Analysis (GSA), geared towards identification of the relative importance of model parameters on observed model outputs and assessment of non-influential parameters to reduce dimensionality of the parameter space; and (iii) a stochastic inverse modeling procedure. The latter is based on a differential-evolution genetic algorithm to efficiently explore the reduced parameter space stemming from the GSA. It enables one to obtain a probabilistic description of the relevant model parameters through their frequency distributions conditional on the detailed type of information collected. Coupling GSA with a stochastic parameter estimation approach based on a genetic algorithm of the type we consider enables streamlining the procedure and effectively cope with the considerable computational efforts linked to the two-phase scenario considered. Results show a remarkable agreement with experimental data and imbue us with confidence on the potential of the approach to embed the type of rich datasets considered towards model parameter estimation fully including uncertainty.Funding was provided by Eni. A.D. acknowledges the funding by the European Commission through the Marie Sklodowska-Curie Individual Fellowship, research project ‘MixUQ’ Grant Agreement No. 895152. The software developed in this study (4D-CoreINV) is protected by copyright.Peer reviewe

Skin DVHs predict cutaneous toxicity in Head and Neck Cancer patients treated with Tomotherapy

Purpose: To explore the association between planning skin dose-volume data and acute cutaneous toxicity after Radio–chemotherapy for Head and Neck (HN) cancer patients. Methods: Seventy HN patients were treated with Helical Tomotherapy (HT) with radical intent (SIB technique: 54/66 Gy to PTV1/PTV2 in 30fr) ± chemotherapy superficial body layer 2 mm thick (SL2) was delineated on planning CT. CTCAE v4.0 acute skin toxicity data were available. Absolute average Dose-Volume Histograms (DVH) of SL2 were calculated for patients with severe (G3) and severe/moderate (G3/G2) skin acute toxicities. Differences against patients with none/mild toxicity (G0/G1) were analyzed to define the most discriminative regions of SL2 DVH; univariable and multivariable logistic analyses were performed on DVH values, CTV volume, age, sex, chemotherapy. Results: Sixty-one % of patients experienced G2/G3 toxicity (rate of G3 = 19%). Differences in skin DVHs were significant in the range 53-68Gy (p-values: 0.005–0.01). V56/V64 were the most predictive parameters for G2/G3 (OR = 1.12, 95%CI = 1.03–1.21, p = 0.001) and G3 (OR = 1.13, 95%CI = 1.01–1.26, p = 0.027) with best cut-off of 7.7cc and 2.7cc respectively. The logistic model for V56 was well calibrated being both, slope and R2, close to 1. Average V64 were 2.2cc and 6cc for the two groups (G3 vs G0-G2 toxicity); the logistic model for V64 was quite well calibrated, with a slope close to 1 and R2 equal to 0.60. Conclusion: SL2 DVH is associated with the risk of acute skin toxicity. Constraining V64 < 3cc (equivalent to a 4x4cm2 skin surface) should keep the risk of G3 toxicity below or around 10%