Proton form factors: Measurement of the proton form factors ratio up to Q(2) = 5.6 GEV(2) by recoil polarimetry

In this thesis, we present the results of the experiment E99-007, which measured the ratio of the electric to magnetic form factors of the proton to the four momentum transfer square Q2 = 5.6 GeV2, by recoil polarimetry. Data were taken in 2000 at the Thomas Jefferson National Accelerator Facility in Virginia, USA. A 4.6 GeV polarized electron beam was scattered off a cryogenic hydrogen target. The polarization of the recoil proton was measured in the Focal Plane Polarimeter, located after one of the two High Resolution Spectrometers in the hall. The ratio of the transverse to longitudinal components of the recoil proton polarization is proportional to the ratio of the form factors. Elastic events were selected by detecting the scattered electron in a large acceptance lead-glass calorimeter.;The main result of this experiment is the linear decrease of the form factor ratio with increasing Q2, corresponding to different spatial distributions of the electric charge and the magnetization. Numerous theoretical calculations show that relativistic effects, such as mixing of spin states due to Lorentz boosts, are important to account for the observed data in this critical intermediate kinematic region

A genetic algorithm for variable selection in logistic regression analysis of radiotherapy treatment outcomes: A genetic algorithm for radiotherapy outcome modeling

A given outcome of radiotherapy treatment can be modeled by analyzing its correlation with a combination of dosimetric, physiological, biological, and clinical factors, through a logistic regression fit of a large patient population. The quality of the fit is measured by the combination of the predictive power of this particular set of factors and the statistical significance of the individual factors in the model. We developed a genetic algorithm (GA), in which a small sample of all the possible combinations of variables are fitted to the patient data. New models are derived from the best models, through crossover and mutation operations, and are in turn fitted. The process is repeated until the sample converges to the combination of factors that best predicts the outcome. The GA was tested on a data set that investigated the incidence of lung injury in NSCLC patients treated with 3DCRT. The GA identified a model with two variables as the best predictor of radiation pneumonitis: the V30 (p=0.048) and the ongoing use of tobacco at the time of referral (p=0.074). This two-variable model was confirmed as the best model by analyzing all possible combinations of factors. In conclusion, genetic algorithms provide a reliable and fast way to select significant factors in logistic regression analysis of large clinical studies

Proton form factors : measurement of the proton form factors ratio mu_pG_Ep/G_Mp to Q^2 = 5.6 GeV^2 by recoil polarimetry

In this thesis, we present the results of the experiment E99-007, which measured the ratio of the electric to magnetic form factors of the proton to the four momentum transfer square Q2 = 5.6 GeV2, by recoil polarimetry. Data were taken in 2000 at the Thomas Jefferson National Accelerator Facility in Virginia, USA. A 4.6 GeV polarized electron beam was scattered off a cryogenic hydrogen target. The polarization of the recoil proton was measured in the Focal Plane Polarimeter, located after one of the two High Resolution Spectrometers in Hall A. The ratio of the transverse to longitudinal components of the recoil proton polarization is proportional to the ratio of the form factors. Elastic events were selected by detecting the scattered electron in a large acceptance lead-glass calorimeter. The main result of this experiment is the linear decrease of the form factor ratio with increasing Q2, corresponding to different spatial distributions of the electric charge and the magnetization. Numerous theoretical calculations show that relativistic effects, such as mixing of spin states due to Lorentz boosts, are important to account for the observed data in this critical intermediate kinematic region.Dans cette thèse sont présentés les résultats de l'expérience E99-007, qui a mesuré le rapport des facteurs de forme électrique et magnétique du proton, jusqu'au quadri-moment de transfert Q2 = 5.6 GeV2, par polarisation de recul. Les données ont été prises en 2000 au Thomas Jefferson National Accelerator Facility en Virginie, Etats-Unis. Un faisceau d'électrons polarisés de 4.6 GeV a été diffusé sur une cible d'hydrogène liquide. La polarisation du proton de recul était mesurée dans le Polarimètre du Plan Focal, situé à l'extrémité de l'un des deux Spectromètres à Haute Résolution du Hall A. Le rapport des composantes transverse et longitudinale de la polarisation du proton de recul est proportionnel au rapport des facteurs de forme. Les événements élastiques étaient identifiés en détectant l'électron diffusé dans un calorimètre en verre au plomb de grande acceptance. Le résultat principal de cette expérience est la décroissance linéaire du rapport des facteurs de forme quand Q2 augmente, correspondant à des distributions spatiales différentes de la charge électrique et de la magnétisation. De nombreux calculs théoriques montrent que des effets relativistes, comme le mélange des états de spin dûs à des transformations de Lorentz, doivent être pris en compte pour expliquer les résultats observés dans cette région cinématique critique

Facteurs de forme du proton. Mesure du rapport des facteurs de forme du proton P GEp/GMp jusqu'à Q2 = 5.6 GeV2 par polarisation de recul

CLERMONT FD-BCIU Sci.et Tech. (630142101) / SudocSudocFranceF

Evaluation of intraoperative magnetic resonance imaging/ultrasound fusion optimization for low-dose-rate prostate brachytherapy

Purpose: Intraoperative planning with transrectal ultrasound (US) is used for accurate seed placement and optimal dosimetry in prostate brachytherapy. However, prostate magnetic resonance imaging (MRI) has shown superiority in delineation of prostate anatomy. Accordingly, MRI/US fusion may be useful for accurate intraoperative planning. We analyzed planning with MRI/US fusion to compare differences in dosimetry and volume to that derived from the postoperative computed tomography (CT). Material and methods: Twenty patients underwent preoperative prostate MRI, which was fused intraoperatively with US during prostate brachytherapy. Intraoperative 125I or 103Pd seed placement was modified by the use of MRI fusion when indicated. Following implantation, dose comparisons were made between data derived from MRI/US and that from post-operative CT scans. Plan parameters analyzed included the D90 (dose to 90% of the prostate), rectal D30, V30 (volume of the rectum receiving 30 percent of dose), and prostate V100. Results: The median number of seeds implanted per patient was seventy-six. The MRI measured prostate volume, which was on average 4.47 cc larger than the CT measured prostate volume. In 9 patients, the apex of the prostate was better identified under MRI with the fusion protocol, and an average of 4 fewer seeds were required to be placed in the apex/urinary sphincter region. Both MRI and US individually showed a reduced intraoperative prostate D90 in comparison to the postoperative CT, with a larger mean difference for MRI in comparison with US (9.71 vs. 4.31 Gy, p = 0.007). This was also true for the prostate V100 (5.18 vs. 2.73 cc, p = 0.009). Post-operative CT underestimated rectal D30 and V30 in comparison to both MRI and US with MRI showing a larger mean difference than US for D30 (40.64 vs. 35.92 Gy, p = 0.04) and V30 (50.20 vs. 44.38 cc, p = 0.009). Conclusions: The MRI/US fusion demonstrated greater prostate volume compared to standard CT/US based planning likely due to the better resolution of the prostate apex. Furthermore, rectal dose was underestimated with CT vs. MRI based planning. Additional study is required to assess long-term clinical implications of disease control and effects on long-term toxicity, especially as related to the rectum and urinary sphincter. MRI/US intraoperative fusion may improve prostate dosimetry while sparing the rectum and urethra, potentially impacting disease control and late toxicity

Measurement of G

The ratio of the electric and magnetic form factors of the proton, G{sub E{sub p}}/G{sub M{sub p}}, was measured at the Thomas Jefferson National Accelerator Facility (JLab) using the recoil polarization technique. The ratio of the form factors is directly proportional to the ratio of the transverse to longitudinal components of the polarization of the recoil proton in the elastic {rvec e}p {yields} e{rvec p} reaction. The new data presented in this article span the range 3.5 < Q{sup 2} < 5.6 GeV{sup 2} and are well described by a linear Q{sup 2} fit. Also, the ratio QF{sub 2p}/F{sub 1p} reaches a constant value above Q{sup 2}=2 GeV{sup 2}

A genetic algorithm for variable selection in logistic regression analysis of radiotherapy treatment outcomes

A given outcome of radiotherapy treatment can be modeled by analyzing its correlation with a combination of dosimetric, physiological, biological, and clinical factors, through a logistic regression fit of a large patient population. The quality of the fit is measured by the combination of the predictive power of this particular set of factors and the statistical significance of the individual factors in the model. We developed a genetic algorithm (GA), in which a small sample of all the possible combinations of variables are fitted to the patient data. New models are derived from the best models, through crossover and mutation operations, and are in turn fitted. The process is repeated until the sample converges to the combination of factors that best predicts the outcome. The GA was tested on a data set that investigated the incidence of lung injury in NSCLC patients treated with 3DCRT. The GA identified a model with two variables as the best predictor of radiation pneumonitis: the V30 (p=0.048) and the ongoing use of tobacco at the time of referral (p=0.074). This two-variable model was confirmed as the best model by analyzing all possible combinations of factors. In conclusion, genetic algorithms provide a reliable and fast way to select significant factors in logistic regression analysis of large clinical studies