MONTE CARLO MODELING BASED PATIENT DOSE OPTIMIZATION IN DIAGNOSTIC RADIOLOGY

Radiation doses are caused by the energy deposited in unit mass of matter from ionizing radiation. In the US, radiation doses from medical imaging increased six-fold in the past generation. Among medical exposures to patients, computed tomography (CT) composes about half of the collective doses, and interventional fluoroscopy composes 14%. Radiation exposure to patients undergoing diagnostic radiological procedures causes increased lifetime carcinogenic risks, especially for pediatric patients who are more radiosensitive than adults. The correlation between procedural x-ray techniques and the radiation doses to patients, as well as the resultant image quality, is not well understood, and therefore the focus of the performed studies. High radiation dose levels can occur as an outcome of complex procedures requiring additional imaging, or when a patient undergoes multiple radiological procedures. Accumulated occupational doses, caused by the scattered radiation from the patient to the staff during the procedures, are also of concern. There are many factors that affect the patient radiation doses, such as different combinations of technical parameter settings and patient characteristics. Due to the complexities and time-consuming nature of clinical dose/exposure measurements, the Monte Carlo technique is the only realistic tool to investigate patient doses and occupational exposure. Therefore, the objective of this Dissertation is to investigate the possible optimization methods of the irradiation technical factors in order to lower radiation doses to patients undergoing diagnostic radiological examinations using Monte Carlo algorithm-based software. Our general hypothesis is that incident x-ray photon energy used in a diagnostic radiological procedure can be optimized to reduce patient doses without sacrificing image quality, and therefore can lower radiation-induced lifetime carcinogenic risks for patients. Our results will be valuable for medical physicists to analyze dose distributions, and for the cardiology clinicians to maximize image guidance capabilities while minimizing potential carcinogenic and deterministic risks to pediatric patients. Firstly, the impact of irradiation parameters on patient doses during CT scans was investigated and possible optimization methods were discussed. Our results about cone beam CT scans showed that there were major differences in organ and effective dose as the x-ray tube rotates around the patient. This suggested that the use of x-ray tube current modulation could produce substantial reductions in organ and effective dose for body imaging with cone beam CT. For chest CT, our results showed that the existing x-ray tube current modulation schemes are expected to reduce patient effective doses in chest CT examinations by about 10%, with longitudinal modulation accounting for two thirds and angular modulation for the remaining one third. It was also shown that the choice of the scanned region affects organ doses in CT. Secondly, the radiation-induced cancer risks from body CT examinations for adult patients were estimated. For patients who differ from a standard sized adult, correction factors based on the patient weight and antero-posterior dimension are provided to adjust organ doses and the corresponding risks. Our results showed that at constant incident radiation intensity, for CT examinations that include the chest, risks in females are markedly higher than those for males, whereas for examinations that include the pelvis, risks in males were slightly higher than those in females. In abdominal CT scans, risks for males and female patients are very similar. A conclusion was reached that cancer risks in body CT can be estimated from the examination Dose Length Product by accounting for sex, age, as well as patient physical characteristics. Thirdly, a set of innovative Monte Carlo models were developed to investigate the role of x-ray photon energy in determining skin dose, energy imparted, and image quality in pediatric interventional radiology using the MCNP5 platform. Contrast, relative noise, and contrast-to-noise ratio (CNR) were obtained for diagnostic imaging with and without the utilization of grids. Our results indicated that using Monte Carlo methods, the optimized x-ray tube voltage for a relatively low patient dose under the desired image quality could be obtained for any specific patient undergoing a certain type of diagnostic examination. Lastly, we investigated the changes in the pattern of energy deposition in patient phantoms following the use of iodinated contrast media using Monte Carlo models built on MCNP5 platform. Relative energy imparted to the volume of interest with iodine contrast agent, as well as to the whole patient phantom, was calculated. Changes in patterns of energy deposition around the contrast-filled volume were also investigated. Our results suggested that adding iodine can result in values of localized absorbed dose increasing by more than an order of magnitude, but the total energy deposition is generally very modest. Furthermore, our results also showed that adding iodine primarily changes the pattern of energy deposition in the irradiated region, rather than increasing the corresponding patient doses. The goal of this project was to establish a better understanding of the roles of different technique factors in the patient doses from diagnostic radiological procedures. Based on these studies, the limitations of the current Monte Carlo software were analyzed and our own Monte Carlo model was proposed for simulations of patient doses during pediatric interventional radiology procedures. The ultimate goal of this study is to develop a comprehensive dosimetry database using Monte Carlo technique, with the output of patient doses, operator doses, and the corresponding radiation-induced carcinogenesis risks for pediatric interventional radiology procedures

Investigation on Remote Monitoring System for Heat-Supply Thermal Characters Based GPRS

AbstractWith the strategy requirements of low-carbon and energy-saving, the appropriate auto-control methods become more and more important. Aiming to monitor the thermal characters of the heat exchange station in the real time, the investigation framework in this paper presents an integral solution. We incorporate wireless data gathering from different heat exchange station, sending data to the service through the Internet and managing by sever.Net. We exploit formalization software by three-layer Browser-Server structure to regulate how thermal characters data should be gathered, communicated among concerned parties and interpreted to server/Date Base in decision-making. Meanwhile, the communication among the nodes that form the distributed system is implemented by means of the utilization of wireless networks, and secondary data transmission services (GSM or GPRS) provided by a mobile telephone operator. This monitoring system has been running in good condition and stable operation with lower fault rate and higher credibility data. This system, once fully deployed, can significantly reduce human labor and provide real-time data monitoring to achieve the propose of energy conservation and emission reduction

Examining how time flies at destinations based on visitors’ perceived consistency of destination experiences

Domestic Chinese tourists traveling to rural destinations in China often face the challenge of local dialects. Based on the theories of flow (Csikszentmihalyi & Csikzentmihaly, 1990; Nakamura & Csikszentmihalyi, 2009), individuals’ need for uniqueness (Tian, Bearden, & Hunter, 2001), and confirmation-disconfirmation (Parasuraman et al., 1994), this study explores two main antecedents for visitors’ perceived absorption experiences during visits at destinations (i.e., the sense of immersion and feeling time flies). Specifically, we suggest that visitors are more likely to experience absorption when they have a positive attitude toward the local dialect of the destination as well as perceive the destination to be distinct. In addition, both of these effects are moderated by visitors’ evaluation of their experiences compared to their expectations (perceived consistency of destination of experiences). With a sample of 352 visitors in a rural destination in China, this study provides strong support for these propositions

Lowpass Filtering of Rate-Distortion Functions for Quality Smoothing in Real-Time Video Communication

Digital Object Identifier 10.1109/TCSVT.2005.852417In variable-bit-rate (VBR) video coding, the video is pre-processed to collect sequence-level statistics, which are used for global bit allocation in the actual encoding stage to obtain a smoothed video presentation quality. However, in real-time video recording and network streaming, this type of two-pass encoding scheme is not allowed because the access to future frames and global statistics is not available. To address this issue, we introduce the concept of low-pass filtering of rate-distortion (R-D) functions and develop a smoothed rate control (SRC) framework for real-time video recording and streaming. Theoretically, we prove that, using a geometric averaging filter, the SRC algorithm is able to maintain a smoothed video presentation quality while achieving the target bit rate automatically. We also analyze the buffer requirement of the SRC algorithm in real-time video streaming, and propose a scheme to seamlessly integrate robust buffer control into the SRC framework. The proposed SRC algorithm has very low computational complexity and implementation cost. Our extensive experimental results demonstrate that the SRC algorithm significantly reduces the picture quality variation in the encoded video clips