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The RS 2400 irradiator has been looked to as a replacement for discontinued gamma irradiators. The RS 2400 has a cylindrical, rather than point, x-ray source, which yields higher dose rates. The irradiator unit allows the user to set the current, voltage, and time for which the sample is to be irradiated, but gives no conversion between these values and the dose delivered. Working with Mississippi State University’s Experimental Seafood Processing Laboratory (ESPL), the purpose of this research was to characterize the dose delivered by the RS 2400 for typical operating conditions. The RS 2400 exposure rate increases, as expected, as the current and voltage are increased. The x-ray beam is uniform within 10% at the surface of the x-ray tube over a wide range of voltages, with the exception of the leftmost 5 cm of the tube, where structural supports are located. At the maximum operating parameters (150 kV and 45 mA), the beam has a first half value layer (HVL1) of 13.66 mm aluminum, a homogeneity coefficient of 0.47, and equivalent photon energy (hveq) of 88.5 keV. This suggests a broad energy x-ray beam. The maximum deliverable dose rate to tissue at the surface of the x-ray tube is 65 Gy min-1 ± 3.1%, but it is unlikely that any sample will ever be irradiated this close to the x-ray tube. The standard sample canisters are 7.62 cm in diameter and the maximum deliverable dose rate to tissue at the canister location (with no canister present) is 37 Gy min-1 ± 3.1%. This is similar to the 45 Gy min-1 value that Rad Source Technologies, Inc. gives for the irradiator. Irradiation of live oysters is of primary interest to the ESPL. For irradiation, oysters will most likely be placed in the 10.2 cm diameter plastic canisters since the 7.62 cm diameter canisters are not wide enough to hold larger oysters. The oyster shells and increased distance from the x-ray source reduce the maximum deliverable dose rate to 14.1 Gy min-1 ± 6.5% for thin-shelled oysters and 12.3 Gy min-1 ± 6.2% for thick-shelled oysters.

Image quality has been found to be positively correlated with diagnosis accuracy. Radiologist aim for the highest quality image possible to determine the location of the suspected pathology. However, the most effective way of producing high quality images is to increase the radiation dosage to the patient. To avoid the many risks that come with radiation, patients want to keep dosage as low as possible. Diagnosing instruments are constantly being re-engineered and optimized to keep image quality high and radiation dosage low. If patients wish to avoid nuclear radiation exposure, alternative non-nuclear and low radiation modalities must be employed. The three most important metrics of image quality are spatial resolution, signal-to-noise (SNR) ratio and contrast-to-noise (CNR) ratio [1]. Radiologists and imaging technicians can do very little to improve the spatial resolution; and to improve the CNR a higher dosage is necessary to increase the value of every pixel. To increase radiation-SNR efficiency, the dosage can be reduced by 50% while only dropping the SNR by about 30% [2]. To simulate lower dosage, data is randomly taken out while the image is reconstructed until the acceptable SNR value is achieved. The broad applications can include reducing the signal-to-dosage ratio for any modality involving ionizing radiation and image reconstruction, reducing the risk for every imaged patient.

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<p>X-ray computed tomography (CT) is a non-invasive medical imaging technique that generates cross-sectional images by acquiring attenuation-based projection measurements at multiple angles. Since its first introduction in the 1970s, substantial technical improvements have led to the expanding use of CT in clinical examinations. CT has become an indispensable imaging modality for the diagnosis of a wide array of diseases in both pediatric and adult populations [1, 2]. Currently, approximately 272 million CT examinations are performed annually worldwide, with nearly 85 million of these in the United States alone [3]. Although this trend has decelerated in recent years, CT usage is still expected to increase mainly due to advanced technologies such as multi-energy [4], photon counting [5], and cone-beam CT [6].</p><p>Despite the significant clinical benefits, concerns have been raised regarding the population-based radiation dose associated with CT examinations [7]. From 1980 to 2006, the effective dose from medical diagnostic procedures rose six-fold, with CT contributing to almost half of the total dose from medical exposure [8]. For each patient, the risk associated with a single CT examination is likely to be minimal. However, the relatively large population-based radiation level has led to enormous efforts among the community to manage and optimize the CT dose.</p><p>As promoted by the international campaigns Image Gently and Image Wisely, exposure to CT radiation should be appropriate and safe [9, 10]. It is thus a responsibility to optimize the amount of radiation dose for CT examinations. The key for dose optimization is to determine the minimum amount of radiation dose that achieves the targeted image quality [11]. Based on such principle, dose optimization would significantly benefit from effective metrics to characterize radiation dose and image quality for a CT exam. Moreover, if accurate predictions of the radiation dose and image quality were possible before the initiation of the exam, it would be feasible to personalize it by adjusting the scanning parameters to achieve a desired level of image quality. The purpose of this thesis is to design and validate models to quantify patient-specific radiation dose prospectively and task-based image quality. The dual aim of the study is to implement the theoretical models into clinical practice by developing an organ-based dose monitoring system and an image-based noise addition software for protocol optimization. </p><p>More specifically, Chapter 3 aims to develop an organ dose-prediction method for CT examinations of the body under constant tube current condition. The study effectively modeled the anatomical diversity and complexity using a large number of patient models with representative age, size, and gender distribution. The dependence of organ dose coefficients on patient size and scanner models was further evaluated. Distinct from prior work, these studies use the largest number of patient models to date with representative age, weight percentile, and body mass index (BMI) range.</p><p>With effective quantification of organ dose under constant tube current condition, Chapter 4 aims to extend the organ dose prediction system to tube current modulated (TCM) CT examinations. The prediction, applied to chest and abdominopelvic exams, was achieved by combining a convolution-based estimation technique that quantifies the radiation field, a TCM scheme that emulates modulation profiles from major CT vendors, and a library of computational phantoms with representative sizes, ages, and genders. The prospective quantification model is validated by comparing the predicted organ dose with the dose estimated based on Monte Carlo simulations with TCM function explicitly modeled. </p><p>Chapter 5 aims to implement the organ dose-estimation framework in clinical practice to develop an organ dose-monitoring program based on a commercial software (Dose Watch, GE Healthcare, Waukesha, WI). In the first phase of the study we focused on body CT examinations, and so the patient’s major body landmark information was extracted from the patient scout image in order to match clinical patients against a computational phantom in the library. The organ dose coefficients were estimated based on CT protocol and patient size as reported in Chapter 3. The exam CTDIvol, DLP, and TCM profiles were extracted and used to quantify the radiation field using the convolution technique proposed in Chapter 4. </p><p>With effective methods to predict and monitor organ dose, Chapters 6 aims to develop and validate improved measurement techniques for image quality assessment. Chapter 6 outlines the method that was developed to assess and predict quantum noise in clinical body CT images. Compared with previous phantom-based studies, this study accurately assessed the quantum noise in clinical images and further validated the correspondence between phantom-based measurements and the expected clinical image quality as a function of patient size and scanner attributes. </p><p>Chapter 7 aims to develop a practical strategy to generate hybrid CT images and assess the impact of dose reduction on diagnostic confidence for the diagnosis of acute pancreatitis. The general strategy is (1) to simulate synthetic CT images at multiple reduced-dose levels from clinical datasets using an image-based noise addition technique; (2) to develop quantitative and observer-based methods to validate the realism of simulated low-dose images; (3) to perform multi-reader observer studies on the low-dose image series to assess the impact of dose reduction on the diagnostic confidence for multiple diagnostic tasks; and (4) to determine the dose operating point for clinical CT examinations based on the minimum diagnostic performance to achieve protocol optimization. </p><p>Chapter 8 concludes the thesis with a summary of accomplished work and a discussion about future research.</p> / Dissertation

Doctor of Health Science / An investigation of clinical Abdominal Computed Tomography (CT)dose, and associated clinical diagnostic protocols, has been ndertaken. This research was carried out to study the pattern of CT dose from routine abdominal examinations in Malaysian practices. From this study it is hoped to establish a Dose Reference Level (DRL) to assist in optimising radiation dose for CT abdominal examination in Malaysia

A Radiological Dispersal Device (RDD) is any device that releases radioactive material into the environment (e.g. Dirty Bomb). Depending on the size of the explosion, location, and the weather conditions the affected area could be several city blocks. In such an event there could be hundreds, even thousands of contaminated victims seeking medical treatment. One concern in the healthcare industry is the uncertainty of the level of radiation exposure to the healthcare providers from these contaminated patients. The intention of this study is to estimate the levels of skin contamination for victims arriving at the hospital needing conventional medical treatment. Given a skin contamination of the victim the effective dose rate to the healthcare providers can be estimated in certain scenarios. The effective dose rate will determine how long the healthcare provider would be able to care for the victims.

Doctor of Health Science / An investigation of clinical Abdominal Computed Tomography (CT)dose, and associated clinical diagnostic protocols, has been ndertaken. This research was carried out to study the pattern of CT dose from routine abdominal examinations in Malaysian practices. From this study it is hoped to establish a Dose Reference Level (DRL) to assist in optimising radiation dose for CT abdominal examination in Malaysia

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