UCLA

Computed Tomography (CT) has been used for medical diagnosis for the past four decades and has made significant contributions to patient healthcare by providing fast and accurate diagnostic information. Besides the extraordinary medical benefits it has brought to society, it delivers radiation dose to the patients, which can be potentially hazardous. Therefore, it has been a significant interest in both scientific research and clinical practice to reduce radiation dose to the patients during CT scans, while still maintaining the diagnostic performance, so that the information provided through this procedure is not compromised and appropriate medical determinations can be made at the minimum cost.

In this research work, a Monte Carlo based simulation package was used to estimate radiation dose to individual radiosensitive organs of patients with a range of body habitus. This package is exam and protocol specific, and it takes into account technical details of CT scanners such as spectra, bowtie filtration, and beam geometry. Modifications were made to the Monte Carlo simulation package to perform detailed radiation dose assessments for both patients and phantoms. These include the estimate of radiation dose to individual organs, the peak radiation dose to a wide spread tissue (such as peak skin dose), and surface dose distribution in a complex CT irradiation environment. Meanwhile, the effect of a variety of traditional dose reduction methods, such as tilting the gantry in brain perfusion scans, was also investigated.

In addition to the traditional dose reduction techniques that are already being utilized in the clinic, an innovative method to reduce organ dose while maintaining image quality was investigated. The distribution of radiation dose within the scan volume was demonstrated to be dependent on the Tube Start Angle (TSA). A change of TSA can cause a shift of dose distribution along the longitudinal axis. This results in variations in the measurement of surface dose during helical scans. This dose variation along the longitudinal direction for patients in CT imaging inspired a novel innovation to reduce organ dose while maintaining image quality by adjusting the TSA and table height in CT exams. Monte Carlo simulations were performed to demonstrate the effectiveness of this method for different patients under various scenarios, including conventional fixed tube current CT scans, and tube current modulated (TCM) scans. Besides the dose benefit this new method brings, its effect on image quality was investigated and demonstrated that there was no significant compromise on the image quality.

Despite the efforts to reduce radiation dose while maintaining image quality, the ultimate tradeoff in the goal of maximizing the benefit to risk ratio in CT examinations is the tradeoff between radiation dose and diagnostic outcome. As radiation dose is decreased, the image quality may be degraded. However, the diagnostic outcome does not necessarily have to be compromised. In other words, the image quality used for specific CT clinical tasks today may have room to be degraded and still be able to maintain accuracy of diagnostic outcomes. In order to investigate this tradeoff between radiation dose and diagnostic outcome for a specific clinical task (appendicitis was selected in this dissertation), a preliminary observer study was conducted to determine the difference of diagnostic performance at various dose levels. Images at reduced radiation dose levels were simulated by adding noise to the projection data using a calibrated method. These methods were employed for a group of patients with right lower quadrant pain who were scanned because of a suspected appendicitis. The results of Receiver Operation Characteristic (ROC) analysis suggested that there was no significant difference between radiation dose levels of 100%, 70% and 50%. Detailed analysis of patient organ (liver) dose demonstrated that the diagnostic performance is nearly perfect when the liver dose is higher than 10mGy. The interrelationship between a simple image quality metric (noise), organ dose, and patient size was also investigated.

In summary, this work assessed dose reduction tools available today that do not affect image quality, proposed a new method to reduce organ dose while maintaining image quality, and evaluated the method to reduce radiation dose, which affects image quality but could maintain diagnostic outcome by investigating the tradeoff between radiation dose and diagnostic outcome, as well as their correlation with image quality metrics (noise).