Prospective Estimation of Radiation Dose and Image Quality for Optimized CT Performance

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].

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.

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.

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.

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.

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.

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.

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.

Chapter 8 concludes the thesis with a summary of accomplished work and a discussion about future research.

Surgical Procedure Characteristics and Risk of Sharps-Related Blood and Body Fluid Exposure.

OBJECTIVE To use a unique multicomponent administrative data set assembled at a large academic teaching hospital to examine the risk of percutaneous blood and body fluid (BBF) exposures occurring in operating rooms. DESIGN A 10-year retrospective cohort design. SETTING A single large academic teaching hospital. PARTICIPANTS All surgical procedures (n=333,073) performed in 2001-2010 as well as 2,113 reported BBF exposures were analyzed. METHODS Crude exposure rates were calculated; Poisson regression was used to analyze risk factors and account for procedure duration. BBF exposures involving suture needles were examined separately from those involving other device types to examine possible differences in risk factors. RESULTS The overall rate of reported BBF exposures was 6.3 per 1,000 surgical procedures (2.9 per 1,000 surgical hours). BBF exposure rates increased with estimated patient blood loss (17.7 exposures per 1,000 procedures with 501-1,000 cc blood loss and 26.4 exposures per 1,000 procedures with >1,000 cc blood loss), number of personnel working in the surgical field during the procedure (34.4 exposures per 1,000 procedures having ≥15 personnel ever in the field), and procedure duration (14.3 exposures per 1,000 procedures lasting 4 to <6 hours, 27.1 exposures per 1,000 procedures lasting ≥6 hours). Regression results showed associations were generally stronger for suture needle-related exposures. CONCLUSIONS Results largely support other studies found in the literature. However, additional research should investigate differences in risk factors for BBF exposures associated with suture needles and those associated with all other device types. Infect. Control Hosp. Epidemiol. 2015;37(1):80-87.

Neural Mechanisms of Young Adult Sexual Decision-Making and Risk Behavior

Sexual risk behavior among young adults is a serious public health concern; 50% will contract a sexually transmitted infection (STI) before the age of 25. The current study collected self-report personality and sexual history data, as well as neuroimaging, experimental behavioral (e.g., real-time hypothetical sexual decision making data), and self-report sexual arousal data from 120 heterosexual young adults ages 18-26. In addition, longitudinal changes in self-reported sexual behavior were collected from a subset (n = 70) of the participants. The primary aims of the study were (1) to predict differences in self-report sexual behavior and hypothetical sexual decision-making (in response to sexually explicit audio-visual cues) as a function of ventral striatum (VS) and amygdala activity, (2) test whether the association between sexual behavior/decision-making and brain function is moderated by gender, self-reported sexual arousal, and/or trait-level personality factors (i.e., self-control, impulsivity, and sensation seeking) and (3) to examine how the main effects of neural function and interaction effects predict sexual risk behavior over time. Our hypotheses were mostly supported across the sexual behavior and decision-making outcome variables, such that neural risk phenotypes (heightened reward-related ventral striatum activity coupled with decreased threat-related amygdala activity) were associated with greater lifetime sexual partners at baseline measured and over time (longitudinal analyses). Impulsivity moderated the relationship between neural function and self-reported number of sexual partners at baseline and follow up measures, as well as experimental condom use decision-making. Sexual arousal and sensation seeking moderated the relationship between neural function and baseline and follow up self-reports of number of sexual partners. Finally, unique gender differences were observed in the relationship between threat and reward-related neural reactivity and self-reported sexual risk behavior. The results of this study provide initial evidence for the potential role for neurobiological approaches to understanding sexual decision-making and risk behavior. With continued research, establishing biomarkers for sexual risk behavior could help inform the development of novel and more effective individually tailored sexual health prevention and intervention efforts.

The Abundance and Behavioral Ecology of Cape Cod Gray Seals Under Predation Risk From White Sharks

The ultimate goal of wildlife recovery is abundance growth of a species, though it must also involve the reestablishment of the species’ ecological role within ecosystems frequently modified by humans. Reestablishment and subsequent recovery may depend on the species’ degree of adaptive behavior as well as the duration of their functional absence and the extent of ecosystem alteration. In cases of long extirpations or extensive alteration, successful reestablishment may entail adjusting foraging behavior, targeting new prey species, and encountering unfamiliar predatory or competitive regimes. Recovering species must also increasingly tolerate heightened anthropogenic presence, particularly within densely inhabited coastal zones. In recent decades, gray seals (Halichoerus grypus) recovered from exploitation, depletion, and partial extirpation in the Northwest Atlantic. On Cape Cod, MA, USA, gray seals have reestablished growing breeding colonies and seasonally interact with migratory white sharks (Carcarodon carcharias). Though well-studied in portions of their range due to concerns over piscivorous impacts on valuable groundfish, there are broad knowledge gaps regarding their ecological role to US marine ecosystems. Furthermore, there are few studies that explicitly analyze gray seal behavior under direct risk of documented shark predation.

In this dissertation, I apply a behavioral and movement ecology approach to telemetry data to understand gray seal abundance and activity patterns along the coast of Cape Cod. This coastal focus complements extensive research documenting and describing offshore movement and foraging behavior and allows me to address questions about movement decisions and risk allocation. Using beach counts of seals visible in satellite imagery, I estimate the total regional abundance of gray seals using correction factors from haul out behavior and demonstrate a sizeable prey base of gray seals locally. Analyzing intra-annual space use patterns, I document small, concentrated home ranges utilizing nearshore habitats that rapidly expand with shifting activity budgets to target disperse offshore habitats following seasonal declines in white sharks. During the season of dense shark presence, seals conducted abbreviated nocturnal foraging trips structured temporally around divergent use of crepuscular periods. The timing of coastal behavior with different levels of twilight indicate risk allocation patterns with diel cycles of empirical white shark activity. The emergence of risk allocation to explain unique behavioral and spatial patterns observed in these gray seals points to the importance of the restored predator-prey dynamic in gray seal behavior along Cape Cod.

Associations between smoking behavior-related alleles and the risk of melanoma.

Several studies have reported that cigarette smoking is inversely associated with the risk of melanoma. This study further tested whether incorporating genetic factors will provide another level of evaluation of mechanisms underlying the association between smoking and risk of melanoma. We investigated the association between SNPs selected from genome-wide association studies (GWAS) on smoking behaviors and risk of melanoma using 2,298 melanoma cases and 6,654 controls. Among 16 SNPs, three (rs16969968 [A], rs1051730 [A] and rs2036534 [C] in the 15q25.1 region) reached significance for association with melanoma risk in men (0.01 < = P values < = 0.02; 0.85 < = Odds Ratios (ORs) <= 1.20). There was association between the genetic scores based on the number of smoking behavior-risk alleles and melanoma risk with P-trend = 0.005 among HPFS. Further association with smoking behaviors indicating those three SNPs (rs16969968 [A], rs1051730 [A] and rs2036534 [C]) significantly associated with number of cigarettes smoked per day, CPD, with P = 0.009, 0.011 and 0.001 respectively. The SNPs rs215605 in the PDE1C gene and rs6265 in the BDNF gene significantly interacted with smoking status on melanoma risk (interaction P = 0.005 and P = 0.003 respectively). Our study suggests that smoking behavior-related SNPs are likely to play a role in melanoma development and the potential public health importance of polymorphisms in the CHRNA5-A3-B4 gene cluster. Further larger studies are warranted to validate the findings.