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.

Screening the human exome: a comparison of whole genome and whole transcriptome sequencing.

BACKGROUND: There is considerable interest in the development of methods to efficiently identify all coding variants present in large sample sets of humans. There are three approaches possible: whole-genome sequencing, whole-exome sequencing using exon capture methods, and RNA-Seq. While whole-genome sequencing is the most complete, it remains sufficiently expensive that cost effective alternatives are important. RESULTS: Here we provide a systematic exploration of how well RNA-Seq can identify human coding variants by comparing variants identified through high coverage whole-genome sequencing to those identified by high coverage RNA-Seq in the same individual. This comparison allowed us to directly evaluate the sensitivity and specificity of RNA-Seq in identifying coding variants, and to evaluate how key parameters such as the degree of coverage and the expression levels of genes interact to influence performance. We find that although only 40% of exonic variants identified by whole genome sequencing were captured using RNA-Seq; this number rose to 81% when concentrating on genes known to be well-expressed in the source tissue. We also find that a high false positive rate can be problematic when working with RNA-Seq data, especially at higher levels of coverage. CONCLUSIONS: We conclude that as long as a tissue relevant to the trait under study is available and suitable quality control screens are implemented, RNA-Seq is a fast and inexpensive alternative approach for finding coding variants in genes with sufficiently high expression levels.

An integrated approach to the prediction of chemotherapeutic response in patients with breast cancer.

BACKGROUND: A major challenge in oncology is the selection of the most effective chemotherapeutic agents for individual patients, while the administration of ineffective chemotherapy increases mortality and decreases quality of life in cancer patients. This emphasizes the need to evaluate every patient's probability of responding to each chemotherapeutic agent and limiting the agents used to those most likely to be effective. METHODS AND RESULTS: Using gene expression data on the NCI-60 and corresponding drug sensitivity, mRNA and microRNA profiles were developed representing sensitivity to individual chemotherapeutic agents. The mRNA signatures were tested in an independent cohort of 133 breast cancer patients treated with the TFAC (paclitaxel, 5-fluorouracil, adriamycin, and cyclophosphamide) chemotherapy regimen. To further dissect the biology of resistance, we applied signatures of oncogenic pathway activation and performed hierarchical clustering. We then used mRNA signatures of chemotherapy sensitivity to identify alternative therapeutics for patients resistant to TFAC. Profiles from mRNA and microRNA expression data represent distinct biologic mechanisms of resistance to common cytotoxic agents. The individual mRNA signatures were validated in an independent dataset of breast tumors (P = 0.002, NPV = 82%). When the accuracy of the signatures was analyzed based on molecular variables, the predictive ability was found to be greater in basal-like than non basal-like patients (P = 0.03 and P = 0.06). Samples from patients with co-activated Myc and E2F represented the cohort with the lowest percentage (8%) of responders. Using mRNA signatures of sensitivity to other cytotoxic agents, we predict that TFAC non-responders are more likely to be sensitive to docetaxel (P = 0.04), representing a viable alternative therapy. CONCLUSIONS: Our results suggest that the optimal strategy for chemotherapy sensitivity prediction integrates molecular variables such as ER and HER2 status with corresponding microRNA and mRNA expression profiles. Importantly, we also present evidence to support the concept that analysis of molecular variables can present a rational strategy to identifying alternative therapeutic opportunities.

Analysis of the genome and transcriptome of Cryptococcus neoformans var. grubii reveals complex RNA expression and microevolution leading to virulence attenuation.

Cryptococcus neoformans is a pathogenic basidiomycetous yeast responsible for more than 600,000 deaths each year. It occurs as two serotypes (A and D) representing two varieties (i.e. grubii and neoformans, respectively). Here, we sequenced the genome and performed an RNA-Seq-based analysis of the C. neoformans var. grubii transcriptome structure. We determined the chromosomal locations, analyzed the sequence/structural features of the centromeres, and identified origins of replication. The genome was annotated based on automated and manual curation. More than 40,000 introns populating more than 99% of the expressed genes were identified. Although most of these introns are located in the coding DNA sequences (CDS), over 2,000 introns in the untranslated regions (UTRs) were also identified. Poly(A)-containing reads were employed to locate the polyadenylation sites of more than 80% of the genes. Examination of the sequences around these sites revealed a new poly(A)-site-associated motif (AUGHAH). In addition, 1,197 miscRNAs were identified. These miscRNAs can be spliced and/or polyadenylated, but do not appear to have obvious coding capacities. Finally, this genome sequence enabled a comparative analysis of strain H99 variants obtained after laboratory passage. The spectrum of mutations identified provides insights into the genetics underlying the micro-evolution of a laboratory strain, and identifies mutations involved in stress responses, mating efficiency, and virulence.

Long-term dynamics of death rates of emphysema, asthma, and pneumonia and improving air quality.

BACKGROUND: The respiratory tract is a major target of exposure to air pollutants, and respiratory diseases are associated with both short- and long-term exposures. We hypothesized that improved air quality in North Carolina was associated with reduced rates of death from respiratory diseases in local populations. MATERIALS AND METHODS: We analyzed the trends of emphysema, asthma, and pneumonia mortality and changes of the levels of ozone, sulfur dioxide (SO2), nitrogen dioxide (NO2), carbon monoxide (CO), and particulate matters (PM2.5 and PM10) using monthly data measurements from air-monitoring stations in North Carolina in 1993-2010. The log-linear model was used to evaluate associations between air-pollutant levels and age-adjusted death rates (per 100,000 of population) calculated for 5-year age-groups and for standard 2000 North Carolina population. The studied associations were adjusted by age group-specific smoking prevalence and seasonal fluctuations of disease-specific respiratory deaths. RESULTS: Decline in emphysema deaths was associated with decreasing levels of SO2 and CO in the air, decline in asthma deaths-with lower SO2, CO, and PM10 levels, and decline in pneumonia deaths-with lower levels of SO2. Sensitivity analyses were performed to study potential effects of the change from International Classification of Diseases (ICD)-9 to ICD-10 codes, the effects of air pollutants on mortality during summer and winter, the impact of approach when only the underlying causes of deaths were used, and when mortality and air-quality data were analyzed on the county level. In each case, the results of sensitivity analyses demonstrated stability. The importance of analysis of pneumonia as an underlying cause of death was also highlighted. CONCLUSION: Significant associations were observed between decreasing death rates of emphysema, asthma, and pneumonia and decreases in levels of ambient air pollutants in North Carolina.

Dietary quality and encephalization in platyrrhine primates.

The high energetic costs of building and maintaining large brains are thought to constrain encephalization. The 'expensive-tissue hypothesis' (ETH) proposes that primates (especially humans) overcame this constraint through reduction of another metabolically expensive tissue, the gastrointestinal tract. Small guts characterize animals specializing on easily digestible diets. Thus, the hypothesis may be tested via the relationship between brain size and diet quality. Platyrrhine primates present an interesting test case, as they are more variably encephalized than other extant primate clades (excluding Hominoidea). We find a high degree of phylogenetic signal in the data for diet quality, endocranial volume and body size. Controlling for phylogenetic effects, we find no significant correlation between relative diet quality and relative endocranial volume. Thus, diet quality fails to account for differences in platyrrhine encephalization. One taxon, in particular, Brachyteles, violates predictions made by ETH in having a large brain and low-quality diet. Dietary reconstructions of stem platyrrhines further indicate that a relatively high-quality diet was probably in place prior to increases in encephalization. Therefore, it is unlikely that a shift in diet quality was a primary constraint release for encephalization in platyrrhines and, by extrapolation, humans.

Structural Basis of RNA Recognition by Mycobacterium tuberculosis MazF Homologues

The MazEF toxin-antitoxin (TA) system consists of the antitoxin MazE and the toxin MazF. MazF is a sequence-specific endoribonuclease that upon activation causes cellular growth arrest and increass the level of persisters. Moreover, MazF-induced cells are in a quasi-dormant state that cells remain metabolically active while stop dividing. The quasi-dormancy is similar to the nonreplicating state of M. tuberculosis during latent tuberculosis, thus suggesting the role of mazEF in M. tuberculosis dormancy and persistence. M. tuberculosis has nine mazEF TA modules, each with different RNA cleavage specificities and implicated in selective gene expression during stress conditions. To date only the Bacillus subtilis MazF-RNA complex structure has been determined. As M. tuberculosis MazF homologues recognize distinct RNA sequences, their molecular mechanisms of substrate specificity remain unclear. By taking advantage of X-ray crystallography, we have determined structures of two M. tuberculosis MazF-RNA complexes, MazF-mt1 (Rv2801c) and MazF-mt3 (Rv1991c) in complex with an uncleavable RNA substrate. These structures have provided the molecular basis of sequence-specific RNA recognition and cleavage by MazF toxins.

Both MazF-mt1-RNA and MazF-mt3-RNA complexes showed similar structural organization with one molecule of RNA bound to a MazF-mt1 or MazF-mt3 dimer and occupying the same pocket within the MazF dimer interface. Similar to B. subtilis MazF-RNA complex, MazF-mt1 and MazF-mt3 displayed a conserved active site architecture, where two highly conserved residues, Arg and Thr, form hydrogen bonds with the scissile phosphate group in the cleavage site of the bound RNA. The MazF-mt1-RNA complex also showed specific interactions with its three-base RNA recognition element. Compared with the B. subtilis MazF-RNA complex, our structures showed that residues involved in sequence-specific recognition of target RNA vary between the MazF homologues, therefore explaining the molecular basis for their different RNA recognition sequences. In addition, local conformational changes of the loops in the RNA binding site of MazF-mt1 appear to play a role in MazF targeting different RNA lengths and sequences. In contrast, the MazF-mt3-RNA complex is in a non-optimal RNA binding state with a symmetry-related MazF-mt3 molecule found to make interactions with the bound RNA in the crystal. The crystal-packing interactions were further examined by isothermal titration calorimetry (ITC) studies on selected MazF-mt3 mutants. Our attempts to utilize a MazF-mt3 mutant bearing mutations involved in crystal contacts all crystallized with few nucleotides, which are still found to interact with a symmetry mate. However, these different crystal forms revealed the conformational flexibility of loops in the RNA binding interface of MazF-mt3, suggesting their role in RNA binding and recognition, which will require further studies on additional MazF-mt3-RNA complex interactions.

In conclusion, the structures of the MazF-mt1-RNA and MazF-mt3-RNA complexes provide the first structural information on any M. tuberculosis MazF homologues. Supplemented with structure-guided mutational studies on MazF toxicity in vivo, this study has addressed the structural basis of different RNA cleavage specificities among MazF homologues. Our work will guide future studies on the function of other M. tuberculosis MazF and MazE-MazF homologues, and will help delineate their physiological roles in M. tuberculosis stress responses and pathogenesis.

Election Quality and International Observation 1975-2004: Two New Datasets

This paper introduces two new datasets on national level elections from 1975 to 2004. The data are grouped into two separate datasets, the Quality of Elections Data and the Data on International Election Monitoring. Together these data sets provide original information on elections, election observation and election quality, and will enable researchers to study a variety of research questions. The datasets will be publicly available and are maintained at a project website.

Fluid management and goal-directed therapy as an adjunct to Enhanced Recovery After Surgery (ERAS)

© 2014, Canadian Anesthesiologists' Society.Optimal perioperative fluid management is an important component of Enhanced Recovery After Surgery (ERAS) pathways. Fluid management within ERAS should be viewed as a continuum through the preoperative, intraoperative, and postoperative phases. Each phase is important for improving patient outcomes, and suboptimal care in one phase can undermine best practice within the rest of the ERAS pathway. The goal of preoperative fluid management is for the patient to arrive in the operating room in a hydrated and euvolemic state. To achieve this, prolonged fasting is not recommended, and routine mechanical bowel preparation should be avoided. Patients should be encouraged to ingest a clear carbohydrate drink two to three hours before surgery. The goals of intraoperative fluid management are to maintain central euvolemia and to avoid excess salt and water. To achieve this, patients undergoing surgery within an enhanced recovery protocol should have an individualized fluid management plan. As part of this plan, excess crystalloid should be avoided in all patients. For low-risk patients undergoing low-risk surgery, a “zero-balance” approach might be sufficient. In addition, for most patients undergoing major surgery, individualized goal-directed fluid therapy (GDFT) is recommended. Ultimately, however, the additional benefit of GDFT should be determined based on surgical and patient risk factors. Postoperatively, once fluid intake is established, intravenous fluid administration can be discontinued and restarted only if clinically indicated. In the absence of other concerns, detrimental postoperative fluid overload is not justified and “permissive oliguria” could be tolerated.

Characterization of a Full-Length TTP Family Member Association with RNA Sequence Elements

Post-transcriptional regulation of cytoplasmic mRNAs is an efficient mechanism of regulating the amounts of active protein within a eukaryotic cell. RNA sequence elements located in the untranslated regions of mRNAs can influence transcript degradation or translation through associations with RNA-binding proteins. Tristetraprolin (TTP) is the best known member of a family of CCCH zinc finger proteins that targets adenosine-uridine rich element (ARE) binding sites in the 3’ untranslated regions (UTRs) of mRNAs, promoting transcript deadenylation through the recruitment of deadenylases. More specifically, TTP has been shown to bind AREs located in the 3’-UTRs of transcripts with known roles in the inflammatory response. The mRNA-binding region of the protein is the highly conserved CCCH tandem zinc finger (TZF) domain. The synthetic TTP TZF domain has been shown to bind with high affinity to the 13-mer sequence of UUUUAUUUAUUUU. However, the binding affinities of full-length TTP family members to the same sequence and its variants are unknown. Furthermore, the distance needed between two overlapping or neighboring UUAUUUAUU 9-mers for tandem binding events of a full-length TTP family member to a target transcript has not been explored. To address these questions, we recombinantly expressed and purified the full-length C. albicans TTP family member Zfs1. Using full-length Zfs1, tagged at the N-terminus with maltose binding protein (MBP), we determined the binding affinities of the protein to the optimal TTP binding sequence, UUAUUUAUU. Fluorescence anisotropy experiments determined that the binding affinities of MBP-Zfs1 to non-canonical AREs were influenced by ionic buffer strength, suggesting that transcript selectivity may be affected by intracellular conditions. Furthermore, electrophoretic mobility shift assays (EMSAs) revealed that separation of two core AUUUA sequences by two uridines is sufficient for tandem binding of MBP-Zfs1. Finally, we found evidence for tandem binding of MBP-Zfs1 to a 27-base RNA oligonucleotide containing only a single ARE-binding site, and showed that this was concentration and RNA length dependent; this phenomenon had not been seen previously. These data suggest that the association of the TTP TZF domain and the TZF domains of other species, to ARE-binding sites is highly conserved. Domains outside of the TZF domain may mediate transcript selectivity in changing cellular conditions, and promote protein-RNA interactions not associated with the ARE-binding TZF domain.

In summary, the evidence presented here suggests that Zfs1-mediated decay of mRNA targets may require additional interactions, in addition to ARE-TZF domain associations, to promote transcript destabilization and degradation. These studies further our understanding of post-transcriptional steps in gene regulation.