Pyramid Multi-resolution Scanning for Two-sample Comparison

Testing for two-sample differences is challenging when the differences are local and only involve a small portion of the data. To solve this problem, we apply a multi- resolution scanning framework that performs dependent local tests on subsets of the sample space. We use a nested dyadic partition of the sample space to get a collection of windows and test for sample differences within each window. We put a joint prior on the states of local hypotheses that allows both vertical and horizontal message passing among the partition tree to reflect the spatial dependency features among windows. This information passing framework is critical to detect local sample differences. We use both the loopy belief propagation algorithm and MCMC to get the posterior null probability on each window. These probabilities are then used to report sample differences based on decision procedures. Simulation studies are conducted to illustrate the performance. Multiple testing adjustment and convergence of the algorithms are also discussed.

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.

Commandeering Aesop’s Bamboo Canon: A 19th Century Confederacy of Creole Fugitive Fables

In my thesis, “Commandeering Aesop’s Bamboo Canon: A 19th Century Confederacy of Creole Fugitive Fables,” I ask and answer the ‘Who? What? Where? When? Why?” of Creole Literature using the 19th century production of Aesopian fables as clues to resolve a set of linguistic, historical, literary, and geographical enigmas pertaining the ‘birth-place(s)’ of Creolophone Literatures in the Caribbean Sea, North and South America, as well as the Indian Ocean. Focusing on the fables in Martinique (1846), Reunion Island (1826), and Mauritius (1822), my thesis should read be as an attempt capture the links between these islands through the creation of a particular archive defined as a cartulary-chronicle, a diplomatic codex, or simply a map in which I chart and trace the flight of the founding documents relating to the lives of the individual authors, editors, and printers in order to illustrate the articulation of a formal and informal confederation that enabled the global and local institutional promotion of Creole Literature. While I integrate various genres and multi-polar networks between the authors of this 19th century canon comprised of sacred and secular texts such as proclamations, catechisms, and proverbs, the principle literary genre charted in my thesis are collections of fables inspired by French 17th century French Classical fabulist, Jean de la Fontaine. Often described as the ‘matrix’ of Creolophone Literature, these blues and fables constitute the base of the canon, and are usually described as either ‘translated,’ ‘adapted,’ and even ‘cross-dressed’ into Creole in all of the French Creolophone spaces. My documentation of their transnational sprouting offers proof of an opaque canonical formation of Creole popular literature. By constituting this archive, I emphasize the fact that despite 200 years of critical reception and major developments and discoveries on behalf of Creole language pedagogues, literary scholars, linguists, historians, librarians, archivist, and museum curators, up until now not only have none have curated this literature as a formal canon. I also offer new empirical evidence in order to try and solve the enigma of “How?” the fables materially circulated between the islands, and seek to come to terms with the anonymous nature of the texts, some of which were published under pseudonyms. I argue that part of the confusion on the part of scholars has been the result of being willfully taken by surprise or defrauded by the authors, or ‘bamboozled’ as I put it. The major paradigmatic shift in my thesis is that while I acknowledge La Fontaine as the base of this literary canon, I ultimately bypass him to trace the ancient literary genealogy of fables to the infamous Aesop the Phrygian, whose biography – the first of a slave in the history of the world – and subsequent use of fables reflects a ‘hidden transcript’ of ‘masked political critique’ between ‘master and slave classes’ in the 4th Century B.C.E. Greece.

This archive draws on, connects and critiques the methodologies of several disciplinary fields. I use post-colonial literary studies to map the literary genealogies Aesop; use a comparative historical approach to the abolitions of slavery in both the 19th century Caribbean and the Indian Ocean; and chart the early appearance of folk music in early colonial societies through Musicology and Performance Studies. Through the use of Sociolinguistics and theories of language revival, ecology, and change, I develop an approach of ‘reflexive Creolistics’ that I ultimately hope will offer new educational opportunities to Creole speakers. While it is my desire that this archive serves linguists, book collectors, and historians for further scientific inquiry into the innate international nature of Creole language, I also hope that this innovative material defense and illustration of Creole Literature will transform the consciousness of Creolophones (native and non-native) who too remain ‘bamboozled’ by the archive. My goal is to erase the ‘unthinkability’ of the existence of this ancient maritime creole literary canon from the collective cultural imaginary of readers around the globe.