UNSUPERVISED INDEXING OF MEDLINE ARTICLES THROUGH GRAPH-BASED RANKING

The biomedical literature is extensively catalogued and indexed in MEDLINE. MEDLINE indexing is done by trained human indexers, who identify the most important concepts in each article, and is expensive and inconsistent. Automating the indexing task is difficult: the National Library of Medicine produces the Medical Text Indexer (MTI), which suggests potential indexing terms to the indexers. MTI’s output is not good enough to work unattended. In my thesis, I propose a different way to approach the indexing task called MEDRank. MEDRank creates graphs representing the concepts in biomedical articles and their relationships within the text, and applies graph-based ranking algorithms to identify the most important concepts in each article. I evaluate the performance of several automated indexing solutions, including my own, by comparing their output to the indexing terms selected by the human indexers. MEDRank outperformed all other evaluated indexing solutions, including MTI, in general indexing performance and precision. MEDRank can be used to cluster documents, index any kind of biomedical text with standard vocabularies, or could become part of MTI itself.

Using citation data to improve retrieval from MEDLINE.

OBJECTIVE: To determine whether algorithms developed for the World Wide Web can be applied to the biomedical literature in order to identify articles that are important as well as relevant. DESIGN AND MEASUREMENTS A direct comparison of eight algorithms: simple PubMed queries, clinical queries (sensitive and specific versions), vector cosine comparison, citation count, journal impact factor, PageRank, and machine learning based on polynomial support vector machines. The objective was to prioritize important articles, defined as being included in a pre-existing bibliography of important literature in surgical oncology. RESULTS Citation-based algorithms were more effective than noncitation-based algorithms at identifying important articles. The most effective strategies were simple citation count and PageRank, which on average identified over six important articles in the first 100 results compared to 0.85 for the best noncitation-based algorithm (p < 0.001). The authors saw similar differences between citation-based and noncitation-based algorithms at 10, 20, 50, 200, 500, and 1,000 results (p < 0.001). Citation lag affects performance of PageRank more than simple citation count. However, in spite of citation lag, citation-based algorithms remain more effective than noncitation-based algorithms. CONCLUSION Algorithms that have proved successful on the World Wide Web can be applied to biomedical information retrieval. Citation-based algorithms can help identify important articles within large sets of relevant results. Further studies are needed to determine whether citation-based algorithms can effectively meet actual user information needs.

THE INTERACTION BETWEEN INTERNAL AND EXTERNAL INFORMATION ON RELATIONAL DATA SEARCH

People often use tools to search for information. In order to improve the quality of an information search, it is important to understand how internal information, which is stored in user’s mind, and external information, represented by the interface of tools interact with each other. How information is distributed between internal and external representations significantly affects information search performance. However, few studies have examined the relationship between types of interface and types of search task in the context of information search. For a distributed information search task, how data are distributed, represented, and formatted significantly affects the user search performance in terms of response time and accuracy. Guided by UFuRT (User, Function, Representation, Task), a human-centered process, I propose a search model, task taxonomy. The model defines its relationship with other existing information models. The taxonomy clarifies the legitimate operations for each type of search task of relation data. Based on the model and taxonomy, I have also developed prototypes of interface for the search tasks of relational data. These prototypes were used for experiments. The experiments described in this study are of a within-subject design with a sample of 24 participants recruited from the graduate schools located in the Texas Medical Center. Participants performed one-dimensional nominal search tasks over nominal, ordinal, and ratio displays, and searched one-dimensional nominal, ordinal, interval, and ratio tasks over table and graph displays. Participants also performed the same task and display combination for twodimensional searches. Distributed cognition theory has been adopted as a theoretical framework for analyzing and predicting the search performance of relational data. It has been shown that the representation dimensions and data scales, as well as the search task types, are main factors in determining search efficiency and effectiveness. In particular, the more external representations used, the better search task performance, and the results suggest the ideal search performance occurs when the question type and corresponding data scale representation match. The implications of the study lie in contributing to the effective design of search interface for relational data, especially laboratory results, which are often used in healthcare activities.

Thoracic target volume delineation using various maximum-intensity projection computed tomography image sets for stereotactic body radiation therapy

The motion of lung tumors during respiration makes the accurate delivery of radiation therapy to the thorax difficult because it increases the uncertainty of target position. The adoption of four-dimensional computed tomography (4D-CT) has allowed us to determine how a tumor moves with respiration for each individual patient. Using information acquired during a 4D-CT scan, we can define the target, visualize motion, and calculate dose during the planning phase of the radiotherapy process. One image data set that can be created from the 4D-CT acquisition is the maximum-intensity projection (MIP). The MIP can be used as a starting point to define the volume that encompasses the motion envelope of the moving gross target volume (GTV). Because of the close relationship that exists between the MIP and the final target volume, we investigated four MIP data sets created with different methodologies (3 using various 4D-CT sorting implementations, and one using all available cine CT images) to compare target delineation. It has been observed that changing the 4D-CT sorting method will lead to the selection of a different collection of images; however, the clinical implications of changing the constituent images on the resultant MIP data set are not clear. There has not been a comprehensive study that compares target delineation based on different 4D-CT sorting methodologies in a patient population. We selected a collection of patients who had previously undergone thoracic 4D-CT scans at our institution, and who had lung tumors that moved at least 1 cm. We then generated the four MIP data sets and automatically contoured the target volumes. In doing so, we identified cases in which the MIP generated from a 4D-CT sorting process under-represented the motion envelope of the target volume by more than 10% than when measured on the MIP generated from all of the cine CT images. The 4D-CT methods suffered from duplicate image selection and might not choose maximum extent images. Based on our results, we suggest utilization of a MIP generated from the full cine CT data set to ensure a representative inclusive tumor extent, and to avoid geometric miss.

Do binucleate cardiomyocytes have a role in myocardial repair? Insights using isolated rodent myocytes and cell culture.

Neonatal and adult cardiomyocytes were isolated from rat hearts. Some of the adult myocytes were cultured to allow for cell dedifferentiation, a phenomenon thought to mimic cell changes that occur in stressed myocardium, with myocytes regressing to a fetal pattern of metabolism and stellate neonatal shape.Using fluorescence deconvolution microscopy, cells were probed with fluorescent markers and scanned for a number of proteins associated with ion control, calcium movements and cardiac function. Image analysis of deconvoluted image stacks and sequential real-time image recordings of calcium transients of cells were made.All three myocyte groups were predominantly comprised of binucleate cells. Clustering of proteins to a single nucleus was a common observation, suggesting that one nucleus is active in protein synthesis pathways, while the other nucleus assumes a 'dormant' or different role and that cardiomyocytes might be mitotically active even in late development, or specific protein syntheses could be targeted and regulated for reintroduction into the cell cycle.Such possibilities would extend cardiac disease associated stem cell research and therapy options, while producing valuable insights into developmental and death pathways of binucleate cardiomyocytes (word count 183).

Evaluation of deformable image registration for improved 4D CT-derived ventilation for image guided radiotherapy

Recent treatment planning studies have demonstrated the use of physiologic images in radiation therapy treatment planning to identify regions for functional avoidance. This image-guided radiotherapy (IGRT) strategy may reduce the injury and/or functional loss following thoracic radiotherapy. 4D computed tomography (CT), developed for radiotherapy treatment planning, is a relatively new imaging technique that allows the acquisition of a time-varying sequence of 3D CT images of the patient's lungs through the respiratory cycle. Guerrero et al. developed a method to calculate ventilation imaging from 4D CT, which is potentially better suited and more broadly available for IGRT than the current standard imaging methods. The key to extracting function information from 4D CT is the construction of a volumetric deformation field that accurately tracks the motion of the patient's lungs during the respiratory cycle. The spatial accuracy of the displacement field directly impacts the ventilation images; higher spatial registration accuracy will result in less ventilation image artifacts and physiologic inaccuracies. Presently, a consistent methodology for spatial accuracy evaluation of the DIR transformation is lacking. Evaluation of the 4D CT-derived ventilation images will be performed to assess correlation with global measurements of lung ventilation, as well as regional correlation of the distribution of ventilation with the current clinical standard SPECT. This requires a novel framework for both the detailed assessment of an image registration algorithm's performance characteristics as well as quality assurance for spatial accuracy assessment in routine application. Finally, we hypothesize that hypo-ventilated regions, identified on 4D CT ventilation images, will correlate with hypo-perfused regions in lung cancer patients who have obstructive lesions. A prospective imaging trial of patients with locally advanced non-small-cell lung cancer will allow this hypothesis to be tested. These advances are intended to contribute to the validation and clinical implementation of CT-based ventilation imaging in prospective clinical trials, in which the impact of this imaging method on patient outcomes may be tested.

Multiple gradient echo propeller (MGREP) MRI: Technical development and potential applications

The PROPELLER (Periodically Rotated Overlapping Parallel Lines with Enhanced Reconstruction) magnetic resonance imaging (MRI) technique has inherent advantages over other fast imaging methods, including robust motion correction, reduced image distortion, and resistance to off-resonance effects. These features make PROPELLER highly desirable for T2*-sensitive imaging, high-resolution diffusion imaging, and many other applications. However, PROPELLER has been predominantly implemented as a fast spin-echo (FSE) technique, which is insensitive to T2* contrast, and requires time-inefficient signal averaging to achieve adequate signal-to-noise ratio (SNR) for many applications. These issues presently constrain the potential clinical utility of FSE-based PROPELLER. ^ In this research, our aim was to extend and enhance the potential applications of PROPELLER MRI by developing a novel multiple gradient echo PROPELLER (MGREP) technique that can overcome the aforementioned limitations. The MGREP pulse sequence was designed to acquire multiple gradient-echo images simultaneously, without any increase in total scan time or RF energy deposition relative to FSE-based PROPELLER. A new parameter was also introduced for direct user-control over gradient echo spacing, to allow variable sensitivity to T2* contrast. In parallel to pulse sequence development, an improved algorithm for motion correction was also developed and evaluated against the established method through extensive simulations. The potential advantages of MGREP over FSE-based PROPELLER were illustrated via three specific applications: (1) quantitative T2* measurement, (2) time-efficient signal averaging, and (3) high-resolution diffusion imaging. Relative to the FSE-PROPELLER method, the MGREP sequence was found to yield quantitative T2* values, increase SNR by ∼40% without any increase in acquisition time or RF energy deposition, and noticeably improve image quality in high-resolution diffusion maps. In addition, the new motion algorithm was found to improve the performance considerably in motion-artifact reduction. ^ Overall, this work demonstrated a number of enhancements and extensions to existing PROPELLER techniques. The new technical capabilities of PROPELLER imaging, developed in this thesis research, are expected to serve as the foundation for further expanding the scope of PROPELLER applications. ^

Comparison of Tumor Shrinkage and Cumulative Dose Distribution for Lung Cancers

Background: The physical characteristic of protons is that they deliver most of their radiation dose to the target volume and deliver no dose to the normal tissue distal to the tumor. Previously, numerous studies have shown unique advantages of proton therapy over intensity-modulated radiation therapy (IMRT) in conforming dose to the tumor and sparing dose to the surrounding normal tissues and the critical structures in many clinical sites. However, proton therapy is known to be more sensitive to treatment uncertainties such as inter- and intra-fractional variations in patient anatomy. To date, no study has clearly demonstrated the effectiveness of proton therapy compared with the conventional IMRT under the consideration of both respiratory motion and tumor shrinkage in non-small cell lung cancer (NSCLC) patients. Purpose: This thesis investigated two questions for establishing a clinically relevant comparison of the two different modalities (IMRT and proton therapy). The first question was whether or not there are any differences in tumor shrinkage between patients randomized to IMRT versus passively scattered proton therapy (PSPT). Tumor shrinkage is considered a standard measure of radiation therapy response that has been widely used to gauge a short-term progression of radiation therapy. The second question was whether or not there are any differences between the planned dose and 5D dose under the influence of inter- and intra-fractional variations in the patient anatomy for both modalities. Methods: A total of 45 patients (25 IMRT patients and 20 PSPT patients) were used to quantify the tumor shrinkage in terms of the change of the primary gross tumor volume (GTVp). All patients were randomized to receive either IMRT or PSPT for NSCLC. Treatment planning goals were identical for both groups. All patients received 5 to 8 weekly repeated 4-dimensional computed tomography (4DCT) scans during the course of radiation treatments. The original GTVp contours were propagated to T50 of weekly 4DCT images using deformable image registration and their absolute volumes were measured. Statistical analysis was performed to compare the distribution of tumor shrinkage between the two population groups. In order to investigate the difference between the planned dose and the 5D dose with consideration of both breathing motion and anatomical change, we re-calculated new dose distributions at every phase of the breathing cycle for all available weekly 4DCT data sets which resulted 50 to 80 individual dose calculations for each of the 7 patients presented in this thesis. The newly calculated dose distributions were then deformed and accumulated to T50 of the planning 4DCT for comparison with the planned dose distribution. Results: At the end of the treatment, both IMRT and PSPT groups showed mean tumor volume reductions of 23.6% ( 19.2%) and 20.9% ( 17.0 %) respectively. Moreover, the mean difference in tumor shrinkage between two groups is 3% along with the corresponding 95% confidence interval, [-8%, 14%]. The rate of tumor shrinkage was highly correlated with the initial tumor volume size. For the planning dose and 5D dose comparison study, all 7 patients showed a mean difference of 1 % in terms of target coverage for both IMRT and PSPT treatment plans. Conclusions: The results of the tumor shrinkage investigation showed no statistically significant difference in tumor shrinkage between the IMRT and PSPT patients, and the tumor shrinkage between the two modalities is similar based on the 95% confidence interval. From the pilot study of comparing the planned dose with the 5D dose, we found the difference to be only 1%. Overall impression of the two modalities in terms of treatment response as measured by the tumor shrinkage and 5D dose under the influence of anatomical change that were designed under the same protocol (i.e. randomized trial) showed similar result.