Development of automated image analysis tools for verification of radiotherapy field accuracy with an electronic portal imaging device

The successful management of cancer with radiation relies on the accurate deposition of a prescribed dose to a prescribed anatomical volume within the patient. Treatment set-up errors are inevitable because the alignment of field shaping devices with the patient must be repeated daily up to eighty times during the course of a fractionated radiotherapy treatment. With the invention of electronic portal imaging devices (EPIDs), patient's portal images can be visualized daily in real-time after only a small fraction of the radiation dose has been delivered to each treatment field. However, the accuracy of human visual evaluation of low-contrast portal images has been found to be inadequate. The goal of this research is to develop automated image analysis tools to detect both treatment field shape errors and patient anatomy placement errors with an EPID. A moments method has been developed to align treatment field images to compensate for lack of repositioning precision of the image detector. A figure of merit has also been established to verify the shape and rotation of the treatment fields. Following proper alignment of treatment field boundaries, a cross-correlation method has been developed to detect shifts of the patient's anatomy relative to the treatment field boundary. Phantom studies showed that the moments method aligned the radiation fields to within 0.5mm of translation and 0.5$\sp\circ$ of rotation and that the cross-correlation method aligned anatomical structures inside the radiation field to within 1 mm of translation and 1$\sp\circ$ of rotation. A new procedure of generating and using digitally reconstructed radiographs (DRRs) at megavoltage energies as reference images was also investigated. The procedure allowed a direct comparison between a designed treatment portal and the actual patient setup positions detected by an EPID. Phantom studies confirmed the feasibility of the methodology. Both the moments method and the cross-correlation technique were implemented within an experimental radiotherapy picture archival and communication system (RT-PACS) and were used clinically to evaluate the setup variability of two groups of cancer patients treated with and without an alpha-cradle immobilization aid. The tools developed in this project have proven to be very effective and have played an important role in detecting patient alignment errors and field-shape errors in treatment fields formed by a multileaf collimator (MLC). ^

Characterization of the human tissue transglutaminase gene promoter

Transglutaminases are a family of calcium-dependent enzymes, that catalyze the covalent cross-linking of proteins by forming $\varepsilon(\gamma$-glutamyl)lysine isopeptide bonds. In order to investigate the molecular mechanisms regulating the expression of the tissue transglutaminase gene and to determine its biological functions, the goal of this research has been to clone and characterize the human tissue transglutaminase promoter. Thirteen clones of the tissue transglutaminase gene were obtained from the screening of a human placental genomic DNA library. A 1.74 Kb fragment derived from DNA located immediately upstream of the translation start site was subcloned and sequenced. Sequence analysis of this DNA fragment revealed that it contains a TATA box (TATAA), a CAAT box (GGACAAT), and a series of potential transcription factor binding sites and hormone response elements. Four regions of significant homology, a GC-rich region, a TG-rich region, an AG-rich region, and HR1, were identified by aligning 1.8 Kb of DNA flanking the human, mouse, and guinea pig tissue transglutaminase genes.^ To measure promoter activity, we subcloned the 1.74 Kb fragment of the tissue transglutaminase gene into a luciferase reporter vector to generate transglutaminase promoter/luciferase reporter constructs. Transfection experiments showed that this DNA segment includes a functional promoter with high constitutive activity. Deletion analysis revealed that the SP1 sites or corresponding sequences contribute to this activity. We investigated the role of DNA methylation in regulating the activity of the promoter and found that in vitro methylation of tissue transglutaminase promoter/luciferase reporter constructs suppressed their basal activity. Methylation of the promoter is inversely correlated with the expression of the tissue transglutaminase gene in vivo. These results suggest that DNA methylation may be one of the mechanisms regulating the expression of the gene. The tumor suppressor gene product p53 was also shown to inhibit the activity of the promoter, suggesting that induction of the tissue transglutaminase gene is not involved in the p53-dependent programmed cell death pathway. Although retinoids regulate the expression of the tissue transglutaminase gene in vivo, retinoid-inducible activity can not be identified in 3.7 Kb of DNA 5$\sp\prime$ to the tissue transglutaminase gene.^ The structure of the 5$\sp\prime$ end of the tissue transglutaminase gene was mapped. Alignment analysis of the human tissue transglutaminase gene with other human transglutaminases showed that tissue transglutaminase is the simplest member of transglutaminase superfamily. Transglutaminase genes show a conserved core of exons and introns but diverse N-terminuses and promoters. These observations suggest that key regulatory sequences and promoter elements have been appended upstream of the core transglutaminase gene to generate the diversity of regulated expression and regulated activity characteristic of the transglutaminase gene family. ^

Procedure for the identification of population characteristics for targeting intervention services on the basis of outcome-goal priorities: Case management services for the chronic mentally ill

Although the processes involved in rational patient targeting may be obvious for certain services, for others, both the appropriate sub-populations to receive services and the procedures to be used for their identification may be unclear. This project was designed to address several research questions which arise in the attempt to deliver appropriate services to specific populations. The related difficulties are particularly evident for those interventions about which findings regarding effectiveness are conflicting. When an intervention clearly is not beneficial (or is dangerous) to a large, diverse population, consensus regarding withholding the intervention from dissemination can easily be reached. When findings are ambiguous, however, conclusions may be impossible.^ When characteristics of patients likely to benefit from an intervention are not obvious, and when the intervention is not significantly invasive or dangerous, the strategy proposed herein may be used to identify specific characteristics of sub-populations which may benefit from the intervention. The identification of these populations may be used both in further informing decisions regarding distribution of the intervention and for purposes of planning implementation of the intervention by identifying specific target populations for service delivery.^ This project explores a method for identifying such sub-populations through the use of related datasets generated from clinical trials conducted to test the effectiveness of an intervention. The method is specified in detail and tested using the example intervention of case management for outpatient treatment of populations with chronic mental illness. These analyses were applied in order to identify any characteristics which distinguish specific sub-populations who are more likely to benefit from case management service, despite conflicting findings regarding its effectiveness for the aggregate population, as reported in the body of related research. However, in addition to a limited set of characteristics associated with benefit, the findings generated, a larger set of characteristics of patients likely to experience greater improvement without intervention. ^