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.

Automatic quantitation of multiple sclerosis lesions on MR images

A two-pronged approach for the automatic quantitation of multiple sclerosis (MS) lesions on magnetic resonance (MR) images has been developed. This method includes the design and use of a pulse sequence for improved lesion-to-tissue contrast (LTC) and seeks to identify and minimize the sources of false lesion classifications in segmented images. The new pulse sequence, referred to as AFFIRMATIVE (Attenuation of Fluid by Fast Inversion Recovery with MAgnetization Transfer Imaging with Variable Echoes), improves the LTC, relative to spin-echo images, by combining Fluid-Attenuated Inversion Recovery (FLAIR) and Magnetization Transfer Contrast (MTC). In addition to acquiring fast FLAIR/MTC images, the AFFIRMATIVE sequence simultaneously acquires fast spin-echo (FSE) images for spatial registration of images, which is necessary for accurate lesion quantitation. Flow has been found to be a primary source of false lesion classifications. Therefore, an imaging protocol and reconstruction methods are developed to generate "flow images" which depict both coherent (vascular) and incoherent (CSF) flow. An automatic technique is designed for the removal of extra-meningeal tissues, since these are known to be sources of false lesion classifications. A retrospective, three-dimensional (3D) registration algorithm is implemented to correct for patient movement which may have occurred between AFFIRMATIVE and flow imaging scans. Following application of these pre-processing steps, images are segmented into white matter, gray matter, cerebrospinal fluid, and MS lesions based on AFFIRMATIVE and flow images using an automatic algorithm. All algorithms are seamlessly integrated into a single MR image analysis software package. Lesion quantitation has been performed on images from 15 patient volunteers. The total processing time is less than two hours per patient on a SPARCstation 20. The automated nature of this approach should provide an objective means of monitoring the progression, stabilization, and/or regression of MS lesions in large-scale, multi-center clinical trials. ^

Delineation of a novel genetic region at 5q11 harboring tumor suppressor gene(s) and identification of the telomeric DNA as a marker for human prostate cancer

Prostate cancer is the most commonly diagnosed cancer and the second leading cause of cancer mortality in American men. The distinction between those cases of prostate cancer destined to progress rapidly to lethal metastatic disease and those with little likelihood of causing morbidity and mortality is a major goal of current research. Some type of diagnostic method is urgently needed to identify which histological prostate cancers have completed the progression to a stage that will produce a life-threatening disease, thus requiring immediate therapeutic intervention. The objectives of this dissertation are to delineate a novel genetic region harboring tumor suppressor gene(s) and to identify a marker for prostate tumorigenesis. I first established an in vitro cell model system from a human prostate epithelial cells derived from tissue fragments surrounding a prostate tumor in a patient with prostatic adenocarcinoma. Since chromosome 5 abnormality was present in early, middle and late passages of this cell model system, I examined long-term established prostate cancer cell lines for this chromosome abnormality. The results implicated the region surrounding marker D5S2068 as the locus of interest for further experimentation and location of a tumor suppressor gene in human prostate cancer. ^ Cancer is a group of complex genetic diseases with uncontrolled cell; division and prostate cancer is no exception. I determined if telomeric DNA, and telomerase activity, alone or together, could serve as biomarkers of prostate tumorigenesis. I studied three newly established human prostate cancer cell lines and three fibroblast cell cultures derived from prostate tissues. In conclusion, my data reveal that in the presence of telomerase activity, telomeric repeats are maintained at a certain optimal length, and analysis of telomeric DNA variations might serve as early diagnostic and prognostic biomarkers for prostate cancer. (Abstract shortened by UMI.)^