The lived experience of healing touch with cancer patients

The recent use of complementary therapies by cancer patients has prompted the study of the use of Healing Touch, an energy based therapy, to learn the meaning of the experience. By using Ray's Caring Inquiry, a phenomenologic-hermeneutic process, the lived experience of receiving Healing Touch was elicited from three cancer patients. Through the interactions of the Healing Touch practitioners, the cancer patient participants, and the energy in and around them, specific themes were expressed: body-physical, emotion-feeling, mental-knowing, and spirit-essence. Further abstracting lead to the metathemes sensation and perception. Through a change in consciousness, a oneness/wholeness was experienced. The unity of meaning elicited was the Rhythm of Oneness Through Energy which is the connecting, opening, and cocreating through caring, the wholeness of each to become one through rhythms of energy. ^

Emotions and Learning in Support Groups of Female Breast Cancer Patients

The understanding of emotions and learning in the participants of breast cancer support groups will assist in better preparation of how to cope with the disease these patients face. It is in working through emotional experiences that participants are able to learn and grow in support groups.

A multi-faceted diagnostic approach to lung infections in patients with cystic fibrosis

One in 3,000 people in the US are born with cystic fibrosis (CF), a genetic disorder affecting the reproductive system, pancreas, and lungs. Lung disease caused by chronic bacterial and fungal infections is the leading cause of morbidity and mortality in CF. Identities of the microbes are traditionally determined by culturing followed by phenotypic and biochemical assays. It was first thought that the bacterial infections were caused by a select handful of bacteria such as S. aureus, H. influenzae, B. cenocepacia, and P. aeruginosa. With the advent of PCR and molecular techniques, the polymicrobial nature of the CF lung became evident. The CF lung contains numerous bacteria and the communities are diverse and unique to each patient. The total complexity of the bacterial infections is still being determined. In addition, only a few members of the fungal communities have been identified. Much of the fungal community composition is still a mystery. This dissertation addresses this gap in knowledge. A snap shot of CF sputa bacterial community was obtained using the length heterogeneity-PCR community profiling technique. The profiles show that south Florida CF patients have a unique, diverse, and dynamic bacterial community which changes over time. The identities of the bacteria and fungi present were determined using the state-of-the-art 454 sequencing. Sequencing results show that the CF lung microbiome contains commonly cultured pathogenic bacteria, organisms considered a part of the healthy core biome, and novel organisms. Understanding the dynamic changes of these identified microbes will ultimately lead to better therapeutical interventions. Early detection is key in reducing the lung damage caused by chronic infections. Thus, there is a need for accurate and sensitive diagnostic tests. This issue was addressed by designing a bacterial diagnostic tool targeted towards CF pathogens using SPR. By identifying the organisms associated with the CF lung and understanding their community interactions, patients can receive better treatment and live longer.

A Multi-Faceted Diagnostic Approach to Lung Infections in Patients with Cystic Fibrosis

One in 3,000 people in the US are born with cystic fibrosis (CF), a genetic disorder affecting the reproductive system, pancreas, and lungs. Lung disease caused by chronic bacterial and fungal infections is the leading cause of morbidity and mortality in CF. Identities of the microbes are traditionally determined by culturing followed by phenotypic and biochemical assays. It was first thought that the bacterial infections were caused by a select handful of bacteria such as S. aureus, H. influenzae, B. cenocepacia, and P. aeruginosa. With the advent of PCR and molecular techniques, the polymicrobial nature of the CF lung became evident. The CF lung contains numerous bacteria and the communities are diverse and unique to each patient. The total complexity of the bacterial infections is still being determined. In addition, only a few members of the fungal communities have been identified. Much of the fungal community composition is still a mystery. This dissertation addresses this gap in knowledge. A snap shot of CF sputa bacterial community was obtained using the length heterogeneity-PCR community profiling technique. The profiles show that south Florida CF patients have a unique, diverse, and dynamic bacterial community which changes over time. The identities of the bacteria and fungi present were determined using the state-of-the-art 454 sequencing. Sequencing results show that the CF lung microbiome contains commonly cultured pathogenic bacteria, organisms considered a part of the healthy core biome, and novel organisms. Understanding the dynamic changes of these identified microbes will ultimately lead to better therapeutical interventions. Early detection is key in reducing the lung damage caused by chronic infections. Thus, there is a need for accurate and sensitive diagnostic tests. This issue was addressed by designing a bacterial diagnostic tool targeted towards CF pathogens using SPR. By identifying the organisms associated with the CF lung and understanding their community interactions, patients can receive better treatment and live longer.

A novel 3-D segmentation algorithm for anatomic liver and tumor volume calculations for liver cancer treatment planning

Three-Dimensional (3-D) imaging is vital in computer-assisted surgical planning including minimal invasive surgery, targeted drug delivery, and tumor resection. Selective Internal Radiation Therapy (SIRT) is a liver directed radiation therapy for the treatment of liver cancer. Accurate calculation of anatomical liver and tumor volumes are essential for the determination of the tumor to normal liver ratio and for the calculation of the dose of Y-90 microspheres that will result in high concentration of the radiation in the tumor region as compared to nearby healthy tissue. Present manual techniques for segmentation of the liver from Computed Tomography (CT) tend to be tedious and greatly dependent on the skill of the technician/doctor performing the task. ^ This dissertation presents the development and implementation of a fully integrated algorithm for 3-D liver and tumor segmentation from tri-phase CT that yield highly accurate estimations of the respective volumes of the liver and tumor(s). The algorithm as designed requires minimal human intervention without compromising the accuracy of the segmentation results. Embedded within this algorithm is an effective method for extracting blood vessels that feed the tumor(s) in order to plan effectively the appropriate treatment. ^ Segmentation of the liver led to an accuracy in excess of 95% in estimating liver volumes in 20 datasets in comparison to the manual gold standard volumes. In a similar comparison, tumor segmentation exhibited an accuracy of 86% in estimating tumor(s) volume(s). Qualitative results of the blood vessel segmentation algorithm demonstrated the effectiveness of the algorithm in extracting and rendering the vasculature structure of the liver. Results of the parallel computing process, using a single workstation, showed a 78% gain. Also, statistical analysis carried out to determine if the manual initialization has any impact on the accuracy showed user initialization independence in the results. ^ The dissertation thus provides a complete 3-D solution towards liver cancer treatment planning with the opportunity to extract, visualize and quantify the needed statistics for liver cancer treatment. Since SIRT requires highly accurate calculation of the liver and tumor volumes, this new method provides an effective and computationally efficient process required of such challenging clinical requirements.^