10 resultados para Approval plans in library acquisitions

em DigitalCommons@The Texas Medical Center


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This study investigated characteristics of optically stimulated luminescent detectors (OSLDs) in protons, allowing comparison to thermoluminescent detectors, and to be implemented into the Radiological Physics Center’s (RPC) remote audit quality assurance program for protons, and for remote anthropomorphic phantom irradiations. The OSLDs used were aluminum oxide (Al2O3:C) nanoDots from Landauer, Inc. (Glenwood, Ill.) measuring 10x10x2 mm3. A square, 20(L)x20(W)x0.5(H) cm3 piece of solid water was fabricated with pockets to allow OSLDs and TLDs to be irradiated simultaneously and perpendicular to the beam. Irradiations were performed at 5cm depth in photons, and in the center of a 10 cm SOBP in a 200MeV proton beam. Additionally, the Radiological Physics Center’s anthropomorphic pelvic phantom was used to test the angular dependence of OSLDs in photons and protons. A cylindrical insert in the phantom allows the dosimeters to be rotated to any angle with a fixed gantry angle. OSLDs were irradiated at 12 angles between 0 and 360 degrees. The OSLDs were read out with a MicroStar reader from Landauer, Inc. Dose response indicates that at angles where the dosimeter is near parallel with the radiation beam response is reduced slightly. Measurements in proton beams do not show significant angular dependence. Post-irradiation fading of OSLDs was studied in proton beams to determine if the fading was different than that of photons. The fading results showed no significant difference from results in photon beams. OSLDs and TLDs are comparable within 3% in photon beams and a correction factor can be posited for proton beams. With angular dependence characteristics defined, OSLDs can be implemented into multiple-field treatment plans in photons and protons and used in the RPC’s quality assurance program.

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Purpose: To evaluate normal tissue dose reduction in step-and-shoot intensity-modulated radiation therapy (IMRT) on the Varian 2100 platform by tracking the multileaf collimator (MLC) apertures with the accelerator jaws. Methods: Clinical radiation treatment plans for 10 thoracic, 3 pediatric and 3 head and neck patients were converted to plans with the jaws tracking each segment’s MLC apertures. Each segment was then renormalized to account for the change in collimator scatter to obtain target coverage within 1% of that in the original plan. The new plans were compared to the original plans in a commercial radiation treatment planning system (TPS). Reduction in normal tissue dose was evaluated in the new plan by using the parameters V5, V10, and V20 in the cumulative dose-volume histogram for the following structures: total lung minus GTV (gross target volume), heart, esophagus, spinal cord, liver, parotids, and brainstem. In order to validate the accuracy of our beam model, MLC transmission measurements were made and compared to those predicted by the TPS. Results: The greatest change between the original plan and new plan occurred at lower dose levels. The reduction in V20 was never more than 6.3% and was typically less than 1% for all patients. The reduction in V5 was 16.7% maximum and was typically less than 3% for all patients. The variation in normal tissue dose reduction was not predictable, and we found no clear parameters that indicated which patients would benefit most from jaw tracking. Our TPS model of MLC transmission agreed with measurements with absolute transmission differences of less than 0.1 % and thus uncertainties in the model did not contribute significantly to the uncertainty in the dose determination. Conclusion: The amount of dose reduction achieved by collimating the jaws around each MLC aperture in step-and-shoot IMRT does not appear to be clinically significant.

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The events of the 1990's and early 2000's demonstrated the need for effective planning and response to natural and man-made disasters. One of those potential natural disasters is pandemic flu. Once defined, the CDC stated that program, or plan, effectiveness is improved through the process of program evaluation. (Centers for Disease Control and Prevention, 1999) Program evaluation should be accomplished not only periodically, but in the course of routine administration of the program. (Centers for Disease Control and Prevention, 1999) Accomplishing this task for a "rare, but significant event" is challenging. (Herbold, John R., PhD., 2008) To address this challenge, the RAND Corporation (under contract to the CDC) developed the "Facilitated Look-Backs" approach that was tested and validated at the state level. (Aledort et al., 2006).^ Nevertheless, no comprehensive and generally applicable pandemic influenza program evaluation tool or model is readily found for use at the local public health department level. This project developed such a model based on the "Facilitated Look-Backs" approach developed by RAND Corporation. (Aledort et al., 2006) Modifications to the RAND model included stakeholder additions, inclusion of all six CDC program evaluation steps, and suggestions for incorporating pandemic flu response plans in seasonal flu management implementation. Feedback on the model was then obtained from three LPHD's—one rural, one suburban, and one urban. These recommendations were incorporated into the final model. Feedback from the sites also supported the assumption that this model promotes the effective and efficient evaluation of both pandemic flu and seasonal flu response by reducing redundant evaluations of pandemic flu plans, seasonal flu plans, and funding requirement accountability. Site feedback also demonstrated that the model is comprehensive and flexible, so it can be adapted and applied to different LPHD needs and settings. It also stimulates evaluation of the major issues associated with pandemic flu planning. ^ The next phase in evaluating this model should be to apply it in a program evaluation of one or more LPHD's seasonal flu response that incorporates pandemic flu response plans.^

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The effectiveness of the Anisotropic Analytical Algorithm (AAA) implemented in the Eclipse treatment planning system (TPS) was evaluated using theRadiologicalPhysicsCenteranthropomorphic lung phantom using both flattened and flattening-filter-free high energy beams. Radiation treatment plans were developed following the Radiation Therapy Oncology Group and theRadiologicalPhysicsCenterguidelines for lung treatment using Stereotactic Radiation Body Therapy. The tumor was covered such that at least 95% of Planning Target Volume (PTV) received 100% of the prescribed dose while ensuring that normal tissue constraints were followed as well. Calculated doses were exported from the Eclipse TPS and compared with the experimental data as measured using thermoluminescence detectors (TLD) and radiochromic films that were placed inside the phantom. The results demonstrate that the AAA superposition-convolution algorithm is able to calculate SBRT treatment plans with all clinically used photon beams in the range from 6 MV to 18 MV. The measured dose distribution showed a good agreement with the calculated distribution using clinically acceptable criteria of ±5% dose or 3mm distance to agreement. These results show that in a heterogeneous environment a 3D pencil beam superposition-convolution algorithms with Monte Carlo pre-calculated scatter kernels, such as AAA, are able to reliably calculate dose, accounting for increased lateral scattering due to the loss of electronic equilibrium in low density medium. The data for high energy plans (15 MV and 18 MV) showed very good tumor coverage in contrast to findings by other investigators for less sophisticated dose calculation algorithms, which demonstrated less than expected tumor doses and generally worse tumor coverage for high energy plans compared to 6MV plans. This demonstrates that the modern superposition-convolution AAA algorithm is a significant improvement over previous algorithms and is able to calculate doses accurately for SBRT treatment plans in the highly heterogeneous environment of the thorax for both lower (≤12 MV) and higher (greater than 12 MV) beam energies.

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An interim analysis is usually applied in later phase II or phase III trials to find convincing evidence of a significant treatment difference that may lead to trial termination at an earlier point than planned at the beginning. This can result in the saving of patient resources and shortening of drug development and approval time. In addition, ethics and economics are also the reasons to stop a trial earlier. In clinical trials of eyes, ears, knees, arms, kidneys, lungs, and other clustered treatments, data may include distribution-free random variables with matched and unmatched subjects in one study. It is important to properly include both subjects in the interim and the final analyses so that the maximum efficiency of statistical and clinical inferences can be obtained at different stages of the trials. So far, no publication has applied a statistical method for distribution-free data with matched and unmatched subjects in the interim analysis of clinical trials. In this simulation study, the hybrid statistic was used to estimate the empirical powers and the empirical type I errors among the simulated datasets with different sample sizes, different effect sizes, different correlation coefficients for matched pairs, and different data distributions, respectively, in the interim and final analysis with 4 different group sequential methods. Empirical powers and empirical type I errors were also compared to those estimated by using the meta-analysis t-test among the same simulated datasets. Results from this simulation study show that, compared to the meta-analysis t-test commonly used for data with normally distributed observations, the hybrid statistic has a greater power for data observed from normally, log-normally, and multinomially distributed random variables with matched and unmatched subjects and with outliers. Powers rose with the increase in sample size, effect size, and correlation coefficient for the matched pairs. In addition, lower type I errors were observed estimated by using the hybrid statistic, which indicates that this test is also conservative for data with outliers in the interim analysis of clinical trials.^

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Purpose. To investigate and understand the illness experiences of patients and their family members living with congestive heart failure (CHF). ^ Design. Focused ethnographic design. ^ Setting. One outpatient cardiology clinic, two outpatient heart failure clinics, and informants' homes in a large metropolitan city located in southeast Texas. ^ Sample. A purposeful sampling technique was used to select a sample of 28 informants. The following somewhat overlapping, sampling strategies were used to implement the purposeful method: criterion; typical case; operational construct; maximum variation; atypical case; opportunistic; and confirming and disconfirming case sampling. ^ Methods. Naturalistic inquiry consisted of data collected from observations, participant observations, and interviews. Open-ended semi-structured illness narrative interviews included questions designed to elicit informant's explanatory models of the illness, which served as a synthesizing framework for the analysis. A thematic analysis process was conducted through domain analysis and construction of data into themes and sub-themes. Credibility was enhanced through informant verification and a process of peer debriefing. ^ Findings. Thematic analysis revealed that patients and their family members living with CHF experience a process of disruption, incoherence, and reconciling. Reconciling emerged as the salient experience described by informants. Sub-themes of reconciling that emerged from the analysis included: struggling; participating in partnerships; finding purpose and meaning in the illness experience; and surrendering. ^ Conclusions. Understanding the experiences described in this study allows for a better understanding of living with CHF in everyday life. Findings from this study suggest that the experience of living with CHF entails more than the medical story can tell. It is important for nurses and other providers to understand the experiences of this population in order to develop appropriate treatment plans in a successful practitioner-patient partnership. ^

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Purpose: Traditional patient-specific IMRT QA measurements are labor intensive and consume machine time. Calculation-based IMRT QA methods typically are not comprehensive. We have developed a comprehensive calculation-based IMRT QA method to detect uncertainties introduced by the initial dose calculation, the data transfer through the Record-and-Verify (R&V) system, and various aspects of the physical delivery. Methods: We recomputed the treatment plans in the patient geometry for 48 cases using data from the R&V, and from the delivery unit to calculate the “as-transferred” and “as-delivered” doses respectively. These data were sent to the original TPS to verify transfer and delivery or to a second TPS to verify the original calculation. For each dataset we examined the dose computed from the R&V record (RV) and from the delivery records (Tx), and the dose computed with a second verification TPS (vTPS). Each verification dose was compared to the clinical dose distribution using 3D gamma analysis and by comparison of mean dose and ROI-specific dose levels to target volumes. Plans were also compared to IMRT QA absolute and relative dose measurements. Results: The average 3D gamma passing percentages using 3%-3mm, 2%-2mm, and 1%-1mm criteria for the RV plan were 100.0 (σ=0.0), 100.0 (σ=0.0), and 100.0 (σ=0.1); for the Tx plan they were 100.0 (σ=0.0), 100.0 (σ=0.0), and 99.0 (σ=1.4); and for the vTPS plan they were 99.3 (σ=0.6), 97.2 (σ=1.5), and 79.0 (σ=8.6). When comparing target volume doses in the RV, Tx, and vTPS plans to the clinical plans, the average ratios of ROI mean doses were 0.999 (σ=0.001), 1.001 (σ=0.002), and 0.990 (σ=0.009) and ROI-specific dose levels were 0.999 (σ=0.001), 1.001 (σ=0.002), and 0.980 (σ=0.043), respectively. Comparing the clinical, RV, TR, and vTPS calculated doses to the IMRT QA measurements for all 48 patients, the average ratios for absolute doses were 0.999 (σ=0.013), 0.998 (σ=0.013), 0.999 σ=0.015), and 0.990 (σ=0.012), respectively, and the average 2D gamma(5%-3mm) passing percentages for relative doses for 9 patients was were 99.36 (σ=0.68), 99.50 (σ=0.49), 99.13 (σ=0.84), and 98.76 (σ=1.66), respectively. Conclusions: Together with mechanical and dosimetric QA, our calculation-based IMRT QA method promises to minimize the need for patient-specific QA measurements by identifying outliers in need of further review.

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Congress and the Department of Health and Human Services (DHHS) intend for the Family Preservation and Support Act of 1993 (P.L. 103-66) to catalyze major reforms in state human services systems. DHHS and numerous other institutions developed conceptual and procedural guidance for the states' planning processes. Review of the planning dimensions of participation and expertise reveals that major emphases on stakeholder participation and technical planning processes obscure the need for expertise in family preservation and family support.

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In spite of the dramatic increase and general concern with U.S. hospital bad debt expense (AMNews, January 12, 2004; Philadelphia Business Journal, April 30, 2004; WSJ, July 23, 2004), there appears to be little available analysis of the precise sources and causes of its growth. This is particularly true in terms of the potential contribution of insured patients to bad debt expense in light of the recent shift in managed care from health maintenance organization (HMO) plans to preferred provider organization (PPO) plans (Kaiser Annual Survey Report, 2003). This study examines and attempts to explain the recent dramatic growth in bad debt expense by focusing on and analyzing data from two Houston-area hospital providers within one healthcare system. In contrast to prior studies in which self-pay was found to be the primary source of hospital bad debt expense (Saywell, R. M., et al., 1989; Zollinger, T. W., 1991; Weissman, Joel S., et al., 1999), this study hypothesizes that the growing hospital bad debt expense is mainly due to the shifting trend away from HMOs to PPOs as a conscious decision by employers to share costs with employees. Compared to HMO plans, the structure of PPOs includes higher co-pays, coinsurance, and deductibles for the patient-pay portion of medical bills, creating the potential for an increase in bad debt for hospital providers (from a case study). This bad debt expense has a greater impact in the community hospital than in the Texas Medical Center hospital. ^