EVALUATION OF THE EFFECTIVENESS OF ANISOTROPIC ANALYTICAL ALGORITHM IN FLATTENED AND FLATTENING-FILTER-FREE BEAMS FOR HIGH ENERGY LUNG DOSE DELIVERY USING THE RADIOLOGICAL PHYSICS CENTER LUNG PHANTOM

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.

Indeterminate QunatiFERON-TB Gold In-Tube assay results in association with procedural specimen collection in children

BACKGROUND. The development of interferon-gamma release assays (IGRA) has introduced powerful tools in diagnosing latent tuberculosis infection (LTBI) and may play a critical role in the future of tuberculosis diagnosis. However, there have been reports of high indeterminate results in young patient populations (0-18 years). This study investigated results of the QunatiFERON-TB Gold In-Tube (QFT-GIT) IGRA in a population of children (0-18 years) at Texas Children's Hospital in association with specimen collection procedures using surrogate variables. ^ METHODS. A retrospective case-control study design was used for this investigation. Cases were defined as having QFT-GIT indeterminate results. Controls were defined as having either positive or negative results (determinates). Patients' admission status, staff performing specimen collection, and specific nurse performing specimen collection were used as surrogates to measure specimen collection procedures. ^ To minimize potential confounding, abstraction of patients' electronic medical records was performed. Abstracted data included patients' medications and evaluation at the time of QFT-GIT specimen collection in addition to their medical history. QFT-GIT related data was also abstracted. Cases and controls were characterized using chi-squared tests or Fisher's exact tests across categorical variables. Continuous variables were analyzed using one-way ANOVA and t-tests for continuous variables. A multivariate model was constructed by backward stepwise removal of statistically significant variables from univariate analysis. ^ RESULTS. Patient data was abstracted from 182 individuals aged 0-18 years from July 2010 to August 2011 at Texas Children's Hospital. 56 cases (indeterminates) and 126 controls (determinates) were enrolled. Cancer was found to be an effect modifier with subsequent stratification resulting in a cancer patient population too small to analyze (n=13). Subsequent analyses excluded these patients. ^ The exclusion of cancer patients resulted in a population of 169 patients with 49 indeterminates (28.99%) and 120 determinates (71.01%), with mean ages of 9.73 (95% CI: 8.03, 11.43) years and 11.66 (95% CI: 10.75, 12.56) years (p = 0.033), respectively. Median age of patients who were indeterminates and determinates were 12.37 and 12.87 years, respectively. Lack of data for our specific nurse surrogate (QFTNurse) resulted in its exclusion from analysis. The final model included only our remaining surrogate variables (QFTStaff and QFTInpatientOutpatient). The staff collecting surrogate (QFTStaff) was found to be modestly associated with indeterminates when nurses collected the specimen (OR = 1.54, 95% CI: 0.51, 4.64, p = 0.439) in the final model. Inpatients were found to have a strong and statistically significant association with indeterminates (OR = 11.65, 95% CI: 3.89, 34.9, p < 0.001) in the final model. ^ CONCLUSION. Inpatient status was used as a surrogate for indication of nurse drawn blood specimens. Nurses have had little to no training regarding shaking of tubes versus phlebotomists regarding QFT-GIT testing procedures. This was also measured by two other surrogates; specifically a medical note stating whether a nurse or phlebotomist collected the specimen (QFTStaff) and the name and title of the specific nurse if collection was performed by a nurse (QFTNurse). Results indicated that inpatient status was a strong and statistically significant factor for indeterminates, however, nurse collected specimens and indeterminate results had no statistically significant association in non-cancer patients. The lack of data denoting the specific nurse performing specimen collection excluded the QFTNurse surrogate in our analysis. ^ Findings suggests training of staff personnel in specimen procedures may have little effect on the number of indeterminates while inpatient status and thus possibly illness severity may be the most important factor for indeterminate results in this population. The lack of congruence between our surrogate measures may imply that our inpatient surrogate gauged illness severity rather than collection procedures as intended. ^ Despite the lack of clear findings, our analysis indicated that more than half of indeterminates were found in specimens drawn by nurses and as such staff training may be explored. Future studies may explore methods in measuring modifiable variables during pre-analytical QFT-GIT procedures that can be discerned and controlled. Identification of such measures may provide insight into ways to lowering indeterminate QFT-GIT rates in children.^