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.

STUDIES ON ENERGY METABOLISM IN THE HIPPOCAMPUS AFTER ISCHEMIA

The gerbil model of ischemia was used to determine the effect of carotid occlusion on energy metabolites in cellular layers of discrete regions of the hippocampus and dentate gyrus. Levels of glucose, glycogen, ATP and phosphocreatine (PCr) were unchanged after 1 minute of ischemia. However, 3 minutes of ischemia produced a dramatic decrease in net levels of all metabolites. No additional decrease was observed after 15 minutes of ischemia. Re-establishment of the blood flow for 5 minutes after a 15 minute ischemic episode returned all metabolites to pre-ischemia levels. Concentrations of glucose and glycogen were elevated in sham-operated animals as a function of the pentobarbital anesthetic employed. In other studies, elevated GABA levels (produced by inhibiting GABA-transaminase with (gamma)-vinyl-GABA (GVG)) were found to decrease the rate of utilization of the high-energy phosphate metabolites ATP and PCr in the mouse cortex. In addition, glucose and glycogen levels were increased. Thus, tonic inhibition by GABA produced decreased cellular activity. Additional experiments demonstrated the attenuation of ischemia-induced metabolite depletion in cellular layers of regions of the hippocampus, dentate gyrus and cortex after GVG administration. Under ether, 1 minute of bilateral carotid occlusion produced a dramatic decrease in metabolite levels. After GVG treatment, the decrease was blocked completely for glucose, glycogen and ATP, and partially for PCr. Therefore, GABA-transaminase inhibition produced increased levels of GABA which subsequently decreased cellular activity. The protection against ischemia may have been due to (a)decreased metabolic rate; the available energy stores were utilized at a slower rate, and (b)increased levels of energy substrates; additional supplies available to maintain viability. These data suggest that the functional state of neural tissue can determine the response to metabolic stress. ^