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Experimental Validation of a Linear Boltzmann Transport Equation Solver for Rapid CT Dose Map Generation

S Principi1*, Y Liu2, Y Lu2, D K Ragan2, A Wang3, A Maslowski4, T Wareing4, T G Schmidt1, (1) BME department, Medical College of Wisconsin and Marquette University, Milwaukee, WI, (2) Department of Radiology, Medical College of Wisconsin, Milwaukee, WI, (3) Department of Radiology, Stanford University, Stanford, CA, (4) Varian Medical Systems, Palo Alto, CA

Presentations

(Sunday, 7/12/2020) 1:00 PM - 2:00 PM [Eastern Time (GMT-4)]

Room: Track 1

Purpose: validate CT dose maps estimated by a deterministic linear Boltzmann transport equation solver against dosimeter measurements performed with anthropomorphic phantoms on a clinical CT system.


Methods: method investigated in this work is Acuros CTD, (Varian Medical Systems, Palo Alto, CA), a linear Boltzmann transport equation solver aimed at generating rapid and reliable dose maps for CT applications. Acuros CTD was previously computationally validated for realistic scanner configurations against the gold standard Monte Carlo method for x-ray transport, showing good agreement between the two algorithms. This study aims at experimentally validating Acuros CTD against anthropomorphic phantom measurements. The CIRS ATOM 5-year-old phantom was used and is composed of 25-mm-thick tissue-equivalent slabs with organ-specific locations for thermoluminescent dosimeters (TLDs) placement. TLDs were placed in several organs in this study: 4 for stomach, 5 for liver, 6 for lungs, 2 for heart, and 1 for spinal bone. The phantom was scanned helically at 80, 100, and 120 kVp at constant tube current for the CAP protocol, with a pitch of 0.984 and 4-cm beam collimation. Acuros CTD running on a Nvidia GeForce GTX 1080 GPU was used to calculate the dose distribution within the phantom for each CT acquisition. The TLD chips were modeled as lithium fluoride (LiF) cylinders. The bowtie filter and over range collimation were modeled by defining discretized x-ray beams, whose spectra and fluence vary across angle and space. The doses at each location were tallied and compared to the experimental values.


Results: show a good agreement between simulations and measurements, with differences ranging from 0% to 10% for all organs except bone. Calculations required under one minute for all configurations.


Conclusion: CTD demonstrated to be a robust and fast dose estimator while accounting for scanner complexities, with errors less than 10% for most organs.

Keywords

Modeling, Validation, Phantoms

Taxonomy

IM- CT: Monte Carlo, modeling

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