Mr. Christopher L. Liptak Profile

Christopher L. Liptak

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Proceedings Article | 18 March 2015 Paper

Analysis of uncertainties in Monte Carlo simulated organ dose for chest CT

John Muryn, Ashraf Morgan, W. Segars, Chris Liptak, Frank Dong, Andrew Primak, Xiang Li

Proceedings Volume 9412, 941232 (2015) https://doi.org/10.1117/12.2076067

KEYWORDS: Monte Carlo methods, Chest, Computed tomography, X-rays, X-ray computed tomography, Manufacturing, Aluminum, Error analysis, Liver, Scanners

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In Monte Carlo simulation of organ dose for a chest CT scan, many input parameters are required (e.g., half-value layer of the x-ray energy spectrum, effective beam width, and anatomical coverage of the scan). The input parameter values are provided by the manufacturer, measured experimentally, or determined based on typical clinical practices. The goal of this study was to assess the uncertainties in Monte Carlo simulated organ dose as a result of using input parameter values that deviate from the truth (clinical reality). Organ dose from a chest CT scan was simulated for a standard-size female phantom using a set of reference input parameter values (treated as the truth). To emulate the situation in which the input parameter values used by the researcher may deviate from the truth, additional simulations were performed in which errors were purposefully introduced into the input parameter values, the effects of which on organ dose per CTDI_vol were analyzed. Our study showed that when errors in half value layer were within ± 0.5 mm Al, the errors in organ dose per CTDI_vol were less than 6%. Errors in effective beam width of up to 3 mm had negligible effect (< 2.5%) on organ dose. In contrast, when the assumed anatomical center of the patient deviated from the true anatomical center by 5 cm, organ dose errors of up to 20% were introduced. Lastly, when the assumed extra scan length was longer by 4 cm than the true value, dose errors of up to 160% were found. The results answer the important question: to what level of accuracy each input parameter needs to be determined in order to obtain accurate organ dose results.

Proceedings Article | 18 March 2015 Paper

Anatomy-based transmission factors for technique optimization in portable chest x-ray

Christopher Liptak, Deborah Tovey, William Segars, Frank Dong, Xiang Li

Proceedings Volume 9412, 941247 (2015) https://doi.org/10.1117/12.2082056

KEYWORDS: X-rays, Sensors, Monte Carlo methods, Chest imaging, Lung, Collimation, Chromium, X-ray imaging, Tissues, Signal attenuation

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Portable x-ray examinations often account for a large percentage of all radiographic examinations. Currently, portable examinations do not employ automatic exposure control (AEC). To aid in the design of a size-specific technique chart, acrylic slabs of various thicknesses are often used to estimate x-ray transmission for patients of various body thicknesses. This approach, while simple, does not account for patient anatomy, tissue heterogeneity, and the attenuation properties of the human body. To better account for these factors, in this work, we determined x-ray transmission factors using computational patient models that are anatomically realistic. A Monte Carlo program was developed to model a portable x-ray system. Detailed modeling was done of the x-ray spectrum, detector positioning, collimation, and source-to-detector distance. Simulations were performed using 18 computational patient models from the extended cardiac-torso (XCAT) family (9 males, 9 females; age range: 2-58 years; weight range: 12-117 kg). The ratio of air kerma at the detector with and without a patient model was calculated as the transmission factor. Our study showed that the transmission factor decreased exponentially with increasing patient thickness. For the range of patient thicknesses examined (12-28 cm), the transmission factor ranged from approximately 21% to 1.9% when the air kerma used in the calculation represented an average over the entire imaging field of view. The transmission factor ranged from approximately 21% to 3.6% when the air kerma used in the calculation represented the average signals from two discrete AEC cells behind the lung fields. These exponential relationships may be used to optimize imaging techniques for patients of various body thicknesses to aid in the design of clinical technique charts.

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