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Automatically estimating size information for dose management systems applied in fluoroscopy and radiography
Author(s): Alexander Neißner; Petar Penchev; Ulf Mäder; Andreas Mahnken; Martin Fiebich
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Paper Abstract

In radiography and fluoroscopy, the dose-area product (DAP) is used for dose documentation and the evaluation, whether the applied dose is too high, adequate or too low. In dose management systems (applied in fluoroscopy and radiography) a mean value of the DAP of a number of consecutive examinations is calculated and compared to the diagnostic reference levels of the different examination types. This shows, if on average the dose level is too high. However, on an individual this would not work. To achieve a radiograph of adequate image quality the required DAP for a slender patient is significantly lower than for a standard patient and vice versa for obese patients. Thereby, without knowledge about patient thickness, there is no way to judge, if the dose level for an individual would be appropriate. To overcome this problem, an estimate of the patient size was calculated from information of the dicom header of the images. By extracting the dose at the detector, the DAP, exam type, information about the beam quality of the used radiation (spectrum) and the exposed area of the detector an estimate of the water equivalent patient thickness can be determined. Monte Carlo simulations and measurements with varying thicknesses of a water phantom were in excellent agreement. The accuracy of the estimate was better than 1 cm. Further clinical experiments with patients undergoing an examination of the lumbar spine showed, that an accuracy better than 20% and a standard derivation of 10% is achievable. Therefore an automatic estimate of the patient thickness in fluoroscopy and radioscopy is feasible and facilitates a computer-based judgement if the dose for an individual patient is adequate.

Paper Details

Date Published: 15 March 2019
PDF: 8 pages
Proc. SPIE 10954, Medical Imaging 2019: Imaging Informatics for Healthcare, Research, and Applications, 1095403 (15 March 2019); doi: 10.1117/12.2512784
Show Author Affiliations
Alexander Neißner, Technische Hochschule Mittelhessen (Germany)
Petar Penchev, Technische Hochschule Mittelhessen (Germany)
Ulf Mäder, Technische Hochschule Mittelhessen (Germany)
Andreas Mahnken, Univ. Giessen-Marburg (Germany)
Martin Fiebich, Technische Hochschule Mittelhessen (Germany)


Published in SPIE Proceedings Vol. 10954:
Medical Imaging 2019: Imaging Informatics for Healthcare, Research, and Applications
Po-Hao Chen; Peter R. Bak, Editor(s)

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