Relative electron density determination using a physics based parameterization of photon interactions in medical DECT

Abstract

Radiotherapy and particle therapy treatment planning require accurate knowledge of the electron density and elemental composition of the tissues in the beam path to predict the local dose deposition. We describe a method for the analysis of dual energy computed tomography (DECT) images that provides the electron densities and effective atomic numbers of tissues. The CT measurement process is modelled by system weighting functions, which apply an energy dependent weighting to the parameterization of the total cross section for photon interactions with matter. This detailed parameterization is based on the theoretical analysis of Jackson and Hawkes and deviates, at most, 0.3% from the tabulated NIST values for the elements H to Zn. To account for beam hardening in the object as present in the CT image we implemented an iterative process employing a local weighting function, derived from the method proposed by Heismann and Balda. With this method effective atomic numbers between 1 and 30 can be determined. The method has been experimentally validated on a commercially available tissue characterization phantom with 16 inserts made of tissue substitutes and aluminium that has been scanned on a dual source CT system with tube potentials of 100 kV and 140 kV using a clinical scan protocol. Relative electron densities of all tissue substitutes have been determined with accuracy better than 1%. The presented DECT analysis method thus provides high accuracy electron densities and effective atomic numbers for radiotherapy and especially particle therapy treatment planning.

The potential of dual-energy CT to reduce proton beam range uncertainties

“…Van Abbema et al . developed a method that is not based on calibration, but requires spectral knowledge.…”

“…Over the last decade, several papers were published on DECT to either show potential benefits for radiotherapy or to propose a mathematical formalism to extract tissue parameters relevant to dose calculation. Recent publications propose the extraction of ED and EAN (or alternatively, the I ‐value), from DECT images . These methods rely on postreconstruction data analysis, conversely to sinogram‐based methods (e.g., Refs …”

“…which are yet to be fully explored. Studies on DECT for proton therapy typically report errors on stopping power determination between 0.5 and 1.5% . Although there exists no direct relation between x‐ray attenuation and stopping powers, it was shown that DECT has the potential to substantially improve proton radiotherapy planning as it is widely clinically available.…”

Methodological accuracy of image-based electron density assessment using dual-energy computed tomography

“…It was also successfully experimentally validated by Hünemohr et al, who found a mean absolute deviation of measured from reference electron densities of 0.4% for tissue substitutes. Studies of other algorithms reported similar results, without any clear advantage for one or the other method.…”

Spectra of clinical CT scanners using a portable Compton spectrometer

“…[8][9][10][11] Moreover, with DECT, the use of a CT number to density calibration curve is not necessary. 11,12 In therapy planning for proton irradiations, accurate knowledge of proton stopping powers is essential. Proton stopping powers can be determined from the electron density and the effec-tive atomic number.…”