CT Image Electron Density Quantification in Regions with Metal Implants: Implications for Radiotherapy Treatment Planning

In radiotherapy planning, computed tomography (CT) images are used to quantify the electron density of tissues and provide spatial anatomical information. Treatment planning systems use these data to calculate the expected spatial distribution of absorbed dose in a patient. CT imaging is complicated by the presence of metal implants which cause increased image noise, produce artifacts throughout the image and can exceed the available range of CT number values within the implant, perturbing electron density estimates in the image. Furthermore, current dose calculation algorithms do not accurately model radiation transport at metal-tissue interfaces. Combined, these issues adversely affect the accuracy of dose calculations in the vicinity of metal implants. As the number of patients with orthopedic and dental implants grows, so does the need to deliver safe and effective radiotherapy treatments in the presence of implants. The Medical Physics group at the Cancer Centre of Southeastern Ontario and Queen's University has developed a Cobalt-60 CT system that is relatively insensitive to metal artifacts due to the high energy, nearly monoenergetic Cobalt-60 photon beam. Kilovoltage CT (kVCT) images, including images corrected using a commercial metal artifact reduction tool, were compared to Cobalt-60 CT images throughout the treatment planning process, from initial imaging through to dose calculation. An effective metal artifact reduction algorithm was also implemented for the Cobalt-60 CT system. Electron density maps derived from the same kVCT and Cobalt-60 CT images indicated the impact of image artifacts on estimates of photon attenuation for treatment planning applications. Measurements showed that truncation of CT number data in kVCT images produced significant mischaracterization of the electron density of metals. Dose measurements downstream of metal inserts in a water phantom were compared to dose data calculated using CT images from kVCT and Cobalt-60 systems with and without artifact correction. The superior accuracy of electron density data derived from Cobalt-60 images compared to kVCT images produced calculated dose with far better agreement with measured results. These results indicated that dose calculation errors from metal image artifacts are primarily due to misrepresentation of electron density within metals rather than artifacts surrounding the implants.

TRIPPy: Trailed Image Photometry in Python

Photometry of moving sources typically suffers from a reduced signal-to-noise ratio (S/N) or flux measurements biased to incorrect low values through the use of circular apertures. To address this issue, we present the software package, TRIPPy: TRailed Image Photometry in Python. TRIPPy introduces the pill aperture, which is the natural extension of the circular aperture appropriate for linearly trailed sources. The pill shape is a rectangle with two semicircular end-caps and is described by three parameters, the trail length and angle, and the radius. The TRIPPy software package also includes a new technique to generate accurate model point-spread functions (PSFs) and trailed PSFs (TSFs) from stationary background sources in sidereally tracked images. The TSF is merely the convolution of the model PSF, which consists of a moffat profile, and super-sampled lookup table. From the TSF, accurate pill aperture corrections can be estimated as a function of pill radius with an accuracy of 10 mmag for highly trailed sources. Analogous to the use of small circular apertures and associated aperture corrections, small radius pill apertures can be used to preserve S/Ns of low flux sources, with appropriate aperture correction applied to provide an accurate, unbiased flux measurement at all S/Ns.