Abstract
An anthropomorphic phantom for image optimization in neonatal radiography was developed, and its usability in optimizing image acquisition and processing demonstrated. The phantom was designed to mimic a patient image of a prematurely born neonate. A clinical x-ray (neonate <1 kg) taken with an effective dose of 11 µSv on a needle-crystal storage phosphor system was retrospectively selected from anonymized images as an appropriate template representing a standard case in neonatology imaging. The low dose level used in clinical imaging results in high image noise content. Therefore, the image had to be processed using structure preserving noise reduction. Pixel values were related to printing material thickness to result in a similar attenuation pattern as the original patient including support mattress. A 3D model generating a similar x-ray attenuation pattern on an image detector as a patient was derived accounting for beam hardening and perspective, and printed using different printing technologies. Best printing quality was achieved using a laser stereolithography printer. Phantom images from different digital radiography systems used in neonatal imaging were compared. Effects of technology, image processing, and radiation dose on diagnostic image quality can be assessed for otherwise identical anthropomorphic neonatal images not possible with patient images, facilitating optimization and standardization of imaging parameters and image appearance.
Highlights
Neonatal imaging is in many respects different to adult and general pediatric radiography
Neonatal imaging at dose levels as presented in this paper represent some of the lowest doses in imaging since patients are very sensitive to radiation, and usually receive repeated x-ray examinations, and optimization of image processing is of utmost importance
It is well documented that physical parameters like effective detective quantum efficiency or contrast to noise (CNR)/signal to noise rations (SNR) are not an adequate predictor of diagnostic image quality[3]
Summary
Neonatal imaging is in many respects different to adult and general pediatric radiography. Commercial image processing algorithms implemented into the radiography systems are usually black boxes and often used with vendor settings rather than being optimized for neonatal imaging[1] These image processing algorithms significantly impact on perceived, i.e. diagnostic, image quality. Images of these phantoms could be used for direct side-by-side comparison between different detector systems, different image processing algorithms on the same or on different systems, and different acquisition settings This approach would necessitate the availability of a truly anthropomorphic phantom producing patient-like x-ray images on an x-ray detector. These phantoms would mimic individual selected patients allowing a set of phantoms representing simple or difficult clinical conditions and a variety of neonate weights. This requires image processing be adapted if exposure conditions, like beam hardness, are changed
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