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Purpose This paper introduces a new approach for the dedicated reduction of high‐frequency metal artifacts, which applies a nonlinear scaling (NLS) transfer function on the high‐frequency projection domain to reduce artifacts, while preserving edge information and anatomic detail by incorporating prior image information. Methods An NLS function is applied to suppress high‐frequency streak artifacts, but to restrict the correction to metal projections only, scaling is performed in the sinogram domain. Anatomic information should be preserved and is excluded from scaling by incorporating a prior image from tissue classification. The corrected high‐frequency sinogram is reconstructed and combined with the low‐frequency component of a normalized metal artifact reduction (NMAR) image. Scans of different anthropomorphic phantoms were acquired (unilateral hip, bilateral hip, dental implants, and embolization coil). Multiple regions of interest (ROIs) were drawn around the metal implants and hounsfield unit (HU) deviations were analyzed. Clinical data sets including single image slices of dental fillings, a bilateral hip implant, spinal fixation screws, and an aneurysm coil were reconstructed and assessed. Results The prior image‐controlled NLS can remove streak artifacts while preserving anatomic detail within the bone and soft tissue. The qualitative analysis of clinical cases showed a tremendous enhancement within dental fillings and neuro coils, and a significant enhancement within spinal screws or hip implants. The phantom scan measurements support this observation. In all phantom setups, the NLS‐corrected result showed lowest HU derivation and the best visualization of the data. Conclusions The prior image‐controlled NLS provides a method to reduce high‐frequency streaks in metal‐corrupted computed tomography (CT) data.

Need for a review Guidelines for management and prevention of contrast media extravasation have not been updated recently. In view of emerging research and changing working practices, this review aims to inform update on the current guidelines. Areas covered In this paper, we review the literature pertaining to the pathophysiology, diagnosis, risk factors and treatments of contrast media extravasation. A suggested protocol and guidelines are recommended based upon the available literature. Key Points • Risk of extravasation is dependent on scanning technique and patient risk factors. • Diagnosis is mostly clinical, and outcomes are mostly favourable. • Referral to surgery should be based on clinical severity rather than extravasated volume.

Metal artifacts drastically impair the image quality in CT images and often reduce their diagnostic value. There are many publications on metal artifact reduction (MAR) which regard the metal-affected parts of the rawdata as completely unreliable and therefore replace it. While those sinogram inpainting methods are in general successful in removing metal artifacts, they cannot exactly recover the true values which are replaced and therefore the corrected image will exhibit new artifacts and blurring.In reference [1] we presented a new method, normalized MAR (NMAR), to replace corrupted rawdata while suppressing most of those new artifacts. Still, a complete replacement scheme is used there, which leads to loss of data. For metal implants with an elongated shape, as for example cardiac pacemakers or pedicle screws, the intersection length of the rays with metal strongly depends on the view direction. If the intersection length is rather short, the corresponding part of the rawdata still contains usable information. The replacement of corrupted projection data with NMAR turned out to be a robust solution, but close to implants the result may exhibit blurring due to a loss of data.In this work we introduce the adaptive normalized metal artifact reduction (ANMAR), an algorithm with rawdatabased merging of original and NMAR projections. It ensures that metal artifacts are reduced considerably, while excessive loss of data is avoided. This adaption could also be combined with MAR methods other than NMAR.We applied ANMAR to data sets from a modern clinical CT scanner, including a patient with a cardiac pacemaker, a patient with a fixateur interne, and a patient with a bilateral hip prosthesis. For comparison, they were also corrected with NMAR and with a standard linear interpolation method as described in reference [2]. ANMAR removes severe metal artifacts while it ensures that usable data from the metal trace is taken into account. Therefore, also details close to and even between implants can be better preserved.

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