Reduction of artefacts caused by hip implants in CT-based attenuation-corrected PET images using 2-D interpolation of a virtual sinogram on an irregular grid

Metallic prosthetic replacements, such as hip or knee implants, are known to cause strong streaking artefacts in CT images. These artefacts likely induce over- or underestimation of the activity concentration near the metallic implants when applying CT-based attenuation correction of positron emission tomography (PET) images. Since this degrades the diagnostic quality of the images, metal artefact reduction (MAR) prior to attenuation correction is required

Measuring femoral lesions despite CT metal artefacts: a cadaveric study

Objective Computed tomography is the modality of choice for measuring osteolysis but suffers from metal-induced artefacts obscuring periprosthetic tissues. Previous papers on metal artefact reduction (MAR) show qualitative improvements, but their algorithms have not found acceptance for clinical applications. We investigated to what extent metal artefacts interfere with the segmentation of lesions adjacent to a metal femoral implant and whether metal artefact reduction improves the manual segmentation of such lesions. Materials and methods We manually created 27 periprosthetic lesions in 10 human cadaver femora. We filled the lesions with a fibrotic interface tissue substitute. Each femur was fitted with a polished tapered cobalt-chrome prosthesis and imaged twice—once with the metal, and once with a substitute resin prosthesis inserted. Metalaffected CTs were processed using standard back-projection as well as projection interpolation (PI) MAR. Two experienced users segmented all lesions and compared segmentation accuracy. Results We achieved accurate delineation of periprosthetic lesions in the metal-free images. The presence of a metal implant led us to underestimate lesion volume and introduced geometrical errors in segmentation boundaries.MediamaticsElectrical Engineering, Mathematics and Computer Scienc

Digital chest radiography: an update on modern technology, dose containment and control of image quality

The introduction of digital radiography not only has revolutionized communication between radiologists and clinicians, but also has improved image quality and allowed for further reduction of patient exposure. However, digital radiography also poses risks, such as unnoticed increases in patient dose and suboptimum image processing that may lead to suppression of diagnostic information. Advanced processing techniques, such as temporal subtraction, dual-energy subtraction and computer-aided detection (CAD) will play an increasing role in the future and are all targeted to decrease the influence of distracting anatomic background structures and to ease the detection of focal and subtle lesions. This review summarizes the most recent technical developments with regard to new detector techniques, options for dose reduction and optimized image processing. It explains the meaning of the exposure indicator or the dose reference level as tools for the radiologist to control the dose. It also provides an overview over the multitude of studies conducted in recent years to evaluate the options of these new developments to realize the principle of ALARA. The focus of the review is hereby on adult applications, the relationship between dose and image quality and the differences between the various detector systems

Phantoms for quality control procedures of digital breast tomosynthesis

For quality control (QC) protocols in full field digital mammography polymethyl methacrylate (PMMA) phantoms are generally used. The possibility of using alternative materials has been investigated for digital breast tomosynthesis (DBT) because of the increased importance of scatter and more complex imaging geometries. We have investigated the use of PMMA in combination with polyethylene (PE) to simulate a range of typical breasts using a computation model of the imaging system. The scatter-to-primary ratios (SPRs) of both breast and phantom were also investigated and a difference up to 18% is found. Neglecting this difference in SPR in designing phantoms for DBT may lead to dosimetry errors. Taking into account estimated SPR values and relevant X-ray spectra, a combination of PMMA-PE slabs has been proposed to simulate typical breasts of thicknesses 30, 60 and 90 mm. The dosimetric error associated with using these phantoms for relevant X-ray spectra is less than 10%. © 2012 Springer-Verlag Berlin Heidelberg

Phantoms for quality control procedures of digital breast tomosynthesis

For quality control (QC) protocols in full field digital mammography polymethyl methacrylate (PMMA) phantoms are generally used. The possibility of using alternative materials has been investigated for digital breast tomosynthesis (DBT) because of the increased importance of scatter and more complex imaging geometries. We have investigated the use of PMMA in combination with polyethylene (PE) to simulate a range of typical breasts using a computation model of the imaging system. The scatter-to-primary ratios (SPRs) of both breast and phantom were also investigated and a difference up to 18% is found. Neglecting this difference in SPR in designing phantoms for DBT may lead to dosimetry errors. Taking into account estimated SPR values and relevant X-ray spectra, a combination of PMMA-PE slabs has been proposed to simulate typical breasts of thicknesses 30, 60 and 90 mm. The dosimetric error associated with using these phantoms for relevant X-ray spectra is less than 10%. © 2012 Springer-Verlag Berlin Heidelberg

Image quality in CT: From physical measurements to model observers

Evaluation of image quality (IQ) in Computed Tomography (CT) is important to ensure that diagnostic questions are correctly answered, whilst keeping radiation dose to the patient as low as is reasonably possible. The assessment of individual aspects of IQ is already a key component of routine quality control of medical x-ray devices. These values together with standard dose indicators can be used to give rise to 'figures of merit' (FOM) to characterise the dose efficiency of the CT scanners operating in certain modes. The demand for clinically relevant IQ characterisation has naturally increased with the development of CT technology (detectors efficiency, image reconstruction and processing), resulting in the adaptation and evolution of assessment methods. The purpose of this review is to present the spectrum of various methods that have been used to characterise image quality in CT: from objective measurements of physical parameters to clinically task-based approaches (i.e. model observer (MO) approach) including pure human observer approach. When combined together with a dose indicator, a generalised dose efficiency index can be explored in a framework of system and patient dose optimisation. We will focus on the IQ methodologies that are required for dealing with standard reconstruction, but also for iterative reconstruction algorithms. With this concept the previously used FOM will be presented with a proposal to update them in order to make them relevant and up to date with technological progress. The MO that objectively assesses IQ for clinically relevant tasks represents the most promising method in terms of radiologist sensitivity performance and therefore of most relevance in the clinical environment.publisher: Elsevier articletitle: Image quality in CT: From physical measurements to model observers journaltitle: Physica Medica articlelink: http://dx.doi.org/10.1016/j.ejmp.2015.08.007 content_type: article copyright: Copyright © 2015 Associazione Italiana di Fisica Medica. Published by Associazione Italiana di Fisica in Medicinastatus: publishe

LUT-QNE: Look-up-table quantum noise equalization in digital mammograms

Quantum noise is a signal-dependent, Poisson-distributed noise and the dominant noise source in digital mammography. Quantum noise removal or equalization has been shown to be an important step in the automatic detection of microcalcifications. However, it is often limited by the difficulty of robustly estimating the noise parameters on the images. In this study, a nonparametric image intensity transformation method that equalizes quantum noise in digital mammograms is described. A simple Look-Up-Table for Quantum Noise Equalization (LUT-QNE) is determined based on the assumption that noise properties do not vary significantly across the images. This method was evaluated on a dataset of 252 raw digital mammograms by comparing noise statistics before and after applying LUT-QNE. Performance was also tested as a preprocessing step in two microcalcification detection schemes. Results show that the proposed method statistically significantly improves microcalcification detection performance