Radiation dose reduction and static image quality assessment using a channelized hotelling observer on an angiography system upgraded with clarity IQ.

The goal of this paper was the comparison of radiation dose and imaging quality before and after the Clarity IQ technology installation in a Philips AlluraXper FD20/20 angiography system using a Channelized Hotelling Observer model (CHO). The core characteristics of the Allura Clarity IQ technology are its real-time noise reduction algorithms (NRT) combined with state-of-the-art hardware; this technology allows to implement acquisition protocols able to significantly reduce patient entrance dose. To measure the system performances in terms of image quality we used a contrast detail phantom in a clinical scatter condition. A Leeds TO10 phantom has been imaged between two 10 cm thick homogeneous solid water slabs. Fluoroscopy images were acquired using a cerebral protocol at 3 dose levels (low, medium and high) with a field- of view (FOV) of 31 cm. Cineangiography images were acquired using a cerebral protocol at 2 fps. Thus, 4 acquisitions were obtained for the conventional technology and 4 acquisitions were taken after the Clarity IQ upgrade, for a total of 8 different image sets. A validated 40 Gabor channels CHO with an internal noise model compared the image sets. Human observers' studies were carried out to tune the internal noise parameter. We showed that the CHO did not detect any significant difference between any of the image sets acquired using the two technologies. Consequently, this x-ray imaging technology provides a non-inferior image quality with an average patient dose reduction of 57% and 28% respectively in cineangiography and fluoroscopy. The Clarity IQ installation has certainly allowed a considerable improvement in patient and staff safety, while maintaining the same image quality.

PHYSICAL CHARACTERISATION OF FOUR DIFFERENT COMMERCIAL DIGITAL BREAST TOMOSYNTHESIS SYSTEMS.

The aim of this article was to characterise the performance of four different digital breast tomosynthesis (DBT) systems in terms of dose and image quality parameters. One of them, GE Pristina, has never been tested before. Average glandular doses were measured both in DBT and 2D full field digital mammography mode. Several phantoms were employed to perform signal difference to noise ratio, slice sensitivity profile, slice to slice incrementation, chest wall offset, z-axis geometry, artefact spread function, low contrast detectability, contrast detail evaluations, image uniformity and in-plane MTF in chest wall-nipple and in tube-travel directions. There are many differences in DBT systems explored: the angular range, detector type, reconstruction algorithms, and the presence or not of the grid. Even if it is not simple to calculate a global figure of merit, the analysis of all the collected data can be useful in a contest of a quality assurance program to define a set of values that could be used as benchmarks.

Size assessment of breast lesions by means of a computer-aided detection (CAD) system for magnetic resonance mammography.

PURPOSE: The aim of this study was to investigate the efficacy of a dedicated software tool for automated volume measurement of breast lesions in contrast-enhanced (CE) magnetic resonance mammography (MRM). MATERIAL AND METHODS: The size of 52 breast lesions with a known histopathological diagnosis (three benign, 49 malignant) was automatically evaluated using different techniques. The volume of all lesions was measured automatically (AVM) from CE 3D MRM examinations by means of a computer-aided detection (CAD) system and compared with the size estimates based on maximum diameter measurement (MDM) on MRM, ultrasonography (US), mammography and histopathology. RESULTS: Compared with histopathology as the reference method, AVM understimated lesion size by 4% on average. This result was similar to MDM (3% understimation, not significantly different) but significantly better than US and mammographic lesion measurements (24% and 33% size underestimation, respectively). CONCLUSIONS: AVM is as accurate as MDM but faster. Both methods are more accurate for size assessment of breast lesions compared with US and mammography.