A multi-phased study of optimisation methodologies and radiation dose savings for head CT examinations

The Acceptability of Iterative Reconstruction Algorithms in Head CT: An Assessment of Sinogram Affirmed Iterative Reconstruction (SAFIRE) vs. Filtered Back Projection (FBP) Using Phantoms

BACKGROUND

Computed tomography (CT) is the primary imaging investigation for many neurologic conditions with a proportion of patients incurring cumulative doses. Iterative reconstruction (IR) allows dose optimization, but head CT presents unique image quality complexities and may lead to strong reader preferences.

OBJECTIVES

This study evaluates the relationships between image quality metrics, image texture, and applied radiation dose within the context of IR head CT protocol optimization in the simulated patient setting. A secondary objective was to determine the influence of optimized protocols on diagnostic confidence using a custom phantom.

METHODS AND SETTING

A three-phase phantom study was performed to characterize reconstruction methods at the local reference standard and a range of exposures. CT numbers and pixel noise were quantified supplemented by noise uniformity, noise power spectrum, contrast-to-noise ratio (CNR), high- and low-contrast resolution. Reviewers scored optimized protocol images based on established reporting criteria.

RESULTS

Increasing strengths of IR resulted in lower pixel noise, lower noise variance, and increased CNR. At the reference standard, the image noise was reduced by 1.5 standard deviation and CNR increased by 2.0. Image quality was maintained at ≤24% relative dose reduction. With the exception of image sharpness, there were no significant differences between grading for IR and filtered back projection reconstructions.

CONCLUSIONS

IR has the potential to influence pixel noise, CNR, and noise variance (image texture); however, systematically optimized IR protocols can maintain the image quality of filtered back projection. This work has guided local application and acceptance of lower dose head CT protocols.

AN INVESTIGATION INTO CT RADIATION DOSE VARIATIONS FOR HEAD EXAMINATIONS ON MATCHED EQUIPMENT

This study investigated radiation dose and image quality differences for computed tomography (CT) head examinations across centres with matched CT equipment. Radiation dose records and imaging protocols currently employed across three European university teaching hospitals were collated, compared and coded as Centres A, B and C from specification matched CT equipment models. Patient scans (n = 40) obtained from Centres A and C were evaluated for image quality, based on the visualisation of Commission of European Community (CEC) image quality criteria using visual grading characteristic (VGC) analysis, where American Board of Radiology examiners (n = 11) stated their confidence in identifying anatomical criteria. Mean doses in terms of CT dose index (CTDI_vol-mGy) and dose length product (DLP-mGy cm) were as follows: Centre A-33.12 mGy and 461.45 mGy cm; Centre B -101 mGy (base)/32 mGy (cerebrum) and 762 mGy cm and Centre C-71.98 mGy and 1047.26 mGy cm, showing a significant difference (p ≤ 0.05) in DLP across centres. VGC analysis indicated better visualisation of CEC criteria on Centre C images (VGC_AUC 0.225). All three imaging protocols are routinely used clinically, and image quality is acceptable in each centre. Clinical centres with identical model CT scanners have variously customised their protocols achieving a range of dose savings and still resulting in clinically acceptable image quality.

VGC ANALYZER: A SOFTWARE FOR STATISTICAL ANALYSIS OF FULLY CROSSED MULTIPLE-READER MULTIPLE-CASE VISUAL GRADING CHARACTERISTICS STUDIES

Visual grading characteristics (VGC) analysis is a non-parametric rank-invariant method for analysis of visual grading data. In VGC analysis, image quality ratings for two different conditions are compared by producing a VGC curve, similar to how the ratings for normal and abnormal cases in receiver operating characteristic (ROC) analysis are used to create an ROC curve. The use of established ROC software for the analysis of VGC data has therefore previously been proposed. However, the ROC analysis is based on the assumption of independence between normal and abnormal cases. In VGC analysis, this independence cannot always be assumed, e.g. if the ratings are based on the same patients imaged under both conditions. A dedicated software intended for analysis of VGC studies, which takes possible dependencies between ratings into account in the statistical analysis of a VGC study, has therefore been developed. The software-VGC Analyzer-determines the area under the VGC curve and its uncertainty using non-parametric resampling techniques. This article gives an introduction to VGC Analyzer, describes the types of analyses that can be performed and instructs the user about the input and output data.

Use of micro-computed tomography for the assessment of periapical lesions in small rodents: a systematic review

This systematic review aimed to evaluate the literature on the acquisition-, reconstruction- and analysis parameters of micro-computed tomography (micro-CT) for the assessment of periapical lesions in rats and mice, and to illustrate the effect of variation in these parameters. The PubMed database was searched from 2000 to January 2015 (English-language publications) for reports on the use of micro-CT to evaluate periapical lesions in rats and mice. QUADAS criteria were used to rate the quality of the studies. To illustrate the effect of variations in acquisition-, reconstruction-, and analysis parameters on images of periapical lesions, micro-CT examination of two hemi-mandibles of mice, with periapical lesions around the first molar was undertaken. Twenty-one studies were identified, which analysed periapical lesions in rats or mice using micro-CT. According to the QUADAS, no study was classified as high-, seven were classified as moderate-, and 14 as low quality. The effect of variation in parameters was that voxel size may interfere with image sharpness, reconstruction may interfere with image sharpness and contrast, and inadequate plane orientation may alter the size of the periapical lesion. Nonpersonalized ROIs resulted in areas that were not part of the periapical lesion. Changing the limits of the threshold for bone-tissue visualization increased lesion size. There is no defined protocol for acquiring and analysing micro-CT images of periapical lesions in rats and mice. Furthermore, acquisition-, reconstruction- and analysis parameters are not adequately explained, which may compromise the scientific impact of the studies.