Damien Racine

Dual-Energy CT: Basic principles, technical approaches, and applications in musculoskeletal imaging (part 1)

In recent years, technological advances have allowed manufacturers to implement dual-energy computed tomography (DECT) on clinical scanners. With its unique ability to differentiate basis materials by their atomic number, DECT has opened new perspectives in imaging. DECT has been used successfully in musculoskeletal imaging with applications ranging from detection, characterization, and quantification of crystal and iron deposits; to simulation of noncalcium (improving the visualization of bone marrow lesions) or noniodine images. Furthermore, the data acquired with DECT can be postprocessed to generate monoenergetic images of varying kiloelectron volts, providing new methods for image contrast optimization as well as metal artifact reduction. The first part of this article reviews the basic principles and technical aspects of DECT including radiation dose considerations. The second part focuses on applications of DECT to musculoskeletal imaging including gout and other crystal-induced arthropathies, virtual noncalcium images for the study of bone marrow lesions, the study of collagenous structures, applications in computed tomography arthrography, as well as the detection of hemosiderin and metal particles.

Anthropomorphic model observer performance in three-dimensional detection task for low-contrast computed tomography

Abstract. X-ray medical imaging is increasingly becoming three-dimensional (3-D). The dose to the population and its management are of special concern in computed tomography (CT). Task-based methods with model observers to assess the dose-image quality trade-off are promising tools, but they still need to be validated for real volumetric images. The purpose of the present work is to evaluate anthropomorphic model observers in 3-D detection tasks for low-contrast CT images. We scanned a low-contrast phantom containing four types of signals at three dose levels and used two reconstruction algorithms. We implemented a multislice model observer based on the channelized Hotelling observer (msCHO) with anthropomorphic channels and investigated different internal noise methods. We found a good correlation for all tested model observers. These results suggest that the msCHO can be used as a relevant task-based method to evaluate low-contrast detection for CT and optimize scan protocols to lower dose in an efficient way.

PATIENT EXPOSURE OPTIMISATION THROUGH TASK-BASED ASSESSMENT OF A NEW MODEL-BASED ITERATIVE RECONSTRUCTION TECHNIQUE

The goal of the present work was to report and investigate the performances of a new iterative reconstruction algorithm, using a model observer. For that, a dedicated low-contrast phantom containing different targets was scanned at four volume computed tomography dose index (CTDIvol) levels on a Siemens SOMATOM Force computed tomography (CT). The acquired images were reconstructed using the ADMIRE algorithm and were then assessed by three human observers who performed alternative forced choice experiments. Next, a channelised hotelling observer model was applied on the same set of images. The comparison between the two was performed using the percentage correct as a figure of merit. The results indicated a strong agreement between human and model observer as well as an improvement in the low-contrast detection when switching from an ADMIRE strength of 1–3. Good results were also observed even in situations where the target was hard to detect, suggesting that patient dose could be further reduced and optimised.

OBJECTIVE TASK-BASED ASSESSMENT OF LOW-CONTRAST DETECTABILITY IN ITERATIVE RECONSTRUCTION

Evaluating image quality by using receiver operating characteristic studies is time consuming and difficult to implement. This work assesses a new iterative algorithm using a channelised Hotelling observer (CHO). For this purpose, an anthropomorphic abdomen phantom with spheres of various sizes and contrasts was scanned at 3 volume computed tomography dose index (CTDIvol) levels on a GE Revolution CT. Images were reconstructed using the iterative reconstruction method adaptive statistical iterative reconstruction-V (ASIR-V) at ASIR-V 0, 50 and 70 % and assessed by applying a CHO with dense difference of Gaussian and internal noise. Both CHO and human observers (HO) were compared based on a four-alternative forced-choice experiment, using the percentage correct as a figure of merit. The results showed accordance between CHO and HO. Moreover, an improvement in the low-contrast detection was observed when switching from ASIR-V 0 to 50 %. The results underpin the finding that ASIR-V allows dose reduction.

Assessment of low contrast detection in CT using model observers: Developing a clinically-relevant tool for characterising adaptive statistical and model-based iterative reconstruction

PURPOSE This study aims to assess CT image quality in a way that would meet specific requirements of clinical practice. Physics metrics like Fourier transform derived metrics were traditionally employed for that. However, assessment methods through a detection task have also developed quite extensively lately, and we chose here to rely on this modality for image quality assessment. Our goal was to develop a tool adapted for a fast and reliable CT image quality assessment in order to pave the way for new CT benchmarking techniques in a clinical context. Additionally, we also used this method to estimate the benefits brought by some IR algorithms. MATERIALS AND METHODS A modified QRM chest phantom containing spheres of 5 and 8mm at contrast levels of 10 and 20HU at 120kVp was used. Images of the phantom were acquired at CTDIvol of 0.8, 3.6, 8.2 and 14.5mGy, before being reconstructed using FBP, ASIR 40 and MBIR on a GE HD 750 CT scanner. They were then assessed by eight human observers undergoing a 4-AFC test. After that, these data were compared with the results obtained from two different model observers (NPWE and CHO with DDoG channels). The study investigated the effects of the acquisition conditions as well as reconstruction methods. RESULTS NPWE and CHO models both gave coherent results and approximated human observer results well. Moreover, the reconstruction technique used to retrieve the images had a clear impact on the PC values. Both models suggest that switching from FBP to ASIR 40 and particularly to MBIR produces an increase of the low contrast detection, provided a minimum level of exposure is reached. CONCLUSION Our work shows that both CHO with DDoG channels and NPWE models both approximate the trend of humans performing a detection task. Both models also suggest that the use of MBIR goes along with an increase of the PCs, indicating that further dose reduction is still possible when using those techniques. Eventually, the CHO model associated to the protocol we described in this study happened to be an efficient way to assess CT images in a clinical environment. In the future, this simple method could represent a sound basis to benchmark clinical practice and CT devices.

Objective comparison of high‐contrast spatial resolution and low‐contrast detectability for various clinical protocols on multiple CT scanners

Purpose We sought to compare objectively computed tomography (CT) scanner performance for three clinically relevant protocols using a task‐based image quality assessment method in order to assess the potential for radiation dose reduction. Methods Four CT scanners released between 2003 and 2007 by different manufacturers were compared with four CT scanners released between 2012 and 2014 by the same manufacturers using ideal linear model observers (MO): prewhitening (PW) MO and channelized Hotelling (CHO) MO with Laguerre‐Gauss channels for high‐contrast spatial resolution and low‐contrast detectability (LCD) performance, respectively. High‐contrast spatial resolution was assessed using a custom‐made phantom that enabled the computation of the target transfer function (TTF) and noise power spectrum (NPS). Low‐contrast detectability was assessed using a commercially available anthropomorphic abdominal phantom providing equivalent diameters of 24, 29.6, and 34.6 cm. Three protocols were reviewed: a head (trauma) and an abdominal (urinary stones) protocol were applied to assess high‐contrast spatial resolution performance; and another abdominal (focal liver lesions) protocol was applied for LCD. The liver protocol was tested using fixed and modulated tube currents. The PW MO was proposed for assessing high‐contrast detectability performance of the various CT scanners. Results Compared with older generation CT scanners, three newer systems displayed significant improvements in high‐contrast detectability over that of their predecessors. A fourth, newer system had lower performance. The CHO MO was appropriate for assessing LCD performance and revealed that an excellent level of image quality could be obtained with newer scanners at significantly lower dose levels. Conclusions This study shows that MO can objectively benchmark CT scanners using a task‐based image quality method, thus helping to estimate the potential for further dose reductions offered by the latest systems. Such an approach may be useful for adequately and quantitatively comparing clinically relevant image quality among various scanners.

BENCHMARKING OF CT FOR PATIENT EXPOSURE OPTIMISATION

Patient dose optimisation in computed tomography (CT) should be done using clinically relevant tasks when dealing with image quality assessments. In the present work, low-contrast detectability for an average patient morphology was assessed on 56 CT units, using a model observer applied on images acquired with two specific protocols of an anthropomorphic phantom containing spheres. Images were assessed using the channelised Hotelling observer (CHO) with dense difference of Gaussian channels. The results were computed by performing receiver operating characteristics analysis (ROC) and using the area under the ROC curve (AUC) as a figure of merit. The results showed a small disparity at a volume computed tomography dose index (CTDIvol) of 15 mGy depending on the CT units for the chosen image quality criterion. For 8-mm targets, AUCs were 0.999 ± 0.018 at 20 Hounsfield units (HU) and 0.927 ± 0.054 at 10 HU. For 5-mm targets, AUCs were 0.947 ± 0.059 and 0.702 ± 0.068 at 20 and 10 HU, respectively. The robustness of the CHO opens the way for CT protocol benchmarking and optimisation processes.

Effects of various generations of iterative CT reconstruction algorithms on low-contrast detectability as a function of the effective abdominal diameter: A quantitative task-based phantom study

PURPOSE To investigate how various generations of iterative reconstruction (IR) algorithms impact low-contrast detectability (LCD) in abdominal computed tomography (CT) for different patient effective diameters, using a quantitative task-based approach. METHODS Investigations were performed using an anthropomorphic abdominal phantom with two optional additional rings to simulate varying patient effective diameters (25, 30, and 35 cm), and containing multiple spherical targets (5, 6, and 8 mm in diameter) with a 20-HU contrast difference. The phantom was scanned using routine abdominal protocols (CTDIvol, 5.9-16 mGy) on four CT systems from two manufacturers. Images were reconstructed using both filtered back-projection (FBP) and various IR algorithms: ASiR 50%, SAFIRE 3 (both statistical IRs), ASiR-V 50%, ADMIRE 3 (both partial model-based IRs), or Veo (full model-based IR). Section thickness/interval was 2/1 mm or 2.5/1.25 mm, except 0.625/0.625 mm for Veo. We assessed LCD using a channelized Hotelling observer with 10 dense differences of Gaussian channels, with the area under the receiver operating characteristic curve (AUC) as a figure of merit. RESULTS For the smallest phantom (25-cm diameter) and smallest lesion size (5-mm diameter), AUC for FBP and the various IR algorithms did not significantly differ for any of the tested CT systems. For the largest phantom (35-cm diameter), Veo yielded the highest AUC improvement (8.5%). Statistical and partial model-based IR algorithms did not significantly improve LCD. CONCLUSION In abdominal CT, switching from FBP to IR algorithms offers limited possibilities for achieving significant dose reductions while ensuring a constant objective LCD.

Derivation of new diagnostic reference levels for neuro-paediatric computed tomography examinations in Switzerland

PURPOSE Definition of new national diagnostic reference levels (DRLs) for volume computed tomography dose index (CTDIvol) and dose length product (DLP) for neuro-paediatric CT examinations depending on the medical indication. METHODS Paediatric cranial CT data sets acquired between January 2013 and December 2016 were retrospectively collected between July 2016 and March 2017 from eight of the largest university and cantonal hospitals that perform most of the neuro-paediatric CTs in Switzerland. A consensus review of CTDIvol and DLP was undertaken for three defined anatomical regions: brain, facial bone, and petrous bone, each with and without contrast medium application. All indications for cranial CT imaging in paediatrics were assigned to one of these three regions. Descriptive statistical analysis of the distribution of the median values for CTDIvol and DLP yielded values in the minimum, maximum, 25th percentile (1st quartile), median (2nd quartile), and 75th percentile (3rd quartile). New DRLs for neuro-paediatric CT examinations in Switzerland were based on the 75th percentiles of the distributions of the median values of all eight centres. Where appropriate, values were rounded such that the DRLs increase or at least remain constant as the age of the patient increases. RESULTS Our results revealed DRLs for CTDIvol and DLP up to 20% lower than the DRLs used so far in Switzerland and elsewhere in Europe. CONCLUSIONS This study provides Swiss neuro-paediatric CT DRL values to establish optimum conditions for paediatric cranial CT examinations. Periodic national updates of DRLs, following international comparisons, are essential.

Task-based quantification of image quality using a model observer in abdominal CT: a multicentre study

ObjectiveWe investigated the variability in diagnostic information inherent in computed tomography (CT) images acquired at 68 different CT units, with the selected acquisition protocols aiming to answer the same clinical question.MethodsAn anthropomorphic abdominal phantom with two optional rings was scanned on 68 CT systems from 62 centres using the local clinical acquisition parameters of the portal venous phase for the detection of focal liver lesions. Low-contrast detectability (LCD) was assessed objectively with channelised Hotelling observer (CHO) using the receiver operating characteristic (ROC) paradigm. For each lesion size, the area under the ROC curve (AUC) was calculated and considered as a figure of merit. The volume computed tomography dose index (CTDIvol) was used to indicate radiation dose exposure.ResultsThe median CTDIvol used was 5.8 mGy, 10.5 mGy and 16.3 mGy for the small, medium and large phantoms, respectively. The median AUC obtained from clinical CT protocols was 0.96, 0.90 and 0.83 for the small, medium and large phantoms, respectively.ConclusionsOur study used a model observer to highlight the difference in image quality levels when dealing with the same clinical question. This difference was important and increased with growing phantom size, which generated large variations in patient exposure. In the end, a standardisation initiative may be launched to ensure comparable diagnostic information for well-defined clinical questions. The image quality requirements, related to the clinical question to be answered, should be the starting point of patient dose optimisation.Key Points• Model observers enable to assess image quality objectively based on clinical tasks.• Objective image quality assessment should always include several patient sizes.• Clinical diagnostic image quality should be the starting point for patient dose optimisation.• Dose optimisation by applying DRLs only is insufficient for ensuring clinical requirements.