Julien G. Ott

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.

Low-dose multidetector computed tomography of the cervical spine: optimization of iterative reconstruction strength levels.

Background Iterative reconstruction (IR) techniques reduce image noise in multidetector computed tomography (MDCT) imaging. They can therefore be used to reduce radiation dose while maintaining diagnostic image quality nearly constant. However, CT manufacturers offer several strength levels of IR to choose from. Purpose To determine the optimal strength level of IR in low-dose MDCT of the cervical spine. Material and Methods Thirty consecutive patients investigated by low-dose cervical spine MDCT were prospectively studied. Raw data were reconstructed using filtered back-projection and sinogram-affirmed IR (SAFIRE, strength levels 1 to 5) techniques. Image noise, signal-to-noise ratio (SNR), and contrast-to-noise ratio (CNR) were measured at C3–C4 and C6–C7 levels. Two radiologists independently and blindly evaluated various anatomical structures (both dense and soft tissues) using a 4-point scale. They also rated the overall diagnostic image quality using a 10-point scale. Results As IR strength levels increased, image noise decreased linearly, while SNR and CNR both increased linearly at C3–C4 and C6–C7 levels (P < 0.001). For the intervertebral discs, the content of neural foramina and dural sac, and for the ligaments, subjective image quality scores increased linearly with increasing IR strength level (P ≤ 0.03). Conversely, for the soft tissues and trabecular bone, the scores decreased linearly with increasing IR strength level (P < 0.001). Finally, the overall diagnostic image quality scores increased linearly with increasing IR strength level (P < 0.001). Conclusion The optimal strength level of IR in low-dose cervical spine MDCT depends on the anatomical structure to be analyzed. For the intervertebral discs and the content of neural foramina, high strength levels of IR are recommended.

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.

MDCT Arthrography of the Hip: Value of the Adaptive Statistical Iterative Reconstruction Technique and Potential for Radiation Dose Reduction

OBJECTIVE The purpose of this article is to assess the effect of the adaptive statistical iterative reconstruction (ASIR) technique on image quality in hip MDCT arthrography and to evaluate its potential for reducing radiation dose. SUBJECTS AND METHODS Thirty-seven patients examined with hip MDCT arthrography were prospectively randomized into three different protocols: one with a regular dose (volume CT dose index [CTDIvol], 38.4 mGy) and two with a reduced dose (CTDIvol, 24.6 or 15.4 mGy). Images were reconstructed using filtered back projection (FBP) and four increasing percentages of ASIR (30%, 50%, 70%, and 90%). Image noise and contrast-to-noise ratio (CNR) were measured. Two musculoskeletal radiologists independently evaluated several anatomic structures and image quality parameters using a 4-point scale. They also jointly assessed acetabular labrum tears and articular cartilage lesions. RESULTS With decreasing radiation dose level, image noise statistically significantly increased (p=0.0009) and CNR statistically significantly decreased (p=0.001). We also found a statistically significant reduction in noise (p=0.0001) and increase in CNR (p≤0.003) with increasing percentage of ASIR; in addition, we noted statistically significant increases in image quality scores for the labrum and cartilage, subchondral bone, overall diagnostic quality (up to 50% ASIR), and subjective noise (p≤0.04), and statistically significant reductions for the trabecular bone and muscles (p≤0.03). Regardless of the radiation dose level, there were no statistically significant differences in the detection and characterization of labral tears (n=24; p=1) and cartilage lesions (n=40; p≥0.89) depending on the ASIR percentage. CONCLUSION The use of up to 50% ASIR in hip MDCT arthrography helps to reduce radiation dose by approximately 35-60%, while maintaining diagnostic image quality comparable to that of a regular-dose protocol using FBP.

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.

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.

Impact of large x-ray beam collimation on image quality

Large X-ray beam collimation in computed tomography (CT) opens the way to new image acquisition techniques and improves patient management for several clinical indications. The systems that offer large X-ray beam collimation enable, in particular, a whole region of interest to be investigated with an excellent temporal resolution. However, one of the potential drawbacks of this option might be a noticeable difference in image quality along the z-axis when compared with the standard helical acquisition mode using more restricted X-ray beam collimations. The aim of this project is to investigate the impact of the use of large X-ray beam collimation and new iterative reconstruction on noise properties, spatial resolution and low contrast detectability (LCD). An anthropomorphic phantom and a custom made phantom were scanned on a GE Revolution CT. The images were reconstructed respectively with ASIR-V at 0% and 50%. Noise power spectra, to evaluate the noise properties, and Target Transfer Functions, to evaluate the spatial resolution, were computed. Then, a Channelized Hotelling Observer with Gabor and Dense Difference of Gaussian channels was used to evaluate the LCD using the Percentage correct as a figure of merit. Noticeable differences of 3D noise power spectra and MTF have been recorded; however no significant difference appeared when dealing with the LCD criteria. As expected the use of iterative reconstruction, for a given CTDIvol level, allowed a significant gain in LCD in comparison to ASIR-V 0%. In addition, the outcomes of the NPS and TTF metrics led to results that would contradict the outcomes of CHO model observers if used for a NPWE model observer (Non- Prewhitening With Eye filter). The unit investigated provides major advantages for cardiac diagnosis without impairing the image quality level of standard chest or abdominal acquisitions.

Low contrast detectability in CT for human and model observers in multi-slice data sets

Task-based medical image quality is often assessed by model observers for single slice images. The goal of the study was to determine if model observers can predict human detection performance of low contrast signals in CT for clinical multi-slice (ms) images. We collected 24 different data subsets from a low contrast phantom: 3 dose levels (40, 90, 150 mAs), 4 signals (6 and 8 mm diameter; 10 and 20 HU at 120kV) and 2 reconstruction algorithms (FBP and iterative (IR)). Images were assessed by human and model observers in 4-alternative forced choice (4AFC) experiments with ms data set in a signal-known-exactly (SKE) paradigm. Model observers with single (msCHOa) and multiple (msCHOb) templates were implemented in a train and test method analysis with Dense Difference of Gaussian (DDoG) and Gabor spatial channels. For human observers, we found that percent correct increased with the dose and was higher for iterative reconstructed images than FBP in all investigated conditions. All model observers implemented overestimated human performance in any condition except one case (6mm and 10HU) for msCHOa and msCHOb with Gabor channels. Internal noise could be implemented and a good agreement was found but necessitates independent fits according to the reconstruction method. Generally msCHOb shows higher detection performance than msCHOa with both types of channels. Gabor channels were less efficient than DDoG in this context. These results allow further developments in 3D analysis technique for low contrast CT.