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Computerised tomography (CT) continues to be a corner stone medical and radiologic imaging modalities in radiology and radiotherapy departments. Its importance lies in its efficiency in low contrast detectability (LCD). The assessment of such capabilities requires rigorous image quality analysis using special designed phantoms with different densities as well as variation in atomic mass numbers (A) of the material. Absence of such ranges of densities and atomic mass numbers, limits the dynamic range of assessment. An example is Catphan phantom which represents only three subject contrast levels 0.3, 0.5 and 1 per cent. This project aims to present a phantom with extended range of available subject contrast to include very low-level values and to increase its dynamic scale. With this design, a relatively large number of different contrast objects (holes) can be presented for imaging by a CT scanner to assess its LCD ability. We shall thus introduce another LCD phantom to complement the existing ones, such as Catphan. The cylindrical phantom is constructed using Poly (methyl methacrylate) (PMMA), with craters (holes) having dimensions that gradually increase from 1.0 to 12.5 mm penetrated in configuration that extend from the centre to the corner. Each line of the drilled holes in the phantom is filled with contrast material of specific concentrations. As opposed to the phantom of low detail contrast used in planar imaging, the iodine (contrast material) in this phantom replaces the depth of the phantom holes. The iodine could be reduced to 0.2 l milli-Molar (mM) and can be varied for the next line of holes by a small increment depending on the required level of contrast detectability assessment required. [ABSTRACT FROM AUTHOR]

Computerised tomography (CT) continues to be a corner stone medical and radiologic imaging modalities in radiology and radiotherapy departments. Its importance lies in its efficiency in low contrast detectability (LCD). The assessment of such capabilities requires rigorous image quality analysis using special designed phantoms with different densities as well as variation in atomic mass numbers (A) of the material. Absence of such ranges of densities and atomic mass numbers, limits the dynamic range of assessment. An example is Catphan phantom which represents only three subject contrast levels 0.3, 0.5 and 1 per cent. This project aims to present a phantom with extended range of available subject contrast to include very low-level values and to increase its dynamic scale. With this design, a relatively large number of different contrast objects (holes) can be presented for imaging by a CT scanner to assess its LCD ability. We shall thus introduce another LCD phantom to complement the existing ones, such as Catphan. The cylindrical phantom is constructed using Poly (methyl methacrylate) (PMMA), with craters (holes) having dimensions that gradually increase from 1.0 to 12.5 mm penetrated in configuration that extend from the centre to the corner. Each line of the drilled holes in the phantom is filled with contrast material of specific concentrations. As opposed to the phantom of low detail contrast used in planar imaging, the iodine (contrast material) in this phantom replaces the depth of the phantom holes. The iodine could be reduced to 0.2 l milli-Molar (mM) and can be varied for the next line of holes by a small increment depending on the required level of contrast detectability assessment required.

• Low Contrast Detectability assessment with dynamic images (Digital Angiography). • Spatio-temporal generalizations of CHO with Gabor channels and NPWE. • Spatio-temporal generalization of a simple statistical method. • Low Contrast Detectability assessment with human observer experiments (i.e. 2AFC). To evaluate the feasibility of spatio-temporal generalisation of mathematical methods for protocol optimisation in interventional radiology. Two model observers were considered: • Channelized Hotelling Observer with spatio-temporal Gabor channels; • Non-Prewhitening Model Observer with spatio-temporal contrast sensitivity function. Furthermore, Low Contrast Detectability (LCD) was evaluated with a generalised statistical method by taking into account the noise integration capability of the human eye. A series of two alternative force choices (2AFC) experiments performed by four observers were used to evaluate the reliability of the proposed models. The evaluation of the mathematical methods was performed by comparing their results to the human observer performances in two steps: 1. Firstly, a series of simulated images were used to tune the models 2. In the second phase, tuned models were applied both to simulated images and actual images obtained with a commercial phantom to evaluate detectability scores. Evaluation with simulated images shows a good agreement with 2AFC results (RMSE < 10%). Phantom-based evaluations show a general decrease of such agreement, characterized by an RMSE lower than 16%. The agreement with human observer experiments supports the feasibility of the proposed generalisations. Thus, they could be introduced in quality control programmes for a deeper protocol-characterisation or for clinical protocol-optimization when dynamic images are involved. [ABSTRACT FROM AUTHOR]

The use of optimised CT protocols regarding radiation exposure is a legal requirement. Since low contrast visibility is intrinsically varying within the CT slice, there is no adequate method for optimisation of dose and image quality. We developed a method to access image quality in a way that represents the situation closer to a real patient. This method is based on a novel difference detail curve (DDC) phantom with low contrast objects representing native tissue contrast and contrast media with different densities and diameters. The position of the contrast objects have been evaluated by a noise level analysis of CT slices of different manufactures. The dose – length – product can be measured within the phantom simultaneously. For all tested manu-factures and CT protocols, the noise analysis revealed a similar spatial variation of the signal -to-noise ratio (SNR). For the DDC method, contrast steps of 6 (4-8) Hounsfield Units (HU) are adequate. For the different CT units, comparable low contrast detectability is associated with remarkably varying dose levels (CTDI range from 8 to 18 mGy for native contrast and 9-16 mGy for contrast media). The novel DDC phantom is sensitive to protocol optimisations and therefore suitable for rating subtle effects caused by protocol optimisation.

• Model Observer methods with a spatio-temporal generalization to deal with dynamic images. • Three experiments of clinical interest with stationary and moving targets. • Channelized Model Observer and Non Pre-whitening Model Observer. • Human observer validation. The purpose of this work is to investigate the feasibility of spatio-temporal generalized Model Observer methods for protocol optimization programs in the field of interventional radiography. Two Model Observers were taken under examination: a Channelized Hotelling Observer with 24 spatio-temporal Gabor channels and a Non Pre-Whitening Model Observer with two different implementations of the spatio-temporal contrast sensitivity function. The images of targets, both stationary and in motion, were acquired in fluoroscopic mode using a CDRAD phantom for signal-present images and an homogenous slab of PMMA for signal-absent ones. After the processing, these images were used to build three series of two alternative forced choice experiments, designed to simulate tasks of clinical interest, and submitted to three human observers in order to set a goal on detectability. A first set of images was used for model tuning and subsequently the verified models were validated throughout a second set of images. Results from the validation phase, for both models, show good agreement with the human observer performances (Root Mean Square Error RMSE ≤ 12%). The tuning phase emerges as a crucial step in building models for angiographic dynamic images; the final agreement underlines the good capability of these spatio-temporal models in simulating human performances, allowing to consider them as a useful and worthwhile tool in protocol optimization when dynamic images are involved. [ABSTRACT FROM AUTHOR]

Abstract: The aim of this work was to quantitate differences in image quality between two GE CT scanner models — the LightSpeed VCT (“VCT”) and Discovery HD750 (“HD”) — based upon feedback from radiologists at our institution. First, 3 yrs of daily QC images of the manufacturer‐provided QC phantom from 10 scanners — five of each model — were analyzed for both noise magnitude, measured as CT‐number standard deviation, and noise power spectrum within the uniform water section. The same phantom was then scanned on four of each model and analyzed for low contrast detectability (LCD) using a built‐in LCD tool at the scanner console. An anthropomorphic phantom was scanned using the same eight scanners. A slice within the abdomen section was chosen and three ROIs were placed in regions representing liver, stomach, and spleen. Both standard deviation of CT‐number and LCD value was calculated for each image. Noise magnitude was 8.5% higher in HD scanners compared to VCT scanners. An associated increase in the magnitude of the noise power spectra were also found, but both peak and mean NPS frequency were not different between the two models. VCT scanners outperformed HD scanners with respect to LCD by an average of 13.1% across all scanners and phantoms. Our results agree with radiologist feedback, and necessitate a closer look at our body CT protocols among different scanner models at our institution. [ABSTRACT FROM AUTHOR]

Purpose: The purposes of this study were to evaluate the low-contrast detectability of CT images assuming hepatocellular carcinoma and to determine whether dose reduction in abdominal plain CT imaging is possible., Methods: A Catphan 600 was imaged at 350, 250, 150, and 50 mA using an Aquilion ONE PRISM Edition (Canon) and reconstructed using deep learning reconstruction (DLR) and model-based iterative reconstruction (MBIR). A low-contrast object-specific contrast-to-noise ratio (CNR LO ) was measured and compared in a 5-mm module with a CT value difference of 10 HU, assuming hepatocellular carcinoma; a visual examination was also performed. Moreover, an NPS within a uniform module was measured., Results: CNR LO was higher for DLR at all doses (1.12 at 150 mA for DLR and 1.07 at 250 mA for MBIR). On visual evaluation, DLR could detect up to 150 mA and MBIR up to 250 mA. The NPS was lower for DLR at 0.1 cycles/mm at 150 mA., Conclusion: The low-contrast detection performance was better with DLR than with MBIR, indicating the possibility of dose reduction.

We report results of the computed tomography reconstruction of the index of refraction in a whole rabbit knee joint examined at the photon energy of 51 keV. Refraction based images make it possible to delineate the bone, cartilage, and soft tissues without adjusting the contrast window width and level. Density variations, which are related to tissue composition and are not visible in absorption X-ray images, are detected in the obtained refraction based images. We discuss why refraction-based images provide better detectability of low contrast features than absorption images. [ABSTRACT FROM AUTHOR]

Detection of low contrast liver metastases varies between radiologists. Training may improve performance for lower-performing readers and reduce inter-radiologist variability. We recruited 31 radiologists (15 trainees, 8 non-abdominal staff, and 8 abdominal staff) to participate in four separate reading sessions: pre-test, search training, classification training, and post-test. In the pre-test, each radiologist interpreted 40 liver CT exams containing 91 metastases, circumscribed suspected hepatic metastases while under eye tracker observation, and rated confidence. In search training, radiologists interpreted a separate set of 30 liver CT exams while receiving eye tracker feedback and after coaching to increase use of coronal reformations, interpretation time, and use of liver windows. In classification training, radiologists interpreted up to 100 liver CT image patches, most with benign or malignant lesions, and compared their annotations to ground truth. Post-test was identical to pre-test. Between pre- and post-test, sensitivity increased by 2.8% (p = 0.01) but AUC did not change significantly. Missed metastases were classified as search errors (<2 seconds gaze time) or classification errors (>2 seconds gaze time) using the eye tracker. Out of 2775 possible detections, search errors decreased (10.8% to 8.1%; p < 0.01) but classification errors were unchanged (5.7% vs 5.7%). When stratified by difficulty, easier metastases showed larger reductions in search errors: for metastases with average sensitivity of 0-50%, 50-90%, and 90-100%, reductions in search errors were 16%, 35%, and 58%, respectively. The training program studied here may be able to improve radiologist performance by reducing errors but not classification errors.

Background: For almost three decades, computed tomography (CT) has been extensively used in medical diagnosis, which led researchers to conduct linking of CT dose exposure with image quality., Methods: In this study, a systematic review and a meta-analysis study were conducted on CT phantom for resolution study especially based on the low contrast detectability (LCD). Furthermore, the association between the CT parameter such as tube voltage and the type of reconstruction algorithm, the amount of phantom scanning affecting the image quality and the exposure dose were also investigated in this study. We utilize PubMed, ScienceDirect, Google Scholar and Scopus databases to search related published articles from the year 2011 until 2020. The notable keywords comprise "computed tomography", "CT phantom", and "low contrast detectability". Of 52 articles, 20 articles are within the inclusion criteria in this systematic review., Results: The dichotomous outcomes were chosen to represent the results in terms of risk ratio as per meta-analysis study. Notably, the noise in iterative reconstruction (IR) reduced by 24%, 33% and 36% with the use of smooth, medium and sharp filters, respectively. Furthermore, adaptive iterative dose reduction (AIDR 3D) improved image quality and the visibility of smaller less dense objects compared to filtered back-projection. Most of the researchers used 120 kVp tube voltage to scan phantom for quality assurance study., Conclusion: Hence, optimizing primary factors such as tube potential reduces the dose exposure significantly, and the optimized IR technique could substantially reduce the radiation dose while maintaining the image quality., (Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.net.)

Purpose: To find an upper bound on the maximum dose reduction possible for any reconstruction algorithm, analytic or iterative, that result from the inclusion of the data statistics. The authors do not analyze noise reduction possible from prior knowledge or assumptions about the object. Methods: The authors examined the task of estimating the density of a circular lesion in a cross section. Raw data were simulated by forward projection of existing images and numerical phantoms. To assess an upper bound on the achievable dose reduction by any algorithm, the authors assume that both the background and the shape of the lesion are completely known. Under these conditions, the best possible estimate of the density can be determined by solving a weighted least squares problem directly in the raw data domain. Any possible reconstruction algorithm that does not use prior knowledge or make assumptions about the object, including filtered backprojection (FBP) or iterative reconstruction methods with this constraint, must be no better than this least squares solution. The authors simulated 10 000 sets of noisy data and compared the variance in density from the least squares solution with those from FBP. Density was estimated from FBP images using either averaging within a ROI, or streak-adaptive averaging with better noise performance. Results: The bound on the possible dose reduction depends on the degree to which the observer can read through the possibly streaky noise. For the described low contrast detection task with the signal shape and background known exactly, the average dose reduction possible compared to FBP with streak-adaptive averaging was 42% and it was 64% if only the ROI average is used with FBP. The exact amount of dose reduction also depends on the background anatomy, with statistically inhomogeneous backgrounds showing greater benefits. Conclusions: The dose reductions from new, statistical reconstruction methods can be bounded. Larger dose reductions in the density estimation task studied here are only possible with the introduction of prior knowledge, which can introduce bias. [ABSTRACT FROM AUTHOR]

Purpose Iterative algorithms introduce new challenges in the field of image quality assessment. The purpose of this study is to use a mathematical model to evaluate objectively the low contrast detectability in CT. Materials and methods A QRM 401 phantom containing 5 and 8 mm diameter spheres with a contrast level of 10 and 20 HU was used. The images were acquired at 120 kV with CTDI vol equal to 5, 10, 15, 20 mGy and reconstructed using the filtered back-projection (FBP), adaptive statistical iterative reconstruction 50% (ASIR 50%) and model-based iterative reconstruction (MBIR) algorithms. The model observer used is the Channelized Hotelling Observer (CHO). The channels are dense difference of Gaussian channels (D-DOG). The CHO performances were compared to the outcomes of six human observers having performed four alternative forced choice (4-AFC) tests. Results For the same CTDI vol level and according to CHO model, the MBIR algorithm gives the higher detectability index. The outcomes of human observers and results of CHO are highly correlated whatever the dose levels, the signals considered and the algorithms used when some noise is added to the CHO model. The Pearson coefficient between the human observers and the CHO is 0.93 for FBP and 0.98 for MBIR. Conclusion The human observers' performances can be predicted by the CHO model. This opens the way for proposing, in parallel to the standard dose report, the level of low contrast detectability expected. The introduction of iterative reconstruction requires such an approach to ensure that dose reduction does not impair diagnostics. [ABSTRACT FROM AUTHOR]

Purpose The purpose of this work was to evaluate the contrast-detail performance of full field digital mammography (FFDM) systems using ideal (Hotelling) observer Signal-to-Noise Ratio (SNR) methodology and ascertain whether it can be considered an alternative to the conventional, automated analysis of CDMAM phantom images. Methods Five FFDM units currently used in the national breast screening programme were evaluated, which differed with respect to age, detector, Automatic Exposure Control (AEC) and target/filter combination. Contrast-detail performance was analysed using CDMAM and ideal observer SNR methodology. The ideal observer SNR was calculated for input signal originating from gold discs of varying thicknesses and diameters, and then used to estimate the threshold gold thickness for each diameter as per CDMAM analysis. The variability of both methods and the dependence of CDMAM analysis on phantom manufacturing discrepancies also investigated. Results Results from both CDMAM and ideal observer methodologies were informative differentiators of FFDM systems' contrast-detail performance, displaying comparable patterns with respect to the FFDM systems' type and age. CDMAM results suggested higher threshold gold thickness values compared with the ideal observer methodology, especially for small-diameter details, which can be attributed to the behaviour of the CDMAM phantom used in this study. In addition, ideal observer methodology results showed lower variability than CDMAM results. Conclusion The Ideal observer SNR methodology can provide a useful metric of the FFDM systems' contrast detail characteristics and could be considered a surrogate for conventional, automated analysis of CDMAM images. [ABSTRACT FROM AUTHOR]

Purpose: The purpose of this work was to develop and evaluate a new method for calibration of medical displays that includes the effect of fixed adaptation and by using equipment and luminance levels typical for a modern radiology department. Methods: Low contrast sinusoidal test patterns were derived at nine luminance levels from 2 to 600 cd/m² and used in a two alternative forced choice observer study, where the adaptation level was fixed at the logarithmic average of 35 cd/m². The contrast sensitivity at each luminance level was derived by establishing a linear relationship between the ten pattern contrast levels used at every luminance level and a detectability index (d') calculated from the fraction of correct responses. A Gaussian function was fitted to the data and normalized to the adaptation level. The corresponding equation was used in a display calibration method that included the grayscale standard display function (GSDF) but compensated for fixed adaptation. In the evaluation study, the contrast of circular objects with a fixed pixel contrast was displayed using both calibration methods and was rated on a five-grade scale. Results were calculated using a visual grading characteristics method. Error estimations in both observer studies were derived using a bootstrap method. Results: The contrast sensitivities for the darkest and brightest patterns compared to the contrast sensitivity at the adaptation luminance were 37% and 56%, respectively. The obtained Gaussian fit corresponded well with similar studies. The evaluation study showed a higher degree of equally distributed contrast throughout the luminance range with the calibration method compensated for fixed adaptation than for the GSDF. The two lowest scores for the GSDF were obtained for the darkest and brightest patterns. These scores were significantly lower than the lowest score obtained for the compensated GSDF. For the GSDF, the scores for all luminance levels were statistically separated from the average value; three were lower and two were higher. For the compensated GSDF, three of the scores could not be separated from the average value. Conclusions: An observer study using clinically relevant displays and luminance settings has demonstrated that the calibration of displays according to the GSDF causes the perceived contrast to be unevenly distributed when using displays with a high luminance range. As the luminance range increases, the perceived contrast in the dark and bright regions will be significantly lower than the perceived contrast in the middle of the luminance range. A new calibration method that includes the effect of fixed adaptation was developed and evaluated in an observer study and was found to distribute the contrast of the display more evenly throughout the grayscale than the GSDF. [ABSTRACT FROM AUTHOR]

Objective . Mammogram image quality in European breast screening systems is defined by threshold gold thickness ( T ) assessment of the CDMAM contrast-detail phantom. Previous studies have outlined several limitations of the phantom including expense, number of images required and inter-phantom manufacturing variability. Two alternative approaches to image quality assessment for routine quality control are examined and compared to the CDMAM technique: (i) A detectability index ( d ') based on a non-prewhitened model observer with an eye filter (NPWE) an d (ii) A statistical estimate of contrast based on image noise levels ( C STAT ). Approach . The d ' calculation follows a previously published methodology based on the NNPS and contrast, both measured from an image of 5 cm of PMMA containing a 0.2 mm Al target, as well as the MTF measured under standard conditions. For the proposed statistical method, pixels in the centre of the same NNPS image were re-binned into a range of equivalent CDMAM target areas. For any area, the minimum contrast necessary to distinguish a signal from the background, C STAT , is 3.29 σ at a 95% level of confidence, where σ is the standard deviation of the background pixels. Theoretical analysis predicts a simple relationships between C STAT , T and d '. Measured values of C STAT were compared to T and d ' as a function of air kerma at the detector for ten digital mammography systems from three different manufacturers. Main Results . Theoretical relationships between C STAT , d ' and T were demonstrated. Minimum acceptable image quality performance for 0.10 and 0.25 mm diameter discs, defined by the European Guidelines in terms of T , are equivalent to d ' values of 0.85 and 5.36 and threshold C STAT values of 0.055 and 0.022. Significance . Strong correlations between log( T ), log( d ') and log( C STAT ) suggest that either alternative approach produces information corresponding to that obtained using the CDMAM. C STAT should be considered as a simple, objective and cost-effective alternative to routine image quality assessment in mammography., (© 2022 Institute of Physics and Engineering in Medicine.)