Objective assessment of low contrast detectability in computed tomography with Channelized Hotelling Observer

Racine, Damien; Ba, Alexandre; Ott, Julien G.; Bochud, François; Verdun, Francis R.

doi:10.1016/j.ejmp.2015.09.011

Cited by 47 publications

(32 citation statements)

References 28 publications

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“…A module can be inserted into the phantom body that includes spheres of different sizes: 8, 6, 5, 4, and 3 mm; each size having a contrast 20 HU relative to the background at 120 kV. For practical reasons, only three spheres (5, 6, and 8 mm) were used . Two additional annuli (increasing the phantom's effective diameter to 29.6 cm and 34.6 cm, respectively) were added to simulate a range of body habitus (from an approximate patient weight of 50 kg for the equivalent diameter of 24 cm to 75 kg and 100 kg for the equivalent diameter of 29.6 cm and 34.6 cm).…”

Section: Methodsmentioning

confidence: 99%

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

et al. 2017

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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 highcontrast 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.

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Section: Methodsmentioning

confidence: 99%

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

et al. 2017

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“…Furthermore, replacing readers with a mathematical observer makes this method less time-consuming and usable in routine image quality assurance. Over the last two decades, model observers, and in particular the Channelized Hotelling Observer (CHO), [5][6][7][8] have been increasingly investigated for the assessment of different imaging modalities: mammography, 9 Digital Breast Tomosynthesis (DBT), 10 fluoroscopy, 11 CT, [12][13][14][15] cone beam CT 16 and nuclear medicine, 17,18 and for different tasks: detection, 13 localization 19,20 and estimation. 21,22 Recently, the US Food and Drug Administration (FDA) proposed using CHOs in virtual clinical trials as evidence of device effectiveness.…”

Section: Introductionmentioning

confidence: 99%

Inter‐laboratory comparison of channelized hotelling observer computation

Abbey

Baek³

et al. 2018

Medical Physics

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This intercomparison helped define the state of the art of model observer performance computation and with thirteen participants, reflects openness and trust within the medical imaging community. The performance of a CHO with explicitly defined channels and a relatively large number of test images was consistently estimated by all participants. In contrast, the paper demonstrates that there is no agreement on estimating the variance of detectability in the training and testing setting.

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“…1 In CT, the vast majority of low contrast detectability studies are performed using simple uniform background phantoms with embedded low-contrast signals. [2][3][4][5][6][7] The increasingly complex and nonlinear nature of modern clinical CT systems may render such studies less clinically relevant due to the fact that background anatomical features and textures can have a strong effect on image quality. 8,9 The effect of texture on image quality is manifest in two primary ways.…”

Section: Introductionmentioning

confidence: 99%

Comparison of low‐contrast detectability between two CT reconstruction algorithms using voxel‐based 3D printed textured phantoms

Solomon

Bochud

et al. 2016

Medical Physics

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Purpose: To use novel voxel-based 3D printed textured phantoms in order to compare low-contrast detectability between two reconstruction algorithms, FBP (filtered-backprojection) and SAFIRE (sinogram affirmed iterative reconstruction) and determine what impact background texture (i.e., anatomical noise) has on estimating the dose reduction potential of SAFIRE. Methods: Liver volumes were segmented from 23 abdominal CT cases. The volumes were characterized in terms of texture features from gray-level co-occurrence and run-length matrices. Using a 3D clustered lumpy background (CLB) model, a fitting technique based on a genetic optimization algorithm was used to find CLB textures that were reflective of the liver textures, accounting for CT system factors of spatial blurring and noise. With the modeled background texture as a guide, four cylindrical phantoms (Textures A-C and uniform, 165 mm in diameter, and 30 mm height) were designed, each containing 20 low-contrast spherical signals (6 mm diameter at nominal contrast levels of ∼3.2, 5.2, 7.2, 10, and 14 HU with four repeats per signal). The phantoms were voxelized and input into a commercial multimaterial 3D printer (Object Connex 350), with custom software for voxel-based printing (using principles of digital dithering). Images of the textured phantoms and a corresponding uniform phantom were acquired at six radiation dose levels (SOMATOM Flash, Siemens Healthcare) and observer model detection performance (detectability index of a multislice channelized Hotelling observer) was estimated for each condition (5 contrasts × 6 doses × 2 reconstructions × 4 backgrounds = 240 total conditions). A multivariate generalized regression analysis was performed (linear terms, no interactions, random error term, log link function) to assess whether dose, reconstruction algorithm, signal contrast, and background type have statistically significant effects on detectability. Also, fitted curves of detectability (averaged across contrast levels) as a function of dose were constructed for each reconstruction algorithm and background texture. FBP and SAFIRE were compared for each background type to determine the improvement in detectability at a given dose, and the reduced dose at which SAFIRE had equivalent performance compared to FBP at 100% dose. Results: Detectability increased with increasing radiation dose (P = 2.7 × 10 −59) and contrast level (P = 2.2 × 10 −86) and was higher in the uniform phantom compared to the textured phantoms (P = 6.9 × 10 −51). Overall, SAFIRE had higher d ′ compared to FBP (P = 0.02). The estimated dose reduction potential of SAFIRE was found to be 8%, 10%, 27%, and 8% for Texture-A, Texture-B, Texture-C and uniform phantoms. Conclusions: In all background types, detectability was higher with SAFIRE compared to FBP. However, the relative improvement observed from SAFIRE was highly dependent on the complexity of the background texture. Iterative algorithms such as SAFIRE should be assessed in the most realistic context possible. C

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Objective assessment of low contrast detectability in computed tomography with Channelized Hotelling Observer

Cited by 47 publications

References 28 publications

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

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

Inter‐laboratory comparison of channelized hotelling observer computation

Comparison of low‐contrast detectability between two CT reconstruction algorithms using voxel‐based 3D printed textured phantoms

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