Effects of computing parameters and measurement locations on the estimation of 3D NPS in non-stationary MDCT images

Miéville, Frédéric A.; Bolard, G.; Bulling, S.; Gudinchet, F.; Bochud, François; Verdun, F.

doi:10.1016/j.ejmp.2012.07.001

Cited by 13 publications

(7 citation statements)

References 26 publications

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“…Noise Power Spectrum: Image noise was quantified and characterised by computing noise power spectra (NPS) according to the recommendations from the International Commission on Radiation Units and Measurements Reports 54 and 87, and the method described by Miéville et al . 36–38 . Measurements were performed on 40 consecutive axial MDCT images taken at the phantom extremity and containing only water (no central insert).…”

Section: Methodsmentioning

confidence: 99%

Task-Based Model Observer Assessment of A Partial Model-Based Iterative Reconstruction Algorithm in Thoracic Oncologic Multidetector CT

Rotzinger

Racine

Beigelman-Aubry

et al. 2018

Sci Rep

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To investigate the impact of a partial model-based iterative reconstruction (ASiR-V) on image quality in thoracic oncologic multidetector computed tomography (MDCT), using human and mathematical model observers. Twenty cancer patients examined with regular-dose thoracic-abdominal-pelvic MDCT were retrospectively included. Thoracic images reconstructed using a sharp kernel and filtered back-projection (reference) or ASiR-V (0–100%, 20% increments; follow-up) were analysed by three thoracic radiologists. Advanced quantitative physical metrics, including detectability indexes of simulated 4-mm-diameter solid non-calcified nodules and ground-glass opacities, were computed at regular and reduced doses using a custom-designed phantom. All three radiologists preferred higher ASiR-V levels (best = 80%). Increasing ASiR-V substantially decreased noise magnitude, with slight changes in noise texture. For high-contrast objects, changing the ASiR-V level had no major effect on spatial resolution; whereas for lower-contrast objects, increasing ASiR-V substantially decreased spatial resolution, more markedly at reduced dose. For both high- and lower-contrast pulmonary lesions, detectability remained excellent, regardless of ASiR-V and dose levels, and increased significantly with increasing ASiR-V levels (all p < 0.001). While high ASiR-V levels (80%) are recommended to detect solid non-calcified nodules and ground-glass opacities in regular-dose thoracic oncologic MDCT, care must be taken because, for lower-contrast pulmonary lesions, high ASiR-V levels slightly change noise texture and substantially decrease spatial resolution, more markedly at reduced dose.

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Section: Methodsmentioning

confidence: 99%

Task-Based Model Observer Assessment of A Partial Model-Based Iterative Reconstruction Algorithm in Thoracic Oncologic Multidetector CT

Rotzinger

Racine

Beigelman-Aubry

et al. 2018

Sci Rep

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“…Burgess (Burgess et al, 2001a), Bochud (Bochud et al, 1999), and others (Heine et al, 1999) have defined the total noise power spectrum, NPS t ( f ), as the sum of the anatomical noise power spectrum, NPS a ( f ), and the quantum noise power spectrum, NPS q ( f ),:

N P S_{t} false(f false) = N P S_{q} false(f false) + N P S_{a} false(f false)

The quantum noise power spectrum is a fundamental analytical tool in detector design, development, and assessment, and has been used extensively in the evaluation of x-ray based medical imaging systems (Yang et al, 2008, Miéville et al). The anatomical noise power spectrum has been discussed in a more limited manner (Bochud et al, 1999, Burgess, 1999, Metheany et al, 2008).…”

Section: Introductionmentioning

confidence: 99%

Association between power law coefficients of the anatomical noise power spectrum and lesion detectability in breast imaging modalities

2013

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Purpose Previous research has demonstrated that a parameter extracted from a power function fit to the anatomical noise power spectrum, β, may be predictive of breast mass lesion detectability in x-ray based medical images of the breast. In this investigation, the value of β was compared with a number of other more widely used parameters, in order to determine the relationship between β and these other parameters. Methods This study made use of breast CT data sets, acquired on two breast CT systems developed in our laboratory. A total of 185 breast data sets in 183 women were used, and only the unaffected breast was used (where no lesion was suspected). The anatomical noise power spectrum was computed from two-dimensional regions of interest (ROI), was fit to a power function (NPS(f) = αf−β), and the exponent parameter (β) was determined using log/log linear regression. Breast density for each of the volume data sets was characterized in previous work. The breast CT data sets analyzed in this study were part of a previous study which evaluated the receiver operating characteristic (ROC) curve performance using simulated spherical lesions and a pre-whitened matched filter computer observer. This ROC information was used to compute the detectability index as well as the sensitivity at 95% specificity. The fractal dimension was computed from the same ROI's which were used for the assessment of β. The value of β was compared to breast density, detectability index, sensitivity, and fractal dimension, and the slope of these relationships was investigated to assess statistical significance from zero slope. A statistically significant non-zero slope was considered to be a positive association in this investigation. Results All comparisons between β and breast density, detectability index, sensitivity at 95% specificity, and fractal dimension demonstrated statistically significant association with p < 0.001 in all cases. The value of β was also found to be associated with patient age and breast diameter, parameters both related to breast density. In all associations between other parameters, lower values of β were associated with increased breast cancer detection performance. Specifically, lower values of β were associated with lower breast density, higher detectability index, higher sensitivity, and lower fractal dimension values. Conclusions While causality was not and probably cannot be demonstrated, the strong, statistically significant association between the β metric and the other more widely used parameters suggest that β may be considered as a surrogate measure for breast cancer detection performance. These findings are specific to breast parenchymal patterns and mass lesions only.

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“…When investigating the empirical relationship with actual reconstruction filters, which range from ramp-like standard filters with conventional apodisation functions, to edge-enhancing high spatial resolution filters, it was found that the relationship was closer to a power of 4 or 5 [29,42]. (28) This is illustrated in the following graph ( Fig. 7a), for the body scans.…”

Section: Spatial Resolution (Fav)mentioning

confidence: 99%

Image quality in CT: From physical measurements to model observers

et al. 2015

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Evaluation of image quality (IQ) in Computed Tomography (CT) is important to ensure that diagnostic questions are correctly answered, whilst keeping radiation dose to the patient as low as is reasonably possible. The assessment of individual aspects of IQ is already a key component of routine quality control of medical x-ray devices. These values together with standard dose indicators can be used to give rise to 'figures of merit' (FOM) to characterise the dose efficiency of the CT scanners operating in certain modes. The demand for clinically relevant IQ characterisation has naturally increased with the development of CT technology (detectors efficiency, image reconstruction and processing), resulting in the adaptation and evolution of assessment methods. The purpose of this review is to present the spectrum of various methods that have been used to characterise image quality in CT: from objective measurements of physical parameters to clinically task-based approaches (i.e. model observer (MO) approach) including pure human observer approach. When combined together with a dose indicator, a generalised dose efficiency index can be explored in a framework of system and patient dose optimisation. We will focus on the IQ methodologies that are required for dealing with standard reconstruction, but also for iterative reconstruction algorithms. With this concept the previously used FOM will be presented with a proposal to update them in order to make them relevant and up to date with technological progress. The MO that objectively assesses IQ for clinically relevant tasks represents the most promising method in terms of radiologist sensitivity performance and therefore of most relevance in the clinical environment.

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Effects of computing parameters and measurement locations on the estimation of 3D NPS in non-stationary MDCT images

Cited by 13 publications

References 26 publications

Task-Based Model Observer Assessment of A Partial Model-Based Iterative Reconstruction Algorithm in Thoracic Oncologic Multidetector CT

Task-Based Model Observer Assessment of A Partial Model-Based Iterative Reconstruction Algorithm in Thoracic Oncologic Multidetector CT

Association between power law coefficients of the anatomical noise power spectrum and lesion detectability in breast imaging modalities

Image quality in CT: From physical measurements to model observers

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