Quantitative Image Quality Measurements of a Digital Breast Tomosynthesis System

Olğar, Turan; Kahn, Thomas; Gosch, D.

doi:10.1055/s-0033-1350106

Cited by 6 publications

(5 citation statements)

References 12 publications

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“…In addition, the MTF plots appear to vary almost as a linear function of frequency. While this behavior is not typically exhibited by x-ray detectors, it is unique to the HSD system in the 2D mode, as previously reported by Olgar et al 26 Figure 6(b,c) shows the variation in the NNPS and DQE characteristics with incident air kerma. Figure 5(c) shows the simulated DQE plots compared against measured data.…”

Section: Experimental Datasupporting

confidence: 77%

Computational models of direct and indirect X‐ray breast imaging detectors for in silico trials

et al. 2022

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Background To facilitate in silico studies that investigate digital mammography (DM) and breast tomosynthesis (DBT), models replicating the variety in imaging performance of the DM and DBT systems, observed across manufacturers are needed. Purpose The main purpose of this work is to develop generic physics models for direct and indirect detector technology used in commercially available systems, with the goal of making them available open source to manufacturers to further tweak and develop the exact in silico replicas of their systems. Methods We recently reported on an in silico version of the SIEMENS Mammomat Inspiration DM/DBT system using an open‐source GPU‐accelerated Monte Carlo x‐ray imaging simulation code (MC‐GPU). We build on the previous version of the MC‐GPU codes to mimic the imaging performances of two other Food and Drug Administration (FDA)‐approved DM/DBT systems, such as Hologic Selenia Dimensions (HSD) and the General Electric Senographe Pristina (GSP) systems. In this work, we developed a hybrid technique to model the optical spread and signal crosstalk observed in the GSP and HSD systems. MC simulations are used to track each x‐ray photon till its first interaction within the x‐ray detector. On the other hand, the signal spread in the x‐ray detectors is modeled using previously developed analytical equations. This approach allows us to preserve the modeling accuracy offered by MC methods in the patient body, while speeding up secondary carrier transport (either electron–hole pairs or optical photons) using analytical equations in the detector. The analytical optical spread model for the indirect detector includes the depth‐dependent spread and collection of optical photons and relies on a pre‐computed set of point response functions that describe the optical spread as a function of depth. To understand the capabilities of the computational x‐ray detector models, we compared image quality metrics like modulation transfer function (MTF), normalized noise power spectrum (NNPS), and detective quantum efficiency (DQE), simulated with our models against measured data. Please note that the purpose of these comparisons with measured data would be to gauge if the model developed as part of this work could replicate commercially used direct and indirect technology in general and not to achieve perfect fits with measured data. Results We found that the simulated image quality metrics such as MTF, NNPS, and DQE were in reasonable agreement with experimental data. To demonstrate the imaging performance of the three DM/DBT systems, we integrated the detector models with the VICTRE pipeline and simulated DM images of a fatty breast model containing a spiculated mass and a calcium oxalate cluster. In general, we found that the images generated using the indirect model appeared more blurred with a different noise texture and contrast as compared to the systems with direct detectors. Conclusions We have presented computational models of three commercially available FDA‐approved DM/DBT systems, which ...

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Section: Experimental Datasupporting

confidence: 77%

Computational models of direct and indirect X‐ray breast imaging detectors for in silico trials

et al. 2022

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“…The zero degree acquisition mode was not available on the early generation Inspiration systems and therefore there was some influence of focus motion on the DQE data in this study. The DQE data of Olgar et al (2013) for a Selenia Dimensions operated in binned zero degree mode showed that DQE was constant for DAK levels above approximately ∼13.5 μGy. Given the essentially flat NPS curves seen for a-Se based DBT systems, DQE(f) has a shape that follows ( ) MTF f 2 and therefore DQE(f) falls rapidly in binned mode compared to non-binned operation Zhao 2008a, Olgar, Kahn andGosch 2013).…”

Section: Nps Measured In the Reconstructed Planesmentioning

confidence: 96%

“…The DQE data of Olgar et al (2013) for a Selenia Dimensions operated in binned zero degree mode showed that DQE was constant for DAK levels above approximately ∼13.5 μGy. Given the essentially flat NPS curves seen for a-Se based DBT systems, DQE(f) has a shape that follows ( ) MTF f 2 and therefore DQE(f) falls rapidly in binned mode compared to non-binned operation Zhao 2008a, Olgar, Kahn andGosch 2013). Zhao et al (2015) developed a version of cascaded linear system analysis for the low and high gain modes of a CsI-CMOS x-ray detector (Dexela 2923 MAM) with emphasis on the detector electronic noise performance.…”

Section: Nps Measured In the Reconstructed Planesmentioning

confidence: 96%

Performance evaluation of digital breast tomosynthesis systems: physical methods and experimental data

Marshall¹,

Bosmans²

2022

Phys. Med. Biol.

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Digital breast tomosynthesis (DBT) has become a well-established breast imaging technique, whose performance has been investigated in many clinical studies, including a number of prospective clinical trials. Results from these studies generally point to non-inferiority in terms of microcalcification detection and superior mass-lesion detection for DBT imaging compared to digital mammography (DM). This modality has become an essential tool in the clinic for assessment and ad-hoc screening but is not yet implemented in most breast screening programmes at a state or national level. While evidence on the clinical utility of DBT has been accumulating, there has also been progress in the development of methods for technical performance assessment and quality control of these imaging systems. DBT is a relatively complicated “pseudo-3D” modality whose technical assessment poses a number of difficulties. This paper reviews methods for the technical performance assessment of DBT devices, starting at the component level in part one and leading up to discussion of system evaluation with physical test objects in part two. We provide some historical and basic theoretical perspective, often starting from methods developed for DM imaging. Data from a multi-vendor comparison are also included, acquired under the medical physics QC protocol developed by EUREF and currently being consolidated by a European Federation of Organisations for Medical Physics (EFOMP) working group. These data and associated methods can serve as a reference for the development of reference data and provide some context for clinical studies.

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“…The factors that affect the image need to be understood before simulation. Evaluations of DBT systems have been undertaken by various authors (Marshall et al 2010, Olgar et al 2013, Rodríguez-Ruiz et al 2016 and in various National Health Service Breast Screening Programme (NHSBSP) reports (www.gov. uk/government/collections/breast-screening-professional-guidance).…”

Section: Introductionmentioning

confidence: 99%

Characterisation of noise and sharpness of images from four digital breast tomosynthesis systems for simulation of images for virtual clinical trials

Mackenzie

Marshall²,

Hadjipanteli

et al. 2017

Phys. Med. Biol.

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In-depth evaluation of the noise and sharpness characteristics of FujiFilm Innovality, GE SenoClaire, Hologic Selenia Dimensions and Siemens Inspiration digital breast tomosynthesis (DBT) systems was performed with the intention of improving image simulation for virtual clinical trials. Noise power spectra (NPS) and modulation transfer function curves (MTF) were measured for planar modes and for the first and central projections for DBT modes. In DBT mode, the x-ray beam was blocked for the projections before the central projection in order to remove the influence of lag and ghosting from the previous images. A quadratic fit between the NPS and linearised pixel value gave the noise coefficients for planar and DBT imaging modes. The spatial frequencies corresponding to an MTF of 0.5 (MTF) were calculated from the MTF measurements made on the breast support and at 40 mm above the breast support. This was done for the first and the central projections. The percentage of signal carried over from the first projection to subsequent images (lag) was measured using a slit. The noise associated with lag was also evaluated. The DBT modes typically had lower electronic noise coefficients but higher structural noise coefficients compared to the respective planar mode MTF measured 40 mm above the table was between 6% and 47% lower for continuous scanning systems compared to 1% lower for step and shoot systems. For wide angle DBT, the MTF of the first projection was 18% (FujiFilm) and 28% (Siemens) lower than for the central projection. Lag in the second projection was 2.2%, 0.3%, 0.8% for the FujiFilm, GE and Hologic systems respectively. In all cases, the noise associated with lag was negligible. Current modelling frameworks for virtual clinical trials of breast DBT systems need to be adapted to account for signals from lag and variations in the MTF at wide angles.

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Quantitative Image Quality Measurements of a Digital Breast Tomosynthesis System

Cited by 6 publications

References 12 publications

Computational models of direct and indirect X‐ray breast imaging detectors for in silico trials

Computational models of direct and indirect X‐ray breast imaging detectors for in silico trials

Performance evaluation of digital breast tomosynthesis systems: physical methods and experimental data

Characterisation of noise and sharpness of images from four digital breast tomosynthesis systems for simulation of images for virtual clinical trials

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