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

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 (MTF0.5) 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 MTF0.5 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 MTF0.5 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.

[1]  Christian G. Graff,et al.  A new, open-source, multi-modality digital breast phantom , 2016, SPIE Medical Imaging.

[2]  Kyle J. Myers,et al.  Virtual Tools for the Evaluation of Breast Imaging: State-of-the Science and Future Directions , 2016, Digital Mammography / IWDM.

[3]  Andrew D. A. Maidment,et al.  Mammogram synthesis using a 3D simulation. I. Breast tissue model and image acquisition simulation. , 2002, Medical physics.

[4]  John P. Apruzese,et al.  Mixing of pump and lasant species in photopumped systems driven by a femtosecond laser , 1995, Optics & Photonics.

[5]  R. Siddon.  Fast calculation of the exact radiological path for a three-dimensional CT array. , 1985, Medical physics.

[6]  Anders Tingberg,et al.  Performance of one-view breast tomosynthesis as a stand-alone breast cancer screening modality: results from the Malmö Breast Tomosynthesis Screening Trial, a population-based study , 2015, European Radiology.

[7]  Michael P. Kempston,et al.  Resolution at oblique incidence angles of a flat panel imager for breast tomosynthesis. , 2006, Medical physics.

[8]  Ying Chen,et al.  Intercomparison of methods for image quality characterization. I. Modulation transfer function. , 2006, Medical physics.

[9]  Ying Chen,et al.  Intercomparison of methods for image quality characterization. II. Noise power spectrum. , 2006, Medical physics.

[10]  T. Kahn,et al.  Quantitative Image Quality Measurements of a Digital Breast Tomosynthesis System , 2013, Fortschritte auf dem Gebiet der Röntgenstrahlen und der bildgebenden Verfahren.

[11]  J A Rowlands,et al.  X-ray imaging using amorphous selenium: inherent spatial resolution. , 1995, Medical physics.

[12]  B. De Man,et al.  Distance-driven projection and backprojection in three dimensions. , 2004, Physics in medicine and biology.

[13]  Wei Zhao,et al.  Ghosting caused by bulk charge trapping in direct conversion flat-panel detectors using amorphous selenium. , 2005, Medical physics.

[14]  E. Samei,et al.  A method for measuring the presampled MTF of digital radiographic systems using an edge test device. , 1998, Medical physics.

[15]  Hilde Bosmans,et al.  Development and validation of a modelling framework for simulating 2D-mammography and breast tomosynthesis images , 2014, Physics in medicine and biology.

[16]  A R Cowen,et al.  Physical imaging performance of a compact computed radiography acquisition device. , 1998, Medical physics.

[17]  Andrew D. A. Maidment,et al.  Conditioning data for calculation of the modulation transfer function. , 2003, Medical physics.

[18]  Kyle J Myers,et al.  A virtual trial framework for quantifying the detectability of masses in breast tomosynthesis projection data. , 2013, Medical physics.

[19]  Hilde Bosmans,et al.  Technical Evaluation of a Digital Breast Tomosynthesis System , 2010, Digital Mammography / IWDM.

[20]  K Bliznakova,et al.  A three-dimensional breast software phantom for mammography simulation. , 2003, Physics in medicine and biology.

[21]  Yit Yoong Lim,et al.  Accuracy of Digital Breast Tomosynthesis for Depicting Breast Cancer Subgroups in a UK Retrospective Reading Study (TOMMY Trial). , 2015, Radiology.

[22]  Takaaki Ito,et al.  A newly developed a-Se mammography flat panel detector with high-sensitivity and low image artifact , 2013, Medical Imaging.

[23]  Martin J. Yaffe,et al.  The effect of lag on image quality for a digital breast tomosynthesis system , 2009, Medical Imaging.

[24]  J A Rowlands,et al.  Digital radiology using active matrix readout of amorphous selenium: theoretical analysis of detective quantum efficiency. , 1997, Medical physics.

[25]  A. Rodríguez-Ruiz,et al.  Evaluation of the technical performance of three different commercial digital breast tomosynthesis systems in the clinical environment. , 2016, Physica medica : PM : an international journal devoted to the applications of physics to medicine and biology : official journal of the Italian Association of Biomedical Physics.

[26]  T. R. Fewell,et al.  Molybdenum, rhodium, and tungsten anode spectral models using interpolating polynomials with application to mammography. , 1997, Medical physics.

[27]  I. Sechopoulos.  A review of breast tomosynthesis. Part I. The image acquisition process. , 2013, Medical physics.

[28]  L. Antonuk,et al.  Additive noise properties of active matrix flat-panel imagers. , 2000, Medical physics.

[29]  Bo Zhao,et al.  A computer simulation platform for the optimization of a breast tomosynthesis system. , 2007, Medical physics.

[30]  Ian A. Cunningham,et al.  Penalty on the detective quantum efficiency from off-axis incident x rays , 2004, SPIE Medical Imaging.

[31]  Oliver Diaz,et al.  Image simulation and a model of noise power spectra across a range of mammographic beam qualities. , 2014, Medical physics.

[32]  Nico Lanconelli,et al.  Physical and psychophysical characterization of a novel clinical system for digital mammography. , 2009, Medical physics.

[33]  Koen Michielsen,et al.  Patchwork reconstruction with resolution modeling for digital breast tomosynthesis. , 2013, Medical physics.

[34]  H Bosmans,et al.  Measurements of system sharpness for two digital breast tomosynthesis systems , 2012, Physics in medicine and biology.

[35]  Michael Sandborg,et al.  Implementation of unsharpness and noise into the model of the imaging system Applications to chest and lumbar spine screen-film radiography , 1999 .

[36]  Kenneth C. Young,et al.  Conversion of mammographic images to appear with the noise and sharpness characteristics of a different detector and x-ray system. , 2012, Medical physics.

[37]  Andriy I. Bandos,et al.  Comparison of digital mammography alone and digital mammography plus tomosynthesis in a population-based screening program. , 2013, Radiology.

[38]  W. Segars,et al.  4D XCAT phantom for multimodality imaging research. , 2010, Medical physics.

[39]  Srinivasan Vedantham,et al.  Detectors for digital mammography , 2012 .