Toward standardized quantitative image quality (IQ) assessment in computed tomography (CT): A comprehensive framework for automated and comparative IQ analysis based on ICRU Report 87.

PURPOSE Based on the guidelines from "Report 87: Radiation Dose and Image-quality Assessment in Computed Tomography" of the International Commission on Radiation Units and Measurements (ICRU), a software framework for automated quantitative image quality analysis was developed and its usability for a variety of scientific questions demonstrated. METHODS The extendable framework currently implements the calculation of the recommended Fourier image quality (IQ) metrics modulation transfer function (MTF) and noise-power spectrum (NPS), and additional IQ quantities such as noise magnitude, CT number accuracy, uniformity across the field-of-view, contrast-to-noise ratio (CNR) and signal-to-noise ratio (SNR) of simulated lesions for a commercially available cone-beam phantom. Sample image data were acquired with different scan and reconstruction settings on CT systems from different manufacturers. RESULTS Spatial resolution is analyzed in terms of edge-spread function, line-spread-function, and MTF. 3D NPS is calculated according to ICRU Report 87, and condensed to 2D and radially averaged 1D representations. Noise magnitude, CT numbers, and uniformity of these quantities are assessed on large samples of ROIs. Low-contrast resolution (CNR, SNR) is quantitatively evaluated as a function of lesion contrast and diameter. Simultaneous automated processing of several image datasets allows for straightforward comparative assessment. CONCLUSIONS The presented framework enables systematic, reproducible, automated and time-efficient quantitative IQ analysis. Consistent application of the ICRU guidelines facilitates standardization of quantitative assessment not only for routine quality assurance, but for a number of research questions, e.g. the comparison of different scanner models or acquisition protocols, and the evaluation of new technology or reconstruction methods.

[1]  M E Phelps,et al.  Correlation of effective atomic number and electron density with attenuation coefficients measured with polychromatic x rays. , 1975, Radiology.

[2]  Anne Catrine Trægde Martinsen,et al.  How to measure CT image quality: variations in CT-numbers, uniformity and low contrast resolution for a CT quality assurance phantom. , 2014, 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.

[3]  R L Morin,et al.  A practical method to measure the MTF of CT scanners. , 1982, Medical physics.

[4]  C. Cann,et al.  Quantitative CT for determination of bone mineral density: a review. , 1988, Radiology.

[5]  J. Boone,et al.  An analytical edge spread function model for computer fitting and subsequent calculation of the LSF and MTF. , 1994, Medical physics.

[6]  A. Rose.  The sensitivity performance of the human eye on an absolute scale. , 1948, Journal of the Optical Society of America.

[7]  Oleg S. Pianykh,et al.  Digital Imaging and Communications in Medicine (DICOM) , 2017, Radiopaedia.org.

[8]  J. Bushberg.  The Essential Physics of Medical Imaging , 2001 .

[9]  Christian Steiding,et al.  A quality assurance framework for the fully automated and objective evaluation of image quality in cone-beam computed tomography. , 2014, Medical physics.

[10]  J. Wardlaw,et al.  Imaging of acute stroke prior to treatment: current practice and evolving techniques. , 2014, The British journal of radiology.

[11]  Norbert J. Pelc,et al.  The noise power spectrum in computed X-ray tomography. , 1978 .

[12]  Kai Yang,et al.  Noise power properties of a cone-beam CT system for breast cancer detection. , 2008, Medical physics.

[13]  Nicolas Normand,et al.  Software tools dedicated for an automatic analysis of the CT scanner quality control images , 2007, SPIE Medical Imaging.

[14]  J. Ehrhardt,et al.  Modulation transfer function of the EMI CT head scanner. , 1977, Medical physics.

[15]  D. Jaffray,et al.  A framework for noise-power spectrum analysis of multidimensional images. , 2002, Medical physics.

[16]  Aya Kamaya,et al.  CT perfusion of the liver: principles and applications in oncology. , 2014, Radiology.

[17]  P. Judy,et al.  The line spread function and modulation transfer function of a computed tomographic scanner. , 1976, Medical physics.

[18]  J. Boone,et al.  Comprar Essential Physics Of Medical Imaging, International Edition | Jerrold T. Bushberg | 9781451118100 | Lippincott Williams & Wilkins , 2012 .

[19]  Jeffrey H Siewerdsen,et al.  A simple approach to measure computed tomography (CT) modulation transfer function (MTF) and noise-power spectrum (NPS) using the American College of Radiology (ACR) accreditation phantom. , 2013, Medical physics.

[20]  J Anthony Seibert,et al.  Normalized CT dose index of the CT scanners used in the National Lung Screening Trial. , 2010, AJR. American journal of roentgenology.

[21]  S. Curley,et al.  Comparison of CT methods for determining the fat content of the liver. , 2007, AJR. American journal of roentgenology.

[22]  A E Burgess,et al.  The Rose model, revisited. , 1999, Journal of the Optical Society of America. A, Optics, image science, and vision.

[23]  Ehsan Samei,et al.  Quantitative comparison of noise texture across CT scanners from different manufacturers. , 2012, Medical physics.

[24]  Eric A. Hoffman,et al.  Automatic lung segmentation for accurate quantitation of volumetric X-ray CT images , 2001, IEEE Transactions on Medical Imaging.

[25]  D. Brenner,et al.  Cancer risks from diagnostic radiology. , 2008, The British journal of radiology.

[26]  John M Boone,et al.  Radiological interpretation 2020: toward quantitative image assessment. , 2007, Medical physics.

[27]  Francis R Verdun,et al.  Iterative reconstruction methods in two different MDCT scanners: physical metrics and 4-alternative forced-choice detectability experiments--a phantom approach. , 2013, 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.

[28]  K. Marten,et al.  Inadequacy of manual measurements compared to automated CT volumetry in assessment of treatment response of pulmonary metastases using RECIST criteria , 2006, European Radiology.

[29]  M. Reiser,et al.  Material differentiation by dual energy CT: initial experience , 2007, European Radiology.

[30]  F. Rademakers,et al.  ROOT — An object oriented data analysis framework , 1997 .

[31]  Katsuyuki Taguchi,et al.  Image quality assessment of an iterative reconstruction algorithm applied to abdominal CT imaging. , 2014, 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.