Optimisation of an MDCT abdominal protocol: Image quality assessment of standard vs. iterative reconstructions.

This work aims to construct a method to objectively evaluate CT image quality when new clinical protocol performances must be compared with a standard reference. We compare iterative reconstruction in the image space with filtered back projection reconstruction and accurately quantify the dose reduction. The comparison strategy accounts for both physical and clinical image qualities that are evaluated using a standard metric. The quasi-ideal observer metric is also explored to verify its reportedly high correlation with perceived image quality. Water or spatial resolution phantom images are used to characterise the physical image quality using the classic metrics in the Fourier domain by calculating the modulation transfer functions and noise power spectra (NPS). The clinical-image quality is evaluated with a 4-alternative forced-choice test. The human observers are asked to detect a positive image that contains a simulated lesion in a background image. Then, the same positive images are characterised with the quasi-ideal observer metric, which calculates the non-prewhitening matched filter signal-to-noise ratio (SNRNPWMF). Iterative reconstruction strongly reduces the image noise, but the NPS are slightly shifted to lower frequencies, which gives the images a coarse graininess. Compared with the reference FBP protocol for abdomen exams, the highest dose reduction is 40% if the standard metric is used and 30% if the SNRNPWMF metric is used. The detectability test results achieve a better correlation with SNRNPWMF than with the standard metric. The identified Fourier metric is a useful descriptor of human quality perception and can be used for future protocol optimisation.

[1]  James K Min,et al.  Estimated radiation dose reduction using adaptive statistical iterative reconstruction in coronary CT angiography: the ERASIR study. , 2010, AJR. American journal of roentgenology.

[2]  K Doi,et al.  A comparison of physical image quality indices and observer performance in the radiographic detection of nylon beads. , 1984, Physics in medicine and biology.

[3]  Daniel Kolditz,et al.  Iterative reconstruction methods in X-ray CT. , 2012, 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.

[4]  J. Remy,et al.  Chest computed tomography using iterative reconstruction vs filtered back projection (Part 2): image quality of low-dose CT examinations in 80 patients , 2011, European Radiology.

[5]  Willi A. Kalender,et al.  Computed tomography : fundamentals, system technology, image quality, applications , 2000 .

[6]  M F McNitt-Gray,et al.  Application of the noise power spectrum in modern diagnostic MDCT: part II. Noise power spectra and signal to noise , 2007, Physics in medicine and biology.

[7]  U. Schoepf,et al.  Image quality and radiation dose of low dose coronary CT angiography in obese patients: sinogram affirmed iterative reconstruction versus filtered back projection. , 2012, European journal of radiology.

[8]  Anne Catrine Trægde Martinsen,et al.  Iterative reconstruction reduces abdominal CT dose. , 2012, European journal of radiology.

[9]  William P. Shuman,et al.  Adaptive statistical iterative reconstruction versus filtered back projection in the same patient: 64 channel liver CT image quality and patient radiation dose , 2011, European Radiology.

[10]  Jacques Felblinger,et al.  CT image quality improvement using adaptive iterative dose reduction with wide-volume acquisition on 320-detector CT , 2012, European Radiology.

[11]  M. Tapiovaara Relationships between Physical Measurements and User Evaluation of Image Quality in Medical Radiology – a Review , 2006 .

[12]  Katsuyuki Taguchi,et al.  Combination of a Low-Tube-Voltage Technique With Hybrid Iterative Reconstruction (iDose) Algorithm at Coronary Computed Tomographic Angiography , 2011, Journal of computer assisted tomography.

[13]  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.

[14]  F. Jäkel,et al.  Spatial four-alternative forced-choice method is the preferred psychophysical method for naïve observers. , 2006, Journal of vision.

[15]  R. Wu,et al.  Radiation dose of non-enhanced chest CT can be reduced 40% by using iterative reconstruction in image space. , 2011, Clinical radiology.

[16]  Eun-Ah Park,et al.  Iterative reconstruction of dual-source coronary CT angiography: assessment of image quality and radiation dose , 2012, The International Journal of Cardiovascular Imaging.

[17]  J. Remy,et al.  Chest computed tomography using iterative reconstruction vs filtered back projection (Part 1): evaluation of image noise reduction in 32 patients , 2011, European Radiology.

[18]  Christian Stahl,et al.  Dose Reduction in Abdominal Computed Tomography: Intraindividual Comparison of Image Quality of Full-Dose Standard and Half-Dose Iterative Reconstructions With Dual-Source Computed Tomography , 2011, Investigative radiology.

[19]  Martin Sedlmair,et al.  Assessment of an iterative reconstruction algorithm (SAFIRE) on image quality in pediatric cardiac CT datasets. , 2012, Journal of cardiovascular computed tomography.

[20]  Thomas Flohr,et al.  Low-dose CT of the lung: potential value of iterative reconstructions , 2012, European Radiology.

[21]  S. Sanada,et al.  Image quality dependence on in-plane positions and directions for MDCT images. , 2010, European journal of radiology.

[22]  R. Raupach,et al.  Iterative reconstruction algorithm for abdominal multidetector CT at different tube voltages: assessment of diagnostic accuracy, image quality, and radiation dose in a phantom study. , 2011, Radiology.

[23]  Stanton A. Glantz,et al.  Primer of biostatistics : statistical software program version 6.0 , 1981 .

[24]  Alvin C. Silva,et al.  Iterative Reconstruction Technique for Reducing Body Radiation Dose at Ct: Feasibility Study Hara Et Al. Ct Iterative Reconstruction Technique Gastrointestinal Imaging Original Research , 2022 .

[25]  C Ghetti,et al.  CT iterative reconstruction in image space: a phantom study. , 2012, 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]  M F McNitt-Gray,et al.  Application of the noise power spectrum in modern diagnostic MDCT: part I. Measurement of noise power spectra and noise equivalent quanta , 2007, Physics in medicine and biology.