A framework for optimising the radiographic technique in digital X-ray imaging.

The transition to digital radiology has provided new opportunities for improved image quality, made possible by the superior detective quantum efficiency and post-processing capabilities of new imaging systems, and advanced imaging applications, made possible by rapid digital image acquisition. However, this transition has taken place largely without optimising the radiographic technique used to acquire the images. This paper proposes a framework for optimising the acquisition of digital X-ray images. The proposed approach is based on the signal and noise characteristics of the digital images and the applied exposure. Signal is defined, based on the clinical task involved in an imaging application, as the difference between the detector signal with and without a target present against a representative background. Noise is determined from the noise properties of uniformly acquired images of the background, taking into consideration the absorption properties of the detector. Incident exposure is estimated or otherwise measured free in air, and converted to dose. The main figure of merit (FOM) for optimisation is defined as the signal-difference-to-noise ratio (SdNR) squared per unit exposure or (more preferably) dose. This paper highlights three specific technique optimisation studies that used this approach to optimise the radiographic technique for digital chest and breast applications. In the first study, which was focused on chest radiography with a CsI flat-panel detector, a range of kV(p) (50-150) and filtration (Z = 13-82) were examined in terms of their associated FOM as well as soft tissue to bone contrast, a factor of importance in digital chest radiography. The results indicated that additive Cu filtration can improve image quality. A second study in digital mammography using a selenium direct flat-panel detector indicated improved SdNR per unit exposure with the use of a tungsten target and a rhodium filter than conventional molybdenum target/molybdenum filter techniques. Finally, a third study focusing on cone-beam computed tomography of the breast using a CsI flat-panel detector indicated that high Z filtration of a tungsten target X-ray beam can notably improve the signal and noise characteristics of the image. The general findings highlight the fact that the techniques that are conventionally assumed to be optimum may need to be revisited for digital radiography.

[1]  Ehsan Samei,et al.  Simulation study of a quasi-monochromatic beam for x-ray computed mammotomography. , 2004, Medical physics.

[2]  James T Dobbins,et al.  Digital x-ray tomosynthesis: current state of the art and clinical potential. , 2003, Physics in medicine and biology.

[3]  Ehsan Samei,et al.  An experimental comparison of detector performance for computed radiography systems. , 2002, Medical physics.

[4]  Ehsan Samei,et al.  Measurements of an optimized beam for x-ray computed mammotomography , 2004, SPIE Medical Imaging.

[5]  E Samei,et al.  Detection of subtle lung nodules: relative influence of quantum and anatomic noise on chest radiographs. , 1999, Radiology.

[6]  Ehsan Samei,et al.  An experimental comparison of detector performance for direct and indirect digital radiography systems. , 2003, Medical physics.

[7]  C E Ravin,et al.  Imaging characteristics of an amorphous silicon flat-panel detector for digital chest radiography. , 2001, Radiology.

[8]  P. Granfors,et al.  Performance of a 41X41-cm2 amorphous silicon flat panel x-ray detector for radiographic imaging applications. , 2000, Medical physics.

[9]  H. Blume,et al.  DQE(f) of four generations of computed radiography acquisition devices. , 1995, Medical physics.

[10]  W. Huda,et al.  Effective dose equivalents, HE, in diagnostic radiology. , 1990, Medical physics.

[11]  J A Rowlands,et al.  X-ray detectors for digital radiography. , 1997, Physics in medicine and biology.

[12]  James A. Scott Photon, Electron, Proton and Neutron Interaction Data for Body Tissues ICRU Report 46. International Commission on Radiation Units and Measurements, Bethesda, 1992, $40.00 , 1993 .

[13]  Ehsan Samei,et al.  Chest radiography: optimization of X-ray spectrum for cesium iodide-amorphous silicon flat-panel detector. , 2003, Radiology.

[14]  N J Hangiandreou,et al.  Effects of x-ray spectra on the DQE of a computed radiography system. , 2001, Medical physics.

[15]  J. Boone Normalized glandular dose (DgN) coefficients for arbitrary X-ray spectra in mammography: computer-fit values of Monte Carlo derived data. , 2002, Medical physics.