In radiography and fluoroscopy, the dose-area product (DAP) is used for dose documentation and the evaluation, whether the applied dose is too high, adequate or too low. In dose management systems (applied in fluoroscopy and radiography) a mean value of the DAP of a number of consecutive examinations is calculated and compared to the diagnostic reference levels of the different examination types. This shows, if on average the dose level is too high. However, on an individual this would not work. To achieve a radiograph of adequate image quality the required DAP for a slender patient is significantly lower than for a standard patient and vice versa for obese patients. Thereby, without knowledge about patient thickness, there is no way to judge, if the dose level for an individual would be appropriate. To overcome this problem, an estimate of the patient size was calculated from information of the dicom header of the images. By extracting the dose at the detector, the DAP, exam type, information about the beam quality of the used radiation (spectrum) and the exposed area of the detector an estimate of the water equivalent patient thickness can be determined. Monte Carlo simulations and measurements with varying thicknesses of a water phantom were in excellent agreement. The accuracy of the estimate was better than 1 cm. Further clinical experiments with patients undergoing an examination of the lumbar spine showed, that an accuracy better than 20% and a standard derivation of 10% is achievable. Therefore an automatic estimate of the patient thickness in fluoroscopy and radioscopy is feasible and facilitates a computer-based judgement if the dose for an individual patient is adequate.
Flat panel detectors have become the standard technology in projection radiography. Further progress in detector technology will result in an improvement of MTF and DQE. The new detector (DX-D45C; Agfa; Mortsel/Belgium) is based on cesium-iodine crystals and has a change in the detector material and the readout electronics. The detector has a size of 30 cm x 24 cm and a pixel matrix of 2560 x 2048 with a pixel pitch of 124 μm. The system includes an automatic exposure detector, which enables the use of the detector without a connection to the x-ray generator. The physical properties of the detector were determined following IEC 62220-1-1 in a laboratory setting. The MTF showed an improvement compared to the previous version of cesium-iodine based flat-panel detectors. Thereby the DQE is also improved especially for the higher frequencies. The new detector showed an improvement in the physical properties compared to the previous versions. This enables a potential for further dose reductions in clinical imaging.
In CT, the magnitude of enhancement is proportional to the amount of contrast medium (CM) injected. However, high doses of iodinated CM pose health risks, ranging from mild side effects to serious complications such as contrast-induced nephropathy (CIN). This work presents a method that enables the reduction of CM dosage, without affecting the diagnostic image quality. The technique proposed takes advantage of the additional spectral information provided by photon-counting CT systems. In the first step, we apply a material decomposition technique on the projection data to discriminate iodine from other materials. Then, we estimated the noise of the decomposed image by calculating the Cramér-Rao lower bound of the parameter estimator. Next, we iteratively reconstruct the iodine-only image by using the decomposed image and the estimation of noise as an input into a maximum-likelihood iterative reconstruction algorithm. Finally, we combine the iodine-only image with the original image to enhance the contrast of low iodine concentrations. The resulting reconstructions show a notably improved contrast in the final images. Quantitatively, the combined image has a significantly improved CNR, while the measured concentrations are closer to the actual concentrations of the iodine. The preliminary results from our technique show the possibility of reducing the clinical dosage of iodine, without affecting the diagnostic image quality.
Flat panel detectors have become the standard technology in projection radiography. Further progress in detector
technology will result in an improvement of MTF and DQE. The new detector (FDR D-Evo plus C24i, Fuji, Japan) is
based on cesium-iodine crystals and has a change in the detector layout. The read-out electrodes are moved to the
irradiated side of the detector. The physical properties of the detector were determined following IEC 62220-1-1 as
close as possible. The MTF showed a significant improvement compared to other cesium-iodine based flat-panel
detectors. Thereby the DQE is improved to other cesium-iodine based detectors especially for the higher frequencies.
The average distance between the point of interaction of the x-rays in the detector and the light collector is shorter, due
to the exponential absorption law in the detector. Thereby there is a reduction in light scatter and light absorption in the
cesium-iodine needle crystals. This might explain the improvement of the MTF and DQE results in our measurements.
The new detector design results in an improvement in the physical properties of flat-panel detectors. This enables a
potential for further dose reductions in clinical imaging.
Photon-counting detectors (PCD) not only have the advantage of providing spectral information but also offer high
quantum efficiencies, producing high image quality in combination with a minimal amount of radiation dose. Due to the
clinical unavailability of photon-counting CT, the need to evaluate different CT simulation tools for researching different
applications for photon-counting systems is essential. In this work, we investigate two different methods to simulate
PCD data: Monte-Carlo based simulation (MCS) and analytical based simulation (AS). The MCS is a general-purpose
photon transport simulation based on EGSnrc C++ class library. The AS uses analytical forward-projection in
combination with additional acquisition parameters. MCS takes into account all physical effects, but is computationally
expensive (several days per CT acquisition). AS is fast (several minutes), but lacks the accurateness of MCS with regard
to physical interactions. To evaluate both techniques an entrance spectra of 100kvp, a modified CTP515 module of the
CatPhan 600 phantom, and a detector system with six thresholds was simulated. For evaluation the simulated projection
data are decomposed via a maximum likelihood technique, and reconstructed via standard filtered-back projection (FBP).
Image quality from both methods is subjectively and objectively assessed. Visually, the difference in the image quality
was not significant. When further evaluated, the relative difference was below 4%. As a conclusion, both techniques
offer different advantages, while at different stages of development the accelerated calculations via AS can make a
significant difference. For the future one could foresee a combined method to join accuracy and speed.
The recent advancement in detector technology contributed towards the development of
photon counting detectors with the ability to discriminate photons according to their energy
on reaching the detector. This provides spectral information about the acquired object; thus,
giving additional data on the type of material as well as its density. In this paper, we
investigate possible reduction of dental artifacts in cone-beam CT (CBCT) via integration of
spectral information into a penalized maximum log-likelihood algorithm. For this
investigation we simulated (with Monte-Carlo CT simulator) a virtual jaw phantom, which
replicates components of a real jaw such as soft-tissue, bone, teeth and gold crowns. A
maximum-likelihood basis-component decomposition technique was used to calculate
sinograms of the individual materials. The decomposition revealed the spatial as well as
material density of the dental implant. This information was passed on as prior information
into the penalized maximum log-likelihood algorithm. The resulting reconstructions showed
significant reduced streaking artifacts. The overall image quality is improved such that the
contrast-to-noise ratio increased compared to the conventional FBP reconstruction. In this
work we presented a new algorithm that makes use of spectral information to provide a prior
for a penalized maximum log-likelihood algorithm.