Estimating of radiation output of X-RAY tube using mathematical model: Case of high-frequency machines

PURPOSE

During any radiological procedure, it is important to know the dose to be-administered to the patient and this can be done by estimating the output of the X-ray tube either with a dosimeter or with a mathematical equation or Monte Carlo simulations. The aim of this work is to develop a new mathematical model equation (NMME) for estimating the output of high-frequency X-ray tubes.

METHODS

To achieve this, data collected from ten machines in many regions of Cameroon were used (for nine machines) to build an initial model that does not take into account the anode angle and the tenth machine was used to test the model. Using the SpekCalc software, some simulations were carried out to evaluate the influence of the anode angle. This allowed the NMME to be proposed.

RESULTS

The deviations frequencies between 0.65% and 19.61% were obtained by comparing the output values obtained using initial model with the measured values. The statistical hypothesis test showed that the estimated values using initial model and NMME are in agreement with those measured unlike the Kothan and Tungjai model. For the tenth machine, the percentage difference between estimated and measured values is less than 8 %.

CONCLUSION

These results show that the proposed model performed better than the previous models. In the absence of a dosimeter, the NMME could be used to estimate the output of high frequency X-ray machines and therefore the radiation doses received by patients during diagnostic X-ray examinations.

Air Kerma Calculation in Diagnostic Medical Imaging Devices Using Group Method of Data Handling Network

The air kerma, which is the amount of energy given off by a radioactive substance, is essential for medical specialists who use radiation to diagnose cancer problems. The amount of energy that a photon has when it hits something can be described as the air kerma (the amount of energy that was deposited in the air when the photon passed through it). Radiation beam intensity is represented by this value. Hospital X-ray equipment has to account for the heel effect, which means that the borders of the picture obtain a lesser radiation dosage than the center, and that air kerma is not symmetrical. The voltage of the X-ray machine can also affect the uniformity of the radiation. This work presents a model-based approach to predict air kerma at various locations inside the radiation field of medical imaging instruments, making use of just a small number of measurements. Group Method of Data Handling (GMDH) neural networks are suggested for this purpose. Firstly, a medical X-ray tube was modeled using Monte Carlo N Particle (MCNP) code simulation algorithm. X-ray tubes and detectors make up medical X-ray CT imaging systems. An X-ray tube's electron filament, thin wire, and metal target produce a picture of the electrons' target. A small rectangular electron source modeled electron filaments. An electron source target was a thin, 19,290 kg/m³ tungsten cube in a tubular hoover chamber. The electron source-object axis of the simulation object is 20° from the vertical. For most medical X-ray imaging applications, the kerma of the air was calculated at a variety of discrete locations within the conical X-ray beam, providing an accurate data set for network training. Various locations were taken into account in the aforementioned voltages inside the radiation field as the input of the GMDH network. For diagnostic radiology applications, the trained GMDH model could determine the air kerma at any location in the X-ray field of view and for a wide range of X-ray tube voltages with a Mean Relative Error (MRE) of less than 0.25%. This study yielded the following results: (1) The heel effect is included when calculating air kerma. (2) Computing the air kerma using an artificial neural network trained with minimal data. (3) An artificial neural network quickly and reliably calculated air kerma. (4) Figuring out the air kerma for the operating voltage of medical tubes. The high accuracy of the trained neural network in determining air kerma guarantees the usability of the presented method in operational conditions.

Evaluation of x-ray effective focal spot size dependency on x-ray exposure settings using edge response analysis

The effective focal spot size of x-ray tubes is one of the major factors that substantially affect the resultant x-ray images, and it is known to be dependent on the x-ray exposure setting used. This study aims to evaluate the relationship between the effective focal spot size and the tube current and voltage and assess its reproducibility among several x-ray tubes. The evaluation was performed using edge response analysis, in which a 1-mm thick tungsten edge was projected onto a flat panel detector with a magnification factor of 2. The edge image was then differentiated to obtain the line spread function, followed by a detector blur-removing process through Fourier analysis to obtain the true focus profile. The resultant focal spot size increased as the tube current increased, whereas it decreased as the tube voltage increased, as expected. The rate of change was similar along the width and the length directions, while the small focus changed more significantly than the large focus. The reproducibility among four x-ray tubes of the same model was excellent as the maximum variation < 20%. In conclusion, the edge response method can provide useful information on the x-ray focal spot relationship with the x-ray exposure settings used, as well as its reproducibility among several x-ray tubes.

Radiographic and fluoroscopic X-ray systems: Quality control of the X-ray tube and automatic exposure control using theoretical spectra to determine air kerma and dose to a homogenous phantom

PURPOSE

To develop a method to perform quality control (QC) of X-ray tubes and automatic exposure control (AEC) as a part of the QC of the radiographic and fluoroscopic X-ray system. Our aim is to verify the output from the X-ray tube by comparing the measured radiation output, or air kerma, to the theoretical output given the applied exposure settings and geometry, in addition to comparing the measured kV to the nominal kV. The AEC system for fluoroscopic and conventional X-ray systems is assessed by determining the absorbed dose to a homogenous phantom with different thicknesses.

METHOD

This study presents a model to verify the X-ray tube measurement results and a method to determine the dose to a homogenous phantom (Dphantom ). The following input is needed: a parameterized model of the X-ray spectrum, the X-ray tube measurements using a multifunctional X-ray meter, the exposure parameters recorded via imaging of polymethyl methacrylate (PMMA) slabs of different thickness that simulate the patient using AEC, and a parameterized model for calculating the dose to water from Monte Carlo simulations. The output is the entrance surface dose (ESD) and absorbed dose in the phantom, Dphantom (µGy). In addition, the parameterized X-ray spectrum is used to compare theoretical and measured air kerma as a part of the QC of the X-ray tube. To verify the proposed method, the X-ray spectrum provided in this study, SPECTRUM, was compared to two commercially available spectra, SpekCalc and Institute of Physics and Engineering in Medicine (IPEM) 78. The fraction of energy imparted to the homogenous phantom was compared to the imparted fraction calculated by PCXMC.

RESULTS

The spectrum provided in this study was in good agreement with two previously published X-ray spectra. The absolute percentage differences of the spectra varied from 0.05% to 3.9%, with an average of 1.4%, compared to SpekCalc. Similarly, the deviation from IPEM report 78 varied from 0.02% to 2.3%, with an average of 0.74%. The SPECTRUM was parameterized for calculation of the imparted fraction for target angles of 10°, 12°, and 15°, kV (50-150 kV) with the materials Al (2.2-8 mm), Cu (0-1 mm), and any combination of the filters, PMMA and water. The deviation of energy imparted from the results by PCXMC was less than 8% for all measurements across different kV, filtration, and vendors, obtained by using PMMA to record the exposure parameters, while the dose was calculated based on water with same thicknesses as the PMMA.

CONCLUSION

This study presents an accurate and suitable method to perform a part of the QC of fluoroscopic and conventional X-ray systems with respect to the X-ray tube and the associated AEC system. The method is suitable for comparing protocols within and between systems via the absorbed dose.

X-ray tube with artificial neural network model as a promising alternative for radioisotope source in radiation based two phase flowmeters

In this paper, X-ray tube is introduced as a potential alternative for radioisotope sources used in radiation based liquid-gas two-phase flowmeters. X-ray tubes have lots of advantages over the radioisotope sources such as having an adjustable emitting photon's energy, being safer from point of view of radiation health physics during the transportation of the source, having ability to generate a high flux photon beam, and etc. The proposed radiation based system in this study composes an X-ray tube with a tube voltage of 150 kV and a 2.5 mm aluminum filter as the radiation source and one sodium iodide crystal as the photon detector. A pipe was positioned between the X-ray tube and the detector. Two main flow regimes of annular and stratified with different void fractions were modelled inside the pipe. Artificial neural network model of multi-layer perceptron (MLP) was also used in this study for analyzing the obtained data. The output spectrum of sodium iodide detector with 150 samples was applied as the input of multi-layer perceptron network and void fraction was considered as its output. The root mean squared error of proposed measuring system was 4.13 which shows the X-ray tube can be implemented as a promising alternative for radioisotope in radiation based two phase flow meters.

Monte Carlo kilovoltage X-ray tube simulation: A statistical analysis and compact simulation method

INTRODUCTION

Monte Carlo (MC) simulations are a powerful tool for improving image quality in X-ray based imaging modalities. An accurate X-ray source model is essential to MC modeling for CBCT but can be difficult to implement on a GPU while maintaining efficiency and memory limitations. A statistical analysis of the photon distribution from a MC X-ray tube simulation is conducted in hopes of building a compact source model.

MATERIALS & METHODS

MC simulations of an X-ray tube were carried out using BEAMnrc. The resulting photons were sorted into four categories: primary, scatter, off-focal radiation (OFR), and both (scatter and OFR). A statistical analysis of the photon components (energy, position, direction) was completed. A novel method for a compact (memory efficient) representation of the PHSP data was implemented and tested using different statistical based linear transformations (PCA, ZCA, ICA), as well as a geometrical transformation.

RESULTS

The statistical analysis showed all photon groupings had strong correlations between position and direction, with the largest correlation in the primary data. The novel method was successful in compactly representing the primary (error < 2%) and scatter (error < 6%) photon groupings by reducing the component correlations.

DISCUSSION & CONCLUSION

Statistical linear transforms provide a method of reducing the memory required to accurately simulate an X-ray source in a GPU MC system. If all photon types are required, the proposed method reduces the memory requirements by 3.8 times. When only primary and scatter data is needed, the memory requirement is reduced from gigabytes to kilobytes.

Reconstruction of x-ray focal spot distribution using a rotating edge

The size and shape of an x-ray source's focal spot is a critical factor in the imaging system's overall spatial resolution. The conventional approach to imaging the focal spot uses a pinhole camera, but this requires careful, manual measurements. Instead, we propose a novel alternative, simply using the collimator available on many x-ray systems. After placing the edge of a collimator blade in the center of the beam, we can obtain an image of its edge spread function (ESF). Each ESF provides information about the focal spot distribution - specifically, the parallel projection of the focal spot in the direction parallel to the edge. If the edge is then rotated about the beam axis, each image provides a different parallel projection of the focal spot until a complete Radon transform of the focal spot distribution is obtained. The focal spot can then be reconstructed by the inverse Radon transform, or parallel-beam filtered backprojection. We conducted a study on a clinical C-arm system with 3 focal spot sizes (0.3, 0.6, 1.0 mm nominal size), comparing the focal spot obtained using the rotating edge method against the conventional pinhole approach. Our results demonstrate accurate characterization of the size and shape of the focal spot.

Simulation of a complete X-ray digital radiographic system for industrial applications

Simulating X-ray images is of great importance in industry and medicine. Using such simulation permits us to optimize parameters which affect image's quality without the limitations of an experimental procedure. This study revolves around a novel methodology to simulate a complete industrial X-ray digital radiographic system composed of an X-ray tube and a computed radiography (CR) image plate using Monte Carlo N Particle eXtended (MCNPX) code. In the process of our research, an industrial X-ray tube with maximum voltage of 300 kV and current of 5 mA was simulated. A 3-layer uniform plate including a polymer overcoat layer, a phosphor layer and a polycarbonate backing layer was also defined and simulated as the CR imaging plate. To model the image formation in the image plate, at first the absorbed dose was calculated in each pixel inside the phosphor layer of CR imaging plate using the mesh tally in MCNPX code and then was converted to gray value using a mathematical relationship determined in a separate procedure. To validate the simulation results, an experimental setup was designed and the images of two step wedges created out of aluminum and steel were captured by the experiments and compared with the simulations. The results show that the simulated images are in good agreement with the experimental ones demonstrating the ability of the proposed methodology for simulating an industrial X-ray imaging system.

Influence of the X-ray beam quality on the dose increment in CT with iodinated contrast medium

BACKGROUND

In computed tomography (CT), the image contrast is given by the difference in X-ray attenuation in the various tissues of the patient and contrast media are used to enhance image contrast in anatomic regions characterized by similar attenuation coefficients.

OBJECTIVE

Aim of the present work is to enlarge the range of applicability of the method previously introduced for organ dosimetry in contrast-enhanced CT, by studying the effects of X-ray beam quality on the parameters of the model. Furthermore, an experimental method for the evaluation of the attenuation properties of iodinated solutions is proposed.

METHODS

Monte Carlo simulations of anthropomorphic phantoms were carried out to determine a bi-parametrical (a and b) analytical relationship between iodine concentration and dose increase in organs of interest as a function of the tube kilo-voltage peak potential (kVp) and filtration. Experimental measurements of increments in Hounsfield Units (HU) were conducted in several CT scanners, at all the kVp available, in order to determine the parameter γ which relates the HU increment with the iodine mass fraction. A cylindrical phantom that can be filled with iodine solutions provided with an axial housing for a pencil ionization chamber was designed and assembled in order to measure the attenuation properties of iodine solutions under irradiation of a CT scanner and to obtain a further validation of Monte Carlo simulations.

RESULTS

The simulation-derived parameters of the model, a and b, are only slightly dependent upon the tube kilo-voltage peak potential and filtration, while such scanner-dependent features influence mainly the experimentally-derived γ parameter. Relative dose variations registered by the ionization chamber inside the iodine-filled cylindrical phantom decrease when the X-ray mean energy increases, and reaches about 50% for 10 mg/ml of iodine.

CONCLUSIONS

The dosimetric method for contrast-enhanced CT can be applied to all CT scanners by adopting average simulative parameters and by carrying out a simple measurement with a series of iodine contrast solutions. The novel experimental methodology introduced can provide a direct measurement of iodine attenuation properties.

First TDCR measurements at low energies using a miniature x-ray tube

Developed for radionuclide standardization using liquid scintillation, the Triple to Double Coincidence Ratio (TDCR) method is applied using coincidence counting obtained with a specific three-photomultiplier system. For activity determination, a statistical model of light emission is classically used to establish a relation between the detection efficiency and the experimental TDCR value. At LNE-LNHB, a stochastic approach of the TDCR modeling was developed using the Monte Carlo code Geant4. The interest of this TDCR-Geant4 model is the possibility to simulate the propagation of optical photons from their creation in the scintillation vial to the production of photoelectrons in photomultipliers. As an alternative to the use of radionuclide sources, first TDCR measurements are presented using a miniature x-ray tube closely coupled to the scintillation vial. The objective of this new set-up was to enable low-energy depositions (lower than 20 keV) in liquid scintillator in order to study the influence of both time and geometrical dependence between PMTs already observed with radioactive sources. As for the statistical TDCR model, the non-linearity of light emission is implemented in the TDCR-Geant4 model using the Birks formula which depends on the kB factor and the scintillation yield. Measurements performed with the x-ray tube are extended to the assessment of these parameters and they are tested afterwards in the TDCR-Geant4 model for activity measurements of (3)H.

Determination of linear x-ray attenuation coefficients of pathological brain tissues and use of filters in tissue contrast enhancement in computed tomography

OBJECTIVE

X-ray attenuation coefficients are used in common radiological, pathological and spectroscopic examinations and in the determination of the radiation dose distribution in biological tissues. In radiology, these coefficients enable diagnosis by differentiating the abnormal tissues from the normal ones using their morphological structure and contrast differences. In this study, our aim is to precisely determine the linear x-ray attenuation coefficients of pathological brain tissues and to use x-ray beam filters to enhance the tissue contrast in computed tomography.

MATERIALS AND METHODS

To directly measure the relative linear attenuation coefficients, an energy dispersive x-ray spectroscopy system (EDXRS-Canberra, Si(Li) with DSA-1000 spectrum analyzer 1998; CT, USA) was used with collimators and a medical-purpose x-ray tube (Siemens, Siremobil, 1985; Erlangen, Germany) in a linear geometry.

RESULTS

Using a Mo filter with Computed Tomography CT and photon energies from 15 to 25 keV, EDXRS acquisitions were found to significantly distinguish grades of brain tumors (p<0.05). For the data acquired from CT systems with the decreasing filtered photon mean energy, the x-ray attenuation coefficients (i.e., the Hounsfield units) show that the ratio of EDXRS to CT for water's attenuation coefficient are increased. With our suggested x-ray filters, the tissue contrast has been found to be increased in ex vivo brain tumor slices compared with slices scanned in conventional CT scanners.

CONCLUSION

X-ray attenuations measured with the EDXRS are found to be statistically more reliable because of the length of acquisition times in this study.