Application of NEMA protocols to verify GATE models based on the Digital Biograph Vision and the Biograph Vision Quadra scanners.

PURPOSE: The Monte Carlo method is an effective tool to simulate and verify PET systems. Furthermore, it can help in the design and optimization of new medical imaging devices and algorithms. In this framework, the goal of this work is to verify the GATE toolkit performance when applied to simulate two Siemens Healthineers PET scanners: a standard axial field-of-view Biograph Vision scanner and the new long axial field-of-view Biograph Vision Quadra scanner. METHODS: The simulation toolkit GATE is based on GEANT4, comprising its main functionalities and a set of domain-specific features in the field of medical physics. To accomplish our purpose, the guidelines described in the NEMA NU 2-2018 protocol are reproduced. Then the simulated results are compared to experimental data available in the literature for both PET scanners. The assessment of the models includes different studies of sensitivity, count rate performances, spatial resolution and image quality. These tests are intended to evaluate the image quality of PET devices. RESULTS: In the spatial resolution test, relative errors lower than 8% are obtained between the experiments and GATE models. The sensitivity is 17.2 cps/kBq (Vision) and 175.9 cps/kBq (Quadra), representing relative differences with the experiment of 6% and 0.3%, respectively. Deviations from peak NECR are less than 9%. In the Image Quality test, the contrast recovery coefficient for hot spheres, with 8 iterations and 5 subsets, ranges between 57-83% for Vision and 54-86% for Quadra. These values represent a maximum deviation between the simulations and the experiments of 10% for the Quadra scanner. In the case of the Vision scanner, the highest difference is observed for the 10 mm sphere (∼38%) due to the higher contrast recovery of the experiment caused by the Gibbs artifact from the use of PSF reconstruction. CONCLUSIONS: The results of the simulations have provided evidence of a good agreement between the experimental data and the results obtained with GATE. Thus, this work supports the capability of this MC toolkit to accurately simulate the models of the Vision and Quadra scanners. This study has laid the basis for further research in this field and has identified several areas that could be explored.

Toolkit implementation to exchange phase-space files between IAEA and MCNP6 monte Carlo code format.

PURPOSE: Some Monte Carlo simulation codes can read and write phase space files in IAEA format, which are used to characterize accelerators, brachytherapy seeds and other radiation sources. Moreover, as the format has been standardized, these files can be used with different simulation codes. However, MCNP6 has not still implemented this capability, which complicate the studies involving this kind of sources and the reproducibility of results among independent researchers. Therefore, the purpose of this work is to develop a tool to perform conversions between IAEA and MCNP6 phase space files formats, to be used for Monte Carlo simulations. MATERIALS AND METHODS: This paper presents a toolkit written in C language that uses the IAEA libraries to convert phase space files between IAEA and MCNP6 format and vice versa. To test the functionality of the provided tool, a set of verification tests has been carried out. In addition, a linear accelerator treatment has been simulated with the PENELOPE library using the PenEasy framework, which is already capable to read and write IAEA phase space files, and MCNP6 using the developed tools. RESULTS: Both codes show compatible depth dose curves and profiles in a water tank, demonstrating that the conversion tools work properly. Moreover, the phase space file formats have been converted from IAEA to MCNP6 format and back again to IAEA format, reproducing the very same results. CONCLUSION: The toolkit developed in this work offers MCNP6 scientific community an external and validated program able to convert phase space files in IAEA format to MCNP6 internal format and use them for Monte Carlo applications. Furthermore, the developed tools provide also the reverse conversion, which allow sharing MCNP6 results with users of other Monte Carlo codes. This capability in the MCNP6 ecosystem provides to the scientific community the ability not only to share radiation sources, but also to facilitate the reproducibility among different groups using different codes via the standard format specified by the IAEA.

High-performance reconstruction of CT medical images by using out-of-core methods in GPU.

BACKGROUND AND OBJECTIVE: Since Computed Tomography (CT) is one of the most widely used medical imaging tests, it is essential to work on methods that reduce the radiation the patient is exposed to. Although there are several possible approaches to achieve this, we focus on reducing the exposure time through sparse sampling. With this approach, efficient algebraic methods are needed to be able to generate the images in real time, and since their computational cost is high, using high-performance computing is essential. METHODS: In this paper we present a GPU (Graphics Processing Unit) software for solving the CT image reconstruction problem using the QR factorization performed with out-of-core (OOC) techniques. This implementation is optimized to reduce the data transfer times between disk, CPU, and GPU, as well as to overlap input/output operations and computations. RESULTS: The experimental study shows that a block cache stored on main page-locked memory is more efficient than using a cache on GPU memory or mirroring it in both GPU and CPU memory. Compared to a CPU version, this implementation is up to 6.5 times faster, providing an improved image quality when compared to other reconstruction methods. CONCLUSIONS: The software developed is an optimized version of the QR factorization for GPU that allows the algebraic reconstruction of CT images with high quality and resolution, with a performance that can be compared with state-of-the-art methods used in clinical practice. This approach allows reducing the exposure time of the patient and thus the radiation dose.

Variability of coil inductance measurements inside an interleaving structure.

The present article is a continuation of our previous works on the anomalies in the decay rates and the capacitance measurements inside a modified Faraday cage. Here we present the anomalous variations in the measurements of inductance when a coil is placed inside an interleaving structure of metal and organic material. The fluctuation in the inductance values was found to be in the range - 0.007 to 0.018 mH. Additionally, it was observed that the temperature coefficient which was 0.0062 mH/°C initially jumped to two distinct levels, 0.0095 mH/°C and 0.0145 mH/°C, respectively. A multiple factor analysis of our results revealed a very strong correlation (R2 = 95.2%) between the inductance and the combination of the temperature and the relative humidity both measured inside the cage, next to the inductor.

Evaluation of image filters for their integration with LSQR computerized tomography reconstruction method.

In CT (computerized tomography) imaging reconstruction, the acquired sinograms are usually noisy, so artifacts will appear on the resulting images. Thus, it is necessary to find the adequate filters to combine with reconstruction methods that eliminate the greater amount of noise possible without altering in excess the information that the image contains. The present work is focused on the evaluation of several filtering techniques applied in the elimination of artifacts present in CT sinograms. In particular, we analyze the elimination of Gaussian and Speckle noise. The chosen filtering techniques have been studied using four functions designed to measure the quality of the filtered image and compare it with a reference image. In this way, we determine the ideal parameters to carry out the filtering process on the sinograms, prior to the process of reconstruction of the images. Moreover, we study their application on reconstructed noisy images when using noisy sinograms and finally we select the best filter to combine with an iterative reconstruction method in order to test if it improves the quality of the images. With this, we can determine the feasibility of using the selected filtering method for our CT reconstructions with projections reduction, concluding that the bilateral filter is the filter that behaves best with our images. We will test it when combined with our iterative reconstruction method, which consists on the Least Squares QR method in combination with a regularization technique and an acceleration step, showing how integrating this filter with our reconstruction method improves the quality of the CT images.

Computed tomography medical image reconstruction on affordable equipment by using Out-Of-Core techniques.

BACKGROUND AND OBJECTIVE: As Computed Tomography scans are an essential medical test, many techniques have been proposed to reconstruct high-quality images using a smaller amount of radiation. One approach is to employ algebraic factorization methods to reconstruct the images, using fewer views than the traditional analytical methods. However, their main drawback is the high computational cost and hence the time needed to obtain the images, which is critical in the daily clinical practice. For this reason, faster methods for solving this problem are required. METHODS: In this paper, we propose a new reconstruction method based on the QR factorization that is very efficient on affordable equipment (standard multicore processors and standard Solid-State Drives) by using Out-Of-Core techniques. RESULTS: Combining both affordable hardware and the new software proposed in our work, the images can be reconstructed very quickly and with high quality. We analyze the reconstructions using real Computed Tomography images selected from a dataset, comparing the QR method to the LSQR and FBP. We measure the quality of the images using the metrics Peak Signal-To-Noise Ratio and Structural Similarity Index, obtaining very high values. We also compare the efficiency of using spinning disks versus Solid-State Drives, showing how the latter performs the Input/Output operations in a significantly lower amount of time. CONCLUSIONS: The results indicate that our proposed me thod and software are valid to efficiently solve large-scale systems and can be applied to the Computed Tomography reconstruction problem to obtain high-quality images.

Analysis of the Possible Persistent Genotoxic Damage in Workers Linked to the Ardystil Syndrome.

BACKGROUND: A combination of several factors including a change in the paint application system; a lack of proper hygiene; and inadequate safety measures caused a severe health impact in the workers of some textile painting factories. This outbreak, mainly characterized by respiratory disorders, caused the death of six people and it has been classified as Ardystil syndrome. MATERIALS AND METHODS: Fifty-two workers involved in the outbreak and 48 healthy subjects not known to have exposed to the potentially mutagenic agents participated in the study. The program evaluated possible genotoxic damage through the sister chromatid exchange (SCE) cytogenetic biomarker assay. We determined the frequency of SCE, high-frequency cells (HFCs), and a ratio, which can be considered as a new parameter, allowing for the study of the SCE distribution pattern among the chromosomes. RESULTS: There was no statistically significant difference in the SCE frequency and in the mean number of HFCs between the control and the Ardystil-affected groups. However, smoking increased the incidence of all parameters studied in both the case and control groups. CONCLUSIONS: This study shows that workers involved in the Ardystil syndrome did not suffer genotoxic damage as measured by SCE and HFCs when compared with the control group.

System Matrix Analysis for Computed Tomography Imaging.

In practical applications of computed tomography imaging (CT), it is often the case that the set of projection data is incomplete owing to the physical conditions of the data acquisition process. On the other hand, the high radiation dose imposed on patients is also undesired. These issues demand that high quality CT images can be reconstructed from limited projection data. For this reason, iterative methods of image reconstruction have become a topic of increased research interest. Several algorithms have been proposed for few-view CT. We consider that the accurate solution of the reconstruction problem also depends on the system matrix that simulates the scanning process. In this work, we analyze the application of the Siddon method to generate elements of the matrix and we present results based on real projection data.

Sister chromatid exchange, (SCE), High-Frequency Cells (HFCs) and SCE distribution patterns in peripheral blood lymphocytes of Spanish adult smokers compared to non-smokers.

According to the International Agency for Research on Cancer, smoking tobacco is a major cause of cancer in humans. It causes about half of all male cancer deaths and an ever increasing number of cancer deaths in females. The aim of this study was to establish whether cigarette smoking increases sister chromatid exchanges (SCEs) in peripheral blood lymphocytes in two Spanish population groups; light and heavy smokers. The mean number of High-Frequency Cells (HFCs) was determined and, the SCE distribution pattern among the chromosomes was analysed represented by a ratio described below. A local sample of 101 adult smokers (n=48) and non-smokers (n=53), aged from 18 to 49 years, was studied using SCE levels in peripheral lymphocytes. Heavy smoking (≥ 10 cigarettes per day) increased significantly the SCE frequency and the HFC parameters. Neither age nor sex significantly influenced the frequencies in the groups studied.

Unfolding X-ray spectra using a flat panel detector.

It is difficult to measure the energy spectrum of X-ray tubes due to the pile up effect produced by the high fluence of photons. Using attenuating materials, appropriate detector devices and the Monte Carlo method, primary X-ray spectrum of these devices can be estimated. In this work, a flat panel detector with a PMMA wedge has been used to obtain a dose curve corresponding to certain working conditions of a radiodiagnostic X-ray tube. The relation between the dose curve recorded by the flat panel and the primary X-ray spectrum is defined by a response function. Normally this function can be approximated by a matrix, which can be obtained by means of the Monte Carlo method. Knowing the measured dose curve and the response matrix, the primary X-ray spectrum can be unfolded. However, there are some problems that strongly affect the applicability of this method: i.e. technical features of the flat panel and inherent characteristics of the involved radiation physics (ill-posed problem). Both aspects are analyzed in this work, concluding that the proposed method can be applied with an acceptable accuracy for spectra without characteristic lines, for instance, tungsten anode in the 50-70 kVp range.

Iterative reconstruction of CT images on GPUs.

Although widely used in nuclear medicine (gamma-camera, single photon emission computed tomography (SPECT), positron emission tomography (PET)), iterative reconstruction has not yet penetrated in CT. The main reason for this is that data sets in CT are much larger than in nuclear medicine and iterative reconstruction then becomes computationally very intensive. Graphical Processing Units (GPUs) provide the possibility to reduce effectively the high computational cost of their implementation. It is the goal of this work to develop a GPU-based algorithm to reconstruct high quality images from under sampled and noisy projection data.

Fast parallel algorithm for CT image reconstruction.

In X-ray computed tomography (CT) the X rays are used to obtain the projection data needed to generate an image of the inside of an object. The image can be generated with different techniques. Iterative methods are more suitable for the reconstruction of images with high contrast and precision in noisy conditions and from a small number of projections. Their use may be important in portable scanners for their functionality in emergency situations. However, in practice, these methods are not widely used due to the high computational cost of their implementation. In this work we analyze iterative parallel image reconstruction with the Portable Extensive Toolkit for Scientific computation (PETSc).

Medical image restoration with different types of noise.

The images obtained by X-Ray or computed tomography (CT) in adverse conditions may be contaminated with noise that can affect the detection of diseases. A large number of image processing techniques (filters) have been proposed to remove noise. These techniques depend on the type of noise present in the image. In this work, we propose a method designed to reduce the Gaussian, the impulsive and speckle noise and combined noise. This filter, called PGNDF, combines a non-linear diffusive filter with a peer group with fuzzy metric technique. The proposed filter is able to reduce efficiently the image noise without any information about what kind of noise might be present. To evaluate the filter performance, we use mammographic images from the mini- MIAS database which we have damaged by adding Gaussian, impulsive and speckle noises of different magnitudes. As a result, the proposed method obtains a good performance in most of the different types of noise.

Estimated radiation dose reduction using non-linear diffusion method in computed radiography.

In this paper we use a non-linear diffusion method to filter the inherent noise in a Computed Radiography (CR) for reducing the dose absorbed by the patients especially children in pediatric applications, related with the exposure mAs. The method is implemented in order to create a lower CR dose based on the selection of lower X-ray exposure and with a reduction of the noise using a non-linear diffusion method. The impact of several milliAmpere-seconds (mAs) setting on image quality has been studied using the RANDO phantom. The obtained results show good agreements between the filtered images and real images in terms of noise variance measurements. The new CR images allow medical researchers to analyze how a low dose affects the patient diagnosis.

Radiation effects in interventional radiology using biological and physical dosimetry methods: a case-control study.

Interventional radiologists and staff members are frequently exposed to protracted and fractionated low doses of ionizing radiation, which extend during all their professional activities. These exposures can derive, due to the irradiation of skin tissues and peripheral blood, in deterministic effects (radiodermitis, aged skin, hands depilation) or stochastic ones (skin and non-solid cancers incidence). Epidemiological studies of population exposed to ionizing radiation provide information of radio-induced effects. The radiation risk or radiological detriment has been estimated from a group of six exposed interventionist radiologists of the Hospital La Fe (Valencia, Spain). Dosimetry has been periodically registered from TLDs and wrist dosimeters (physical methods) and estimated through translocations in lymphocytes of peripheral blood (biological methods), by extrapolating the yield of translocations to their respective dose-effect curves. The probability of non-melanoma skin cancer and leukaemia (acute myelogenous, acute lymphocytic and chronic myelogenous leukaemia) incidence has been estimated through the software RADRISK. This software is based on a transport model from epidemiological studies of population exposed to external low-LET ionizing radiation [1]. Other non-solid carcinomas have not been considered due to their low statistical power, such as myeloid and non-Hodgkin lymphomas. The discrepancies observed between the physically recorded doses and biological estimated doses could indicate that exposed workers did not always wear their dosimeters or these dosimeters were not always exposed to the radiation field.