Electrical Capacitance Volume Tomography (ECVT) for industrial and medical applications-An Overview

Tomography is a non-invasive, non-intrusive imaging technique allowing the visualization of phase dynamics in industrial and biological processes. This article reviews progress in Electrical Capacitance Volume Tomography (ECVT). ECVT is a direct 3D visualizing technique, unlike three-dimensional imaging, which is based on stacking 2D images to obtain an interpolated 3D image. ECVT has recently matured for real time, non-invasive 3-D monitoring of processes involving materials with strong contrast in dielectric permittivity. In this article, ECVT sensor design, optimization and performance of various sensors seen in literature are summarized. Qualitative Analysis of ECVT image reconstruction techniques has also been presented

Optimization strategies for respiratory motion management in stereotactic body radiation therapy

Various challenges arise during the treatment of lung tumors with stereotactic body radiation therapy (SBRT), which is a form of hypofractionated high precision conformal radiation therapy delivered to small targets. The dose is applied in only a few fractions and respiratory organ and tumor motion is a source of uncertainty additional to interfractional set-up errors. Respiratory organ and tumor motion is highly patient-specific and it affects the whole radiotherapy treatment chain. In this thesis, motion management techniques for SBRT are evaluated and improved in a clinical setting. A clinical need for improvement has been present at the LMU university hospital for each issue addressed in this thesis: Initially, the usage of respiratory correlated computed tomography (4DCT), which is vital for SBRT treatment, was seen as impractical and prone to uncertainties in the data reconstruction in its current form. Therefore, the 4DCT reconstruction workflow has been improved to minimize these potential error sources. Secondly, treatment planning for tumors affected by respiratory motion was evaluated and subsequently improved. Finally, the treatment technique of respiratory gating was implemented at the clinic, which led to the need of evaluating the respiratory gating characteristics of the novel system configuration. At first, the 4DCT reconstruction workflow used in clinical practice was investigated, as in the presence of respiratory motion the knowledge of tumor position over time is essential in SBRT treatments. Using 4DCT, the full motion range of the individual tumor can be determined. However, certain 4DCT reconstruction methods can under- or overestimate tumor motion due to limitations in the data acquisition scheme and due to the incorrect sorting of certain X-ray computed tomography (CT) image slices into different respiratory phases. As the regular clinical workflow of cycle-based sorting (CBS) without maximum inspiration detection (and therefore no clear starting point for the individual breathing cycles) seemed to be affected by these potential errors, the usage of CBS with correct maximum detection and another sorting algorithm of the respiration states, so-called local amplitude-based sorting (LAS), both have been implemented for a reduction of image artifacts and improved 4DCT quality. The three phase binning algorithms have been investigated in a phantom study (using 10 different breathing waveforms) and in a patient study (with 10 different patients). The mis-representation of the tumor volume was reduced in both implemented sorting algorithms compared to the previously used CBS approach (without correct maximum detection) in the phantom and the patient study. The clinical recommendation was the use of CBS with improved maximum detection, as too many manual interventions would be needed for the LAS workflow. Secondly, a combination of the actual patient breathing trace during treatment, the log files generated by the linear accelerator (LINAC), and Monte Carlo (MC) four-dimensional (4D) dose calculations for each individual fraction was implemented as a 4D dose evaluation tool. This workflow was tested in a clinical environment for SBRT treatment planning on multiple CT datasets featuring: a native free-breathing 3DCT, an average intensity projection (AIP) as well as a maximum intensity projection (MIP), both obtained from the patient's 4DCT, and density overrides (DOs) in a 3DCT. This study has been carried out for 5 SBRT patients for three-dimensional conformal radiation therapy (3D-CRT) and volumetric modulated arc therapy (VMAT) treatment plans. The dose has been recalculated on each 4DCT breathing phase according the the patient's breathing waveform and accumulated to the gross tumor volume (GTV) at the end-of-exhale (EOE) breathing phase using deformable image registration. Even though the least differences in planned and recalculated dose were found for AIP and MIP treatment planning, the results indicate a strong dependency on individual tumor motion due to the variability of breathing motion in general, and on tumor size. The combination of the patient's individual breathing trace during each SBRT fraction with 4D MC dose calculation based on the LINAC log file information leads to a good approximation of actual dose delivery. Finally, in order to ensure precise and accurate treatment for respiratory gating techniques, the technical characteristics of the LINAC in combination with a breathing motion monitoring system as s surrogate for tumor motion have to be identified. The dose delivery accuracy and the latency of a surface imaging system in connection with a modern medical LINAC were investigated using a dynamic breathing motion phantom. The dosimetric evaluation has been carried out using a static 2D-diode array. The measurement of the dose difference between gated and ungated radiation delivery was found to be below 1% (for clinical relevant gating levels of about 30%). The beam-on latency, or time delay, determined using radiographic films was found to be up to 851 ms±100 ms. With these known parameters, an adjustment of the pre-selected gating level or the internal target volume (ITV) margins could be made. With the highly patient-specific character of respiratory motion, lung SBRT faces many additional challenges besides the specific issues addressed in this thesis. However, the findings of this thesis have improved clinical workflows at the Department of Radiation Oncology of the LMU University hospital. In a future perspective, a workflow using evaluation of the actual 4D dose in combination with accurate 4DCT image acquisition and specialized treatment delivery (such as respiratory gating) has the potential for a safe further reduction of treatment margins and increased sparing of organs-at-risk (OARs) in SBRT without compromising tumor dose targeting accuracy

Adaption in Dynamic Contrast-Enhanced MRI

In breast DCE MRI, dynamic data are acquired to assess signal changes caused by contrast agent injection in order to classify lesions. Two approaches are used for data analysis. One is to fit a pharmacokinetic model, such as the Tofts model, to the data, providing physiological information. For accurate model fitting, fast sampling is needed. Another approach is to evaluate architectural features of the contrast agent distribution, for which high spatial resolution is indispensable. However, high temporal and spatial resolution are opposing aims and a compromise has to be found. A new area of research are adaptive schemes, which sample data at combined resolutions to yield both, accurate model fitting and high spatial resolution morphological information. In this work, adaptive sampling schemes were investigated with the objective to optimize fitting accuracy, whilst providing high spatial resolution images. First, optimal sampling design was applied to the Tofts model. By that it could be determined, based on an assumed parameter distribution, that time points during the onset and the initial fast kinetics, lasting for approximately two minutes, are most relevant for fitting. During this interval, fast sampling is required. Later time points during wash-out can be exploited for high spatial resolution images. To achieve fast sampling during the initial kinetics, data acquisition has to be accelerated. A common way to increase imaging speed is to use view-sharing methods, which omit certain k-space data and interpolate the missing data from neighboring time frames. In this work, based on phantom simulations, the influence of different view-sharing techniques during the initial kinetics on fitting accuracy was investigated. It was found that all view-sharing methods imposed characteristic systematic errors on the fitting results of Ktrans. The best fitting performance was achieved by the scheme ``modTRICKS'', which is a combination of the often used schemes keyhole and TRICKS. It is not known prior to imaging, when the contrast agent will arrive in the lesion or when the wash-out begins. Currently used adaptive sequences change resolutions a fixed time points. However, missing time points on the upslope may cause fitting errors and missing the signal peak may lead to a loss in morphological information. This problem was addressed with a new automatic resolution adaption (AURA) sequence. Acquired dynamic data were analyzed in real-time to find the onset and the beginning of the wash-out and consequently the temporal resolution was automatically adapted. Using a perfusion phantom it could be shown that AURA provides both, high fitting accuracy and reliably high spatial resolution images close to the signal peak. As alternative approach to AURA, a sequence which allows for retrospective resolution adaption, was assesses. Advantages are that adaption does not have to be a global process, and can be tailored regionally to local sampling requirements. This can be useful for heterogeneous lesions. For that, a 3D golden angle radial sequence was used, which acquires contrast information with each line and the golden angles allow arbitrary resolutions at arbitrary time points. Using a perfusion phantom, it could be shown that retrospective resolution adaption yields high fitting accuracy and relatively high spatial resolution maps

Adaption in Dynamic Contrast-Enhanced MRI

In breast DCE MRI, dynamic data are acquired to assess signal changes caused by contrast agent injection in order to classify lesions. Two approaches are used for data analysis. One is to fit a pharmacokinetic model, such as the Tofts model, to the data, providing physiological information. For accurate model fitting, fast sampling is needed. Another approach is to evaluate architectural features of the contrast agent distribution, for which high spatial resolution is indispensable. However, high temporal and spatial resolution are opposing aims and a compromise has to be found. A new area of research are adaptive schemes, which sample data at combined resolutions to yield both, accurate model fitting and high spatial resolution morphological information. In this work, adaptive sampling schemes were investigated with the objective to optimize fitting accuracy, whilst providing high spatial resolution images. First, optimal sampling design was applied to the Tofts model. By that it could be determined, based on an assumed parameter distribution, that time points during the onset and the initial fast kinetics, lasting for approximately two minutes, are most relevant for fitting. During this interval, fast sampling is required. Later time points during wash-out can be exploited for high spatial resolution images. To achieve fast sampling during the initial kinetics, data acquisition has to be accelerated. A common way to increase imaging speed is to use view-sharing methods, which omit certain k-space data and interpolate the missing data from neighboring time frames. In this work, based on phantom simulations, the influence of different view-sharing techniques during the initial kinetics on fitting accuracy was investigated. It was found that all view-sharing methods imposed characteristic systematic errors on the fitting results of Ktrans. The best fitting performance was achieved by the scheme ``modTRICKS'', which is a combination of the often used schemes keyhole and TRICKS. It is not known prior to imaging, when the contrast agent will arrive in the lesion or when the wash-out begins. Currently used adaptive sequences change resolutions a fixed time points. However, missing time points on the upslope may cause fitting errors and missing the signal peak may lead to a loss in morphological information. This problem was addressed with a new automatic resolution adaption (AURA) sequence. Acquired dynamic data were analyzed in real-time to find the onset and the beginning of the wash-out and consequently the temporal resolution was automatically adapted. Using a perfusion phantom it could be shown that AURA provides both, high fitting accuracy and reliably high spatial resolution images close to the signal peak. As alternative approach to AURA, a sequence which allows for retrospective resolution adaption, was assesses. Advantages are that adaption does not have to be a global process, and can be tailored regionally to local sampling requirements. This can be useful for heterogeneous lesions. For that, a 3D golden angle radial sequence was used, which acquires contrast information with each line and the golden angles allow arbitrary resolutions at arbitrary time points. Using a perfusion phantom, it could be shown that retrospective resolution adaption yields high fitting accuracy and relatively high spatial resolution maps

Histopathological image analysis : a review

Over the past decade, dramatic increases in computational power and improvement in image analysis algorithms have allowed the development of powerful computer-assisted analytical approaches to radiological data. With the recent advent of whole slide digital scanners, tissue histopathology slides can now be digitized and stored in digital image form. Consequently, digitized tissue histopathology has now become amenable to the application of computerized image analysis and machine learning techniques. Analogous to the role of computer-assisted diagnosis (CAD) algorithms in medical imaging to complement the opinion of a radiologist, CAD algorithms have begun to be developed for disease detection, diagnosis, and prognosis prediction to complement the opinion of the pathologist. In this paper, we review the recent state of the art CAD technology for digitized histopathology. This paper also briefly describes the development and application of novel image analysis technology for a few specific histopathology related problems being pursued in the United States and Europe

Respiratory organ motion in interventional MRI : tracking, guiding and modeling

Respiratory organ motion is one of the major challenges in interventional MRI, particularly in interventions with therapeutic ultrasound in the abdominal region. High-intensity focused ultrasound found an application in interventional MRI for noninvasive treatments of different abnormalities. In order to guide surgical and treatment interventions, organ motion imaging and modeling is commonly required before a treatment start. Accurate tracking of organ motion during various interventional MRI procedures is prerequisite for a successful outcome and safe therapy. In this thesis, an attempt has been made to develop approaches using focused ultrasound which could be used in future clinically for the treatment of abdominal organs, such as the liver and the kidney. Two distinct methods have been presented with its ex vivo and in vivo treatment results. In the first method, an MR-based pencil-beam navigator has been used to track organ motion and provide the motion information for acoustic focal point steering, while in the second approach a hybrid imaging using both ultrasound and magnetic resonance imaging was combined for advanced guiding capabilities. Organ motion modeling and four-dimensional imaging of organ motion is increasingly required before the surgical interventions. However, due to the current safety limitations and hardware restrictions, the MR acquisition of a time-resolved sequence of volumetric images is not possible with high temporal and spatial resolution. A novel multislice acquisition scheme that is based on a two-dimensional navigator, instead of a commonly used pencil-beam navigator, was devised to acquire the data slices and the corresponding navigator simultaneously using a CAIPIRINHA parallel imaging method. The acquisition duration for four-dimensional dataset sampling is reduced compared to the existing approaches, while the image contrast and quality are improved as well. Tracking respiratory organ motion is required in interventional procedures and during MR imaging of moving organs. An MR-based navigator is commonly used, however, it is usually associated with image artifacts, such as signal voids. Spectrally selective navigators can come in handy in cases where the imaging organ is surrounding with an adipose tissue, because it can provide an indirect measure of organ motion. A novel spectrally selective navigator based on a crossed-pair navigator has been developed. Experiments show the advantages of the application of this novel navigator for the volumetric imaging of the liver in vivo, where this navigator was used to gate the gradient-recalled echo sequence