Diabetes therapies in renal impairment

Depending on age, duration of diabetes and glycaemic control, 20-40% of patients with type 2 diabetes will incur a moderate or severe deterioration of renal function. This will impact the choice of blood glucose-lowering therapy and require more frequent monitoring of both renal function and glycaemic control. Moderate renal impairment (glomerular filtration rate 30-<60 ml/min) requires consideration of dose reduction or treatment cessation for metformin, glucagon-like peptide-1 receptor agonists, some sulphonylureas and some dipeptidyl peptidase-4 inhibitors. At lower rates of glomerular filtration down to about 15 ml/min it may be appropriate to use a meglitinide, pioglitazone or certain sulphonylureas with careful consideration of dose and co-morbidities. Dipeptidyl peptidase-4 inhibitors can be used at reduced dose in patients with very low rates of glomerular filtration, and linagliptin can be used without dose reduction, and has been used in patients on dialysis. Insulin can be used at any stage of renal impairment, but the regimen and the dose must be suitably adjusted and accompanied by adequate monitoring. © The Author(s), 2012.

Positron emission tomography (PET) tumor segmentation and quantification: Development of new algorithms

Tumor functional volume (FV) and its mean activity concentration (mAC) are the quantities derived from positron emission tomography (PET). These quantities are used for estimating radiation dose for a therapy, evaluating the progression of a disease and also use it as a prognostic indicator for predicting outcome. PET images have low resolution, high noise and affected by partial volume effect (PVE). Manually segmenting each tumor is very cumbersome and very hard to reproduce. To solve the above problem I developed an algorithm, called iterative deconvolution thresholding segmentation (IDTS) algorithm; the algorithm segment the tumor, measures the FV, correct for the PVE and calculates mAC. The algorithm corrects for the PVE without the need to estimate camera's point spread function (PSF); also does not require optimizing for a specific camera. My algorithm was tested in physical phantom studies, where hollow spheres (0.5-16 ml) were used to represent tumors with a homogeneous activity distribution. It was also tested on irregular shaped tumors with a heterogeneous activity profile which were acquired using physical and simulated phantom. The physical phantom studies were performed with different signal to background ratios (SBR) and with different acquisition times (1-5 min). The algorithm was applied on ten clinical data where the results were compared with manual segmentation and fixed percentage thresholding method called T50 and T60 in which 50% and 60% of the maximum intensity respectively is used as threshold. The average error in FV and mAC calculation was 30% and -35% for 0.5 ml tumor. The average error FV and mAC calculation were ~5% for 16 ml tumor. The overall FV error was ∼10% for heterogeneous tumors in physical and simulated phantom data. The FV and mAC error for clinical image compared to manual segmentation was around -17% and 15% respectively. In summary my algorithm has potential to be applied on data acquired from different cameras as its not dependent on knowing the camera's PSF. The algorithm can also improve dose estimation and treatment planning.^

Fontes de matéria orgânica para a formulação de fertilizantes organominerais peletizados no desenvolvimento da cultura do sorgo

Organo-mineral fertilizers have been used to both meet plants’ nutritional needs and reduce producers’ reliance on mineral fertilizers. This practice improves both the use of nutrients by plants and the soil structure due to the organic matter in these fertilizers. This study aimed to determine the effect of organic matter sources in the composition of organomineral fertilizers and compare it to the effect of traditional mineral fertilizers when it comes to the initial development of sorghum. Research was carried out in a greenhouse at the Federal University of Uberlandia, in Uberlandia, Minas Gerais, Brazil. Sorghum seeds of grain-bearing simple hybrid 1G100 were used in the seeding process. The experiment followed a randomized complete block design in a 4 x 3 + 2 factorial arrangement. Factors included four levels (50, 75, 100 and 125% of 450 kg ha-1, which is the recommended dose for sorghum crops), three organic matter sources in the composition of the organomineral fertilizers (sewage sludge, filter cake, and peat), a control (100% mineral fertilizer), and an untreated check (no fertilizers). Each experimental plot consisted of four plants divided into two pots. Oxisol was used in all pots. Analyses were performed at 30 and 60 days after seeding (DAS) and targeted: plant height, stem diameter, chlorophyll A, chlorophyll B, and leaf area. After this period, plants were removed from the soil, and had their aerial parts isolated to be dried in an air-forced oven before measurement of their dry mass. Means of the organomineral fertilizers outperformed those of both control and untreated check plots in almost all variables at 30 DAS. The only exception was variable stem diameter, in which organomineral fertilizers outperformed untreated check plots only. Sorghum fertilized with organomineral fertilizers also showed positive results in the variables analyzed at 60 DAS: even with dose reduction, their means were similar to those found in control plots. Organomineral fertilizers had higher means in some variables, such as diameter and dry mass of the aerial part, than both control and untreated check plots. In the conditions set in this study and considering the variables herein reported, organomineral fertilizers can substitute mineral fertilizers in the initial development of sorghum, even with some dose reductions.

Radiotherapy Treatment Assessment using DCE-MRI

Abstract

The goal of modern radiotherapy is to precisely deliver a prescribed radiation dose to delineated target volumes that contain a significant amount of tumor cells while sparing the surrounding healthy tissues/organs. Precise delineation of treatment and avoidance volumes is the key for the precision radiation therapy. In recent years, considerable clinical and research efforts have been devoted to integrate MRI into radiotherapy workflow motivated by the superior soft tissue contrast and functional imaging possibility. Dynamic contrast-enhanced MRI (DCE-MRI) is a noninvasive technique that measures properties of tissue microvasculature. Its sensitivity to radiation-induced vascular pharmacokinetic (PK) changes has been preliminary demonstrated. In spite of its great potential, two major challenges have limited DCE-MRI’s clinical application in radiotherapy assessment: the technical limitations of accurate DCE-MRI imaging implementation and the need of novel DCE-MRI data analysis methods for richer functional heterogeneity information.

This study aims at improving current DCE-MRI techniques and developing new DCE-MRI analysis methods for particular radiotherapy assessment. Thus, the study is naturally divided into two parts. The first part focuses on DCE-MRI temporal resolution as one of the key DCE-MRI technical factors, and some improvements regarding DCE-MRI temporal resolution are proposed; the second part explores the potential value of image heterogeneity analysis and multiple PK model combination for therapeutic response assessment, and several novel DCE-MRI data analysis methods are developed.

I. Improvement of DCE-MRI temporal resolution. First, the feasibility of improving DCE-MRI temporal resolution via image undersampling was studied. Specifically, a novel MR image iterative reconstruction algorithm was studied for DCE-MRI reconstruction. This algorithm was built on the recently developed compress sensing (CS) theory. By utilizing a limited k-space acquisition with shorter imaging time, images can be reconstructed in an iterative fashion under the regularization of a newly proposed total generalized variation (TGV) penalty term. In the retrospective study of brain radiosurgery patient DCE-MRI scans under IRB-approval, the clinically obtained image data was selected as reference data, and the simulated accelerated k-space acquisition was generated via undersampling the reference image full k-space with designed sampling grids. Two undersampling strategies were proposed: 1) a radial multi-ray grid with a special angular distribution was adopted to sample each slice of the full k-space; 2) a Cartesian random sampling grid series with spatiotemporal constraints from adjacent frames was adopted to sample the dynamic k-space series at a slice location. Two sets of PK parameters’ maps were generated from the undersampled data and from the fully-sampled data, respectively. Multiple quantitative measurements and statistical studies were performed to evaluate the accuracy of PK maps generated from the undersampled data in reference to the PK maps generated from the fully-sampled data. Results showed that at a simulated acceleration factor of four, PK maps could be faithfully calculated from the DCE images that were reconstructed using undersampled data, and no statistically significant differences were found between the regional PK mean values from undersampled and fully-sampled data sets. DCE-MRI acceleration using the investigated image reconstruction method has been suggested as feasible and promising.

Second, for high temporal resolution DCE-MRI, a new PK model fitting method was developed to solve PK parameters for better calculation accuracy and efficiency. This method is based on a derivative-based deformation of the commonly used Tofts PK model, which is presented as an integrative expression. This method also includes an advanced Kolmogorov-Zurbenko (KZ) filter to remove the potential noise effect in data and solve the PK parameter as a linear problem in matrix format. In the computer simulation study, PK parameters representing typical intracranial values were selected as references to simulated DCE-MRI data for different temporal resolution and different data noise level. Results showed that at both high temporal resolutions (<1s) and clinically feasible temporal resolution (~5s), this new method was able to calculate PK parameters more accurate than the current calculation methods at clinically relevant noise levels; at high temporal resolutions, the calculation efficiency of this new method was superior to current methods in an order of 102. In a retrospective of clinical brain DCE-MRI scans, the PK maps derived from the proposed method were comparable with the results from current methods. Based on these results, it can be concluded that this new method can be used for accurate and efficient PK model fitting for high temporal resolution DCE-MRI.

II. Development of DCE-MRI analysis methods for therapeutic response assessment. This part aims at methodology developments in two approaches. The first one is to develop model-free analysis method for DCE-MRI functional heterogeneity evaluation. This approach is inspired by the rationale that radiotherapy-induced functional change could be heterogeneous across the treatment area. The first effort was spent on a translational investigation of classic fractal dimension theory for DCE-MRI therapeutic response assessment. In a small-animal anti-angiogenesis drug therapy experiment, the randomly assigned treatment/control groups received multiple fraction treatments with one pre-treatment and multiple post-treatment high spatiotemporal DCE-MRI scans. In the post-treatment scan two weeks after the start, the investigated Rényi dimensions of the classic PK rate constant map demonstrated significant differences between the treatment and the control groups; when Rényi dimensions were adopted for treatment/control group classification, the achieved accuracy was higher than the accuracy from using conventional PK parameter statistics. Following this pilot work, two novel texture analysis methods were proposed. First, a new technique called Gray Level Local Power Matrix (GLLPM) was developed. It intends to solve the lack of temporal information and poor calculation efficiency of the commonly used Gray Level Co-Occurrence Matrix (GLCOM) techniques. In the same small animal experiment, the dynamic curves of Haralick texture features derived from the GLLPM had an overall better performance than the corresponding curves derived from current GLCOM techniques in treatment/control separation and classification. The second developed method is dynamic Fractal Signature Dissimilarity (FSD) analysis. Inspired by the classic fractal dimension theory, this method measures the dynamics of tumor heterogeneity during the contrast agent uptake in a quantitative fashion on DCE images. In the small animal experiment mentioned before, the selected parameters from dynamic FSD analysis showed significant differences between treatment/control groups as early as after 1 treatment fraction; in contrast, metrics from conventional PK analysis showed significant differences only after 3 treatment fractions. When using dynamic FSD parameters, the treatment/control group classification after 1st treatment fraction was improved than using conventional PK statistics. These results suggest the promising application of this novel method for capturing early therapeutic response.

The second approach of developing novel DCE-MRI methods is to combine PK information from multiple PK models. Currently, the classic Tofts model or its alternative version has been widely adopted for DCE-MRI analysis as a gold-standard approach for therapeutic response assessment. Previously, a shutter-speed (SS) model was proposed to incorporate transcytolemmal water exchange effect into contrast agent concentration quantification. In spite of richer biological assumption, its application in therapeutic response assessment is limited. It might be intriguing to combine the information from the SS model and from the classic Tofts model to explore potential new biological information for treatment assessment. The feasibility of this idea was investigated in the same small animal experiment. The SS model was compared against the Tofts model for therapeutic response assessment using PK parameter regional mean value comparison. Based on the modeled transcytolemmal water exchange rate, a biological subvolume was proposed and was automatically identified using histogram analysis. Within the biological subvolume, the PK rate constant derived from the SS model were proved to be superior to the one from Tofts model in treatment/control separation and classification. Furthermore, novel biomarkers were designed to integrate PK rate constants from these two models. When being evaluated in the biological subvolume, this biomarker was able to reflect significant treatment/control difference in both post-treatment evaluation. These results confirm the potential value of SS model as well as its combination with Tofts model for therapeutic response assessment.

In summary, this study addressed two problems of DCE-MRI application in radiotherapy assessment. In the first part, a method of accelerating DCE-MRI acquisition for better temporal resolution was investigated, and a novel PK model fitting algorithm was proposed for high temporal resolution DCE-MRI. In the second part, two model-free texture analysis methods and a multiple-model analysis method were developed for DCE-MRI therapeutic response assessment. The presented works could benefit the future DCE-MRI routine clinical application in radiotherapy assessment.

Open-source virtual bronchoscopy for image guided navigation

This thesis describes the development of an open-source system for virtual bronchoscopy used in combination with electromagnetic instrument tracking. The end application is virtual navigation of the lung for biopsy of early stage cancer nodules. The open-source platform 3D Slicer was used for creating freely available algorithms for virtual bronchscopy. Firstly, the development of an open-source semi-automatic algorithm for prediction of solitary pulmonary nodule malignancy is presented. This approach may help the physician decide whether to proceed with biopsy of the nodule. The user-selected nodule is segmented in order to extract radiological characteristics (i.e., size, location, edge smoothness, calcification presence, cavity wall thickness) which are combined with patient information to calculate likelihood of malignancy. The overall accuracy of the algorithm is shown to be high compared to independent experts' assessment of malignancy. The algorithm is also compared with two different predictors, and our approach is shown to provide the best overall prediction accuracy. The development of an airway segmentation algorithm which extracts the airway tree from surrounding structures on chest Computed Tomography (CT) images is then described. This represents the first fundamental step toward the creation of a virtual bronchoscopy system. Clinical and ex-vivo images are used to evaluate performance of the algorithm. Different CT scan parameters are investigated and parameters for successful airway segmentation are optimized. Slice thickness is the most affecting parameter, while variation of reconstruction kernel and radiation dose is shown to be less critical. Airway segmentation is used to create a 3D rendered model of the airway tree for virtual navigation. Finally, the first open-source virtual bronchoscopy system was combined with electromagnetic tracking of the bronchoscope for the development of a GPS-like system for navigating within the lungs. Tools for pre-procedural planning and for helping with navigation are provided. Registration between the lungs of the patient and the virtually reconstructed airway tree is achieved using a landmark-based approach. In an attempt to reduce difficulties with registration errors, we also implemented a landmark-free registration method based on a balanced airway survey. In-vitro and in-vivo testing showed good accuracy for this registration approach. The centreline of the 3D airway model is extracted and used to compensate for possible registration errors. Tools are provided to select a target for biopsy on the patient CT image, and pathways from the trachea towards the selected targets are automatically created. The pathways guide the physician during navigation, while distance to target information is updated in real-time and presented to the user. During navigation, video from the bronchoscope is streamed and presented to the physician next to the 3D rendered image. The electromagnetic tracking is implemented with 5 DOF sensing that does not provide roll rotation information. An intensity-based image registration approach is implemented to rotate the virtual image according to the bronchoscope's rotations. The virtual bronchoscopy system is shown to be easy to use and accurate in replicating the clinical setting, as demonstrated in the pre-clinical environment of a breathing lung method. Animal studies were performed to evaluate the overall system performance.

Evaluation of a ToF Camera for Remote Surveying of Underground Cavities Excavated by Jet Boring

Cigar Lake is a high-grade uranium deposit, located in northern Saskatchewan, Canada. In order to extract the uranium ore remotely, thus ensuring minimal radiation dose to workers and also to access the ore from stable ground, the Jet Boring System (JBS) was developed by Cameco Corporation. This system uses a high-powered water jet to remotely excavate cavities. Survey data is required to determine the final shape, volume, and location of the cavity for mine planning purposes and construction. This paper provides an overview of the challenges involved in remotely surveying a JBS-mined cavity and studies the potential use of a time-of-flight (ToF) camera for remote cavity surveying. It reports on data collected and analyzed from inside an experimental environment as well as on real data acquired on site from the Cigar Lake and Rabbit Lake mines.

Usability of clay mixed red mud in Hungarian building material production industry

The naturally occurring radionuclide (²²⁶Ra,²³²Th and⁴⁰K) content of building Materials (NORM) contributes to the total radiation dose experienced by humans. In this survey 27 clay and 68 red mud samples were surveyed with gamma spectrometry and screened according to European Basic Safety Standards (BSS) I-index. It was found that average I-index of clays was 0.6 (0.4–0.8) less than the I-index of 1, which makes them suitable for building material production. The average I-index of red mud 2.3 (1.3–3.0). The maximal mixing ratio of red mud was calculated, varied between 12 and 39 %, with 23 % average.

Conception et caractérisation d'un dosimètre à fibre scintillante pour des applications en imagerie diagnostique et interventionnelle

Cette thèse a pour sujet le développement d’un détecteur à fibre scintillante plastique pour la dosimétrie des faisceaux de photons de basses énergies. L’objectif principal du projet consiste à concevoir et caractériser cet instrument en vue de mesurer la dose de radiation reçue au cours des examens d’imagerie diagnostique et interventionnelle. La première section est consacrée à la conception de six différents systèmes et à l’évaluation de leur performance lorsqu’ils sont exposés à des rayonnements de hautes et basses énergies. Tous les systèmes évalués présentaient un écart type relatif (RSD) de moins de 5 % lorsqu’ils étaient exposés à des débits de dose de plus de 3 mGy/s. Cette approche systématique a permis de déterminer que le tube photomultiplicateur répondait le mieux aux conditions d’exposition propres à la radiologie. Ce dernier présentait une RSD de moins de 1 % lorsque le débit de dose était inférieur à 0.10 mGy/s. L’étude des résultats permis également de suggérer quelques recommandations dans le choix d’un système en fonction de l’application recherchée. La seconde partie concerne l’application de ce détecteur à la radiologie interventionnelle en procédant à des mesures de dose à la surface d’un fantôme anthropomorphique. Ainsi, plusieurs situations cliniques ont été reproduites afin d’observer la précision et la fiabilité du détecteur. Ce dernier conserva une RSD inférieure à 2 % lorsque le débit de dose était supérieur à 3 mGy/min et d’environ 10 % au débit le plus faible (0.25 mGy/min). Les mesures sur fantôme montrèrent une différence de moins de 4 % entre les mesures du détecteur et celles d’une chambre d’ionisation lors du déplacement de la table ou du bras de l’appareil de fluoroscopie. Par ailleurs, cette différence est demeurée sous les 2 % lors des mesures de débit de dose en profondeur. Le dernier sujet de cette thèse porta sur les fondements physiques de la scintillation dans les scintillateurs plastiques. Les différents facteurs influençant l’émission lumineuse ont été analysés afin d’identifier leur contribution respective. Ainsi, la réponse du détecteur augmente de près d’un facteur 4 entre un faisceau de 20 kVp et 250 kVp. De ce signal, la contribution de la fluorescence produite dans la fibre claire était inférieure à 0.5 % lorsque les fibres étaient exposées sur 10 cm par des faisceaux de 20 à 250 kVp. Le phénomène d’extinction de la fluorescence par ionisation a également été étudié. Ainsi, l’atténuation du signal variait en fonction de l’énergie du faisceau et atteignit environ 20 % pour un faisceau de 20 kVp. En conclusion, cette étude suggère que les détecteurs à fibres scintillantes peuvent mesurer avec précision la dose de radiation reçue en imagerie diagnostique et interventionnelle, mais une calibration rigoureuse s’avère essentielle.

Equipment quality control

Mammography equipment must be evaluated to ensure that images will be of acceptable diagnostic quality with lowest radiation dose. Quality Assurance (QA) aims to provide systematic and constant improvement through a feedback mechanism to address the technical, clinical and training aspects. Quality Control (QC), in relation to mammography equipment, comprises a series of tests to determine equipment performance characteristics. The introduction of digital technologies promoted changes in QC tests and protocols and there are some tests that are specific for each manufacturer. Within each country specifi c QC tests should be compliant with regulatory requirements and guidance. Ideally, one mammography practitioner should take overarching responsibility for QC within a service, with all practitioners having responsibility for actual QC testing. All QC results must be documented to facilitate troubleshooting, internal audit and external assessment. Generally speaking, the practitioner’s role includes performing, interpreting and recording the QC tests as well as reporting any out of action limits to their service lead. They must undertake additional continuous professional development to maintain their QC competencies. They are usually supported by technicians and medical physicists; in some countries the latter are mandatory. Technicians and/or medical physicists often perform many of the tests indicated within this chapter. It is important to recognise that this chapter is an attempt to encompass the main tests performed within European countries. Specific tests related to the service that you work within must be familiarised with and adhered too.

Mammography equipment

Mammography is one of the most technically demanding examinations in radiology, and it requires X-ray technology designed specifi cally for the task. The pathology to be imaged ranges from small (20–100 μm) high density microcalcifications to ill-defi ned low contrast masses. These must be imaged against a background of mixed densities. This makes demonstrating pathology challenging. Because of its use in asymptomatic screening, mammography must also employ as low a radiation dose as possible.

Le suivi des anti-épileptiques

All antiepileptic medications have potential side-effects. Some are rather specific like diplopia for carbamazepin or lamotrigin, whereas others are not, like fatigue or unsteadiness. Most are dose- related and can therefore be alleviated by dose reduction (e.g. somnolence or tremor) but a few are idiosyncratic (e.g. rash) and require cessation of the causative agent. Some can be detected and followed-up on a clinical basis but others necessitate specific examinations.