Strain and strain rate by two-dimensional speckle tracking echocardiography in a maned wolf

The measurement of cardiovascular features of wild animals is important, as is the measurement in pets, for the assessment of myocardial function and the early detection of cardiac abnormalities, which could progress to heart failure. Speckle tracking echocardiography (2D STE) is a new tool that has been used in veterinary medicine, which demonstrates several advantages, such as angle independence and the possibility to provide the early diagnosis of myocardial alterations. The aim of this study was to evaluate the left myocardial function in a maned wolf by 2D STE. Thus, the longitudinal, circumferential and radial strain and strain rate were obtained, as well as, the radial and longitudinal velocity and displacement values, from the right parasternal long axis four-chamber view, the left parasternal apical four chamber view and the parasternal short axis at the level of the papillary muscles. The results of the longitudinal variables were -13.52±7.88, -1.60±1.05, 4.34±2.52 and 3.86±3.04 for strain (%), strain rate (1/s), displacement (mm) and velocity (cm/s), respectively. In addition, the radial and circumferential Strain and Strain rate were 24.39±14.23, 1.86±0.95 and -13.69±6.53, -1.01±0.48, respectively. Thus, the present study provides the first data regarding the use of this tool in maned wolves, allowing a more complete quantification of myocardial function in this species.

Rocket tracking and decoupling eigenstructure control law

A control law was designed for a satellite launcher ( rocket ) vehicle using eigenstructure assignment in order that the vehicle tracks a reference attitude and also to decouple the yaw response from roll and pitch manoeuvres and to decouple the pitch response from roll and yaw manoeuvres. The design was based on a complete linear coupled model obtained from the complete vehicle non linear model by linearization at each trajectory point. After all, the design was assessed with the vehicle time varying non-linear model showing a good performance and robustness. The used design method is explained and a case study for the Brazilian satellite launcher ( VLS Rocket ) is reported.

Real-time Image-based RGB-D Camera Motion Tracking and Environment Mapping

In this work, image based estimation methods, also known as direct methods, are studied which avoid feature extraction and matching completely. Cost functions use raw pixels as measurements and the goal is to produce precise 3D pose and structure estimates. The cost functions presented minimize the sensor error, because measurements are not transformed or modified. In photometric camera pose estimation, 3D rotation and translation parameters are estimated by minimizing a sequence of image based cost functions, which are non-linear due to perspective projection and lens distortion. In image based structure refinement, on the other hand, 3D structure is refined using a number of additional views and an image based cost metric. Image based estimation methods are particularly useful in conditions where the Lambertian assumption holds, and the 3D points have constant color despite viewing angle. The goal is to improve image based estimation methods, and to produce computationally efficient methods which can be accomodated into real-time applications. The developed image-based 3D pose and structure estimation methods are finally demonstrated in practise in indoor 3D reconstruction use, and in a live augmented reality application.

Fluorescence-based imaging of cellular defect in lysinuric protein intolerance (LPI)

Fluoresenssiperusteiset kuvantamismenetelmät lysinurisen proteiini-intoleranssin (LPI) soluhäiriön tutkimuksessa Lysinurinen proteiini-intoleranssi on suomalaiseen tautiperintöön kuuluva autosomaalisesti peit¬tyvästi periytyvä sairaus, jonka aiheuttaa kationisten aminohappojen kuljetushäiriö munuaisten ja ohutsuolen epiteelisolujen basolateraalikalvolla. Aminohappojen kuljetushäiriö johtaa moniin oirei¬siin, kuten kasvuhäiriöön, osteoporoosiin, immuunijärjestelmän häiriöihin, oksenteluun ja runsaspro¬teiinisen ravinnon nauttimisen jälkeiseen hyperammonemiaan. LPI-geeni SLC7A7 (solute carrier family 7 member 7) koodaa y+LAT1 proteiinia, joka on basolateraali¬nen kationisten ja neutraalien aminohappojen kuljettimen kevyt ketju, joka muodostaa heterodimee¬rin raskaan alayksikön 4F2hc:n kanssa. Tällä hetkellä SLC7A7-geenistä tunnetaan yli 50 LPI:n aiheut¬tavaa mutaatiota. Tässä tutkimuksessa erityyppisiä y+LAT1:n LPI-mutaatiota sekä yhdeksän C-terminaalista polypep¬tidiä lyhentävää deleetiota kuvannettiin nisäkässoluissa y+LAT1:n GFP (green fluorescent protein) -fuusioproteiineina. Tulokset vahvistivat muissa soluissa tehdyt havainnot siitä, että 4F2hc on edel¬lytyksenä y+LAT1:n solukalvokuljetukselle, G54V-pistemutantti sijaitsee solukalvolla samoin kuin vil¬lityyppinen proteiini, mutta lukukehystä muuttavia ja proteiinia lyhentäviä mutantteja ei kuljeteta solukalvoon. Lisäksi havaittiin, että poikkeuksena tästä säännöstä ovat y+LAT1-deleetioproteiinit, joista puuttui korkeintaan 50 C-terminaalista aminohappoa. Nämä lyhentyneet kuljettimet sijaitsevat solukalvolla kuten villityyppiset ja LPI-pistemutanttiproteiinit. Dimerisaation osuutta kuljetushäiriön synnyssä tutkittiin käyttämällä fluorescence resonance energy transfer (FRET) menetelmää. Heterodimeerin alayksiköistä kloonattiin ECFP (cyan) ja EYFP (yellow) fuusioproteiinit, joita ilmennettiin nisäkässoluissa, ja FRET mitattiin virtaussytometri-FRET -menetel¬mällä (FACS-FRET). Tutkimuksissa kaikkien mutanttien havaittiin dimerisoituvan yhtä tehokkaasti. Kul¬jetushäiriön syynä ei siten ole alayksiköiden dimerisaation estyminen mutaation seurauksena. Tutkimuksessa havaittiin, että kaikki mutantti-y+LAT1-transfektiot tuottavat vähemmän transfektoi¬tuneita soluja kuin villityyppisen y+LAT1:n transfektiot. Solupopulaatioissa, joihin oli tranfektoitu lu¬kukehystä muuttava tai stop-kodonin tuottava mutaatio havaittiin suurempi kuolleisuus kuin saman näytteen transfektoitumattomissa soluissa, kun taas villityyppistä tai G54V-pistemutanttia tuottavas¬sa solupopulaatiossa oli pienempi kuolleisuus kuin saman näytteen fuusioproteiinia ilmentämättö¬missä soluissa. Tulos osoittaa mutanttiproteiinien erilaiset vaikutukset niitä ilmentäviin soluihin, joko suoraan y+LAT1:n tai 4F2hc:n kautta aiheutuneina. LPIFin SLC7A7 lähetti-RNA:n määrä ei merkittävästi poikennut villityyppisen määrästä fibroblasteissa ja lymfoblasteissa. SLC7A7:n promoottorianalyysissä oli osoitettavissa säätelyalueita geenin 5’ ei-koo¬daavalla alueella sekä ensimmäisten kahden intronin alueella. LPI-taudin tautimekanismin kannalta keskeisin tekijä on kuitenkin aminohappokuljetuksen häiriö, jonka vaikutuksesta näistä aminohapoista riippuvaiset prosessit elimistössä eivät toimi normaalisti. Havaittu virheellinen y+LAT1/4F2hc kuljetuskompleksin sijainti edellyttää lisätutkimuksia sen mahdol¬lisen kliinisen merkityksen selvittämiseksi.

Diffusion Tensor Imaging as a Diagnostic and Research Tool: A Study on Preterm Infants

Diffusion tensor imaging (DTI) is an advanced magnetic resonance imaging (MRI) technique. DTI is based on free thermal motion (diffusion) of water molecules. The properties of diffusion can be represented using parameters such as fractional anisotropy, mean diffusivity, axial diffusivity, and radial diffusivity, which are calculated from DTI data. These parameters can be used to study the microstructure in fibrous structure such as brain white matter. The aim of this study was to investigate the reproducibility of region-of-interest (ROI) analysis and determine associations between white matter integrity and antenatal and early postnatal growth at term age using DTI. Antenatal growth was studied using both the ROI and tract-based spatial statistics (TBSS) method and postnatal growth using only the TBSS method. The infants included to this study were born below 32 gestational weeks or birth weight less than 1,501 g and imaged with a 1.5 T MRI system at term age. Total number of 132 infants met the inclusion criteria between June 2004 and December 2006. Due to exclusion criteria, a total of 76 preterm infants (ROI) and 36 preterm infants (TBSS) were accepted to this study. The ROI analysis was quite reproducible at term age. Reproducibility varied between white matter structures and diffusion parameters. Normal antenatal growth was positively associated with white matter maturation at term age. The ROI analysis showed associations only in the corpus callosum. Whereas, TBSS revealed associations in several brain white matter areas. Infants with normal antenatal growth showed more mature white matter compared to small for gestational age infants. The gestational age at birth had no significant association with white matter maturation at term age. It was observed that good early postnatal growth associated negatively with white matter maturation at term age. Growth-restricted infants seemed to have delayed brain maturation that was not fully compensated at term, despite catchup growth.

Differentiation of Metabolically Distinct Areas within Head and Neck Region using Dynamic 18F-FDG Positron Emission Tomography Imaging

Positron Emission Tomography (PET) using ¹⁸F-FDG is playing a vital role in the diagnosis and treatment planning of cancer. However, the most widely used radiotracer, ¹⁸F-FDG, is not specific for tumours and can also accumulate in inflammatory lesions as well as normal physiologically active tissues making diagnosis and treatment planning complicated for the physicians. Malignant, inflammatory and normal tissues are known to have different pathways for glucose metabolism which could possibly be evident from different characteristics of the time activity curves from a dynamic PET acquisition protocol. Therefore, we aimed to develop new image analysis methods, for PET scans of the head and neck region, which could differentiate between inflammation, tumour and normal tissues using this functional information within these radiotracer uptake areas. We developed different dynamic features from the time activity curves of voxels in these areas and compared them with the widely used static parameter, SUV, using Gaussian Mixture Model algorithm as well as K-means algorithm in order to assess their effectiveness in discriminating metabolically different areas. Moreover, we also correlated dynamic features with other clinical metrics obtained independently of PET imaging. The results show that some of the developed features can prove to be useful in differentiating tumour tissues from inflammatory regions and some dynamic features also provide positive correlations with clinical metrics. If these proposed methods are further explored then they can prove to be useful in reducing false positive tumour detections and developing real world applications for tumour diagnosis and contouring.

Model-Based Tracking Initialization in Ship Building Environment

An augmented reality (AR) device must know observer’s location and orientation, i.e. observer’s pose, to be able to correctly register the virtual content to observer’s view. One possible way to determine and continuously follow-up the pose is model-based visual tracking. It supposes that a 3D model of the surroundings is known and that there is a video camera that is fixed to the device. The pose is tracked by comparing the video camera image to the model. Each new pose estimate is usually based on the previous estimate. However, the first estimate must be found out without a prior estimate, i.e. the tracking must be initialized, which in practice means that some model features must be identified from the image and matched to model features. This is known in literature as model-to-image registration problem or simultaneous pose and correspondence problem. This report reviews visual tracking initialization methods that are suitable for visual tracking in ship building environment when the ship CAD model is available. The environment is complex, which makes the initialization non-trivial. The report has been done as part of MARIN project.

Quantitative Magnetic Resonance Imaging of the Liver and Heart In Iron Overload

Systemic iron overload (IO) is considered a principal determinant in the clinical outcome of different forms of IO and in allogeneic hematopoietic stem cell transplantation (alloSCT). However, indirect markers for iron do not provide exact quantification of iron burden, and the evidence of iron-induced adverse effects in hematological diseases has not been established. Hepatic iron concentration (HIC) has been found to represent systemic IO, which can be quantified safely with magnetic resonance imaging (MRI), based on enhanced transverse relaxation. The iron measurement methods by MRI are evolving. The aims of this study were to implement and optimise the methodology of non-invasive iron measurement with MRI to assess the degree and the role of IO in the patients. An MRI-based HIC method (M-HIC) and a transverse relaxation rate (R2*) from M-HIC images were validated. Thereafter, a transverse relaxation rate (R2) from spin-echo imaging was calibrated for IO assessment. Two analysis methods, visual grading and rSI, for a rapid IO grading from in-phase and out-of-phase images were introduced. Additionally, clinical iron indicators were evaluated. The degree of hepatic and cardiac iron in our study patients and IO as a prognostic factor in patients undergoing alloSCT were explored. In vivo and in vitro validations indicated that M-HIC and R2* are both accurate in the quantification of liver iron. R2 was a reliable method for HIC quantification and covered a wider HIC range than M-HIC and R2*. The grading of IO was able to be performed rapidly with the visual grading and rSI methods. Transfusion load was more accurate than plasma ferritin in predicting transfusional IO. In patients with hematological disorders, the prevalence of hepatic IO was frequent, opposite to cardiac IO. Patients with myelodysplastic syndrome were found to be the most susceptible to IO. Pre-transplant IO predicted severe infections during the early post-transplant period, in contrast to the reduced risk of graft-versus-host disease. Iron-induced, poor transplantation results are most likely to be mediated by severe infections.

Adaptive Markov chain Monte Carlo and Bayesian filtering for state space models

This thesis is concerned with the state and parameter estimation in state space models. The estimation of states and parameters is an important task when mathematical modeling is applied to many different application areas such as the global positioning systems, target tracking, navigation, brain imaging, spread of infectious diseases, biological processes, telecommunications, audio signal processing, stochastic optimal control, machine learning, and physical systems. In Bayesian settings, the estimation of states or parameters amounts to computation of the posterior probability density function. Except for a very restricted number of models, it is impossible to compute this density function in a closed form. Hence, we need approximation methods. A state estimation problem involves estimating the states (latent variables) that are not directly observed in the output of the system. In this thesis, we use the Kalman filter, extended Kalman filter, Gauss–Hermite filters, and particle filters to estimate the states based on available measurements. Among these filters, particle filters are numerical methods for approximating the filtering distributions of non-linear non-Gaussian state space models via Monte Carlo. The performance of a particle filter heavily depends on the chosen importance distribution. For instance, inappropriate choice of the importance distribution can lead to the failure of convergence of the particle filter algorithm. In this thesis, we analyze the theoretical Lᵖ particle filter convergence with general importance distributions, where p ≥2 is an integer. A parameter estimation problem is considered with inferring the model parameters from measurements. For high-dimensional complex models, estimation of parameters can be done by Markov chain Monte Carlo (MCMC) methods. In its operation, the MCMC method requires the unnormalized posterior distribution of the parameters and a proposal distribution. In this thesis, we show how the posterior density function of the parameters of a state space model can be computed by filtering based methods, where the states are integrated out. This type of computation is then applied to estimate parameters of stochastic differential equations. Furthermore, we compute the partial derivatives of the log-posterior density function and use the hybrid Monte Carlo and scaled conjugate gradient methods to infer the parameters of stochastic differential equations. The computational efficiency of MCMC methods is highly depend on the chosen proposal distribution. A commonly used proposal distribution is Gaussian. In this kind of proposal, the covariance matrix must be well tuned. To tune it, adaptive MCMC methods can be used. In this thesis, we propose a new way of updating the covariance matrix using the variational Bayesian adaptive Kalman filter algorithm.

Brain SPECT imaging in Sydenham's chorea

The objective of the present study was to determine whether brain single-photon emission computed tomography (SPECT) imaging is capable of detecting perfusional abnormalities. Ten Sydenham's chorea (SC) patients, eight females and two males, 8 to 25 years of age (mean 13.4), with a clinical diagnosis of SC were submitted to brain SPECT imaging. We used HMPAO labeled with technetium-99m at a dose of 740 MBq. Six examinations revealed hyperperfusion of the basal ganglia, while the remaining four were normal. The six patients with abnormal results were females and their data were not correlated with severity of symptoms. Patients with abnormal brain SPECT had a more recent onset of symptoms (mean of 49 days) compared to those with normal SPECT (mean of 85 days) but this difference did not reach statistical significance. Brain SPECT can be a helpful method to determine abnormalities of the basal ganglia in SC patients but further studies on a larger number of patients are needed in order to detect the phase of the disease during which the examination is more sensitive.

New [18F]Tracers for Alzheimer's Disease Imaging. Labeling Synthesis And Biological Testing

Alzheimer’s disease (AD) is the most common form of dementia. Characteristic changes in an AD brain are the formation of β-amyloid protein (Aβ) plaques and neurofibrillary tangles, though other alterations in the brain have also been connected to AD. No cure is available for AD and it is one of the leading causes of death among the elderly in developed countries. Liposomes are biocompatible and biodegradable spherical phospholipid bilayer vesicles that can enclose various compounds. Several functional groups can be attached on the surface of liposomes in order to achieve long-circulating target-specific liposomes. Liposomes can be utilized as drug carriers and vehicles for imaging agents. Positron emission tomography (PET) is a non-invasive imaging method to study biological processes in living organisms. In this study using nucleophilic 18F-labeling synthesis, various synthesis approaches and leaving groups for novel PET imaging tracers have been developed to target AD pathology in the brain. The tracers were the thioflavin derivative [18F]flutemetamol, curcumin derivative [18F]treg-curcumin, and functionalized [18F]nanoliposomes, which all target Aβ in the AD brain. These tracers were evaluated using transgenic AD mouse models. In addition, 18F-labeling synthesis was developed for a tracer targeting the S1P3 receptor. The chosen 18F-fluorination strategy had an effect on the radiochemical yield and specific activity of the tracers. [18F]Treg-curcumin and functionalized [18F]nanoliposomes had low uptake in AD mouse brain, whereas [18F]flutemetamol exhibited the appropriate properties for preclinical Aβ-imaging. All of these tracers can be utilized in studies of the pathology and treatment of AD and related diseases.

Decreased left temporal lobe volume of panic patients measured by magnetic resonance imaging

Reported neuroimaging studies have shown functional and morphological changes of temporal lobe structures in panic patients, but only one used a volumetric method. The aim of the present study was to determine the volume of temporal lobe structures in patients with panic disorder, measured by magnetic resonance imaging. Eleven panic patients and eleven controls matched for age, sex, handedness, socioeconomic status and years of education participated in the study. The mean volume of the left temporal lobe of panic patients was 9% smaller than that of controls (t21 = 2.37, P = 0.028). In addition, there was a trend (P values between 0.05 and 0.10) to smaller volumes of the right temporal lobe (7%, t21 = 1.99, P = 0.06), right amygdala (8%, t21 = 1.83, P = 0.08), left amygdala (5%, t21 = 1.78, P = 0.09) and left hippocampus (9%, t21 = 1.93, P = 0.07) in panic patients compared to controls. There was a positive correlation between left hippocampal volume and duration of panic disorder (r = 0.67, P = 0.025), with recent cases showing more reduction than older cases. The present results show that panic patients have a decreased volume of the left temporal lobe and indicate the presence of volumetric abnormalities of temporal lobe structures.

Radiography, computed tomography and magnetic resonance imaging at 0.5 Tesla of mechanically inducedosteoarthritis in rabbit knees

In the present experimental study we assessed induced osteoarthritis data in rabbits, compared three diagnostic methods, i.e., radiography (XR), computed tomography (CT) and magnetic resonance imaging (MRI), and correlated the imaging findings with those obtained by macroscopic evaluation. Ten young female rabbits of the Norfolk breed were used. Seven rabbits had the right knee immobilized in extension for a period of 12 weeks (immobilized group), and three others did not have a limb immobilized and were maintained under the same conditions (control group). Alterations observed by XR, CT and MRI after the period of immobilization were osteophytes, osteochondral lesions, increase and decrease of joint space, all of them present both in the immobilized and non-immobilized contralateral limbs. However, a significantly higher score was obtained for the immobilized limbs (XT: P = 0.016, CT: P = 0.031, MRI: P = 0.0156). All imaging methods were able to detect osteoarthritis changes after the 12 weeks of immobilization. Macroscopic evaluation identified increased thickening of joint capsule, proliferative and connective tissue in the femoropatellar joint, and irregularities of articular cartilage, especially in immobilized knees. The differences among XR, CT and MRI were not statistically significant for the immobilized knees. However, MRI using a 0.5 Tesla scanner was statistically different from CT and XR for the non-immobilized contralateral knees. We conclude that the three methods detected osteoarthritis lesions in rabbit knees, but MRI was less sensitive than XR and CT in detecting lesions compatible with initial osteoarthritis. Since none of the techniques revealed all the lesions, it is important to use all methods to establish an accurate diagnosis.

Late-life depression, heart failure and frontal white matter hyperintensity: a structural magnetic resonance imaging study

The relevance of the relationship between cardiac disease and depressive symptoms is well established. White matter hyperintensity, a bright signal area in the brain on T2-weighted magnetic resonance imaging scans, has been separately associated with cardiovascular risk factors, cardiac disease and late-life depression. However, no study has directly investigated the association between heart failure, major depressive symptoms and the presence of hyperintensities. Using a visual assessment scale, we have investigated the frequency and severity of white matter hyperintensities identified by magnetic resonance imaging in eight patients with late-life depression and heart failure, ten patients with heart failure without depression, and fourteen healthy elderly volunteers. Since the frontal lobe has been the proposed site for the preferential location of white matter hyperintensities in patients with late-life depression, we focused our investigation specifically on this brain region. Although there were no significant group differences in white matter hyperintensities in the frontal region, a significant direct correlation emerged between the severity of frontal periventricular white matter hyperintensity and scores on the Hamilton scale for depression in the group with heart failure and depression (P = 0.016, controlled for the confounding influence of age). There were no significant findings in any other areas of the brain. This pattern of results adds support to a relationship between cardiovascular risk factors and depressive symptoms, and provides preliminary evidence that the presence of white matter hyperintensities specifically in frontal regions may contribute to the severity of depressive symptoms in cardiac disease.