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Sökning: AMNE:(MEDICAL AND HEALTH SCIENCES Clinical Medicine Radiology, Nuclear Medicine and Medical Imaging) > Doktorsavhandling

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1.
  • Khoshnood, Ardavan (författare)
  • Prehospital Diagnosis and Oxygen Treatment in ST Elevation Myocardial Infarction
  • 2017
  • Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
    • IntroductionPaper I: An Artificial Neural Network (ANN) was constructed to identify ST Elevation Myocardial Infarction (STEMI) and predict the need for Percutaneous Coronary Intervention (PCI). Paper II, III and IV: Studies suggest that O2 therapy may be harmful in STEMI patients. We therefore conducted the SOCCER study to evaluate the effects of O2 therapy in STEMI patients.MethodsPaper I: 560 ambulance ECGs sent to the Cardiac Care Unit (CCU), was together with the CCU physicians interpretation and decision of conducting an acute PCI or not collected, and compared with the interpretation and PCI decision of the ANN. Paper II, III, IV: Normoxic (≥94%) STEMI patients accepted for acute PCI were in the ambulance randomized to standard care with 10 L/min O2 or room air. A subset of the patients underwent echocardiography for determination of the Left Ventricular Ejection Fraction (LVEF) and the Wall Motion Score Index (WMSI). All patients had a Cardiac Magnetic Resonance Imaging (CMRI) to evaluate Myocardial area at Risk (MaR), Infarct Size (IS) and Myocardial Salvage Index (MSI).ResultsPaper I: The area under the ANN’s receiver operating characteristics curve for STEMI detection as well as predicting the need of acute PCI were very good.Paper II, III, IV: No significant differences could be shown in discussing MaR, MSI or IS between the O2 group (n=46) and the air group (n=49). Neither could any differences be shown for LVEF and WMSI at the index visit as well after six months between the O2 group (n=46) and the air group (n=41)ConclusionsPaper I: The results indicate that the number of ECGs sent to the CCU could be reduced with 2/3 as the ANN would safely identify ECGs not being STEMI.Paper II, III, IV: The results suggest that it is safe to withhold O2 therapy in normoxic, stable STEMI patients.
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2.
  • Ahlander, Britt-Marie, 1954- (författare)
  • Magnetic Resonance Imaging of the Heart : Image quality, measurement accuracy and patient experience
  • 2016
  • Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
    • Background: Non-invasive diagnostic imaging of atherosclerotic coronary artery disease (CAD) is frequently carried out with cardiovascular magnetic resonance imaging (CMR) or myocardial perfusion single photon emission computed tomography (MPS). CMR is the gold standard for the evaluation of scar after myocardial infarction and MPS the clinical gold standard for ischemia. Magnetic Resonance Imaging (MRI) is at times difficult for patients and may induce anxiety while patient experience of MPS is largely unknown.Aims: To evaluate image quality in CMR with respect to the sequences employed, the influence of atrial fibrillation, myocardial perfusion and the impact of patient information. Further, to study patient experience in relation to MRI with the goal of improving the care of these patients.Method: Four study designs have been used. In paper I, experimental cross-over, paper (II) experimental controlled clinical trial, paper (III) psychometric crosssectional study and paper (IV) prospective intervention study. A total of 475 patients ≥ 18 years with primarily cardiac problems (I-IV) except for those referred for MRI of the spine (III) were included in the four studies.Result: In patients (n=20) with atrial fibrillation, a single shot steady state free precession (SS-SSFP) sequence showed significantly better image quality than the standard segmented inversion recovery fast gradient echo (IR-FGRE) sequence (I). In first-pass perfusion imaging the gradient echo-echo planar imaging sequence (GREEPI) (n=30) had lower signal-to-noise and contrast–to-noise ratios than the steady state free precession sequence (SSFP) (n=30) but displayed a higher correlation with the MPS results, evaluated both qualitatively and quantitatively (II). The MRIAnxiety Questionnaire (MRI-AQ) was validated on patients, referred for MRI of either the spine (n=193) or the heart (n=54). The final instrument had 15 items divided in two factors regarding Anxiety and Relaxation. The instrument was found to have satisfactory psychometric properties (III). Patients who prior CMR viewed an information video scored significantly (lower) better in the factor Relaxation, than those who received standard information. Patients who underwent MPS scored lower on both factors, Anxiety and Relaxation. The extra video information had no effect on CMR image quality (IV).Conclusion: Single shot imaging in atrial fibrillation produced images with less artefact than a segmented sequence. In first-pass perfusion imaging, the sequence GRE-EPI was superior to SSFP. A questionnaire depicting anxiety during MRI showed that video information prior to imaging helped patients relax but did not result in an improvement in image quality.
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3.
  • Latini, Francesco, M.D. 1982- (författare)
  • Significance of white matter anatomy in interpreting features and behaviour of low-grade gliomas and implications for surgical treatment
  • 2021
  • Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
    • Diffuse gliomas are extremely heterogeneous tumours characterized by slow growth but extensive infiltration. Their kinetic features reflect the complex interaction over time with the surrounding brain, influencing treatment planning and outcome. Indeed, resection of diffuse gliomas present a surgical challenge due to their invasiveness and the preferential location in eloquent regions. White matter bundles are the main eloquent limit to surgical resection, but this anatomical-functional information cannot be predicted preoperatively on the individual level. The incomplete description of the human brain connectome, the complex application of pathological/lesion model to the brain connectomic organization, and the underestimated role of white matter anatomy in radiological classification systems are among the major limitations for the comprehension of the glioma/white matter interaction. The overall aim of this thesis was to explore a new approach and new techniques to study the glioma/white matter interaction. A combination of white matter dissection and diffusion tensor tractography (DTT) was used to describe the connectomic organization of two major temporo-occipital connections, the inferior and the middle longitudinal fasciculus. This information was applied to patients with diffuse gliomas, demonstrating how white matter analysis was important to decode patient specific cognitive and language impairment. A new classification system for diffuse gliomas, the Brain-Grid, was created, merging local radiological anatomy with a DTT atlas for infiltration analysis. This standardized radiological tool provided information on subcortical extension (tumour invasiveness), speed, and preferential direction of glioma progression. Applied to a larger cohort of patients, differences were detected between diffuse gliomas subtypes. Tumour invasiveness and the preferential location, type, and extent of white matter involvement differed, impacting overall survival. Regional differences in white matter infiltration were detected among five major white matter bundles, and possible favourable morphological and diffusion features were investigated with transmission electron microscopy and DTT. Fibre diameter, myelin thickness, and the organization of the white matter fibres were different in regions with high infiltration frequency, providing a possible link to the preferential location of diffuse gliomas. Finally, the white matter connectivity, tumour-induced neuroplasticity, clinical and demographic information, preoperative assessment (neuropsychological and language evaluation) were compared with intraoperative findings during awake surgery. Neuropsychological impairment was associated with more invasive tumours and a higher risk of the intraoperative finding of eloquent tumour. The pattern of early cortical neuroplasticity seemed exhausted at the time of diagnosis, with age as a factor predicting the neuroplasticity potential. The combined use of these new techniques revealed new insights into the glioma/white matter interaction. The results provided in this thesis, describe a new way to structure the multidisciplinary perioperative management of these patients. This new information may improve the functional outcome at the individual level, resulting in prolonged survival for adults with diffuse gliomas.
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4.
  • Fredenberg, Erik, 1979- (författare)
  • Spectral Mammography with X-Ray Optics and a Photon-Counting Detector
  • 2009
  • Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
    • Early detection is vital to successfully treating breast cancer, and mammography screening is the most efficient and wide-spread method to reach this goal. Imaging low-contrast targets, while minimizing the radiation exposure to a large population is, however, a major challenge. Optimizing the image quality per unit radiation dose is therefore essential. In this thesis, two optimization schemes with respect to x-ray photon energy have been investigated: filtering the incident spectrum with refractive x-ray optics (spectral shaping), and utilizing the transmitted spectrum with energy-resolved photon-counting detectors (spectral imaging). Two types of x-ray lenses were experimentally characterized, and modeled using ray tracing, field propagation, and geometrical optics. Spectral shaping reduced dose approximately 20% compared to an absorption-filtered reference system with the same signal-to-noise ratio, scan time, and spatial resolution. In addition, a focusing pre-object collimator based on the same type of optics reduced divergence of the radiation and improved photon economy by about 50%. A photon-counting silicon detector was investigated in terms of energy resolution and its feasibility for spectral imaging. Contrast-enhanced tumor imaging with a system based on the detector was characterized and optimized with a model that took anatomical noise into account. Improvement in an ideal-observer detectability index by a factor of 2 to 8 over that obtained by conventional absorption imaging was found for different levels of anatomical noise and breast density. Increased conspicuity was confirmed by experiment. Further, the model was extended to include imaging of unenhanced lesions. Detectability of microcalcifications increased no more than a few percent, whereas the ability to detect large tumors might improve on the order of 50% despite the low attenuation difference between glandular and cancerous tissue. It is clear that inclusion of anatomical noise and imaging task in spectral optimization may yield completely different results than an analysis based solely on quantum noise.
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5.
  • Sandström, Agneta, 1959- (författare)
  • Neurocognitive and endocrine dysfunction in women with exhaustion syndrome
  • 2010
  • Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
    • Stress has emerged as one of the most important factors to consider in psychiatric diagnoses and has become a common reason for long-term sick leave (LTSL). Roughly 50% of LTSL due to psychiatric diseases are thought to be associated with work-related stress. The demarcation towards major depression is disputed, and no international consensus exists for how to diagnose and rehabilitate these individuals. The Swedish National Board of Health has suggested the term “exhaustion syndrome” to integrate these individuals into stress-related disorders. Prominent features of this syndrome are fatigue, sleeping disorders, and cognitive dysfunction. The cognitive dysfunction may be due to an interaction between personality features, environmental factors, the biological effects of stress hormones, and dysfunction in key brain areas, notably the hippocampus and prefrontal cortex. A consistent feature of chronic stress is activation of the cortisol, or hypothalamic-pituitary-adrenal, axis, which may be linked to cognitive dysfunction. Increased glucocorticoid levels, mainly cortisol in humans, are known to impair memory performance. The aim of this thesis was to investigate whether patients with exhaustion syndrome exhibit specific alterations in an extensive set of biological, psychological and immunological variables. Patients in Study 1 had significant cognitive impairment for specific tasks assumed to tap frontal lobe functioning. In Study 2 anxiety prone, worrying, pessimistic individuals with low executive drive and a persistent personality type were more likely to develop exhaustion syndrome. Decreased reactivity was found on the pituitary level after corticotropin releasing hormone (CRH) in exhaustion syndrome patients. The cortisol/adrenocorticotropic hormone response to CRH was slightly higher in patients compared to controls, indicating increased sensitivity at the adrenal cortex level. No differences were found in hippocampal volume. In Study 3, functional imaging revealed a different pattern of brain activation in working memory tests in patients with exhaustion syndrome compared to healthy individuals and patients with depression. In summary, our data suggests an intimate link between personality and wellbeing, cognitive performance and neuroendocrine dysfunction, in exhaustion syndrome. We thus find similarities with major depression but also distinct differences between the exhaustion syndrome and major depression.
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6.
  • Gingnell, Malin, 1982- (författare)
  • Ovarian Steroid Hormones, Emotion Processing and Mood
  • 2013
  • Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
    • It is known that some psychiatric disorders may deteriorate in relation to the menstrual cycle. However, in some conditions, such as premenstrual dysphoric disorder (PMDD), symptomatology is triggered mainly by the variations in ovarian steroid hormones. Although symptoms induced by fluctuations in ovarian steroids often are affective, little is known about how emotion processing in women is influenced by variations, or actual levels, of ovarian steroid hormones.The general aim of this thesis was to evaluate menstrual cycle effects on reactivity in emotion generating and controlling areas in the corticolimbic system to emotional stimulation and anticipation, in healthy controls and women with PMDD. A second aim was to evaluate corticolimbic reactivity during long-term administration of exogenous ovarian steroids.In study I, III and IV effects of the menstrual cycle on emotional reactivity in women with PMDD was studied. In study I, women with PMDD in displayed higher amygdala reactivity than healthy controls to emotional faces, not in the luteal phase as was hypothesised, but in the follicular phase. No difference between menstrual cycle phases was obtained in women with PMDD, while healthy controls had an increased reactivity in the luteal phase. The results of study I was further elaborated in study III, where women with PMDD were observed to have an increased anticipatory reactivity to negative emotional stimuli. However, no differences in amygdala reactivity to emotional stimuli were obtained across the menstrual cycle. Finally, in study IV the hypothesis that amygdala reactivity increase in the luteal phase in women with PMDD is linked to social stimuli rather than generally arousing stimuli was suggested, tested and supported.In study II, re-exposure to COC induced mood symptoms de novo in women with a previous history of COC-induced adverse mood. Women treated with COC reported increased levels of mood symptoms both as compared to before treatment, and as compared to the placebo group. There was a relatively strong correlation between depressive scores before and during treatment. The effects of repeated COC administration on subjective measures and brain function were however dissociated with increased aversive experiences accompanied by reduced reactivity in the insular cortex.
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7.
  • Vu, Minh Hoang, 1988- (författare)
  • Resource efficient automatic segmentation of medical images
  • 2023
  • Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
    • Cancer is one of the leading causes of death worldwide. In 2020, there were around 10 million cancer deaths and nearly 20 million new cancer cases in the world. Radiation therapy is essential in cancer treatments because half of the cancer patients receive radiation therapy at some point. During a radiotherapy treatment planning (RTP), an oncologist must manually outline two types of areas of the patient’s body: target, which will be treated, and organs-at-risks (OARs), which are essential to avoid. This step is called delineation. The purpose of the delineation is to generate a sufficient dose plan that can provide adequate radiation dose to a tumor and limit the radiation exposure to healthy tissue. Therefore, accurate delineations are essential to achieve this goal.Delineation is tedious and demanding for oncologists because it requires hours of concentrating work doing a repeated job. This is a RTP bottleneck which is often time- and resource-intensive. Current software, such as atlasbased techniques, can assist with this procedure by registering the patient’s anatomy to a predetermined anatomical map. However, the atlas-based methods are often slowed down and erroneous for patients with abnormal anatomies.In recent years, deep learning (DL) methods, particularly convolutional neural networks (CNNs), have led to breakthroughs in numerous medical imaging applications. The core benefits of CNNs are weight sharing and that they can automatically detect important visual features. A typical application of CNNs for medical images is to automatically segment tumors, organs, and structures, which is assumed to save radiation oncologists much time when delineating. This thesis contributes to resource efficient automatic segmentation and covers different aspects of resource efficiency.In Paper I, we proposed a novel end-to-end cascaded network for semantic segmentation in brain tumors in the multi-modal magnetic resonance imaging challenge in 2019. The proposed method used the hierarchical structure of the tumor sub-regions and was one of the top-ranking teams in the task of quantification of uncertainty in segmentation. A follow-up work to this paper was ranked second in the same task in the same challenge a year later.We systematically assessed the segmentation performance and computational costs of the technique called pseudo-3D as a function of the number of input slices in Paper II. We compared the results to typical two-dimensional (2D) and three-dimensional (3D) CNNs and a method called triplanar orthogonal 2D. The typical pseudo-3D approach considers adjacent slices to be several image input channels. We discovered that a substantial benefit from employing multiple input slices was apparent for a specific input size.We introduced a novel loss function in Paper III to address diverse issues, including imbalanced datasets, partially labeled data, and incremental learning. The proposed loss function adjusts to the given data to use all accessible data, even if some lack annotations. We show that the suggested loss function also performs well in an incremental learning context, where an existing model can be modified to incorporate the delineations of newly appearing organs semi-automatically.In Paper IV, we proposed a novel method for compressing high-dimensional activation maps, which are the primary source of memory use in modern systems. We examined three distinct compression methods for the activation maps to accomplishing this. We demonstrated that the proposed method induces a regularization effect that acts on the layer weight gradients. By employing the proposed technique, we reduced activation map memory usage by up to 95%.We investigated the use of generative adversarial networks (GANs) to enlarge a small dataset by generating synthetic images in Paper V. We use the real and generated data during training CNNs for the downstream segmentation tasks. Inspired by an existing GAN, we proposed a conditional version to generate high-dimensional and high-quality medical images of different modalities and their corresponding label maps. We evaluated the quality of the generated medical images and the effect of this augmentation on the performance of the segmentation task on six datasets.
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8.
  • Cronqvist, Mats (författare)
  • Results and complications of endovascular neurointerventions in intracranial aneurysms and arteriovenous malformations, evaluated by conventional angiography and diffusion-perfusion MRI
  • 2005
  • Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
    • Aims - To describe and evaluate the efficacy and safety of intra-arterial fibrinolysis and the clinical outcome in SAH patients with thromboembolic complications during endovascular coiling of a ruptured aneurysm. (Paper I) - To describe the use and feasibility of magnetic resonance imaging (MRI), especially diffusion and perfusion imaging, in three patients treated endovascularly for various cerebrovascular disorders. (Paper II) - To evaluate treatment safety as well as complication frequency and management in endovascular coiling of ruptured and unruptured intracranial aneurysms using MR diffusion and perfusion imaging. (Paper III). - To evaluate treatment safety in patients with cerebral arteriovenous malformations and to correlate the anatomical results with regard to complications and clinical outcome using MRI, including diffusion-weighted (DWI) and perfusion imaging (PI). (Paper IV).
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9.
  • Ge, Chenjie, 1991 (författare)
  • Machine Learning Methods for Image Analysis in Medical Applications, from Alzheimer's Disease, Brain Tumors, to Assisted Living
  • 2020
  • Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
    • Healthcare has progressed greatly nowadays owing to technological advances, where machine learning plays an important role in processing and analyzing a large amount of medical data. This thesis investigates four healthcare-related issues (Alzheimer's disease detection, glioma classification, human fall detection, and obstacle avoidance in prosthetic vision), where the underlying methodologies are associated with machine learning and computer vision. For Alzheimer’s disease (AD) diagnosis, apart from symptoms of patients, Magnetic Resonance Images (MRIs) also play an important role. Inspired by the success of deep learning, a new multi-stream multi-scale Convolutional Neural Network (CNN) architecture is proposed for AD detection from MRIs, where AD features are characterized in both the tissue level and the scale level for improved feature learning. Good classification performance is obtained for AD/NC (normal control) classification with test accuracy 94.74%. In glioma subtype classification, biopsies are usually needed for determining different molecular-based glioma subtypes. We investigate non-invasive glioma subtype prediction from MRIs by using deep learning. A 2D multi-stream CNN architecture is used to learn the features of gliomas from multi-modal MRIs, where the training dataset is enlarged with synthetic brain MRIs generated by pairwise Generative Adversarial Networks (GANs). Test accuracy 88.82% has been achieved for IDH mutation (a molecular-based subtype) prediction. A new deep semi-supervised learning method is also proposed to tackle the problem of missing molecular-related labels in training datasets for improving the performance of glioma classification. In other two applications, we also address video-based human fall detection by using co-saliency-enhanced Recurrent Convolutional Networks (RCNs), as well as obstacle avoidance in prosthetic vision by characterizing obstacle-related video features using a Spiking Neural Network (SNN). These investigations can benefit future research, where artificial intelligence/deep learning may open a new way for real medical applications.
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10.
  • Byenfeldt, Marie, 1967- (författare)
  • Ultrasound based shear wave elastography of the liver : a non-invasive method for evaluation of liver disease
  • 2020
  • Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
    • Background: Detecting liver disease at an early stage is important, given that early intervention decreases the risk of developing cirrhosis and subsequently hepatocellular cancer (HCC). The non-invasive ultrasound-based shear wave elastography (SWE) has been used clinically for a decade to assess liver stiffness. This method is reliable, rapid and can be performed in an outpatient setting without known risks for the patient. However, increased variance in SWE results has been detected, without clear explanation. Factors that affect SWE results needs to be identified. Data are insufficient regarding the reliability of SWE with different body positions and probe pressures. Men have higher SWE results than women, also for unclear reasons. Increasing the reliability of SWE is crucial for understanding how factors such as overweight and obesity, cardiovascular and antiviral medication, age, sex, smoking habits, hepatic steatosis and cirrhosis affect SWE results.Aims: The overall aim of the studies included in this thesis was to increase the reliability of SWE liver. The specific aims were to investigate patient-related factors associated with increased uncertainty in SWE results. Another aim was to investigate the influence of increased intercostal probe pressure on liver stiffness assessment with SWE liver.  The final aims were to investigate the influence of postural changes, sagittal abdominal diameter (SAD) and skin-to-liver capsule distance (SCD) on SWE results, along with sex-based differences for SWE results and cardiovascular medication.Methods: All enrolled participants in these studies were consecutive patients with various liver diseases presenting at the radiology department Östersunds Hospital. The patients were examined using SWE liver method at the ultrasound unit between April 2014 and May 2018. Inclusion criteria were that participants be adults (age ≥18 years) who had provided written consent for participating in the study. The exclusion criterion was an inability to communicate. Current guidelines for SWE of the liver were used in the thesis with the following exceptions: In study II, increased intercostal probe pressure was used, and in study III, postural change was used. Study I included 188 patients; study II included 112 patients, and studies III and IV involved 200 patients. The four studies were conducted as cross-sectional and clinical trial, using quantitative methods.Results: Factors associated with low variance for SWE results were age, sex, and presence of cirrhosis, the use of antiviral and/or cardiovascular medication, smoking habits, and body mass index.  Factors associated with increased uncertainty in SWE results were increased SCD and the presence of steatosis. With increased probe pressure SCD decreased and the quality of shear wave increased. The results showed that the number of required measurements can be reduced. A postural change to left decubitus decreased SCD. For patients with increased SAD and increased SWE result in the supine position, SWE result decreased with a postural change to left decubitus.  The SWE results, SCD and SAD significantly differed between women and men. SWE results was higher in the presence of increased SAD (≥23 cm) among men, but not among women.Conclusions:  SWE of the liver is a reliable, non-invasive method for diagnosing liver disease. Results in this thesis suggest that for patients with SCD ≥2.5 cm, shear wave measures could be of poor quality and the SWE exam less reliable. In these cases, increased probe pressure may facilitate a reliable SWE exam. With such adjustments in probe pressure, the ultrasound-based SWE method can be superior for examination in patients with overweight or obesity. An effect of SAD ≥23 cm was seen for men with liver fibrosis only, which may explain the higher SWE result for men compared to women. Depending on the severity of liver disease and SAD, a postural change to left decubitus can produce a different outcome. As SAD increased, liver stiffness did, as well. Increased SAD thus is linked to increased liver stiffness, indicating that SAD should be taken into account when performing SWE of the liver.
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