Diffuse optical tomography (DOT) is one of the promising imaging modalities that pro- vides functional information of the soft biological tissues in-vivo, such as breast and brain tissues. The near infrared (NIR) light (600-1000 nm) is the interrogating radiation, which is typically delivered and collected using fiber bundles placed on the boundary of the tissue. The internal optical property distribution is estimated via model-based image reconstruction algorithm using these limited boundary measurements. Image reconstruction problem in DOT is known to be non-linear, ill-posed, and some times under-determined due to the multiple scattering of NIR light in the tissue. Solving this inverse problem requires regularization to obtain meaningful results, with Tikhonov-type regularization being the most popular one. The choice of the regularization parameter dictates the reconstructed optical image quality and is typically chosen empirically or based on prior experience. An automated method for optimal selection of regularization parameter that is based on regularized minimal residual method (MRM) is proposed and is compared with the traditional generalized cross-validation method. The results obtained using numerical and gelatin phantom data indicate that the MRM-based method is capable of providing the optimal regularization parameter. A new approach that can easily incorporate any generic penalty function into the diffuse optical tomographic image reconstruction is introduced to show the utility of non-quadratic penalty functions. The penalty functions that were used include, quadratic (`2), absolute (`1), Cauchy, and Geman-McClure. The regularization parameter in each of these cases were obtained automatically using the generalized cross-validation (GCV) method. The reconstruction results were systematically compared with each other via utilization of quantitative metrics, such as relative error and Pearson correlation. The reconstruction results indicate that while quadratic penalty may be able to provide better separation between two closely spaced targets, it's contrast recovery capability is limited and the sparseness promoting penalties, such as `1, Cauchy, Geman-McClure have better utility in reconstructing high-contrast and complex-shaped targets with Geman-McClure penalty being the most optimal one. Effective usage of image guidance by incorporating the refractive index (RI) variation in computational modeling of light propagation in tissue is investigated to assess its impact on optical-property estimation. With the aid of realistic patient breast three-dimensional models, the variation in RI for different regions of tissue under investigation is shown to influence the estimation of optical properties in image-guided diffuse optical tomography (IG-DOT) using numerical simulations. It is also shown that by assuming identical RI for all regions of tissue would lead to erroneous estimation of optical properties. The a priori knowledge of the RI for the segmented regions of tissue in IG-DOT, which is difficult to obtain for the in vivo cases, leads to more accurate estimates of optical properties. Even inclusion of approximated RI values, obtained from the literature, for the regions of tissue resulted in better estimates of optical properties, with values comparable to that of having the correct knowledge of RI for different regions of tissue. Image reconstruction in IG-DOT procedure involves reduction of the number of optical parameters to be reconstructed equal to the number of distinct regions identified in the structural information provided by the traditional imaging modality. This makes the image reconstruction problem to be well-determined compared to traditional under- determined case. Still, the methods that are deployed in this case are same as the one used for traditional diffuse optical image reconstruction, which involves regularization term as well as computation of the Jacobian. A gradient-free Nelder-Mead simplex method was proposed here to perform the image reconstruction procedure and shown to be providing solutions that are closely matching with ones obtained using established methods. The proposed method also has the distinctive advantage of being more efficient due to being regularization free, involving only repeated forward calculations.

This document is a critical synopsis of prior work by Michael Dwyer submitted in support of a PhD by published work. The selected work is focused on the application of quantitative magnet resonance imaging (MRI) analysis techniques to the study of multiple sclerosis (MS). MS is a debilitating disease with a multi-factorial pathology, progression, and clinical presentation. Its most salient feature is focal inflammatory lesions, but it also includes significant parenchymal atrophy and microstructural damage. As a powerful tool for in vivo investigation of tissue properties, MRI can provide important clinical and scientific information regarding these various aspects of the disease, but precise, accurate quantitative analysis techniques are needed to detect subtle changes and to cope with the vast amount of data produced in an MRI session. To address this, eight new techniques were developed by Michael Dwyer and his co-workers to better elucidate focal, atrophic, and occult/"invisible" pathology. These included: a method to better evaluate errors in lesion identification; a method to quantify differences in lesion distribution between scanner strengths; a method to measure optic nerve atrophy; a more precise method to quantify tissue-specific atrophy; a method sensitive to dynamic myelin changes; and a method to quantify iron in specific brain structures. Taken together, these new techniques are complementary and improve the ability of clinicians and researchers to reliably assess various key elements of MS pathology in vivo.

Abstract Wood is an essential material that has many applications in the fields of engineering and especially in the forest industry, which is particularly important in Fennoscandia. Among the various modification methods for wood, thermal modification has grown substantially over the past decades. It is an environmentally friendly method for increasing the lifetime and usability of timber. The aim of this thesis is to characterize the properties of thermally modified wood as well as to obtain new information on the changes taking place in pinewood due to the thermal modification process. Several NMR methods were used to gain information on the effect of thermal modification on the microstructure and moisture components of Pinus sylvestris pinewood. Pinewood samples thermally modified at different temperatures were studied and compared to corresponding unmodified wood samples. Diffusion of water and methane was studied using pulsed-field-gradient stimulated-echo measurements to determine the highly anisotropic size distribution of pores in different cell structures of pinewood. NMR cryoporometry and relaxometry measurements were conducted to gain information on the amounts and environments of both the bound and free water absorbed into the wood samples. Cryoporometry measurements resulted in an upper limit value for the size of bound water sites and the combination of cryoporometry and relaxometry data enabled the size determination of cell wall micropores. Magnetic resonance imaging was used to visualize the spatial distribution of absorbed free water in the studied samples. Together these methods give a broad overall picture of the effects of the modification process. The results of this work give new insight into the microstructure of thermally modified pinewood and its relationship to moisture, which is of importance for both wood science as well as industry. The applicability of the NMR techniques used here to the study of wood is also proven in this work. Using the techniques developed, it is possible to determine the optimal modification temperature, which is high enough to obtain the desired effects, but low enough not to destroy the microstructure of wood. / Tiivistelmä Puuta pystytään hyödyntämään useilla eri aloilla ja se on materiaalina tärkeä etenkin Fennoskandiassa merkittävälle metsäteollisuudelle. Useiden erilaisten puun käsittelymenetelmien joukossa lämpökäsittely on kasvattanut voimakkaasti suosiotaan viime vuosikymmeninä. Kyseessä on ympäristöystävällinen menetelmä, jolla voidaan pidentää puun käyttöikää sekä käytettävyyttä erilaisissa sovelluskohteissa. Tämän väitöskirjan päämääränä on ollut lämpökäsitellyn puun ominaisuuksien tutkiminen ja uuden tiedon saaminen puussa lämpökäsittelyprosessin myötä tapahtuvista muutoksista. Työssä käytettiin useita eri NMR-menetelmiä lämpökäsitellyn mäntypuun (Pinus sylvestris) mikrorakenteen sekä puussa olevan kosteuden aiheuttamien vaikutusten tutkimiseksi. Työssä tutkittiin eri lämpötiloissa käsiteltyjä mäntypuunäytteitä, joita verrattiin vastaaviin käsittelemättömiin näytteisiin. Veden ja metaanin diffuusiota tutkittiin PGSTE-menetelmällä puun erittäin anisotrooppisen solurakenteen sisältämien huokosten mittojen määrittämiseksi. NMR-kryoporometria- ja -relaksometriamittaukset antoivat tietoa puuhun imeytyneen sidotun ja vapaan veden määrästä ja esiintymisympäristöstä. Kryoporometria-mittausten tuloksista saatiin yläraja sidotun veden esiintymispaikkojen koolle, ja kryoporometria- ja relaksometriamittausten tuottaman tiedon yhdistäminen mahdollisti soluseinämien mikrohuokosten koon määrittämisen. Magneettikuvausta käytettiin näytteisiin absorboituneen veden avaruudellisen jakauman määrittämiseen. Käytetyt menetelmät tarjoavat laajan kokonaiskuvan lämpökäsittelyprosessin vaikutuksista puulle. Tämän työn tulokset antavat puutiedettä ja -teollisuutta hyödyttävää uutta tietoa lämpökäsitellyn männyn mikrorakenteesta sekä sen suhteesta kosteuteen. Väitöskirja myös osoittaa käytettyjen NMR-menetelmien soveltuvan hyvin puun tutkimiseen. Tämän tutkimuksen myötä kehitettyjen menetelmien avulla voidaan määrittää mm. optimaalinen lämpökäsittelylämpötila, joka on riittävän korkea haluttujen ominaisuuksien kannalta aiheuttamatta kuitenkaan puun mikrorakenteen hajoamista.

In translational medicine, complementary functional and morphological imaging techniques are used extensively to observe physiological processes in vivo and to assess structural changes as a result of disease progression. The combination of magnetic resonance imaging (MRI) and positron emission tomography (PET) provides excellent soft tissue contrast from MRI with exceptional sensitivity and specificity from PET. This thesis explores the use of sequentially acquired PET and MR images to improve the quantification of small animal PET data. The primary focus was to improve image-based estimates of the arterial input function (AIF), which defines the amount of PET tracer within blood plasma over time. The AIF is required to produce physiological parameters quantifying key processes such as metabolism or perfusion from dynamic PET images. The gold standard for AIF measurement, however, requires serial blood sampling over the course of a PET scan, which is invasive in rat studies but prohibitive in mice due to small total blood volumes. To address this issue, the geometric transfer matrix (GTM) and recovery coefficient (RC) techniques were applied using anatomical MR images to enable the extraction of partial volume corrected image based AIFs from mouse PET images. A non-invasive AIF extraction method was also developed for rats, beginning with the optimization of an automated voxel selection algorithm to assist in extracting MR contrast agent signal time courses from dynamic susceptibility contrast (DSC) MRI data. This procedure was then combined with dynamic contrast enhanced (DCE) MRI to track a combined injection of Gadolinium-based contrast agent and PET tracer through the rat brain. By comparison with gold standard tracer blood sample data, it was found that normalized MRI-based AIFs could be successfully converted into PET tracer AIFs in the first pass phase when fitted with gamma variate functions. Finally, a MR image segmentation method used to provide PET attenuation correction in mice was validated using the Cambridge split magnet PET/MR scanner?s transmission scanning capabilities. This work recommends that contributions from MR hardware in the PET field of view must be accounted forto gain accurate estimates of tracer uptake and standard uptake values (SUVs). This thesis concludes that small animal MR data taken in the same imaging session can provide non-invasive methods to improve PET image quantification, giving added value to combined PET/MR studies over those conducted using PET alone.

The side-effects of chemotherapy treatment are an increasingly important research focus as more cancer patients are reaching survivorship. While treatment allows for survival, it can also lead to problems which can significantly affect quality of life. Cognitive impairments after chemotherapy treatment are one such factor. First presented as anecdotal patient reports, over the last decade empirical evidence for this cognitive concern has been obtained. Much attention has been focused on post-chemotherapy research, yet little attention has been granted to these same patients’ cognition before treatment commences. Breast cancer (BC) patients face many obstacles before chemotherapy treatment such as: surgery and side-effects of anesthesia, increased cytokine activity, stress of a new disease diagnosis and upcoming challenges, and emotional burdens such as depression and anxiety. Many of these factors have independently been shown to affect cognitive abilities in both healthy populations as well as other patient groups. Therefore, the pre-treatment (or baseline) BC patient status warrants systematic study. This would then reduce mistakenly attributing carried-over cognitive deficits to side effects of chemotherapy. As well, it is possible that certain confounding variables may have neural manifestations at baseline that could be exacerbated by chemotherapy agents. The following thesis first presents a review paper which critically describes the current literature examining chemotherapy-related cognitive impairments (CRCIs), as well as possible confound variables affecting this population. Subsequently, three original research papers present pre-chemotherapy data showing significant neuroanatomical and neurofunctional differences in BC patients compared to controls. In particular, these neural differences are present in brain regions that have been reported in post-chemotherapy papers. This, as well as the effects of variables such as the number of days since surgery, depression and anxiety scores and more, support the initiative that research attention should increase focus on these patients at baseline in order to better understand their post-chemotherapy results.

L’utilisation intensive des produits phytosanitaires, en particulier les insecticides, provoque des effets indésirables sur les organismes vivants et leur environnement. Mon travail de thèse a consisté à évaluer l’effet de deux insecticides chez un insecte modèle la drosophile. Une première étude concernait l’effet d’un néonicotinoïde, l’imidaclopride. Nous avons pu montrer que l’exposition chronique à des doses sublétales de cet insecticide perturbe la fonction de reproduction chez la drosophile. D’autre part, une exposition aiguë à l’imidaclopride a mis en évidence une résistance chez les femelles d’une souche de drosophile dite ``des champs´´. Deux mécanismes différents ont été mis en évidence dans la résistance à l’imidaclopride de cette souche. Le premier concerne la sous expression d’une sous-unité (D1) du récepteur nicotinique à l’acétylcholine, cible de l’imidaclopride. Le deuxième concerne l’implication des glutathion S-transférases, enzymes de détoxification, dans le métabolisme de l’imidaclopride. Ces études montrent que les insecticides peuvent avoir en plus des effets sur les insectes ravageurs, des effets néfastes sur des organismes non cibles. La deuxième étude avait pour but de modéliser chez la drosophile, l’impact d’un organochloré, la dieldrine, potentiellement impliquée dans la maladie de Parkinson chez l’homme. L’exposition à cet insecticide conduit à une dégénérescence des neurones dopaminergiques ainsi qu’une perturbation de la structure de régions particulières du cerveau. Nous avons également montré des altérations du métabolisme et l’implication de processus épigénétiques dans la neurodégénérescence induite par la dieldrine. Au cours de ce travail, nous avons pu montrer l’intérêt de nouvelles méthodes comme l’Imagerie par Résonance Magnétique (IRM) ou le High Resolution Magic Angle Spinning (HRMAS) dans ce type d’étude. / Pesticides have been used extensively and induce harmful effects on organisms and their environment. The aim of my PhD work was to investigate the effects of two insecticides by using Drosophila as a model. The first study concerns the effect of a neonicotinoid, imidacloprid. The results obtained have shown that a chronic exposure at sublethal doses of this insecticide affects reproduction in flies. Moreover, acute exposure at high doses has pointed out a resistance phenomenon in females of a field strain. We have shown that two mechanisms are implicated: (i) low expression of a subunit of a nicotinic acetylcholine receptor that is the target of imidaclopride and (ii) role of glutathione S-transférases, detoxication enzymes, in imidaclopride metabolism. These results highlight impact of insecticides, in particular imidaclopride, on non target organisms. The aim of the second study was to characterize in Drosophila, effects of an organochlorine, dieldrin, potentially implicated in the etiology of Parkinson’s disease in humans. Dieldrin exposure at low doses promotes neurodegeneration of dopaminergic neurons and alters structures of particular regions of the brain. Disruption of metabolism is also induced after exposition to dieldrin. In addition, we have shown that epigenetic processes are implicated in neurodegenration induced by dieldrin. This work show advantages of new techniques such as Magnetic Resonance Imaging (MRI) and High Reslution Magic Angle Spinning in this kind of study.

Magnetic resonance imaging is a routine and powerful diagnostic technique capable of providing detailed information about the structure and composition of the tissues. This diploma thesis is concerned with the mechanisms of contrast origin and contrast modifications by molecular and nanoparticle contrast agents. First sections of the thesis summarize basic knowledge about pulse sequences and it aims to provide an overview on MRI contrast agent with a special emphasis on paramagnetic gadolinium contrast agents and superparamagnetic nanoparticles. The main purpose of this study is to develop the software called MRICalc, which is able to optimize contrast in MRI images. Based on analysis of signal formula of typical pulse sequences, MRICalc is able to propose the parameters of the pulse sequence for compartment-specific enhancement of the contrast. User chooses from the list of the samples and after calculation he obtains the values of echo time, repetition time and flip angle, all of which simultaneously seem to create the appropriate setting to enhance the contrast. MRICalc also allows to plot contrast function with respect to the chosen parameter. Software, including its graphical user interface, is designed in Python. The sample consists from solution of CuSO4 and distilled water was designed to verify the correct function of MRICalc. Sulphate represents a contrast agent. Preclinical MR system Bruker BioSpec 94/30 USR located at Institute of Scientific Instruments of the ASCR, v.v.i was used to measure contrast curve of FLASH pulse sequence, which is a typical representative of gradient echo. Results of the measurement were compared to the theoretical model provided by MRICalc.

Indiana University-Purdue University Indianapolis (IUPUI) / Alzheimer’s disease (AD) is the most common age-related neurodegenerative disease. Many researchers believe that an effective AD treatment will prevent the development of disease rather than treat the disease after a diagnosis. Therefore, the development of tools to detect AD-related pathology in early stages is an important goal. In this report, MRI-based markers of neurodegeneration are explored as biomarkers of AD. In the first chapter, the sensitivity of cross-sectional MRI biomarkers to neurodegenerative changes is evaluated in AD patients and in patients with a diagnosis of mild cognitive impairment (MCI), a prodromal stage of AD. The results in Chapter 1 suggest that cross-sectional MRI biomarkers effectively measure neurodegeneration in AD and MCI patients and are sensitive to atrophic changes in patients who convert from MCI to AD up to 1 year before clinical conversion. Chapter 2 investigates longitudinal MRI-based measures of neurodegeneration as biomarkers of AD. In Chapter 2a, measures of brain atrophy rate in a cohort of AD and MCI patients are evaluated; whereas in Chapter 2b, these measures are assessed in a pre-MCI stage, namely older adults with cognitive complaints (CC) but no significant deficits. The results from Chapter 2 suggest that dynamic MRI-based measures of neurodegeneration are sensitive biomarkers for measuring progressive atrophy associated with the development of AD. In the final chapter, a novel biomarker for AD, visual contrast sensitivity, was evaluated. The results demonstrated contrast sensitivity impairments in AD and MCI patients, as well as slightly in CC participants. Impaired contrast sensitivity was also shown to be significantly associated with known markers of AD, including cognitive impairments and temporal lobe atrophy on MRI-based measures. The results of Chapter 3 support contrast sensitivity as a potential novel biomarker for AD and suggest that future studies are warranted. Overall, the results of this report support MRI-based measures of neurodegeneration as effective biomarkers for AD, even in early clinical and preclinical disease stages. Future therapeutic trials may consider utilizing these measures to evaluate potential treatment efficacy and mechanism of action, as well as for sample enrichment with patients most likely to rapidly progress towards AD.

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