Automated Vascular Smooth Muscle Segmentation, Reconstruction, Classification and Simulation on Whole-Slide Histology

Histology of the microvasculature depicts detailed characteristics relevant to tissue perfusion. One important histologic feature is the smooth muscle component of the microvessel wall, which is responsible for controlling vessel caliber. Abnormalities can cause disease and organ failure, as seen in hypertensive retinopathy, diabetic ischemia, Alzheimer’s disease and improper cardiovascular development. However, assessments of smooth muscle cell content are conventionally performed on selected fields of view on 2D sections, which may lead to measurement bias. We have developed a software platform for automated (1) 3D vascular reconstruction, (2) detection and segmentation of muscularized microvessels, (3) classification of vascular subtypes, and (4) simulation of function through blood flow modeling. Vessels were stained for α-actin using 3,3\u27-Diaminobenzidine, assessing both normal (n=9 mice) and regenerated vasculature (n=5 at day 14, n=4 at day 28). 2D locally adaptive segmentation involved vessel detection, skeletonization, and fragment connection. 3D reconstruction was performed using our novel nucleus landmark-based registration. Arterioles and venules were categorized using supervised machine learning based on texture and morphometry. Simulation of blood flow for the normal and regenerated vasculature was performed at baseline and during demand based on the structural measures obtained from the above tools. Vessel medial area and vessel wall thickness were found to be greater in the normal vasculature as compared to the regenerated vasculature (p\u3c0.001) and a higher density of arterioles was found in the regenerated tissue (p\u3c0.05). Validation showed: a Dice coefficient of 0.88 (compared to manual) for the segmentations, a 3D reconstruction target registration error of 4 μm, and area under the receiver operator curve of 0.89 for vessel classification. We found 89% and 67% decreases in the blood flow through the network for the regenerated vasculature during increased oxygen demand as compared to the normal vasculature, respectively for 14 and 28 days post-ischemia. We developed a software platform for automated vasculature histology analysis involving 3D reconstruction, segmentation, and arteriole vs. venule classification. This advanced the knowledge of conventional histology sampling compared to whole slide analysis, the morphological and density differences in the regenerated vasculature, and the effect of the differences on blood flow and function

Morphological characterisation of unstained and intact tissue microarchitecture by x-ray computed micro- and nano-tomography

Characterisation and quantification of tissue structures is limited by sectioning-induced artefacts and by the difficulties of visualising and segmenting 3D volumes. Here we demonstrate that, even in the absence of X-ray contrast agents, X-ray computed microtomography (microCT) and nanotomography (nanoCT) can circumvent these problems by rapidly resolving compositionally discrete 3D tissue regions (such as the collagen-rich adventitia and elastin-rich lamellae in intact rat arteries) which in turn can be segmented due to their different X-ray opacities and morphologies. We then establish, using X-ray tomograms of both unpressurised and pressurised arteries that intra-luminal pressure not only increases lumen cross-sectional area and straightens medial elastic lamellae but also induces profound remodelling of the adventitial layer. Finally we apply microCT to another human organ (skin) to visualise the cell-rich epidermis and extracellular matrix-rich dermis and to show that conventional histological and immunohistochemical staining protocols are compatible with prior X-ray exposure. As a consequence we suggest that microCT could be combined with optical microscopy to characterise the 3D structure and composition of archival paraffin embedded biological materials and of mechanically stressed dynamic tissues such as the heart, lungs and tendons

Advanced perfusion quantification methods for dynamic PET and MRI data modelling

The functionality of tissues is guaranteed by the capillaries, which supply the microvascular network providing a considerable surface area for exchanges between blood and tissues. Microcirculation is affected by any pathological condition and any change in the blood supply can be used as a biomarker for the diagnosis of lesions and the optimization of the treatment. Nowadays, a number of techniques for the study of perfusion in vivo and in vitro are available. Among the several imaging modalities developed for the study of microcirculation, the analysis of the tissue kinetics of intravenously injected contrast agents or tracers is the most widely used technique. Tissue kinetics can be studied using different modalities: the positive enhancement of the signal in the computed tomography and in the ultrasound dynamic contrast enhancement imaging; T1-weighted MRI or the negative enhancement of T2* weighted MRI signal for the dynamic susceptibility contrast imaging or, finally, the uptake of radiolabelled tracers in dynamic PET imaging. Here we will focus on the perfusion quantification of dynamic PET and MRI data. The kinetics of the contrast agent (or the tracer) can be analysed visually, to define qualitative criteria but, traditionally, quantitative physiological parameters are extracted with the implementation of mathematical models. Serial measurements of the concentration of the tracer (or of the contrast agent) in the tissue of interest, together with the knowledge of an arterial input function, are necessary for the calculation of blood flow or perfusion rates from the wash-in and/or wash-out kinetic rate constants. The results depend on the acquisition conditions (type of imaging device, imaging mode, frequency and total duration of the acquisition), the type of contrast agent or tracer used, the data pre-processing (motion correction, attenuation correction, correction of the signal into concentration) and the data analysis method. As for the MRI, dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) is a non-invasive imaging technique that can be used to measure properties of tissue microvasculature. It is sensitive to differences in blood volume and vascular permeability that can be associated with tumour angiogenesis. DCE-MRI has been investigated for a range of clinical oncologic applications (breast, prostate, cervix, liver, lung, and rectum) including cancer detection, diagnosis, staging, and assessment of treatment response. Tumour microvascular measurements by DCE-MRI have been found to correlate with prognostic factors (such as tumour grade, microvessel density, and vascular endothelial growth factor expression) and with recurrence and survival outcomes. Furthermore, DCE-MRI changes measured during treatment have been shown to correlate with outcome, suggesting a role as a predictive marker. The accuracy of DCE-MRI relies on the ability to model the pharmacokinetics of an injected contrast agent using the signal intensity changes on sequential magnetic resonance images. DCE-MRI data are usually quantified with the application of the pharmacokinetic two-compartment Tofts model (also known as the standard model), which represents the system with the plasma and tissue (extravascular extracellular space) compartments and with the contrast reagent exchange rates between them. This model assumes a negligible contribution from the vascular space and considers the system in, what-is-known as, the fast exchange limit, assuming infinitely fast transcytolemmal water exchange kinetics. In general, the number, as well as any assumption about the compartments, depends on the properties of the contrast agent used (mainly gadolinium) together with the tissue physiology or pathology studied. For this reason, the choice of the model is crucial in the analysis of DCE-MRI data. The value of PET in clinical oncology has been demonstrated with studies in a variety of cancers including colorectal carcinomas, lung tumours, head and neck tumours, primary and metastatic brain tumours, breast carcinoma, lymphoma, melanoma, bone cancers, and other soft-tissue cancers. PET studies of tumours can be performed for several reasons including the quantification of tumour perfusion, the evaluation of tumour metabolism, the tracing of radiolabelled cytostatic agents. In particular, the kinetic analysis of PET imaging has showed, in the past few years, an increasing value in tumour diagnosis, as well as in tumour therapy, through providing additional indicative parameters. Many authors have showed the benefit of kinetic analysis of anticancer drugs after labelling with radionuclide in measuring the specific therapeutic effect bringing to light the feasibility of applying the kinetic analysis to the dynamic acquisition. Quantification methods can involve visual analysis together with compartmental modelling and can be applied to a wide range of different tracers. The increased glycolysis in the most malignancies makes 18F-FDG-PET the most common diagnostic method used in tumour imaging. But, PET metabolic alteration in the target tissue can depend by many other factors. For example, most types of cancer are characterized by increased choline transport and by the overexpression of choline kinase in highly proliferating cells in response to enhanced demand of phosphatidylcholine (prostate, breast, lung, ovarian and colon cancers). This effect can be diagnosed with choline-based tracers as the 18Ffluoromethylcholine (18F-FCH), or the even more stable 18F-D4-Choline. Cellular proliferation is also imaged with 18F-fluorothymidine (FLT), which is trapped within the cytosol after being mono phosphorylated by thymidine kinase-1 (TK1), a principal enzyme in the salvage pathway of DNA synthesis. 18F-FLT has been found to be useful for noninvasive assessment of the proliferation rate of several types of cancer and showed high reproducibility and accuracy in breast and lung cancer tumours. The aim of this thesis is the perfusion quantification of dynamic PET and MRI data of patients with lung, brain, liver, prostate and breast lesions with the application of advanced models. This study covers a wide range of imaging methods and applications, presenting a novel combination of MRI-based perfusion measures with PET kinetic modelling parameters in oncology. It assesses the applicability and stability of perfusion quantification methods, which are not currently used in the routine clinical practice. The main achievements of this work include: 1) the assessment of the stability of perfusion quantification of D4-Choline and 18F-FLT dynamic PET data in lung and liver lesions, respectively (first applications in the literature); 2) the development of a model selection in the analysis of DCE-MRI data of primary brain tumours (first application of the extended shutter speed model); 3) the multiparametric analysis of PET and MRI derived perfusion measurements of primary brain tumour and breast cancer together with the integration of immuohistochemical markers in the prediction of breast cancer subtype (analysis of data acquired on the hybrid PET/MRI scanner). The thesis is structured as follows: - Chapter 1 is an introductive chapter on cancer biology. Basic concepts, including the causes of cancer, cancer hallmarks, available cancer treatments, are described in this first chapter. Furthermore, there are basic concepts of brain, breast, prostate and lung cancers (which are the lesions that have been analysed in this work). - Chapter 2 is about Positron Emission Tomography. After a brief introduction on the basics of PET imaging, together with data acquisition and reconstruction methods, the chapter focuses on PET in the clinical settings. In particular, it shows the quantification techniques of static and dynamic PET data and my results of the application of graphical methods, spectral analysis and compartmental models on dynamic 18F-FDG, 18F-FLT and 18F-D4- Choline PET data of patients with breast, lung cancer and hepatocellular carcinoma. - Chapter 3 is about Magnetic Resonance Imaging. After a brief introduction on the basics of MRI, the chapter focuses on the quantification of perfusion weighted MRI data. In particular, it shows the pharmacokinetic models for the quantification of dynamic contrast enhanced MRI data and my results of the application of the Tofts, the extended Tofts, the shutter speed and the extended shutter speed models on a dataset of patients with brain glioma. - Chapter 4 introduces the multiparametric imaging techniques, in particular the combined PET/CT and the hybrid PET/MRI systems. The last part of the chapter shows the applications of perfusion quantification techniques on a multiparametric study of breast tumour patients, who simultaneously underwent DCE-MRI and 18F-FDG PET on a hybrid PET/MRI scanner. Then the results of a predictive study on the same dataset of breast tumour patients integrated with immunohistochemical markers. Furthermore, the results of a multiparametric study on DCE-MRI and 18F-FCM brain data acquired both on a PET/CT scanner and on an MR scanner, separately. Finally, it will show the application of kinetic analysis in a radiomic study of patients with prostate cancer

Laser doppler perfusion imaging of the normal and diseased vulva.

Vulval lichen sclerosus (LS) and high-grade intraepithelial neoplasia (VIN 3) are two common and distressing diseases. Significant morbidity is caused by symptoms of persistent pruritus and surgical treatment of skin areas suspicious of malignancy. The risk of developing cancer in a background of LS and VIN 3 is poorly defined. The methods currently available for clinical assessment of the vulva are limited. There is abundant research on the application of the LASER Doppler technique - laser Doppler Flowmetry (LDF) - showing changes in perfusion within the small blood vessels of the skin as a useful parameter for more accurate disease classification. There is also research on immunohistochemical microvessel density (MVD) studies showing increases in blood supply in tissues prone to develop cancer or as a prognostic marker of cancer outcome. The Laser Doppler perfusion imager (LDPI) provides a rapid, real time, non-invasive and non-contact method to measure skin blood flow in an area as opposed to a single point by the LDF, making the LDPI more suitable for application to the vulva. This thesis reports for the first time, the application of the LDPI to the vulva. Initially the LDPI was applied to the clinically normal vulva to study perfusion variance related to menstrual cycle, age and local skin temperature provocation. The application was then extended to vulval disease, LS and VIN 3, and validated against morphological differences in MVD. The LDPI and MVD studies suggest that in VIN 3 there is an actual increase in skin perfusion. In LS the situation is more complex and suggests that the LDPI measured perfusion at a greater depth than the MVD. Studies on base line perfusion variance of vulval LS to topical therapy show that there is no overall difference in baseline perfusion in spite of symptom improvement. Temperature provocation studies suggest differences in skin blood flow response in diseased compared to the normal vulva

Emerging radiopharmaceuticals for PET-imaging gliomas. A multi-: radiopharmaceutical, camera, modality, model, and modelling assessment

Gliomas, which are a type of brain tumour derived from the non-neuronal and nutrient-supplying glial cells of the brain, are particularly devastating disease due to the importance and delicate nature of cerebral matter. Surgical removal, chemotherapy, and radiation therapy often have unwanted consequences depending on a variety of physiological and probability factors. With the human life expectancy averaging 12-15 months after clinical diagnosis (with treatment) for aggressive brain tumours, accurately detecting and characterizing these tumours non-invasively is important for treatment planning. Currently, the highest anatomical resolution imaging modality available for brain imaging is magnetic resonance imaging (MRI), but this lacks biochemical information. Positron emission tomography paired with computed tomography for anatomical reference (PET-CT) divulges quantifiable biochemical information. By selecting imaging radiopharmaceuticals for PET imaging that have relevance to tumour surface proteins or other cellular metabolic processes it is possible to not only aid in detecting or delineating gliomas, but also gain specific biochemical-property insight into these lesions. The aim of these studies was to evaluate the two emerging radiopharmaceuticals (2S, 4R)-4-[18F]fluoroglutamine ([18F]FGln) and Al[18F]F-NOTA-Folate ([18F]FOL) and to directly compare them with routinely clinically-used radiopharmaceuticals 2-deoxy-2-[18F]fluoro-ᴅ-glucose ([18F]FDG) and ʟ-[11C]methionine ([11C]Met) for the PET imaging of gliomas in animal models. Other parameters, such as the in vivo stability, ex vivo biodistribution, in vitro binding and blocking, and the presence of relevant receptors on human tissue samples were investigated in to divulge additional information. The results demonstrated that both [18F]FGln and [18F]FOL provided an enhanced level of contrast between tumour and adjacent non-tumour brain tissue versus that of the clinically used radiopharmaceuticals [18F]FDG and [11C]Met in animal models.Uudet radiolääkeaineet glioomien PET-kuvantamiseen. Tutkimuksia radiolääkeaineista, modaliteeteista, kameroista, kokeellisista malleista ja mallintamisesta Glioomat ovat aivokasvaimia, jotka syntyvät ravinteiden kuljetusta hoitavista glia- eli hermotukisoluista. Ne ovat erityisen tuhoisia sairauksia aivokudoksen tärkeyden ja herkkyyden vuoksi. Kirurgisella leikkauksella, kemoterapialla, ja sädehoidolla on usein ei-toivottuja seurauksia riippuen fysiologisista ja todennäköisyystekijöistä. Koska elinajanodote aggressiivisen aivokasvaimen diagnoosin jälkeen on keskimäärin 12–15 kuukautta (hoidon kanssa), ei-invasiivinen tarkka havaitseminen ja karakterisointi on tärkeää hoidon suunnittelussa. Tällä hetkellä parhaat työkalut aivojen kuvantamiseen ovat magneettikuvaus (MRI), joka mahdollistaa parhaimman anatomisen tarkkuuden, ja positroniemissiotomografia (PET), joka paljastaa biokemiallisen informaation. Valitsemalle PET-kuvantamiseen radiolääkeaine, joka kiinnittyy syöpäsolun pintaproteiineihin tai liittyy solun aineenvaihduntaprosessiin on mahdollista paitsi havaita tai rajata glioomia, myös saada erityistä biokemiallista tietoa näistä leesioista. Tämän tutkimuksen tavoitteena oli arvioida kahta uutta radiolääkeainetta; (2S, 4R)-4-[18F]fluoriglutamiinia ([18F]FGln) ja Al[18F]F-NOTA-folaattia ([18F]FOL) ja verrata niitä kliinisessä käytössä oleviin 2-deoxy-2-[18F]fluori-ᴅ-glukoosiin ([18F]FDG) ja ʟ-[11C]metioniiniin ([11C]Met) glioomien PET-kuvantamisessa. Stabiilisuutta, biologista jakautumista, sitoutumista ja sitoutumisen salpautumista, sekä farmakokineettista mallintamista tutkittiin in vivo, ex vivo ja in vitro olosuhteissa eläinmalleissa ja kudosnäytteillä. Tulokset osoittivat, että eläinmalleissa sekä [18F]FGln että [18F]FOL mahdollistavat paremman kontrastin tuumorin ja viereisen tuumorittoman aivokudoksen välillä verrattuna kliinisessä käytössä oleviin [18F]FDG ja [11C]Met radiolääkeaineisiin

Development of three-dimensional, ex vivo optical imaging

The ability to analyse tissue in 3-D at the mesoscopic scale (resolution: 2-50 µm) has proven essential in the study of whole specimens and individual organs. Techniques such as ex vivo magnetic resonance imaging (MRI) and X-ray computed tomography (CT) have been successful in a number of applications. Although MRI has been used to image embryo development and gene expression in 3-D, its resolution is not sufficient to discriminate between the small structures in embryos and individual organs. Furthermore, since neither MRI nor X-ray CT are optical imaging techniques, none of them is able to make use of common staining techniques. 3-D images can be generated with confocal microscopy by focusing a laser beam to a point within the sample and collecting the fluorescent light coming from that specific plane, eliminating therefore out-of-focus light. However, the main drawback of this microscopy technique is the limited depth penetration of light (~1 mm). Tomographic techniques such as optical projection tomography (OPT) and light sheet fluorescence microscopy (also known as single plane illumination microscopy, SPIM) are novel methods that fulfil a requirement for imaging of specimens which are too large for confocal imaging and too small for conventional MRI. To allow sufficient depth penetration, these approaches require specimens to be rendered transparent via a process known as optical clearing, which can be achieved using a number of techniques. The aim of the work presented in this thesis was to develop methods for threedimensional, ex vivo optical imaging. This required, in first instance, sample preparation to clear (render transparent) biological tissue. In this project several optical clearing techniques have been tested in order to find the optimal method per each kind of tissue, focusing on tumour tissue. Indeed, depending on its structure and composition (e.g. amount of lipids or pigments within the tissue) every tissue clears at a different degree. Though there is currently no literature reporting quantification of the degree of optical clearing. Hence a novel, spectroscopic technique for measuring the light attenuation in optically cleared samples is described in this thesis and evaluated on mouse brain. 5 Optical clearing was applied to the study of cancer. The main cancer model investigated in this report is colorectal carcinoma. Fluorescently labelled proteins were used to analyse the vascular network of colorectal xenograft tumours and to prove the effect of vascular disrupting agents on the vascular tumour network. Furthermore, optical clearing and fluorescent compounds were used for ex vivo analysis of perfusion of a human colorectal liver metastasis model

Understanding quantitative DCE-MRI of the breast : towards meaningful clinical application

In most industrialized countries breast cancer will affect one out of eight women during her lifetime. In the USA, after continuously increasing for more than two decades, incidence rates are slowly decreasing since 2001. Since 1990, death rates from breast cancer have steadily decreased in women, which is attributed to both earlier detection and improved treatment. Still, it is second only to lung cancer as a cause of cancer death in women. In this work we set out to improve early detection of breast cancer via quantitative analysis of magnetic resonance images (MRI). Screening and diagnosis of breast cancer are generally performed using X-ray mammography, possibly in conjunction with ultrasonography. However, MRI is becoming an important modality for screening of women at high-risk due to for instance hereditary gene mutations, as a problem-solving tool in case of indecisive mammographic and / or ultrasonic imaging, and for anti-cancer therapy assessment. In this work, we focused on MR imaging of the breast. More specifically, the dynamic contrast-enhanced (DCE) part of the protocol was highlighted, as well as radiological assessment of DCE-MRI data. The T_1-weighted (T_1: longitudinal relaxation time, a tissue property) signal-versus-time curve that can be extracted from the DCE-MRI series that is acquired at the time of and after injection of a T_1-shortening (shorter T_1 results in higher signal) contrast agent, is usually visually assessed by the radiologist. For example, a fast initial rise to the peak (1-2 minutes post injection) followed by loss of signal within a time frame of about 5-6 minutes is a sign for malignancy, whereas a curve showing persistent (slow) uptake within the same time frame is a sign for benignity. This difference in contrast agent uptake pattern is related to physiological changes in tumorous tissue that for instance result in a stronger uptake of the contrast agent. However, this descriptive way of curve type classification is based on clinical statistics, not on knowledge about tumor physiology. We investigated pharmacokinetic modeling as a quantitative image analysis tool. Pharmacokinetics describes what happens to a substance (e.g. drug or contrast agent) after it has been administered to a living organism. This includes the mechanisms of absorption and distribution. The terms in which these mechanisms are described are physiological and can therefore provide parameters describing the functioning of the tissue. This physiological aspect makes it an attractive approach to investigate (aberrant) tissue functioning. In addition, this type of analysis excludes confounding factors due to inter- and intra-patient differences in the systemic blood circulation, as well as differences in the injection protocol. In this work, we discussed the physiological basis and details of different types of pharmacokinetic models, with the focus on compartmental models. Practical implications such as obtaining an arterial input function and model parameter estimation were taken into account as well. A simulation study of the data-imposed limitations – in terms of temporal resolution and noise properties – on the complexity of pharmacokinetic models led to the insight that only one of the tested models, the basic Tofts model, is applicable to DCE-MRI data of the breast. For the basic Tofts model we further investigated the aspect of temporal resolution, because a typical diagnostic DCE-MRI scan of the breast is acquired at a rate of about 1 image volume every minute; whereas pharmacokinetic modeling usually requires a sampling time of less than 10 s. For this experiment we developed a new downsampling method using high-temporal-resolution raw k-space data to simulate what uptake curves would have looked like if they were acquired at lower temporal resolutions. We made use of preclinical animal data. With this data we demonstrated that the limit of 10 s can be stretched to about 1 min if the arterial input function (AIF, the input to the pharmacokinetic model) is inversely derived from a healthy reference tissue, instead of measured in an artery or taken from the literature. An important precondition for the application of pharmacokinetic modeling is knowledge of the relationship between the acquired DCE-MRI signal and the actual concentration of the contrast agent in the tissue. This relationship is not trivial because with MRI we measure the indirect effect of the contrast agent on water protons. To establish this relationship via calculation of T_1 (t), we investigated both a theoretical and an empirical approach, making use of an in-house (University of Chicago) developed reference object that is scanned concurrently with the patient. The use of the calibration object can shorten the scan duration (an empirical approach requires less additional scans than an approach using a model of the acquisition technique), and can demonstrate if theoretical approaches are valid. Moreover we produced concentration images and estimated tissue proton density, also making use of the calibration object. Finally, via pharmacokinetic modeling and other MRI-derived measures we partly revealed the actions of a novel therapeutic in a preclinical study. In particular, the anti-tumor activity of a single dose of liposomal prednisolone phosphate was investigated, which is an anti-inflammatory drug that has demonstrated tumor growth inhibition. The work presented in this thesis contributes to a meaningful clinical application and interpretation of quantitative DCE-MRI of the breast