Good Gottesman-Kitaev-Preskill codes from the NTRU cryptosystem

We introduce a new class of random Gottesman-Kitaev-Preskill (GKP) codes derived from the cryptanalysis of the so-called NTRU cryptosystem. The derived codes are good in that they exhibit constant rate and average distance scaling Δ∝√n with high probability, where n is the number of bosonic modes, which is a distance scaling equivalent to that of a GKP code obtained by concatenating single mode GKP codes into a qubit-quantum error correcting code with linear distance. The derived class of NTRU-GKP codes has the additional property that decoding for a stochastic displacement noise model is equivalent to decrypting the NTRU cryptosystem, such that every random instance of the code naturally comes with an efficient decoder. This construction highlights how the GKP code bridges aspects of classical error correction, quantum error correction as well as post-quantum cryptography. We underscore this connection by discussing the computational hardness of decoding GKP codes and propose, as a new application, a simple public key quantum communication protocol with security inherited from the NTRU cryptosystem

Application of artificial vision algorithms to images of microscopy and spectroscopy for the improvement of cancer diagnosis

El diagnóstico final de la mayoría de tipos de cáncer lo realiza un médico experto en anatomía patológica que examina muestras tisulares o celulares sospechosas extraídas del paciente. Actualmente, esta evaluación depende en gran medida de la experiencia del médico y se lleva a cabo de forma cualitativa mediante técnicas de imagen tradicionales como la microscopía óptica. Esta tarea tediosa está sujeta a altos grados de subjetividad y da lugar a niveles de discordancia inadecuados entre diferentes patólogos, especialmente en las primeras etapas de desarrollo del cáncer. La espectroscopía infrarroja por Transformada de Fourier (siglas FTIR en inglés) es una tecnología ampliamente utilizada en la industria que recientemente ha demostrado una capacidad creciente para mejorar el diagnóstico de diferentes tipos de cáncer. Esta técnica aprovecha las propiedades del infrarrojo medio para excitar los modos vibratorios de los enlaces químicos que forman las muestras biológicas. La principal señal generada consiste en un espectro de absorción que informa sobre la composición química de la muestra iluminada. Los microespectrómetros FTIR modernos, compuestos por complejos componentes ópticos y detectores matriciales de alta sensibilidad, permiten capturar en un laboratorio de investigación común imágenes hiperespectrales de alta calidad que aúnan información química y espacial. Las imágenes FTIR son estructuras de datos ricas en información que se pueden analizar individualmente o junto con otras modalidades de imagen para realizar diagnósticos patológicos objetivos. Por lo tanto, esta técnica de imagen emergente alberga un alto potencial para mejorar la detección y la graduación del riesgo del paciente en el cribado y vigilancia de cáncer. Esta tesis estudia e implementa diferentes metodologías y algoritmos de los campos interrelacionados de procesamiento de imagen, visión por ordenador, aprendizaje automático, reconocimiento de patrones, análisis multivariante y quimiometría para el procesamiento y análisis de imágenes hiperespectrales FTIR. Estas imágenes se capturaron con un moderno microscopio FTIR de laboratorio a partir de muestras de tejidos y células afectadas por cáncer colorrectal y de piel, las cuales se prepararon siguiendo protocolos alineados con la práctica clínica actual. Los conceptos más relevantes de la espectroscopía FTIR se investigan profundamente, ya que deben ser comprendidos y tenidos en cuenta para llevar a cabo una correcta interpretación y tratamiento de sus señales especiales. En particular, se revisan y analizan diferentes factores fisicoquímicos que influyen en las mediciones espectroscópicas en el caso particular de muestras biológicas y pueden afectar críticamente su análisis posterior. Todos estos conceptos y estudios preliminares entran en juego en dos aplicaciones principales. La primera aplicación aborda el problema del registro o alineación de imágenes hiperespectrales FTIR con imágenes en color adquiridas con microscopios tradicionales. El objetivo es fusionar la información espacial de distintas muestras de tejido medidas con esas dos modalidades de imagen y centrar la discriminación en las regiones seleccionadas por los patólogos, las cuales se consideran más relevantes para el diagnóstico de cáncer colorrectal. En la segunda aplicación, la espectroscopía FTIR se lleva a sus límites de detección para el estudio de las entidades biomédicas más pequeñas. El objetivo es evaluar las capacidades de las señales FTIR para discriminar de manera fiable diferentes tipos de células de piel que contienen fenotipos malignos. Los estudios desarrollados contribuyen a la mejora de métodos de decisión objetivos que ayuden al patólogo en el diagnóstico final del cáncer. Además, revelan las limitaciones de los protocolos actuales y los problemas intrínsecos de la tecnología FTIR moderna, que deberían abordarse para permitThe final diagnosis of most types of cancers is performed by an expert clinician in anatomical pathology who examines suspicious tissue or cell samples extracted from the patient. Currently, this assessment largely relies on the experience of the clinician and is accomplished in a qualitative manner by means of traditional imaging techniques, such as optical microscopy. This tedious task is subject to high degrees of subjectivity and gives rise to suboptimal levels of discordance between different pathologists, especially in early stages of cancer development. Fourier Transform infrared (FTIR) spectroscopy is a technology widely used in industry that has recently shown an increasing capability to improve the diagnosis of different types of cancer. This technique takes advantage of the ability of mid-infrared light to excite the vibrational modes of the chemical bonds that form the biological samples. The main generated signal consists of an absorption spectrum that informs of the chemical composition of the illuminated specimen. Modern FTIR microspectrometers, composed of complex optical components and high-sensitive array detectors, allow the acquisition of high-quality hyperspectral images with spatially-resolved chemical information in a common research laboratory. FTIR images are information-rich data structures that can be analysed alone or together with other imaging modalities to provide objective pathological diagnoses. Hence, this emerging imaging technique presents a high potential to improve the detection and risk stratification in cancer screening and surveillance. This thesis studies and implements different methodologies and algorithms from the related fields of image processing, computer vision, machine learning, pattern recognition, multivariate analysis and chemometrics for the processing and analysis of FTIR hyperspectral images. Those images were acquired with a modern benchtop FTIR microspectrometer from tissue and cell samples affected by colorectal and skin cancer, which were prepared by following protocols close to the current clinical practise. The most relevant concepts of FTIR spectroscopy are thoroughly investigated, which ought to be understood and considered to perform a correct interpretation and treatment of its special signals. In particular, different physicochemical factors are reviewed and analysed, which influence the spectroscopic measurements for the particular case of biological samples and can critically affect their later analysis. All these knowledge and preliminary studies come into play in two main applications. The first application tackles the problem of registration or alignment of FTIR hyperspectral images with colour images acquired with traditional microscopes. The aim is to fuse the spatial information of distinct tissue samples measured by those two imaging modalities and focus the discrimination on regions selected by the pathologists, which are meant to be the most relevant areas for the diagnosis of colorectal cancer. In the second application, FTIR spectroscopy is pushed to their limits of detection for the study of the smallest biomedical entities. The aim is to assess the capabilities of FTIR signals to reliably discriminate different types of skin cells containing malignant phenotypes. The developed studies contribute to the improvement of objective decision methods to support the pathologist in the final diagnosis of cancer. In addition, they reveal the limitations of current protocols and intrinsic problems of modern FTIR technology, which should be tackled in order to enable its transference to anatomical pathology laboratories in the future.El diagnòstic final de la majoria de tipus de càncer ho realitza un metge expert en anatomia patològica que examina mostres tissulars o cel¿lulars sospitoses extretes del pacient. Actualment, aquesta avaluació depèn en gran part de l'experiència del metge i es porta a terme de forma qualitativa mitjançant tècniques d'imatge tradicionals com la microscòpia òptica. Aquesta tasca tediosa està subjecta a alts graus de subjectivitat i dóna lloc a nivells de discordança inadequats entre diferents patòlegs, especialment en les primeres etapes de desenvolupament del càncer. L'espectroscòpia infraroja per Transformada de Fourier (sigles FTIR en anglès) és una tecnologia àmpliament utilitzada en la indústria que recentment ha demostrat una capacitat creixent per millorar el diagnòstic de diferents tipus de càncer. Aquesta tècnica aprofita les propietats de l'infraroig mitjà per excitar els modes vibratoris dels enllaços químics que formen les mostres biològiques. El principal senyal generat consisteix en un espectre d'absorció que informa sobre la composició química de la mostra il¿luminada. Els microespectrómetres FTIR moderns, compostos per complexos components òptics i detectors matricials d'alta sensibilitat, permeten capturar en un laboratori d'investigació comú imatges hiperespectrals d'alta qualitat que uneixen informació química i espacial. Les imatges FTIR són estructures de dades riques en informació que es poden analitzar individualment o juntament amb altres modalitats d'imatge per a realitzar diagnòstics patològics objectius. Per tant, aquesta tècnica d'imatge emergent té un alt potencial per a millorar la detecció i la graduació del risc del pacient en el cribratge i vigilància de càncer. Aquesta tesi estudia i implementa diferents metodologies i algoritmes dels camps interrelacionats de processament d'imatge, visió per ordinador, aprenentatge automàtic, reconeixement de patrons, anàlisi multivariant i quimiometria per al processament i anàlisi d'imatges hiperespectrals FTIR. Aquestes imatges es van capturar amb un modern microscopi FTIR de laboratori a partir de mostres de teixits i cèl¿lules afectades per càncer colorectal i de pell, les quals es van preparar seguint protocols alineats amb la pràctica clínica actual. Els conceptes més rellevants de l'espectroscòpia FTIR s'investiguen profundament, ja que han de ser compresos i tinguts en compte per dur a terme una correcta interpretació i tractament dels seus senyals especials. En particular, es revisen i analitzen diferents factors fisicoquímics que influeixen en els mesuraments espectroscòpiques en el cas particular de mostres biològiques i poden afectar críticament la seua anàlisi posterior. Tots aquests conceptes i estudis preliminars entren en joc en dues aplicacions principals. La primera aplicació aborda el problema del registre o alineació d'imatges hiperespectrals FTIR amb imatges en color adquirides amb microscopis tradicionals. L'objectiu és fusionar la informació espacial de diferents mostres de teixit mesurades amb aquestes dues modalitats d'imatge i centrar la discriminació en les regions seleccionades pels patòlegs, les quals es consideren més rellevants per al diagnòstic de càncer colorectal. En la segona aplicació, l'espectroscòpia FTIR es porta als seus límits de detecció per a l'estudi de les entitats biomèdiques més xicotetes. L'objectiu és avaluar les capacitats dels senyals FTIR per discriminar de manera fiable diferents tipus de cèl¿lules de pell que contenen fenotips malignes. Els estudis desenvolupats contribueixen a la millora de mètodes de decisió objectius que ajuden el patòleg en el diagnòstic final del càncer. A més, revelen les limitacions dels protocols actuals i els problemes intrínsecs de la tecnologia FTIR moderna, que haurien d'abordar per permetre la seva transferència als laboratoris d'anatomia patològica en el futur.Peñaranda Gómez, FJ. (2018). Application of artificial vision algorithms to images of microscopy and spectroscopy for the improvement of cancer diagnosis [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/99748TESI

Screening of Human Serum/Plasma using Vibrational Spectroscopy for Early Disease Diagnostics and Therapeutic Drug Monitoring

Analysis of analytes present in the blood stream can potentially deliver crucial information on patient health and indicate the presence of numerous pathologies. Existing clinical techniques for this analysis can, however, be costly and time-consuming. The potential of Raman spectroscopic analysis of human plasma and/or serum for diagnostic purposes has been widely investigated and, increasingly, its feasibility for clinical translation has been explored. However, as the concentration of many analytes in plasma/serum is relatively low, to date such analysis has commonly been performed on air-dried drops deposited on substrates, leading to inhomogeneity and inconsistencies. This study explores the potential of Raman spectroscopy, coupled with fractionation and concentration techniques, as well as multivariate regression analysis, to quantitatively monitor diagnostically relevant changes in high and low molecular weight proteins as well as therapeutic drugs, in liquid plasma/serum. Having optimised the protocols for pure aqueous solutions and spiked serum samples, measurement protocols to detect the imbalances in plasma/serum analytes (fibrinogen, albumin, γ globulins, total protein content, glucose and urea), as an indicator of various diseases, and therapeutic monitoring of drugs (busulfan and methotrexate), using Raman spectroscopy were optimised in liquid serum, such that strategic clinical applications for early stage disease diagnostics and therapeutic drug monitoring can be evaluated. Furthermore, an adapted Extended Multiplicative Signal Correction algorithm was applied to raw spectra to remove background signal and spectral interferents. Using a validated partial least squares regression method, prediction models were built for the analytes, with accuracies which are comparable with those reported for the conventional methods, without any additional sample preparation steps. This methodology was extended to determine the Limit of Detection (LOD) and Limit of Quantification (LOQ) for therapeutic drug monitoring in human serum, using the examples of Busulfan, a cell cycle non-specific alkylating antineoplastic agent, and, Methotrexate, a chemotherapeutic agent. This study demonstrates the options and alternatives that are available to make Raman spectroscopy suitable for the human bodily fluid analysis in the liquid form, leading to a better accuracy and repeatability and thus a better sensitivity

Optimisation and applications of chemical exchange saturation transfer MRI techniques for cancer imaging on clinical scanners

Chemical Exchange Saturation Transfer (CEST) is receiving growing attention in the field of cancer imaging due to its ability to provide molecular information with good spatial resolution within clinically acceptable scan-times. Translation to the clinic requires a solid evidence-base demonstrating the clinical utility and a range of anatomical regions and pathologies have already been studied. These have traditionally been evaluated in terms of asymmetry-based metrics, the most common of which is the magnetization transfer ratio. However, alternative and potentially more informative metrics are also possible. Investigation of fitting metrics has not been reported at clinical field strengths and there is currently no standard approach for optimising the acquisition and post-processing protocols. The work described in this thesis focuses on the practical development and implementation of z-spectrum fitting methods in vivo at 3.0T. After the technical and clinical introductory chapters, chapter three describes the evaluation and comparison of the use of two different lineshapes for modelling the water direct saturation effect. Chapter four describes the optimization of an acquisition and post-processing protocol suitable for CEST imaging of the human prostate at 3.0T. The repeatability of the method is evaluated and in chapter five the optimized protocol is applied in two cancer patients. In chapter six a method is proposed for identification of CEST and NOE resonances in z- spectra acquired at low-field strengths. Chapter seven describes a pre-clinical study of healthy rat brains at 9.4T highlighting the need to consider the interplay between CEST and perfusion effects. In chapter eight the effects of gadolinium administration on CEST signal and contrast in glioma patients is investigated. I hope that the work described herein and the contributions stemming from it will be of some practical benefit to scientists and clinicians interested in exploring the future potential of the growing field of CEST imaging

Imidazole and beta-carotene photoprotection against photodynamic therapy evaluated by synchrotron infrared microscopy

In order to better understand the role of β-carotene and imidazole on the Photodynamic Therapy (PDT) mechanism, synchrotron infrared microscopywas used to detect the associated intracellular biochemical modifications following the visible light irradiation of HeLa cells incubated with these compounds as typical hydrophobic and hydrophilic singlet oxygen quenchers, respectively. For this purpose, PDT was performed employing the hydrophilic sensitizer 5,10,15,20-Tetrakis (1-methyl-4-pyridinio) porphyrin tetra (p-toluenesulfonate), TMPyP, and the hydrophobic sensitizer 5-(4-Methoxycarboxyphenyl)-10,15,20-triphenyl-21H,23H–porphyrin. The single cell IR spectra of PDT-treated, PDT plus quencher-treated and control HeLa cellswere recorded at the SOLEIL Synchrotron Infrared SMIS beamline targeting specifically the cell nucleus. Principal Component Analysis (PCA) was used to assess the IR spectral changes. PCA revealed that there is a frequency shift of the protein Amide I vibrational band for the assays with the TMPyP sensitizer, indicating changes in the protein secondary structures of the PDT-treated cancer cells compared to the controls. In addition, the scores in those cells treated with both quenchers appear to be similar to the controls indicating a photoprotective effect. Comparative experiments carried out with SKMEL-28 and HaCat cells showed non- significant photoprotective effects of β-carotene and imidazole.Instituto de Investigaciones Fisicoquímicas Teóricas y AplicadasInstituto Multidisciplinario de Biología Celula

Magnetic resonance imaging of resting cerebral oxygen metabolism : applications in Alzheimer’s disease

The BOLD contrast employed in functional MRI studies is an ambiguous signal composed of changes in blood flow, blood volume and oxidative metabolism. In situations where the vasculature and metabolism may have been affected, such as in aging and in certain diseases, the dissociation of the more physiologically-specific components from the BOLD signal becomes crucial. The latest generation of calibrated functional MRI methods allows the estimation of both resting blood flow and absolute oxygen metabolism. The work presented here is based on one such proof-of-concept approach, dubbed QUO2, whereby taking into account, within a generalized model, both arbitrary changes in blood flow and blood O2 content during a combination of hypercapnia and hyperoxia breathing manipulations, yields voxel-wise estimates of resting oxygen extraction fraction and oxidative metabolism. In the first part of this thesis, the QUO2 acquisition protocol and data analysis were revisited in order to enhance the temporal stability of individual blood flow and BOLD responses, consequently improving reliability of the model-derived estimates. Thereafter, an assessment of the within and between-subject variability of the optimized QUO2 measurements was performed on a group of healthy volunteers. In parallel, an analysis was performed of the sensitivity of the model to different sources of random and systematic errors, respectively due to errors in measurements and choice of assumed parameters values. Moreover, the various impacts of the oxygen concentration administered during the hyperoxia manipulation were evaluated through a simulation and experimentally, indicating that a mild hyperoxia was beneficial. Finally, the influence of Alzheimer’s disease in vascular and metabolic changes was explored for the first time by applying the QUO2 approach in a cohort of probable Alzheimer’s disease patients and age-matched control group. Voxel-wise and region-wise differences in resting blood flow, oxygen extraction fraction, oxidative metabolism, transverse relaxation rate constant R2* and R2* changes during hypercapnia were identified. A series of limitations along with recommended solutions was given with regards to the delayed transit time, the susceptibility artifacts and the challenge of performing a hypercapnia manipulation in cohorts of elderly and Alzheimer’s patients.Le contraste BOLD employé dans les études d’imagerie par résonance magnétique fonctionnelle (IRMf) provient d’une combinaison ambigüe de changements du flux sanguin cérébral, du volume sanguin ainsi que du métabolisme oxydatif. Dans un contexte où les fonctions vasculaires ou métaboliques du cerveau ont pu être affectées, tel qu’avec l’âge ou certaines maladies, il est crucial d’effectuer une décomposition du signal BOLD en composantes physiologiquement plus spécifiques. La dernière génération de méthodes d’IRMf calibrée permet d’estimer à la fois le flux sanguin cérébral et le métabolisme oxydatif au repos. Le présent travail est basé sur une telle technique, appelée QUantitative O2 (QUO2), qui, via un model généralisé, prend en considération les changements du flux sanguin ainsi que ceux en concentrations sanguine d’O2 durant des périodes d’hypercapnie et d’hyperoxie, afin d’estimer, à chaque voxel, la fraction d’extraction d’oxygène et le métabolisme oxydatif au repos. Dans la première partie de cette thèse, le protocole d’acquisition ainsi que la stratégie d’analyse de l’approche QUO2 ont été revus afin d’améliorer la stabilité temporelle des réponses BOLD et du flux sanguin, conséquemment, afin d’accroître la fiabilité des paramètres estimés. Par la suite, une évaluation de la variabilité intra- et inter-sujet des différentes mesures QUO2 a été effectuée auprès d’un groupe de participants sains. En parallèle, une analyse de la sensibilité du model à différentes sources d’erreurs aléatoires (issues des mesures acquises) et systématiques (dues aux assomptions du model) a été réalisée. De plus, les impacts du niveau d’oxygène administré durant les périodes d’hyperoxie ont été évalués via une simulation puis expérimentalement, indiquant qu’une hyperoxie moyenne était bénéfique. Finalement, l’influence de la maladie d’Alzheimer sur les changements vasculaires et métaboliques a été explorée pour la première fois en appliquant le protocole QUO2 à une cohorte de patients Alzheimer et à un groupe témoin du même âge. Des différences en terme de flux sanguin, fraction d’oxygène extraite, métabolisme oxydatif, et taux de relaxation transverse R2* au repos comme en réponse à l’hypercapnie, ont été identifiées au niveau du voxel, ainsi qu’au niveau de régions cérébrales vulnérables à la maladie d’Alzheimer. Une liste de limitations accompagnées de recommandations a été dressée en ce qui a trait au temps de transit différé, aux artéfacts de susceptibilité magnétique, de même qu’au défi que représente l’hypercapnie chez les personnes âgées ou atteintes de la maladie d’Alzheimer

Proximal sensing for soil carbon accounting

Maintaining or increasing soil organic carbon (C) is vital for securing food production and for mitigating greenhouse gas (GHG) emissions, climate change, and land degradation. Some land management practices in cropping, grazing, horticultural, and mixed farming systems can be used to increase organic C in soil, but to assess their effectiveness, we need accurate and cost-efficient methods for measuring and monitoring the change. To determine the stock of organic C in soil, one requires measurements of soil organic C concentration, bulk density, and gravel content, but using conventional laboratory-based analytical methods is expensive. Our aim here is to review the current state of proximal sensing for the development of new soil C accounting methods for emissions reporting and in emissions reduction schemes. We evaluated sensing techniques in terms of their rapidity, cost, accuracy, safety, readiness, and their state of development. The most suitable method for measuring soil organic C concentrations appears to be visible-near-infrared (vis-NIR) spectroscopy and, for bulk density, active gamma-ray attenuation. Sensors for measuring gravel have not been developed, but an interim solution with rapid wet sieving and automated measurement appears useful. Field-deployable, multi-sensor systems are needed for cost-efficient soil C accounting. Proximal sensing can be used for soil organic C accounting, but the methods need to be standardized and procedural guidelines need to be developed to ensure proficient measurement and accurate reporting and verification. These are particularly important if the schemes use financial incentives for landholders to adopt management practices to sequester soil organic C. We list and discuss requirements for developing new soil C accounting methods based on proximal sensing, including requirements for recording, verification, and auditing

Analysis and processing of dynamic and structural magnetic resonance imaging signals for studying small vessel disease

Cerebral small vessel disease (CSVD) describes multiple and dynamic pathological processes disrupting the optimum functioning of perforating arterioles, capillaries and venules, increasing the risk of stroke and dementia. Although the pathogenesis of this disease is still elusive, the breakdown of the blood-brain barrier (BBB), which would hinder brain waste clearance, is thought to play a pivotal factor in it. Nonetheless, the microscopic origin and nature of these abnormalities and the lack of a ground truth make the study of CSVD in vivo in humans via magnetic resonance imaging (MRI) challenging and signal processing schemes likely to be sub-optimal. In this doctoral thesis, we proposed signal analysis and processing techniques to improve the quantification and characterisation of subtle and clinically relevant neuroimaging features of CSVD. We applied our proposals to analyses of structural and dynamic-contrast enhanced MRI (sMRI and DCE-MRI) to better characterise CSVD. DCE-MRI is commonly used to investigate cerebrovascular dysfunction, but the extremely subtle nature of the signal in CSVD makes it unclear whether signal changes are caused by microscopic yet critical BBB abnormalities. Moreover, ethical and safety considerations in vivo and the lack of validation frameworks hinder optimising imaging protocols and processing schemes. To cope with these issues, we thus proposed an open-source computational human brain model for mimicking the four-dimensional DCE-MRI acquisition process. With it, we quantified the substantial impact of spatiotemporal considerations on permeability mapping, detected sources of errors that had been overlooked in the past, and provided evidence of the harmful effect of post-processing or lack thereof on DCE-MRI assessments. Perivascular spaces (PVS) in the brain, which are involved in brain waste clearance, can become visible in sMRI scans of patients with neuroimaging features of CSVD, but their automatic quantification is challenging due to the size of PVS, the incidence and presence of imaging artefacts, and the lack of a ground truth. We first proposed a computational model of sMRI to study and compare current PVS segmentation techniques and identify major areas of improvement. We confirmed that optimal segmentation requires tuning depending on image quality and that motion artefacts are particularly detrimental to PVS quantification. We then proposed a processing strategy that distinguished high-quality from motion-corrupted images and processed them accordingly. We demonstrated such an approximation leads to estimates that correlate better with clinical visual scores and agree more with full manual counts. After optimisation using our proposals, we also found PVS measurements were associated with BBB permeability, in accordance with the link between brain waste clearance and endothelial dysfunction. This work provides means for understanding the effect of image acquisition and processing on the assessment of subtle markers of brain health to maximise confidence of studies of endothelial dysfunction and brain waste clearance via MRI. It also constitutes a cornerstone on which future optimisation and development can be based upon

Applications of Raman micro-spectroscopy for cancer diagnostics

Bladder cancer has the highest recurrence rate of any cancer, and as with most solid organ malignancies, early diagnosis, detection, and treatment are imperative for good clinical outcomes. Cystoscopy is the cornerstone of bladder diagnostics for real-time visualization of the bladder mucosa. However, it is an uncomfortable, invasive procedure, and is not without significant risk and potential complications for the patient. Urine cytology is currently the only non-invasive diagnostic tool available for the diagnosis of bladder cancer; this method is highly sensitive for high grade tumours, but has low sensitivity for low grade tumours, which accounts for the majority of cases. Therefore, there exists a clinical need to develop and integrate a non-invasive, accurate technique to assist in the diagnosis of bladder cancer. The combination of Raman micro-spectroscopy and voided urine cytology may provide an ideal platform to replace cystoscopy for bladder cancer diagnostics. By recording Raman spectra from cells obtained from urine cytology, it is possible to analyse the spectral differences associated with the biomolecular continuum of disease progression, as well as being able to classify between different pathological subgroups. Previous studies to date have shown promising results in the application of Raman based urine cytology; however, there appears a high degree of variability across experimental protocols, which is believed to have hindered the advancement of this technique into the clinic. This thesis involves the design and building of a confocal Raman micro-spectrometer to be utilised for the analysis of urine cytology samples, with a key emphasis on the translation of Raman based urine cytology into the clinic. In order to achieve this, a range of traditional protocols and consumables are systematically examined in terms of their compatibility with Raman micro-spectroscopy, as well as comparing the differences between Raman micro-spectroscopy and another form of vibrational spectroscopy for bladder and prostate cancer diagnostics. Although no patient urine cytology samples are used in this thesis, simulated samples are generated using bladder and prostate cell lines along with commercially available synthetic urine. Additional experimentation is provided in order to investigate the impact of hypoxia and exosomal communication on cellular biochemistry