Parametric Study of Infrared Imaging Based Breast Cancer Detection Program

Breast cancer is one of the most common cancers among women and is responsible for over 41,000 lives every year in the US according to The American Cancer Society. Current screening and imaging methods such as mammography, breast magnetic resonance imaging, and breast ultrasound imaging have helped in improving survival rate when the cancer is detected at an early stage. The problems with these techniques include: low sensitivity, patient discomfort, invasiveness, and cost. Due to current advancements in infrared and computational technologies, infrared thermography has been utilized as a noninvasive adjunctive screening modality. A computerized approach using infrared imaging (IRI) has been recently developed at RIT in collaboration with Rochester General Hospital for breast cancer detection and image localization. The parameters used in this simulation have been selected based on limited information available in the literature. This study focuses on analyzing the effects of different tissue thermal parameters used in the simulation on the accuracy of prediction. Thermal conductivity and perfusion rate are systematically varied, and their effects are presented by comparing simulated images with the actual infrared images captured from a biopsy-proven breast cancer patient. The results indicate a strong influence of perfusion rate within the breast tissue surrounding the tumor on heat transfer within the breast. This study is expected to help in proper selection of thermal properties while conducting the simulations. Future directions for research are also presented

Non-invasive, innovative and promising strategy for breast cancer diagnosis based on metabolomic profile of urine, cancer cell lines and tissue

The work presented in this thesis aimed to establish the metabolomic profile of urine and breast cancer (BC) tissue from BC patients (samples cordially provided by Funchal Hospital), in addition to BC cell lines (MCF-7, MDA-MB-231, T-47D) as a powerful strategy to identify metabolites as potential BC biomarkers, helping on the development of non-invasive approaches for BC diagnosis and management. To achieve the main goal and obtain a deeper and comprehensive knowledge on BC metabolome, different analytical platforms, namely headspace solid-phase microextraction (HSSPME) combined with gas chromatography-quadrupole mass spectrometry (GC-qMS) and nuclear magnetic ressonance (1H NMR) spectroscopy were used. The application of multivariate statistical methods - principal component analysis (PCA) and orthogonal partial least square – discriminant analysis (OPLS-DA), to data matrix obtained from the different target samples allowed to find a set of highly sensitive and specific metabolites metabolites, namely, 4-heptanone, acetic acid and glutamine, able to be used as potential biomarkers in BC diagnosis. Significant group separation was observed in OPLS-DA score plot between BC and CTL indicating intrinsic metabolic alterations in each group. To attest the robustness of the model, a random permutation test with 1000 permutations was performed with OPLS-DA. The permutation test yielded R2 (represents goodness of fit) and Q2 values (represents predictive ability) with values higher than 0.717 and 0.691, respectively. Several metabolic pathways were dysregulated in BC considering the analytical approaches used. The main pathways included pyruvate, glutamine and sulfur metabolisms, indicating that there might be an association between the metabolites arising from the type of biological sample of the same donor used to perform the investigation. The integration of data obtained from different analytical platforms (GC-qMS and 1H NMR) for urinary and tissue samples revealed that five metabolites (e.g., acetone, 3-hexanone, 4-heptanone, 2methyl-5-(methylthio)-furan and acetate), were found significant using a dual analytical approach.O trabalho apresentado nesta tese teve como objetivo estabelecer o perfil metabolómico da urina e do tecido da mama de doentes com cancro de mama (BC) (amostras cordialmente fornecidas pelo Hospital do Funchal), além das linhas celulares de BC (MCF-7, MDA-MB-231, T -47D) como uma poderosa estratégia para identificar metabolitos como potenciais biomarcadores de BC, auxiliando no desenvolvimento de abordagens não invasivas para o diagnóstico e a gestão da patologia. Para obter um conhecimento mais profundo e abrangente do metaboloma de BC, diferentes plataformas analíticas, nomeadamente a microextração em fase sólida em modo headspace (HS-SPME) combinada com a cromatografia em fase gasosa acoplada à espectrometria de massa (GC-qMS) e espectroscopia de ressonância magnética nuclear (1H RMN), foram usadas para atingir o objetivo principal. A aplicação de métodos estatísticos multivariados - análise de componentes principais (PCA) e análise discriminante de mínimos quadrados parciais ortogonais (OPLS-DA) à matriz de dados obtida a partir das diferentes amostras alvo, permitiu estabelecer um grupo de metabolitos sensíveis e específicos, nomeadamente a 4-heptanona, o ácido acético e a glutamina, possíveis de serem utilizados como potenciais biomarcadores no diagnóstico de BC. Uma separação significativa entre os grupos BC e CTL foi observada pelo OPLS-DA, indicando alterações metabólicas em cada grupo. Para verificar a robustez do modelo, foi realizado um teste de permutação aleatória com 1000 permutações com o sistema OPLS-DA. Valores de R2 (representa o ajuste) e Q2 (representa a capacidade preditiva) superiores a 0,717 e 0,691, foram obtidos utilizando o teste da permutação. Diversas vias metabólicas estavam desreguladas no BC considerando as abordagens analíticas utilizadas. As principais vias incluíram os metabolismos do piruvato e glutamina, indicando que poderá haver uma associação entre os metabolitos derivados do tipo de amostra biológica do mesmo doador utilizado para realizar a investigação. A integração de dados obtidos pelas diferentes plataformas analíticas (GC-qMS e 1H RMN) para amostras urinárias e de tecido revelou cinco metabolitos significativos usando a dupla abordagem analítica. (i.e., acetona, 3-hexanona, 4-heptanona, 2-metil-5- (metiltio) - furano e acetato)

A Patient-Specific Approach for Breast Cancer Detection and Tumor Localization Using Infrared Imaging

Breast cancer (BC) is the most common cancer among women in the United States; approximately one out of every 24 women die of related causes. BC screening is a critical factor for improving patient prognosis and survival rate. Infrared (IR) thermography is an accurate, inexpensive and operator independent modality that is not affected by tissue density as it captures surface temperature variations induced by the presence of tumors. A novel patient-specific approach for IR imaging and simulation is proposed. In this work, multi-view IR images of isolated breasts are obtained in the prone position (face down), which allows access to the entire breast surface because the breasts hang freely. The challenge of accurately determining size and location of tumors within the breasts is addressed through numerical simulations of a patient-specific digital breast model. The digital breast models for individual patients are created from clinical images of the breast, such as IR imaging, digital photographs or magnetic resonance images. The numerical simulations of the digital breast model are conducted using ANSYS Fluent, where computed temperature images are generated in the same corresponding views as clinical IRI images. The computed and clinical IRI images are aligned and compared to measure their match. The determination of tumor size and location was conducted through the Levenberg-Marquardt algorithm, which iteratively minimized the mean squared error. The methodology was tested on the breasts of seven patients with biopsy-proven breast cancer with tumor diameters ranging from 8 mm to 27 mm. The method successfully predicted the equivalent tumor diameter within 2 mm and the location was predicted within 6.3 mm in all cases. The time required for the estimation is 48 minutes using a 10-core, 3.41 GHz workstation. The method presented is accurate, fast and has potential to be used as an adjunct modality to mammography in BC screening, especially for dense breasts

Methodology and Applications of Disease Biomarker Identification in Human Serum

Biomarkers are biomolecules that serve as indicators of biological and pathological processes, or physiological and pharmacological responses to a drug treatment. Because of the high abundance of albumin and heterogeneity of plasma lipoproteins and glycoproteins, biomarkers are difficult to identify in human serum. Due to the clinical significance the identification of disease biomarkers in serum holds great promise for personalized medicine, especially for disease diagnosis and prognosis. This review summarizes some common and emerging proteomics techniques utilized in the separation of serum samples and identification of disease signatures. The practical application of each protein separation or identification technique is analyzed using specific examples. Biomarkers of cancers of prostate, breast, ovary, and lung in human serum have been reviewed, as well as those of heart disease, arthritis, asthma, and cystic fibrosis. Despite the advancement of technology few biomarkers have been approved by the Food and Drug Administration for disease diagnosis and prognosis due to the complexity of structure and function of protein biomarkers and lack of high sensitivity, specificity, and reproducibility for those putative biomarkers. The combination of different types of technologies and statistical analysis may provide more effective methods to identify and validate new disease biomarkers in blood

Infrared Spectroscopy of Serum Samples for Disease Diagnostics

The fundamental vibrational modes of biological constituents in the tissues and the complex body fluids coincide with optical frequencies in the infrared region. Therefore, spatially resolved molecular compositions and interaction information within the biological materials can be extracted non-destructively using IR radiation without the use of labels or probes. However, the feasibility of this technique to elucidate constituent molecular compositions and interactions within the diagnostic mediums is not well explored. This study demonstrates an application of infrared (IR) spectroscopy of sera for monitoring inflammatory bowel diseases (IBD) and various cancers. Using samples from experimental mice and human patients, the power of IR spectroscopy in structural studies of proteins and other complex band contours are explored to find spectral signatures. Two experimental models of IBD; interleukin 10 knockouts (IL10-/-) and Dextran Sodium Sulfate (DSS) induced mouse shows diagnostic accuracy with 80-100% sensitivity and specificity values. Importantly, the findings of human IBD patients’ serum also show promising results resembling our proofs-of-concept investigations of mouse models. Maximum values of sensitivity and specificity are 100% and 86%, respectively, in human samples. Similarly, in cancer studies, the EL4 mouse model of non-Hodgkin lymphoma (NHL) and a B16 mouse model of the subcutaneous melanoma are used to extract a snapshot of tumor-associated alteration in the serum. The study of both cancer-bearing mouse models in wild types (WT) and their corresponding control types emphasizes the diagnostic potential of this approach as a screening technique for the NHL and melanoma skin cancer. The breast cancer (BC) -associated protein conformational alteration in the serum samples shows the sensitivity and the specificity of identifying spectral signatures were both 90%. All in all, IR spectroscopy of serum samples accompanied by spectral analysis technique shows some promising results for disease diagnostics. The brief outlook of the fundamentals of the infrared detection technique and their applicability for the development of portable spectroscopy is also provided

Novel miniaturised and highly versatile biomechatronic platforms for the characterisation of melanoma cancer cells

There has been an increasing demand to acquire highly sensitive devices that are able to detect and characterize cancer at a single cell level. Despite the moderate progress in this field, the majority of approaches failed to reach cell characterization with optimal sensitivity and specificity. Accordingly, in this study highly sensitive, miniaturized-biomechatronic platforms have been modeled, designed, optimized, microfabricated, and characterized, which can be used to detect and differentiate various stages of melanoma cancer cells. The melanoma cell has been chosen as a legitimate cancer model, where electrophysiological and analytical expression of cell-membrane potential have been derived, and cellular contractile force has been obtained through a correlation with micromechanical deflections of a miniaturized cantilever beam. The main objectives of this study are in fourfold: (1) to quantify cell-membrane potential, (2) correlate cellular biophysics to respective contractile force of a cell in association with various stages of the melanoma disease, (3) examine the morphology of each stage of melanoma, and (4) arrive at a relation that would interrelate stage of the disease, cellular contractile force, and cellular electrophysiology based on conducted in vitro experimental findings. Various well-characterized melanoma cancer cell lines, with varying degrees of genetic complexities have been utilized. In this study, two-miniaturized-versatile-biomechatronic platforms have been developed to extract the electrophysiology of cells, and cellular mechanics (mechanobiology). The former platform consists of a microfluidic module, and stimulating and recording array of electrodes patterned on a glass substrate, forming multi-electrode arrays (MEAs), whereas the latter system consists of a microcantilever-based biosensor with an embedded Wheatstone bridge, and a microfluidic module. Furthermore, in support of this work main objectives, dedicated microelectronics together with customized software have been attained to functionalize, and empower the two-biomechatronic platforms. The bio-mechatronic system performance has been tested throughout a sufficient number of in vitro experiments.Open Acces

Assessing the enhancement performance of a novel aptasensor for osteopontin detection

Dupla diplomação com a Université Libre de TunisCancer diseases are associated with the presence of a wide range of protein biomarkers. Aptasensor arrays may enable early multiple-detection of these biomarkers which can make important improvements in the lives of cancer patients. Clinical researches suggest that osteopontin, an overexpressed protein by tumor cells may be used as a diagnostic biomarker for several types of cancer. In this perspective, the objective of this dissertation was to evaluate the performance of a previously selected aptamer (C10K7) to detect osteopontin using cyclic voltammetry. The electrochemical detection of osteopontin was assessed using different screen-printed gold electrodes with the selected aptamer immobilized, being determined the detection and quantification limits. The specificity of the DNA aptasensor to other proteins was also studied using thrombin, lysozyme and bovine serum albumin which were evaluated by a previous research as possible interferents. The preliminary work carried out showed that this new aptamer allowed achieving a detection limit of 1.3 nM and a quantification limit of 4.0 nM for osteopontin. Considering that the reported range of plasma osteopontin concentrations in patients with either metastatic or recurrent breast cancer is up to 290 ng/mL (~ 4.46 nM) which is higher than the detection and quantification limits found and which suggest that the proposed aptasensor could be applied in both osteopontin detection and quantification. On the other hand, with the studied aptamer, the detection and quantification limits were lower than those reported in the literature for cyclic voltammetry, which were of 2.6 nM for a DNA aptamer (designated as C10K2) and 3.7 nM for an RNA aptamer (called OPN-R3). The repeatability assays showed a coefficient of variation equal to 7% which demonstrate the closeness of the agreement between the results. The evaluation of the specificity of the DNA aptasensor towards osteopontin showed little or almost no interference to other proteins. However, the interference study showed that the C10K7 aptamer was more prone to interferences from lysozyme and bovine serum albumin than the C10K2 aptamer, previously studied by the research team but showed a lower interference from thrombin. These results highlight the promising capability of the new DNA aptamer (C10K7) to be used in the development of an electrochemical aptasensor for the osteopontin detection, which could be foreseen as a diagnosis and therapy monitoring tool. Nevertheless, these preliminary satisfactory results need to be further checked, namely by the evaluation of its performance for the detection of human osteopontin in biological fluids like blood or plasma.O cancro é uma doença à qual se pode associar a presença de diversas proteínas nos fluidos biológicos de pacientes com essa patologia, as quais podem ser usadas como biomarcadores. Aptasensores baseados em diferentes aptâmeros selecionados para biomarcadores específicos podem permitir a sua deteção num estágio precoce da doença, contribuindo para melhorar a vida dos pacientes com cancro. Estudos clínicos sugerem que a osteopontina, é uma proteína sobre-expressa por células tumorais, podendo ser utilizada como biomarcador no diagnóstico de vários tipos de cancro. O objetivo do presente trabalho foi avaliar o desempenho de um aptâmero previamente selecionado (C10K7) para detectar osteopontina recorrendo à técnica de voltametria cíclica. O estudo realizado permitiu verificar que este novo aptasensor possui um limite de deteção de 1.3 nM e um limite de quantificação de 4.0 nM. Estes valores permitem antever a aplicabilidade prática deste dispositivo como uma ferramenta de deteção de osteopontina uma vez que as concentrações reportadas em plasma de pacientes com o cancro são da ordem dos 4.46 nM (290 ng/mL). Por outro lado, convém referir que o novo aptasensor apresenta limites de detecção e de quantificação inferiores aos descritos na literatura para outros aptasensores baseados em aptâmeros de RNA (OPN-R3) e DNA (C10K2), nomeadamente 3.7 nM e 2.6 nM, também estabelecidos por voltametria cíclica. Os ensaios de repetibilidade realizados mostraram que o aptasensor desenvolvido apresentava um desempenho satisfatório (coeficientes de variação inferiores a 7%). Por fim, o novo aptasensor mostrou-se bastante específico relativamente à osteopontina, molécula alvo, com reduzida interferência por parte de outras protéinas tipo (lisozima, albumina bovina e trombina). Os resultados obtidos sãp bastante promissores indicando o novo aptasensor de DNA (C10K7) uma possível ferramenta de diagnóstico e/ou monitorização da evolução do cancro. No entanto, o desempenho satisfatório descrito terá de ser validado na deteção de osteopontina humano em líquidos biológicos como o sangue ou o plasma.This work was partially financially supported by Associate Laboratory LSRE-LCM - UID/EQU/50020/2019 and by the strategic project PEst-OE/AGR/UI0690/2014 –CIMO funded by national funds through FCT/MCTES (PIDDAC). Professor António Peres, supervisor of this work, is member of CIMO and of the Associate Laboratory LSRE-LCM