Gradient-based quantitative image reconstruction in ultrasound-modulated optical tomography: first harmonic measurement type in a linearised diffusion formulation

Ultrasound-modulated optical tomography is an emerging biomedical imaging modality which uses the spatially localised acoustically-driven modulation of coherent light as a probe of the structure and optical properties of biological tissues. In this work we begin by providing an overview of forward modelling methods, before deriving a linearised diffusion-style model which calculates the first-harmonic modulated flux measured on the boundary of a given domain. We derive and examine the correlation measurement density functions of the model which describe the sensitivity of the modality to perturbations in the optical parameters of interest. Finally, we employ said functions in the development of an adjoint-assisted gradient based image reconstruction method, which ameliorates the computational burden and memory requirements of a traditional Newton-based optimisation approach. We validate our work by performing reconstructions of optical absorption and scattering in two- and three-dimensions using simulated measurements with 1% proportional Gaussian noise, and demonstrate the successful recovery of the parameters to within +/-5% of their true values when the resolution of the ultrasound raster probing the domain is sufficient to delineate perturbing inclusions.Comment: 12 pages, 6 figure

Real-time Three-dimensional Photoacoustic Imaging

Photoacoustic imaging is a modality that combines the benefits of two prominent imaging techniques; the strong contrast inherent to optical imaging techniques with the enhanced penetration depth and resolution of ultrasound imaging. PA waves are generated by illuminating a light-absorbing object with a short laser pulse. The deposited energy causes a pressure change in the object and, consequently, an outwardly propagating acoustic wave. Images are produced by using characteristic optical information contained within the waves. We have developed a 3D PA imaging system by using a staring, sparse array approach to produce real-time PA images. The technique employs the use of a limited number of transducers and by solving a linear system model, 3D PA images are rendered. In this thesis, the development of an omni-directional PA source is introduced as a method to characterize the shift-variant system response. From this foundation, a technique is presented to generate an experimental estimate of the imaging operator for a PA system. This allows further characterization of the object space by two techniques; the crosstalk matrix and singular value decomposition. Finally, the results of the singular value decomposition analysis coupled with the linear system model approach to image reconstruction, 3D PA images are produced at a frame rate of 0.7 Hz. This approach to 3D PA imaging has provided the foundation for 3D PA images to be produced at frame rates limited only by the laser repetition rate, as straightforward system improvements could see the imaging process reduced to tens of milliseconds

Quantification of Pulmonary Arterial Wall Distensibility Using Parameters Extracted from Volumetric Micro-CT Images

Stiffening, or loss of distensibility, of arterial vessel walls is among the manifestations of a number of vascular diseases including pulmonary arterial hypertension. We are attempting to quantify the mechanical properties of vessel walls of the pulmonary arterial tree using parameters derived from high-resolution volumetric x-ray CT images of rat lungs. The pulmonary arterial trees of the excised lungs are filled with a contrast agent. The lungs are imaged with arterial pressures spanning the physiological range. Vessel segment diameters are measured from the inlet to the periphery, and distensibilities calculated from diameters as a function of pressure. The method shows promise as an adjunct to other morphometric techniques such as histology and corrosion casting. It possesses the advantages of being nondestructive, characterizing the vascular structures while the lungs are imaged rapidly and in a near-physiological state, and providing the ability to associate mechanical properties with vessel location in the intact tree hierarchy

Fluorescence molecular tomography: Principles and potential for pharmaceutical research

Fluorescence microscopic imaging is widely used in biomedical research to study molecular and cellular processes in cell culture or tissue samples. This is motivated by the high inherent sensitivity of fluorescence techniques, the spatial resolution that compares favorably with cellular dimensions, the stability of the fluorescent labels used and the sophisticated labeling strategies that have been developed for selectively labeling target molecules. More recently, two and three-dimensional optical imaging methods have also been applied to monitor biological processes in intact biological organisms such as animals or even humans. These whole body optical imaging approaches have to cope with the fact that biological tissue is a highly scattering and absorbing medium. As a consequence, light propagation in tissue is well described by a diffusion approximation and accurate reconstruction of spatial information is demanding. While in vivo optical imaging is a highly sensitive method, the signal is strongly surface weighted, i.e., the signal detected from the same light source will become weaker the deeper it is embedded in tissue, and strongly depends on the optical properties of the surrounding tissue. Derivation of quantitative information, therefore, requires tomographic techniques such as fluorescence molecular tomography (FMT), which maps the three-dimensional distribution of a fluorescent probe or protein concentration. The combination of FMT with a structural imaging method such as X-ray computed tomography (CT) or Magnetic Resonance Imaging (MRI) will allow mapping molecular information on a high definition anatomical reference and enable the use of prior information on tissue’s optical properties to enhance both resolution and sensitivity. Today many of the fluorescent assays originally developed for studies in cellular systems have been successfully translated for experimental studies in animals. The opportunity of monitoring molecular processes non-invasively in the intact organism is highly attractive from a diagnostic point of view but even more so for the drug developer, who can use the techniques for proof-of-mechanism and proof-of-efficacy studies. This review shall elucidate the current status and potential of fluorescence tomography including recent advances in multimodality imaging approaches for preclinical and clinical drug development

Imaging workflow and calibration for CT-guided time-domain fluorescence tomography

In this study, several key optimization steps are outlined for a non-contact, time-correlated single photon counting small animal optical tomography system, using simultaneous collection of both fluorescence and transmittance data. The system is presented for time-domain image reconstruction in vivo, illustrating the sensitivity from single photon counting and the calibration steps needed to accurately process the data. In particular, laser time- and amplitude-referencing, detector and filter calibrations, and collection of a suitable instrument response function are all presented in the context of time-domain fluorescence tomography and a fully automated workflow is described. Preliminary phantom time-domain reconstructed images demonstrate the fidelity of the workflow for fluorescence tomography based on signal from multiple time gates

MULTIMODAL NONCONTACT DIFFUSE OPTICAL REFLECTANCE IMAGING OF BLOOD FLOW AND FLUORESCENCE CONTRASTS

In this study we design a succession of three increasingly adept diffuse optical devices towards the simultaneous 3D imaging of blood flow and fluorescence contrasts in relatively deep tissues. These metrics together can provide future insights into the relationship between blood flow distributions and fluorescent or fluorescently tagged agents. A noncontact diffuse correlation tomography (ncDCT) device was firstly developed to recover flow by mechanically scanning a lens-based apparatus across the sample. The novel flow reconstruction technique and measuring boundary curvature were advanced in tandem. The establishment of CCD camera detection with a high sampling density and flow recovery by speckle contrast followed with the next instrument, termed speckle contrast diffuse correlation tomography (scDCT). In scDCT, an optical switch sequenced coherent near-infrared light into contact-based source fibers around the sample surface. A fully noncontact reflectance mode device finalized improvements by combining noncontact scDCT (nc_scDCT) and diffuse fluorescence tomography (DFT) techniques. In the combined device, a galvo-mirror directed polarized light to the sample surface. Filters and a cross polarizer in stackable tubes promoted extracting flow indices, absorption coefficients, and fluorescence concentrations (indocyanine green, ICG). The scDCT instrumentation was validated through detection of a cubical solid tissue-like phantom heterogeneity beneath a liquid phantom (background) surface where recovery of its center and dimensions agreed with the known values. The combined nc_scDCT/DFT identified both a cubical solid phantom and a tube of stepwise varying ICG concentration (absorption and fluorescence contrast). The tube imaged by nc_scDCT/DFT exhibited expected trends in absorption and fluorescence. The tube shape, orientation, and localization were recovered in general agreement with actuality. The flow heterogeneity localization was successfully extracted and its average relative flow values in agreement with previous studies. Increasing ICG concentrations induced notable disturbances in the tube region (≥ 0.25 μM/1 μM for 785 nm/830 nm) suggesting the graduating absorption (320% increase at 785 nm) introduced errors. We observe that 830 nm is lower in the ICG absorption spectrum and the correspondingly measured flow encountered less influence than 785 nm. From these results we anticipate the best practice in future studies to be utilization of a laser source with wavelength in a low region of the ICG absorption spectrum (e.g., 830 nm) or to only monitor flow prior to ICG injection or post-clearance. In addition, ncDCT was initially tested in a mouse tumor model to examine tumor size and averaged flow changes over a four-day interval. The next steps in forwarding the combined device development include the straightforward automation of data acquisition and filter rotation and applying it to in vivo tumor studies. These animal/clinical models may seek information such as simultaneous detection of tumor flow, fluorescence, and absorption contrasts or analyzing the relationship between variably sized fluorescently tagged nanoparticles and their tumor deposition relationship to flow distributions

Objective assessment of image quality (OAIQ) in fluorescence-enhanced optical imaging

The statistical evaluation of molecular imaging approaches for detecting, diagnosing, and monitoring molecular response to treatment are required prior to their adoption. The assessment of fluorescence-enhanced optical imaging is particularly challenging since neither instrument nor agent has been established. Small animal imaging does not address the depth of penetration issues adequately and the risk of administering molecular optical imaging agents into patients remains unknown. Herein, we focus upon the development of a framework for OAIQ which includes a lumpy-object model to simulate natural anatomical tissue structure as well as the non-specific distribution of fluorescent contrast agents. This work is required for adoption of fluorescence-enhanced optical imaging in the clinic. Herein, the imaging system is simulated by the diffusion approximation of the time-dependent radiative transfer equation, which describes near infra-red light propagation through clinically relevant volumes. We predict the time-dependent light propagation within a 200 cc breast interrogated with 25 points of excitation illumination and 128 points of fluorescent light collection. We simulate the fluorescence generation from Cardio-Green at tissue target concentrations of 1, 0.5, and 0.25 µM with backgrounds containing 0.01 µM. The fluorescence boundary measurements for 1 cc spherical targets simulated within lumpy backgrounds of (i) endogenous optical properties (absorption and scattering), as well as (ii) exogenous fluorophore crosssection are generated with lump strength varying up to 100% of the average background. The imaging data are then used to validate a PMBF/CONTN tomographic reconstruction algorithm. Our results show that the image recovery is sensitive to the heterogeneous background structures. Further analysis on the imaging data by a Hotelling observer affirms that the detection capability of the imaging system is adversely affected by the presence of heterogeneous background structures. The above issue is also addressed using the human-observer studies wherein multiple cases of randomly located targets superimposed on random heterogeneous backgrounds are used in a “double-blind” situation. The results of this study show consistency with the outcome of above mentioned analyses. Finally, the Hotelling observer’s analysis is used to demonstrate (i) the inverse correlation between detectability and target depth, and (ii) the plateauing of detectability with improved excitation light rejection

Automatically finding tumors using structural-prior guided optical tomography

Tese de mestrado integrado em Engenharia Biomédica e Biofísica, apresentada à Universidade de Lisboa, através da Faculdade de Ciências, 2015O cancro consiste na proliferação anormal de células. No seu estado normal, as células crescem e dividem-se em novas células (regeneração celular). Quando estas envelhecem ou são danificadas, morrem naturalmente. No entanto, as células podem perder este mecanismo de controlo, tornando-se células cancerígenas, que produzem novas células de forma descontrolada, resultando na formação de um tumor. Os tumores podem ser benignos ou malignos. Apenas os tumores malignos são considerados cancro, sendo que as células podem invadir e danificar os tecidos e órgãos (metastização). O cancro da mama é o tipo de cancro mais comum entre as mulheres (não considerando o cancro da pele) e corresponde à segunda causa de morte no Mundo e de acordo com o RON (Registo Oncológico Nacional), em Portugal, anualmente são detectados cerca de 4500 novos casos de cancro da mama, e 1500 mulheres morrem com esta doença. Desta forma, o diagnóstico precoce do cancro da mama é essencial, sendo que a mamografia convencional continua a ser a principal técnica de imagiologia utilizada para o efeito. No entanto, contribui para falsos negativos e não deteta cerca de 10-15% dos cancros da mama, principalmente em mulheres com mamas mais densas. Tomografia ótica difusa (do inglês, Diffuse Optical Tomography, DOT) é uma técnica de imagiologia que permite obter imagens funcionais da mama. A técnica de tomografia ótica difusa é não-invasiva uma vez que utiliza luz na região espectral próxima do infravermelho (do inglês, Near Infrared, NIR), o que corresponde a comprimentos de onda entre aproximadamente 600 e 1000 nm. Nesta região espectral, a absorção da luz pelos tecidos é fraca e portanto a dispersão é maior em todas as direções, o que torna possível a detecção da luz emergente. Os principais absorvedores da luz na região próxima do infravermelho são: a oxi-hemoglobina (HbO) e a deoxi-hemoglobina (HbR), que contribuirão para o coeficiente de absorção medido ( a). O coeficiente de dispersão reduzido ( 0s) irá depender do tecido mamário, já que está relacionado com a densidade e tamanho das partículas constituintes do meio. Com base nesses parâmetros, são obtidos mapas espaciais das propriedades óticas do tecido, tais como a concentração de hemoglobina total (HbT ), a saturação de oxigénio (So2) e o coeficiente reduzido de dispersão ( 0s) através de algoritmos de reconstrução da imagem. Tais propriedades permitem inferir acerca da oxigenação e vascularização do tecido. No entanto, as imagens de DOT apresentam baixa resolução espacial devido à extrema sensibilidade ao ruído durante o processo de reconstrução da imagem. Para tal, tem sido alvo de muito investigação a incorporação de outras técnicas de imagiologia, especialmente as que fornecem informação estrutural. Nesse sentido, foi desenvolvido um sistema combinado de DOT e Raio-X no Massachusetts General Hospital (Boston, EUA) para o diagnóstico de cancro da mama. Sendo que, por um lado, é possível explorar a distribuição da absorção e dispersão da luz no tecido fisiológico e, por outro, adquirir informação de cariz anatómico. Na maioria dos estudos de sistemas híbridos com DOT, as modalidades de imagiologia estruturais têm sido utilizadas apenas para fornecer o limite exterior da mama, ou então através da sobreposição nas imagens reconstruídas de DOT e posterior interpretação das imagens pelo médico/radiologista. No entanto, a estrutura anatómica interna é um fator chave que está em falta para produzir imagens com melhor resolução espacial. Assim, de modo a incorporar este fator na recontrução das imagens de DOT, têm sido propostos e testados novos algoritmos. Juntamente com outros grupos de investigação, Fang et al. desenvolveu o método de reconstrução prior-guided. Neste método é considerada uma segmentação composicional da mama e assume-se que cada pixel na imagem anatómica resulta da combinação de dois ou mais tipos de tecido. Estudos posteriores tem revelado que este método permite manter a resolução espacial das imagens anatómicas e, para além disso, tem mostrado ser robusto no processamento de imagens em meio clínico. Recentemente, um estudo realizado por Deng et al. revelou que esse método de reconstrução permite detectar quando a localização do tumor fornecida é falsa. Ou seja, apenas quando a localização do tumor fornecida é verdadeira, é que se observa uma diferença significativa no contraste óptico. Esse estudo serviu como motivação para a realização do trabalho descrito nesta tese. A presente tese reflecte o trabalho realizado no Athinoula A. Martinos Center for Biomedical Imaging, parte do Massachusetts General Hospital e Harvard Medical School sob a orientação do Professor Qianqian Fang e ainda sob orientação do Professor Nuno Matela da Faculdade de Ciências da Universidade de Lisboa, Portugal - num período de estágio de duração de 8 meses, em Boston. Até agora, a maioria dos estudos clínicos usando sistemas híbridos de imagem da mama com DOT têm-se concentrado em caracterizar apenas tumores conhecidos. Não tem sido demonstrado que os métodos de reconstrução de imagem DOT podem ser utilizados para identificar a localização e o tipo de lesão desconhecido. Desta forma, o objetivo principal desta tese consistiu no desenvolvimento de um método de detecção automático para identificar a localização e tipos de lesão sem a interferência de um radiologista. A tese apresentada reflecte os métodos, resultados e conclusões de uma ferramenta de detecção automática que realça potenciais regiões para a localização e classificação do tumor. Esta ferramenta foi desenvolvida com base no desenvolvimento de múltiplas métricas de contraste. Para tal, recorreu-se em primeira análise, a dados provenientes de uma amostra de 126 mamas, dos quais 60 são consideradas mamas anormais (com tumor) e 66 normais (sem tumor). Posteriormente, utilizou-se modelos digitais da mama (fantomas) de modo a simular diferentes tamanhos e tipos de tumor. De modo geral, as etapas chave para o desenvolvimento deste trabalho foram as seguintes: 1. Implementação de uma grelha que define as localizações do tumor; 2. Desenvolvimento de múltiplas métricas para casos malignos, benignos e normais; 3. Verificação e validação das métricas utilizando dados provenientes de uma amostra de pacientes e de modelos digitais da mama; 4. As métricas de contraste foram combinadas de modo a localizar o tumor; 5. As métricas foram utilizadas para confirmar a natureza do tumor. Os resultados obtidos mostraram que as métricas de contraste definidas, permitem identificar a região onde as propriedades ópticas têm uma alteração significativa de contraste e consequentemente permitem localizar o tumor. No entanto, esses resultados variam consoante a natureza do tumor. Assim, lesões malignas causam um contraste positivo, contrariamente às lesões benignas, cujo contraste é negativo. As métricas de contraste designadas por M1, M2, 2 e M3 são eficazes para a localização de tumores malignos, enquanto que as métricas de contraste B1, 2 e B2 são eficazes para identificar a localização de tumores benignos. De modo a tornar a localização do tumor mais robusta, recorreu-se a análise de duas propriedades óticas, à concentração de hemoglobina total (HbT ) e ao coeficiente de dispersão reduzido (_0s) para lesões malignas. Do mesmo modo para as lesões benignas, no entanto em vez do coeficiente de dispersão reduzido, considerou-se a saturação de oxigénio (So2). A partir da combinação de múltiplas métricas foi desenvolvida uma ferramenta que permite localizar e classificar o tumor. Este método permite classificar a mama como normal ou não. No caso de a mama ser classificada como anormal, o método aponta no mínimo duas regiões "suspeitas" para a localização do tumor dependendo da natureza do tumor. Assim, este método resulta numa imagem de raio-x com duas localizações: 1) região "suspeita" para tumor maligno; e 2) região "suspeita" para tumor benigno. A aplicação deste método na amostra de 126 mamas apresentou uma taxa de sucesso de cerca de 82%, porém considerando-se apenas as lesões benignas foi observado que em metade da amostra, o método falhou na localização do tumor. Uma das desvantagens deste método, é que a decisão final continua a ser dependente do doctor/radiologista. Os resultados são de interesse para a comunidade científica, principalmente grupos de investigação na área de imagiologia ótica. Este estudo revela que recorrendo ao método de localização e classificação do tumor é possível localizar de modo preciso o tumor. Este método merece investigação futura, no que diz respeito à sua aplicação em meio clínico como o sistema de apoio computorizado ao diagnóstico (do inglês, Computer Aided Detection, CAD), permitindo auxiliar o médico/radiologista a detectar lesões durante a leitura da imagem. Este trabalho poderá vir a encorajar estudos futuros de modo a otimizar o algoritmo. Para tal, é fundamental a análise da influência do tamanho do tumor e da fatia (do inglês, slice) da imagem reconstruída considerada; seria igualmente importante aumentar consideravelmente o número de pacientes em estudo, de forma a validar e metodologia implementada; e por fim, o desenvolvimento de um método capaz de distinguir um tumor benigno de um maligno seria um fator chave.Diffuse optical tomography (DOT) is a diagnostic tool that relies on functional processes for contrast. This technique provides several unique measurable parameters with the potential to enhance breast tumor sensitivity and specificity. DOT utilizes non-ionizing radiation and it is non-invasive. Several groups have begun incorporating DOT with other imaging modalities. This approach can potentially overcome the resolution limitation problem by using spatial information provided by other imaging modalities. In this sense, a co-registered DOT with 3D X-ray mammography (also known as tomosynthesis) has been developed at Massachusetts General Hospital in order to utilize anatomical information as a structural prior. Literature reveals that the compositional-prior-guided reconstruction algorithm is sensitive to false priors on tumor location. So far, most clinical research of either standalone or multi-modal DOT breast imaging system have been focusing on characterizing known tumors. It has not been shown that, DOT based imaging methods can be used to identify the location, and type of an unknown lesion. So, the purpose of this work is the development of a computer aided detection (CAD) method to automatically identify the location and types of an unknown lesion without interference from a radiologist. In this thesis, to reconstruct the images was used the compositional prior guided reconstruction algorithm considering 2-composition prior (adipose and fibroglandular tissues) and 3-composition prior (adipose, fibroglandular and tumor tissues), which depends of the tumor location. The tumor contrast from those results were investigated using quantitative contrast metrics. The development of the tumor contrast metrics was based on the measurements from a set of 126 breasts (66 normal and 60 abnormal) using the DOT/X-ray breast imaging system. Furthermore, the validation of the algorithm was provided using phatoms to systematically evaluate the impact of lesion sizes, contrasts and tissue background on the recovery of breast tumors. The results show that, the tumor contrast metrics can find a region where the optical properties have a significant increase or decrease depending of the tumor type. Moreover, the optical properties to obtain reliable contrast metrics in a malignant lesion are the total hemoglobin concentration (HbT ) and the reduced scattering coefficient ( 0s), and for a benign lesion are HbT and the oxygen saturation (So2). In respect to the automatic tumor location and classification method, the retrieved information is capable of diagnosing the breast, as normal or not. In an abnormal case, our algorithm can potentially pinpoint the "suspicious" regions for the location of the tumor. The application of this method in the set of 126 breasts had a success rate of 82%. However, considering only the benign lesions was observed that in half of the sample, the algorithm failed. These promising results could be used to provide more knowledge regarding the tumor location. Moreover, combining this results with further investigation and optimization they would be useful to achieve a tool that automatically gives precise "suspicious" regions for the tumor location to the doctor during the image reading

Improving performance of reflectance diffuse optical imaging using a multicentered mode

We propose a novel multicentered mode for arrangement of optical fibers to improve the imaging performance of reflectance diffuse optical imaging (rDOI). Simulations performed using a semi-infinite model show that the proposed multicentered geometries can achieve a maximum of 42 overlapping measurements. The contrast-to-noise ratio (CNR) analysis indicates that the best spatial resolution is 1 mm in radius and the contrast resolution is less than 1.05 for the multicentered geometries. The results from simulations indicate significant improvement in image quality compared to the single-centered mode and previous geometries. Additional experimental results on a single human subject lead to the conclusion that the proposed multicentered geometries are appropriate for exploring activations in the human brain. From the results of this research, we conclude that the proposed multicentered mode could advance the performance of rDOI both in image quality and practical convenience