Imaging Sensors and Applications

In past decades, various sensor technologies have been used in all areas of our lives, thus improving our quality of life. In particular, imaging sensors have been widely applied in the development of various imaging approaches such as optical imaging, ultrasound imaging, X-ray imaging, and nuclear imaging, and contributed to achieve high sensitivity, miniaturization, and real-time imaging. These advanced image sensing technologies play an important role not only in the medical field but also in the industrial field. This Special Issue covers broad topics on imaging sensors and applications. The scope range of imaging sensors can be extended to novel imaging sensors and diverse imaging systems, including hardware and software advancements. Additionally, biomedical and nondestructive sensing applications are welcome

Photoacoustic fluctuation imaging: theory and application to blood flow imaging

Photoacoustic fluctuation imaging, which exploits randomness in photoacoustic generation, provides enhanced images in terms of resolution and visibility, as compared to conventional photoacoustic images. While a few experimental demonstrations of photoacoustic fluctuation imaging have been reported, it has to date not been described theoretically. In the first part of this work, we propose a theory relevant to fluctuations induced either by random illumination patterns or by random distributions of absorbing particles. The theoretical predictions are validated by Monte Carlo finite-difference time-domain simulations of photoacoustic generation in random particle media. We provide a physical insight into why visibility artefacts are absent from second-order fluctuation images. In the second part, we demonstrate experimentally that harnessing randomness induced by the flow of red blood cells produce photoacoustic fluctuation images free of visibility artefacts. As a first proof of concept, we obtain two-dimensional images of blood vessel phantoms. Photoacoustic fluctuation imaging is finally applied in vivo to obtain 3D images of the vascularization in a chicken embryo

In Vivo Vascular Imaging with Photoacoustic Microscopy

Photoacoustic (PA) tomography (PAT) has received extensive attention in the last decade for its capability to provide label-free structural and functional imaging in biological tissue with highly scalable spatial resolution and penetration depth. Compared to modern optical modalities, PAT offers speckle-free images and is more sensitive to optical absorption contrast (with 100% relative sensitivity). By implementing different regimes of optical wavelength, PAT can be used to image diverse light-absorbing biomolecules. For example, hemoglobin is of particular interest in the visible wavelength regime owing to its dominant absorption, and lipids and water are more commonly studied in the near-infrared regime. In this dissertation, one challenge was to quantitatively investigate red-blood-cell dynamics in nailfold capillaries with single-cell resolution PA microscopy (PAM). We recruited healthy volunteers and measured multiple hemodynamic parameters based on individual red blood cells (RBCs). Statistical analysis revealed the process of oxygen release and changes in flow speed for RBCs in a capillary. For the first time on record, oxygen release from individual RBCs in human capillaries was imaged with nearly real-time speed, and the work paved the way for our following study of a specific blood disorder. We next conducted a pilot study on sickle cell disease (SCD), measuring and comparing the parameters related to RBC dynamics between healthy subjects and patients with SCD. In the patient group, we found that capillaries tended to be more tortuous, dilated, and had higher number density. In addition, abnormal RBCs tended to have lower oxygenation in the inlet of a capillary, from where they flowed slower and released a larger fraction of oxygen than normal RBCs. As the only imaging modality able to observe the real-time dynamics of the oxygen release of individual RBCs, PAM provides medically valuable information for diagnostic purposes. As the last focus of this dissertation, we tackled the limited view problem in PAM by introducing an off-axis illumination technique for complementing the original detection view. We demonstrated this technique numerically and then experimentally on phantoms and animals. This simple but very effective method revealed abundant vertical vasculature in a mouse brain that had long been missed by conventional top-illumination PAM. This technique greatly advances future studies on neurovascular responses in mouse brains

EVALUATION OF EARLY TUMOR ANGIOGENESIS USING ULTRASOUND ACOUSTIC ANGIOGRAPHY

Cancer angiogenesis is a feature of tumor growth that produces disorganized and dysfunctional vascular networks. Acoustic angiography is a unique implementation of contrast-enhanced ultrasound that allows us to visualize microvasculature with high resolution and contrast, including blood vessels as small as 100 to 150 micrometers. These angiography images can be analyzed to evaluate the morphology of the blood vessels for the purpose of detecting and diagnosing tumors. This thesis describes the implementation, advantages, and disadvantages of acoustic angiography and evaluates tumor vasculature in a pre-clinical cancer model. Measurements of tortuosity and vascular density in tumor regions were significantly higher than those of control regions, including in the smallest palpable tumors (2-3 mm). Additionally, abnormal tortuosity extended beyond the margin of tumors, as distal tissue separated from the tumor by at least 4 mm exhibited higher tortuosity than healthy individuals. Vascular tortuosity was negatively correlated to distance from the tumor margin using linear regression. Analysis of full images to detect tumors was performed using a reader study approach to assess visual interpretations, and quantitative analysis combined tortuosity with spatial relationships between vessels using a density-based clustering approach. Visual assessment using a reader study design resulted in an area under the receiver operating characteristic (ROC) curve of approximately 0.8, and the ROC curve was significantly correlated with tumor diameter, indicating that larger tumors were detected more accurately using this approach. Quantitative analysis of the same images used a density-based clustering algorithm to combine vessels in an image into clusters based on their tortuosity (using 2 metrics), radius, and proximity to one another. In tumors, highly tortuous vessels were closely packed, forming large clusters in the analysis, while control images lacked such patterns and formed much smaller clusters. Therefore, maximum cluster size was used to detect tumors, achieving an area under the ROC curve of 0.96. Finally, superharmonic molecular imaging was used to image targeted microbubbles with higher contrast to tissue ratios than conventional molecular imaging. These molecular images were combined with vascular acoustic angiography images to begin to relate the expression of endothelial markers of angiogenesis with vascular features such as tortuosity.Doctor of Philosoph