This PDF file contains the front matter associated with SPIE Proceedings Volume 11241, including the Title Page, Copyright information, Table of Contents, Author and Conference Committee lists.

Transcranical photobiomodulation (tPBM, 1267 nm, 32 J/cm2) is effective non-invasive method for clearance of beta-amyloid from the brain in mice with Alzheimer’s disease and for improvemen of their neurological status.

We constructed multifunction nano systems and investigated the synergize photothermal and immunological effects. Here, we design new synergistic nano-particles, both have the photothermal effects and immunological effects. We investigate the therapeutic effects and detect the immune response with metastatic mouse tumor models. We also study the therapeutic mechanism after treatment in vitro and in vivo. With the enhancement of nano-materials on photothermal effects, laser treatment could destroy primary tumor and protect normal tissue with low dose laser irradiation. With the immunological effects of nano-materials, the treatment could trigger specific antitumor immune response, to eliminate the metastasis tumor. It is providing a promising treatment modality for the metastatic cancers.

Laser Immunotherapy (LIT) is a novel treatment for metastatic cancer that uses laser irradiation and an immunostimulant to achieve lasting anti-tumor immunity. To increase photothermal conversion efficiency, LIT has used several types of agents tuned to absorb near-infrared (NIR) light. Polypyrrole (PPy) is an organic polymer with similar light absorbing characteristics to previously studied nanomaterials. We carried out dose-dependent PPy toxicity, stability, and photothermal experiments using a mouse breast cancer model. The marked stability under laser irradiation, coupled with PPy’s high photothermal conversion efficiency and low toxicity suggest that PPy could replace nanomaterials as a photothermal and drug-delivery agent.

Most fatalities from cancer are caused by metastases produced by circulating tumor cells (CTCs). Despite its importance, CTC diagnosis at an early treatable stage of disease is challenging. Early CTCs can escape from routine blood tests because they are rare events and can migrate between lymph and blood systems. To solve this problem, we introduced photoacoustic flow cytometry in vivo. This clinically-relevant technology is capable of noninvasively counting blood and lymphatic CTCs over disease progression with >1000-times higher sensitivity than existing methods. Here we summarize our preclinical results demonstrating advances of combined lymph+blood diagnosis of CTCs using metastatic melanoma model.

Circulating tumor cells (CTCs) are considered as the “seeds” which disseminate from the solid tumors, circulate within the vasculature and colonize the distant organs (“soil”). CTCs level in peripheral blood has been used for diagnosis, staging, prognosis of cancer, as well as treatment evaluation. Currently, the ex vivo CTC isolation methods (e.g. CellSearch system) are limited to several milliliters of blood and do not take into account the temporal distribution of CTCs in the peripheral blood, However, few studies were conducted to investigate whether CTCs were released into the blood vessel erratically and whether the distribution of CTCs in the blood is uniform. A reliable research tool that can provide sufficient quantity of CTCs, as well as the temporal information of each CTC is necessary to study the temporal distribution of CTCs. In vivo flow cytometry (IVFC) has been demonstrated to be a powerful tool for real-time and continuous monitoring of circulating cells. The time points of each CTC events are recorded with IVFC detection. Here, we established an orthotopic mouse model of prostate cancer by using GFP labeled PC3 cell lines and monitored the variation of CTCs in mouse ear arteries during 24-h of a day with IVFC. Our results suggested that the temporal distribution of CTCs was not even in the orthotopic mouse model of prostate cancer and CTC release may be regulated by circadian rhythm. Our work is thus hopeful to provide a guideline on the time of blood sampling and gain insight into the shedding process of CTCs.

Automatic classification of epithelium and stroma regions on histopathological images is critically important in digital pathology. Although many studies have been conducted in this research area, few investigations have been focused on model generalizability between different types of tissue samples. The objective of this study is to initially verify the classification effectiveness of a sufficiently optimized transfer model. Accordingly, two datasets were assembled, which contain 157 breast cancer images (Dataset I) and 11 ovarian cancer images (Dataset II), respectively. A computer aided detection (CAD) scheme was developed for this classification task. The scheme first divided each image into small regions of interest (ROI) containing only epithelium or stroma tissues, using multi-resolution super-pixel algorithm. Then, a total of 26 quantitative features were computed for each ROI, which were used as the input of five different machine learning classifiers, namely, linear support vector machine (SVM), linear discriminant analysis (LDA), logistic regression, decision tree and k-nearest neighbors (KNN). The scheme was trained and optimized on Dataset I, and five-fold cross validation strategy was utilized for performance evaluation. After the scheme was sufficiently optimized on Dataset I, it was applied “as is” on dataset II. The results of the breast cancer dataset show that linear SVM achieved the highest classification accuracy of 0.910. When applied on the 11 ovarian cancer cases (Dataset II), the SVM model achieved an average classification accuracy of 0.744. This preliminary study initially demonstrates the model transfer performance for epithelium-stroma classification task.

Modern medicine requires to combine the imaging and therapy tools in one object. Two types of nanostructured shells were elaborated. The first type of shell that exhibited the highest photoacoustic and fluorescent signals have utilized a combination of gold nanorods and indocyanine green dispersed in the matrix of biodegradable polymers. The second type based on composite indocyanine green/polymer using a self-quenching effect has been successfully prepared and characterized by fluorescent and optoacoustic tomographies. Optimal compositions and structures of nanostructured shells from point of view of photoacoustic and fluorescent signal intensities required for detection of nanostructured shell in vivo were found.

Bone disease is a growing epidemic in the world today that will lead to billions of dollars of medical bills. While a range of lifestyle and genetic factors play a role in the progression of disease, in overarching symptom of increased bone porosity leads to decreased mobility, pain, fracture, and even death. Therefore, it is important to monitor trabecular bone for better care of affected individuals. Photoacoustic microscopy (PAM) is a hybrid modality that combines high optical absorption qualities of biological tissue with high spatial resolution of ultrasound. Our study aims to further assess the ability to image bone microarchitecture with photoacoustic imaging. A picosecond-pulsed laser with a wavelength of 532 nm was used to excite the bone while ultrasonic transients were captured by a 20 MHz transducer. We first preformed studies to characterize our lateral resolution and optimize our system using phantoms mimicking different bone porosity. We then imaged pig bone ex-vivo. Our results show that this photoacoustic (PA) imaging has the potential to identify normal and osteoporosis diseased bone. The capability to noninvasively quantify bone tissue composition suggests a possible use of PAM as an optical biopsy for the diagnosis of bone pathologies such as osteoporosis, which are characterized by a progressive reduction and transformation of mineral in the bone matrix.

Melanoma, developing from melanocytes, is the deadliest type of malignant skin tumors in the world. Due to high light absorption of melanin, rare circulating melanoma cells, as an endogenous marker for metastasis at the early stage, can be quantitatively detected in small superficial vessels of mouse ears by in vivo photoacoustic flow cytometry (PAFC). Before clinical application, the capability of promising PAFC platform should be verified and optimized by mouse vessels, which are similar in size and depth to human vessels. In the current study, compared with optical resolution PAFC (OR-PAFC), we build acoustic resolution PAFC (AR-PAFC) using focused ultrasonic transducer and 1064 nm laser with lower pulse rate, leading to higher detection depth and lower laser power density in mouse models. Besides, based on laser frequency doubling and high absorption coefficient of hemoglobin at 532nm wavelength, the blood vessels can be positioned by lowcost navigation system rather than the expensive system of two coupled lasers or charged coupled device with depth limitation. We confirm that AR-PAFC can be applied to noninvasive label-free counting of circulating melanoma cells in mouse tail veins, and validated by in vitro assays using phantom models, which simulates the scattering and absorption coefficients of living tissue. These results show that AR-PAFC platform has great potential for preoperative diagnosis and postoperative evaluation of melanoma patients.

Integrin α5β1 is a widely-recognized target for molecular probes in various pathological conditions, especially cancer. The development of computer screening approaches to identify novel high affinity ligands to tumor markers has paved the way for a new generation of tumor identification technology. In this study, we have developed an efficient pharmacophore-based computational strategy to screen two novel peptides, RYr and H5, with high affinity to integrin α5β1. Noninvasive optical imaging data showed that these two peptides could be specifically uptaken by α5β1 overexpressed-tumor cells in vitro and in vivo. And these peptides-based probes could retain in tumor tissue for precise tumor identification. Results indicated that the newly identified peptides with high affinity to integrin α5β1 can be used for precise tumor identification and treatment. And this work exploited more functionalities of pharmacophore-based computational strategy for screening targeting-peptides.

This study aims to utilize the primary tumor characteristics from CT images to detect lymph node (LN) metastasis for accurately categorizing locally advanced cervical cancer patients (LACC). In clinical practice, LN metastasis is a critical indicator for patients’ prognostic assessment, which is usually investigated by PET/CT (i.e., positron emission tomography/computed tomography) examination. However, the high cost of the PET/CT imaging modality limits its application and also leads to heavy financial burden on patients. Thus it is clinically imperative to develop an economic solution for the LN metastasis identification. For this purpose, a novel image marker was developed, which is based on the primary cervical tumors segmented from CT images. Accordingly, a total of 99 handcrafted features were computed, and an optimal feature set was determined by Laplacian Score (LS) method. Next, a logistic regression model was applied on the optimal feature set to generate a likelihood score for the identification of LN metastasis. Using a retrospective dataset that contains a total of 82 LACC patients, this new model was trained and optimized by leave one out cross validation (LOOCV) strategy. The marker performance was assessed by receiver operator characteristic curve (ROC). The results indicate that the area under the ROC curve (AUC) of this identification model was 0.774±0.050, which demonstrates its strong discriminative power. This study may be able to provide gynecologic oncologists a CT image based low cost clinical marker to identify LN metastasis occurred on LACC patients.

Mammographic studies have always been a challenge in women with large or dense breasts. A contrast-detail (CD) phantom and an American College of Radiology (ACR) accredited phantom are used in this study to compare the detectability of the mid-energy phase-contrast x-ray imaging system and conventional x-ray imaging mode among women with hyper-glandular breast tissue. Insert wax from ACR phantom and the contrast-detail test pattern are both inserted between two 70/30 glandular-adipose tissue equivalent plates, to simulate a 5 cm thick compressed dense breast. Both phantoms are imaged by the two modalities: (a): the x-ray bench-top imaging system in contact mode, similar to conventional mammography, operated at 35kV with 0.5 mm aluminum filter, and (b): the mid-energy in-line phasesensitive prototype, which is operated at 59kV, 1.3 mm aluminum filter and the magnification factor of 2.5. Both imaging systems applied an average glandular radiation dose of 1.6 mGy. The results show that the image of ACR phantom which is acquired by mid-energy phase-contrast imaging system reveals more embedded objects within the phantom compare to conventional imaging system under the similar average glandular dose. The contrast-detail curves for CD phantom, obtained from two imaging prototypes, confirm the superior detectability of phase contrast imaging system. Therefore, this preliminary experiment demonstrates that mid-energy phase-contrast x-ray imaging system exceeds the performance of conventional mammography in hyper-glandular breast tissue at the equal level of radiation dose to the patients.