As a hybrid imaging modality that combines optical excitation with acoustic detection, photoacoustic tomography (PAT) has become one of the fastest growing biomedical imaging modalities. Among various types of transducer arrays used in a PAT system configuration, the linear array is the most commonly utilized due to its convenience and low-cost. Although linear array-based PAT has been quickly developed within the recent decade, there are still two major challenges that impair the overall performance of the PAT imaging system. The first challenge is that the three-dimensional (3D) imaging capability of a linear array is limited due to its poor elevational resolution. The other challenge is that the geometrical shape of the linear array constrains light illumination. To date, substantial efforts have been made to address the aforementioned challenges. This review will present current technologies for improving the elevation resolution and light delivery of linear array-based PAT systems.

Photodynamic therapy (PDT) is a promising tool for least-invasive alternative methods for the treatment of brain tumors. The newly discovered PDT-induced opening of the blood–brain barrier (BBB) permeability open novel strategies for drug-brain delivery during post-surgical treatment of glioblastoma GBM. Here we discuss mechanisms of PDT-mediated opening of the BBB and age differences in PDT-related increase in BBB permeability, including with formation of brain edema. The meningeal lymphatic system plays a crucial role in the mechanism of brain drainage and clearance from metabolites and toxic molecules. We discuss that noninvasive photonic stimulation of fluid clearance via meningeal lymphatic vessels, and application of optical coherence tomography (OCT) for bed-side monitoring of meningeal lymphatic drainage has the promising perspective to be widely applied in both experimental and clinical studies of PDT and improving guidelines of PDT of brain tumors.

The effect of optical cleaning method combined with laser speckle imaging (LSI) was discussed to improve the detection depth of LSI due to high scattering characteristics of skin, which limit its clinical application. A double-layer skin tissue model embedded with a single blood vessel was established, and the Monte Carlo method was used to simulate photon propagation under the action of light-permeating agent. 808 nm semiconductor and 632.8nm He–Ne lasers were selected to study the effect of optical clearing agents (OCAs) on photon deposition in tissues. Results show that the photon energy deposition density in the epidermis increases with the amount of tissue fluid replaced by OCA. Compared with glucose solution, polyethylene glycol 400 (PEG 400) and glycerol can considerably increase the average penetration depth of photons in the skin tissue, thereby raising the sampling depth of the LSI. After the action of glycerol, PEG 400, and glucose, the average photon penetration depth is increased by 51.78%, 51.06%, and 21.51% for 808 nm, 68.93%, 67.94%, and 26.67% for 632.8 nm lasers, respectively. In vivo experiment by dorsal skin chamber proves that glycerol can cause a substantial decrease in blood flow rate, whereas PEG 400 can significantly improve the capability of light penetration without affecting blood velocity, which exhibits considerable potential in the monitoring of blood flow in skin tissues.

Screening and diagnosing of abnormal Leukocytes are crucial for the diagnosis of immune diseases and Acute Lymphoblastic Leukemia (ALL). As the deterioration of abnormal leukocytes is mainly due to the changes in the chromatin distribution, which significantly affects the absorption and reflection of light, the spectral feature is proved to be important for leukocytes classification and identification. This paper proposes an accurate identification method for healthy and abnormal leukocytes based on microscopic hyperspectral imaging (HSI) technology which combines the spectral information. The segmentation of nucleus and cytoplasm is obtained by the morphological watershed algorithm. Then, the spectral features are extracted and combined with the spatial features. Based on this, the support vector machine (SVM) is applied for classification of five types of leukocytes and abnormal leukocytes. Compared with different classification methods, the proposed method utilizes spectral features which highlight the differences between healthy leukocytes and abnormal leukocytes, improving the accuracy in the classification and identification of leukocytes. This paper only selects one subtype of ALL for test, and the proposed method can be applied for detection of other leukemia in the future.

Coptidis Rhizoma (Chinese: Huanglian) and Phellodendri Chinensis Cortex (Chinese: Huangbo) are widely used Traditional Chinese Medicine, and often used in combination because of their similar pharmacological effects in clinical practice. However, the quality control methods of the two drugs are different and complicated, which is time consuming and laborious in practical application. In this paper, rapid and simultaneous determination of moisture and berberine in Coptidis Rhizoma (CR) and Phellodendri Chinensis Cortex (PC) was realized by near-infrared spectroscopy (NIRs) combined with global models. Competitive adaptive reweighted sampling (CARS) and successive projection algorithm (SPA) method were applied for variable selection. Principal component analysis (PCA) and partial least squares regression method (PLSR) were applied for qualitative and quantitative analysis, respectively. The characteristic variables of berberine showed similarity and consistency in distribution, providing basis for the global models. For moisture content, the global model had relative standard error of prediction set (RSEP) value of 3.04% and 2.53% for CR and PC, respectively. For berberine content, the global model had RSEP value of 5.41% and 3.97% for CR and PC, respectively. These results indicated the global models based on CARS-PLS method achieved satisfactory prediction for moisture and berberine content, improving the determination e±ciency. Furthermore, the greater range and larger number of samples enhanced the reliance of the global model. The NIRs combined with global models could be a powerful tool for quality control of CR and PC.

To date, numerous studies have been performed to elucidate the complex cellular dynamics in skin diseases, but few have attempted to characterize these cellular events under conditions similar to the native environment. To address this challenge, a three-dimensional (3D) multimodal analysis platform was developed for characterizing in vivo cellular dynamics in skin, which was then utilized to process in vivo wound healing data to demonstrate its applicability. Special attention is focused on in vivo biological parameters that are di±cult to study with ex vivo analysis, including 3D cell tracking and techniques to connect biological information obtained from different imaging modalities. These results here open new possibilities for evaluating 3D cellular dynamics in vivo, and can potentially provide new tools for characterizing the skin microenvironment and pathologies in the future.

Rubber sheets are one of the primary products of natural rubber and are the main raw material in various rubber industries. The quality of a rubber sheet can be visually examined by holding it against clear light to inspect for any specks and impurities inside, but its moisture content is di±cult to evaluate based on a visual inspection and this might lead to unfair trading. Herein, we developed a rapid, robust and nondestructive near-infrared spectroscopy (NIRS)-based method for moisture content determination in rubber sheets. A set of 300 rubber sheets were divided into a calibration (200 samples) and prediction groups (100 samples). The calibration set was used to develop NIRS calibration equation using different calibration models, Partial Least Square Regression (PLSR), Least Square Support Vector Machine (LS-SVM) and Artificial Neural Network (ANN). Among the models investigated, the ANN model with the first derivative of spectral preprocessing presented the best prediction with a coe±cient of determination (R2P) of 0.993, root mean square error of calibration (RMSEC) of 0.126% and root mean square error of prediction (RMSEP) of 0.179%. The results indicated that the proposed NIRS-ANN model will be able to reduce human error and provide a highly accurate estimate of the moisture content in a rubber sheet compared to traditional wet chemistry estimation methods according to AOAC standards.

Histopathological examination is still the gold standard for diagnoses of oral-maxillofacial lesions, but it is invasive and time-consuming. Optical coherence tomography (OCT) provides a kind of noninvasive, label-free, real-time and high-resolution imaging technology. In this study, in order to assess the feasibility of OCT in oral clinical application, fresh excised tissue specimens from 59 patients undergoing oral-maxillofacial surgery were imaged in detail by using a benchtop sweptsource OCT system. It is shown that different lesions or tissues can be obviously distinguished based on their different microstructural features in OCT images, and the features are similar to those of their corresponding histopathological images. It is proven that OCT has great feasibility and potential as a diagnostic aid for surgeons in oral medicine.