Determination of the diameter of simulated human capillaries using shifted position-diffuse reflectance imaging

Microscopy Image Dataset for Deep Learning-Based Quantitative Assessment of Pulmonary Vascular Changes

Pulmonary hypertension (PH) is a syndrome complex that accompanies a number of diseases of different etiologies, associated with basic mechanisms of structural and functional changes of the pulmonary circulation vessels and revealed pressure increasing in the pulmonary artery. The structural changes in the pulmonary circulation vessels are the main limiting factor determining the prognosis of patients with PH. Thickening and irreversible deposition of collagen in the pulmonary artery branches walls leads to rapid disease progression and a therapy effectiveness decreasing. In this regard, histological examination of the pulmonary circulation vessels is critical both in preclinical studies and clinical practice. However, measurements of quantitative parameters such as the average vessel outer diameter, the vessel walls area, and the hypertrophy index claimed significant time investment and the requirement for specialist training to analyze micrographs. A dataset of pulmonary circulation vessels for pathology assessment using semantic segmentation techniques based on deep-learning is presented in this work. 609 original microphotographs of vessels, numerical data from experts' measurements, and microphotographs with outlines of these measurements for each of the vessels are presented. Furthermore, here we cite an example of a deep learning pipeline using the U-Net semantic segmentation model to extract vascular regions. The presented database will be useful for the development of new software solutions for the analysis of histological micrograph.

Ultrasound-responsive microbubbles and nanodroplets: A pathway to targeted drug delivery

Ultrasound-responsive agents have shown great potential as targeted drug delivery agents, effectively augmenting cell permeability and facilitating drug absorption. This review focuses on two specific agents, microbubbles and nanodroplets, and provides a sequential overview of their drug delivery process. Particular emphasis is given to the mechanical response of the agents under ultrasound, and the subsequent physical and biological effects on the cells. Finally, the state-of-the-art in their pre-clinical and clinical implementation are discussed. Throughout the review, major challenges that need to be overcome in order to accelerate their clinical translation are highlighted.

Experimental Validation of Shifted Position-Diffuse Reflectance Imaging (SP-DRI) on Optical Phantoms

Numerous diseases such as hemorrhage, sepsis or cardiogenic shock induce a heterogeneous perfusion of the capillaries. To detect such alterations in the human blood flow pattern, diagnostic devices must provide an appropriately high spatial resolution. Shifted position-diffuse reflectance imaging (SP-DRI) has the potential to do so; it is an all-optical diagnostic technique. So far, SP-DRI has mainly been developed using Monte Carlo simulations. The present study is therefore validating this algorithm experimentally on realistic optical phantoms with thread structures down to 10 μm in diameter; a SP-DRI sensor prototype was developed and realized by means of additive manufacturing. SP-DRI turned out to be functional within this experimental framework. The position of the structures within the optical phantoms become clearly visible using SP-DRI, and the structure thickness is reflected as modulation in the SP-DRI signal amplitude; this performed well for a shift along the x axis as well as along the y axis. Moreover, SP-DRI successfully masked the pronounced influence of the illumination cone on the data. The algorithm showed significantly superior to a mere raw data inspection. Within the scope of the study, the constructive design of the SP-DRI sensor prototype is discussed and potential for improvement is explored.

The influence of the optical properties on the determination of capillary diameters

Various clinically applicable scores and indices are available to help identify the state of a microcirculatory disorder in a patient. Several of these methods, however, leave room for interpretation and only provide clues for diagnosis. Thus, a measurement method that allows a reliable detection of impending or manifest circulatory malfunctions would be of great value. In this context, the optical and non-invasive method of shifted position-diffuse reflectance imaging (SP-DRI) was developed. It allows to determine the capillary diameter and thus to assess the state of the microcirculation. The aim of the present study is to investigate how the quantification of capillary diameters by SP-DRI behaves in different individuals, i.e. for a wide range of optical properties. For this, within Monte-Carlo simulations all optical properties (seven skin layers, hemoglobin) were randomly varied following a Gaussian distribution. An important finding from the present investigation is that SP-DRI works when the optical properties are chosen randomly. Furthermore, it is shown that appropriate data analysis allows calibration-free absolute quantification of the capillary diameter across individuals using SP-DRI. This underpins the potential of SP-DRI to serve as an early alert system for the onset of microcirculatory associated diseases.