Visualization of pulmonary inflammation using noninvasive fluorescence molecular imaging.

The ability to visualize molecular processes and cellular regulators of complex pulmonary diseases such as asthma, chronic obstructive pulmonary disease (COPD), or adult respiratory distress syndrome (ARDS), would aid in the diagnosis, differentiation, therapy assessment and in small animal-based drug-discovery processes. Herein we report the application of normalized transillumination and fluorescence molecular tomography (FMT) for the noninvasive quantitative imaging of the mouse lung in vivo. We demonstrate the ability to visualize and quantitate pulmonary response in a murine model of LPS-induced airway inflammation. Twenty-four hours prior to imaging, BALB/c female mice were injected via tail vein with 2 nmol of a cathepsin-sensitive activatable fluorescent probe (excitation: 750 nm; emission: 780 nm) and 2 nmol of accompanying intravascular agent (excitation: 674 nm; emission: 694 nm). Six hours later, the mice were anesthetized with isoflurane and administered intranasal LPS in sterile 0.9% saline in 25 microl aliquots (one per nostril). Fluorescence molecular imaging revealed the in vivo profile of cysteine protease activation and vascular distribution within the lung typifying the inflammatory response to LPS insult. Results were correlated with standard in vitro laboratory tests (Western blot, bronchoalveolar lavage or BAL analysis, immunohistochemistry) and revealed good correlation with the underlying activity. We demonstrated the capacity of fluorescence tomography to noninvasively and longitudinally characterize physiological, cellular, and subcellular processes associated with inflammatory disease burden in the lung. The data presented herein serve to further evince fluorescence molecular imaging as a technology highly appropriate for the biomedical laboratory.     

LV-GAN: A deep learning approach for limited-view optoacoustic imaging based on hybrid datasets

The optoacoustic imaging (OAI) methods are rapidly evolving for resolving optical contrast in medical imaging applications. In practice, measurement strategies are commonly implemented under limited-view conditions due to oversized image objectives or system design limitations. Data acquired by limited-view detection may impart artifacts and distortions in reconstructed optoacoustic (OA) images. We propose a hybrid data-driven deep learning approach based on generative adversarial network (GAN), termed as LV-GAN, to efficiently recover high quality images from limited-view OA images. Trained on both simulation and experiment data, LV-GAN is found capable of achieving high recovery accuracy even under limited detection angles less than 60^°. The feasibility of LV-GAN for artifact removal in biological applications was validated by ex vivo experiments based on two different OAI systems, suggesting high potential of a ubiquitous use of LV-GAN to optimize image quality or system design for different scanners and application scenarios.     

Intravascular molecular-structural imaging with a miniaturized integrated near-infrared fluorescence and ultrasound catheter

Coronary artery disease (CAD) remains a leading cause of mortality and warrants new imaging approaches to better guide clinical care. We report on a miniaturized, hybrid intravascular catheter and imaging system for comprehensive coronary artery imaging in vivo. Our catheter exhibits a total diameter of 1.0 mm (3.0 French), equivalent to standalone clinical intravascular ultrasound (IVUS) catheters but enables simultaneous near-infrared fluorescence (NIRF) and IVUS molecular-structural imaging. We demonstrate NIRF-IVUS imaging in vitro in coronary stents using NIR fluorophores, and compare NIRF signal strengths for prism and ball lens sensor designs in both low and high scattering media. Next, in vivo intravascular imaging in pig coronary arteries demonstrates simultaneous, co-registered molecular-structural imaging of experimental CAD inflammation on IVUS and distance-corrected NIRF images. The obtained results suggest substantial potential for the NIRF-IVUS catheter to advance standalone IVUS, and enable comprehensive phenotyping of vascular disease to better assess and treat patients with CAD.     

Habitat discrimination of juvenile sardines in the Aegean Sea using remotely sensed environmental data

Despite the importance of the recruitment process for small pelagic fish and the high economic importance of European sardine (Sardina pilchardus, Walbaum 1792) in the Mediterranean Sea, knowledge on the distribution and environmental characteristics of its nursery grounds is very limited. In the present study, we used pelagic trawl data collected during 1995–2006 to explore the spatial distribution of sardine juveniles in the Aegean Sea in early summer. Based on sardine abundance per length class, a cluster analysis was initially used to define hauls dominated by juveniles. In a subsequent step, Discriminant Function Analysis (DFA) was applied to discriminate stations with high relative abundance of juveniles using satellite environmental data and bottom depth. The parameters contributing mostly to the discrimination of juvenile grounds were sea level anomaly, photosynthetically active radiation, sea surface temperature, chlorophyll-α and bottom depth. The classification functions of DFA were finally used to post classify unsampled areas in the Greek Seas and the Mediterranean Sea in order to map grounds that meet characteristic environmental conditions for young sardine. Such areas were mostly located inshore, in semi-closed productive areas and often in proximity to river mouths, a pattern that is generally supported by existing information. Guest editor: V. D. Valavanis Essential Fish Habitat Mapping in the Mediterranean