Custom Scanning Hyperspectral Imaging System for Biomedical Applications: Modeling, Benchmarking, and Specifications.

Prototyping hyperspectral imaging devices in current biomedical optics research requires taking into consideration various issues regarding optics, imaging, and instrumentation. In summary, an ideal imaging system should only be limited by exposure time, but there will be technological limitations (e.g., actuator delay and backlash, network delays, or embedded CPU speed) that should be considered, modeled, and optimized. This can be achieved by constructing a multiparametric model for the imaging system in question. The article describes a rotating-mirror scanning hyperspectral imaging device, its multiparametric model, as well as design and calibration protocols used to achieve its optimal performance. The main objective of the manuscript is to describe the device and review this imaging modality, while showcasing technical caveats, models and benchmarks, in an attempt to simplify and standardize specifications, as well as to incentivize prototyping similar future designs.

Identification of Human Pathological Mitral Chordae Tendineae Using Polarization-sensitive Optical Coherence Tomography.

Defects of the mitral valve complex imply heart malfunction. The chordae tendineae (CTs) are tendinous strands connecting the mitral and tricuspid valve leaflets to the papillary muscles. These CTs are composed of organized, wavy collagen bundles, making them a strongly birefringent material. Disorder of the collagen structure due to different diseases (rheumatic, degenerative) implies the loss or reduction of tissue birefringence able to be characterized with Polarization Sensitive Optical Coherence Tomography (PS-OCT). PS-OCT is used to discriminate healthy from diseased chords, as the latter must be excised and replaced in clinical conventional interventions. PS-OCT allows to quantify birefringence reduction in human CTs affected by degenerative and rheumatic pathologies. This tissue optical property is proposed as a diagnostic marker for the identification of degradation of tendinous chords to guide intraoperative mitral valve surgery.

Computational modeling and fluorescence microscopy characterization of a two-phase magnetophoretic microsystem for continuous-flow blood detoxification.

Magnetic beads can be functionalized to capture and separate target pathogens from blood for extracorporeal detoxification. The beads can be magnetically separated from a blood stream and collected into a coflowing buffer solution using a two-phase liquid-liquid continuous-flow microfluidic device in the presence of an external field. However, device design and process optimization, i.e. high bead recovery with minimum blood loss or dilution remain a substantial technological challenge. We introduce a CFD-based Eulerian-Lagrangian computational model that enables the rational design and optimization of such systems. The model takes into account dominant magnetic and hydrodynamic forces on the beads as well as coupled bead-fluid interactions. Fluid flow (Navier-Stokes equations) and mass transfer (Fick's law) between the coflowing fluids are solved numerically, while the magnetic force on the beads is predicted using analytical methods. The model is demonstrated via application to a prototype device and used to predict key performance metrics; degree of bead separation, flow patterns, and mass transfer, i.e. blood diffusion to the buffer phase. The impact of different process variables and parameters - flow rates, bead and magnet dimensions and fluid viscosities - on both bead recovery and blood loss or dilution is quantified for the first time. The performance of the prototype device is characterized using fluorescence microscopy and the experimental results are found to match theoretical predictions within an absolute error of 15%. While the model is demonstrated here for analysis of a detoxification device, it can be readily adapted to a broad range of magnetically-enabled microfluidic applications, e.g. bioseparation, sorting and sensing.

Directional Kernel Density Estimation for Classification of Breast Tissue Spectra.

In Breast Conserving Therapy, surgeons measure the thickness of healthy tissue surrounding an excised tumor (surgical margin) via post-operative histological or visual assessment tests that, for lack of enough standardization and reliability, have recurrence rates in the order of 33%. Spectroscopic interrogation of these margins is possible during surgery, but algorithms are needed for parametric or dimension reduction processing. One methodology for tumor discrimination based on dimensionality reduction and nonparametric estimation-in particular, Directional Kernel Density Estimation-is proposed and tested on spectral image data from breast samples. Once a hyperspectral image of the tumor has been captured, a surgeon assists by establishing Regions of Interest where tissues are qualitatively differentiable. After proper normalization, Directional KDE is used to estimate the likelihood of every pixel in the image belonging to each specified tissue class. This information is enough to yield, in almost real time and with 98% accuracy, results that coincide with those provided by histological H&E validation performed after the surgery.

Hessian analysis for the delineation of amorphous anomalies in optical coherence tomography images of the aortic wall.

The aortic aneurysm is a disease originated mainly in the media layer of the aortic wall due to the occurrence of degraded areas of altered biological composition. These anomalous regions affect the structure and strength of the aorta artery, being their occurrence and extension proportional to the arterial vessel health. Optical Coherence Tomography (OCT) is applied to obtain cross-sectional images of the artery wall. The backscattering mechanisms in tissue make aorta images difficult to analyze due to noise and strong attenuation with penetration. The morphology of anomalies in pathological specimens is also diverse with amorphous shapes and varied dimensions, being these factors strongly related with tissue degradation and the aorta physiological condition. Hessian analysis of OCT images from aortic walls is used to assess the accurate delineation of these anomalous regions. A specific metric of the Hessian determinant is used to delineate degraded regions under blurry conditions and noise. A multiscale approach, based on an anisotropic Gaussian kernel filter, is applied to highlight and aggregate all the heterogeneity present in the aortic wall. An accuracy estimator metric has been implemented to evaluate and optimize the delineation process avoiding subjectivity. Finally, a degradation quantification score has been developed to assess aorta wall condition by OCT with validation against common histology.

Identification of vessel wall degradation in ascending thoracic aortic aneurysms with OCT.

Degradation of the wall of human ascending thoracic aorta has been assessed through Optical Coherence Tomography (OCT). OCT images of the media layer of the aortic wall exhibit micro-structure degradation in case of diseased aortas from aneurysmal vessels. The OCT indicator of degradation depends on the dimension of areas of the media layer where backscattered reflectivity becomes smaller due to a disorder on the morphology of elastin, collagen and smooth muscle cells (SMCs). Efficient pre-processing of the OCT images is required to accurately extract the dimension of degraded areas after an optimized thresholding procedure. OCT results have been validated against conventional histological analysis. The OCT qualitative assessment has achieved a pair sensitivity-specificity of 100%-91.6% in low-high degradation discrimination when a threshold of 4965.88µm(2) is selected. This threshold suggests to have physiological meaning. The OCT quantitative evaluation of degradation achieves a correlation of 0.736 between the OCT indicator and the histological score. This in-vitro study can be transferred to the clinical scenario to provide an intraoperative assessment tool to guide cardiovascular surgeons in open repair interventions.

Optical coherence tomography assessment of vessel wall degradation in thoracic aortic aneurysms.

Optical coherence tomography images of human thoracic aorta from aneurysms reveal elastin disorders and smooth muscle cell alterations when visualizing the media layer of the aortic wall. These disorders can be employed as indicators for wall degradation and, therefore, become a hallmark for diagnosis of risk of aneurysm under intraoperative conditions. Two approaches are followed to evaluate this risk: the analysis of the reflectivity decay along the penetration depth and the textural analysis of a two-dimensional spatial distribution of the aortic wall backscattering. Both techniques require preprocessing stages for the identification of the air-sample interface and for the segmentation of the media layer. Results show that the alterations in the media layer of the aortic wall are better highlighted when the textural approach is considered and also agree with a semiquantitative histopathological grading that assesses the degree of wall degradation. The correlation of the co-occurrence matrix attains a sensitivity of 0.906 and specificity of 0.864 when aneurysm automatic diagnosis is evaluated with a receiver operating characteristic curve.