Quantitative principal component model for skin chromophore mapping using multi-spectral images and spatial priors

Noninvasive hemoglobin sensing and imaging: optical tools for disease diagnosis

SIGNIFICANCE

Measurement and imaging of hemoglobin oxygenation are used extensively in the detection and diagnosis of disease; however, the applied instruments vary widely in their depth of imaging, spatiotemporal resolution, sensitivity, accuracy, complexity, physical size, and cost. The wide variation in available instrumentation can make it challenging for end users to select the appropriate tools for their application and to understand the relative limitations of different methods.

AIM

We aim to provide a systematic overview of the field of hemoglobin imaging and sensing.

APPROACH

We reviewed the sensing and imaging methods used to analyze hemoglobin oxygenation, including pulse oximetry, spectral reflectance imaging, diffuse optical imaging, spectroscopic optical coherence tomography, photoacoustic imaging, and diffuse correlation spectroscopy.

RESULTS

We compared and contrasted the ability of different methods to determine hemoglobin biomarkers such as oxygenation while considering factors that influence their practical application.

CONCLUSIONS

We highlight key limitations in the current state-of-the-art and make suggestions for routes to advance the clinical use and interpretation of hemoglobin oxygenation information.

Current and Future Tools for Diagnosis of Kaposi's Sarcoma

Simple Summary

Kaposi’s sarcoma, a rare opportunistic tumor, is observed in four epidemiological conditions (AIDS-related, iatrogenic, endemic or classic KS). Although in most cases KS is an indolent disease, it can be locally aggressive and/or it can invade other organs than the skin, resulting in more severe presentations, especially in patients with severe immunosuppression. There is no consensus on the imaging workup that is necessary for either the initial staging of the disease or the follow-up. Future perspectives include the use of certain non-invasive imaging tools that may help to evaluate the clinical response to treatment, as well as certain new histological markers that may help in guiding the treatment planning for this atypical neoplasm.

Abstract

Kaposi’s sarcoma (KS) is a rare, atypical malignancy associated with immunosuppression and can be qualified as an opportunistic tumor, which responds to immune modulation or restoration. Four different epidemiological forms have been individualized (AIDS-related, iatrogenic, endemic or classic KS). Although clinical examination is sufficient to diagnose cutaneous lesions of KS, additional explorations are necessary in order to detect lesions involving other organs. New histological markers have been developed in recent years concerning the detection of HHV-8 latent or lytic proteins in the lesions, helping to confirm the diagnosis when it is clinically doubtful. More recently, the evaluation of the local immune response has also been shown to provide some guidance in choosing the appropriate therapeutic option when necessary. We also review the indication and the results of conventional radiological imaging and of non-invasive imaging tools such as ¹⁸F-fluoro-deoxy-glucose positron emission tomography, thermography and laser Doppler imaging for the diagnosis of KS and for the follow-up of therapeutic response in patients requiring systemic treatment.

Helical Nanostructures of Ferroelectric Liquid Crystals as Fast Phase Retarders for Spectral Information Extraction Devices: A Comparison with the Nematic Liquid Crystal Phase Retarders

Extraction of spectral information using liquid crystal (LC) retarders has recently become a topic of great interest because of its importance for creating hyper- and multispectral images in a compact and inexpensive way. However, this method of hyperspectral imaging requires thick LC-layer retarders (50 µm-100 µm and above) to obtain spectral modulation signals for reliable signal reconstruction. This makes the device extremely slow in the case of nematic LCs (NLCs), since the response time of NLCs increases proportionally to the square of the LC-layer thickness, which excludes fast dynamic processes monitoring. In this paper, we explore two approaches for solving the speed problem: the first is based on the use of faster nanospiral ferroelectric liquid crystals as an alternative to NLCs, and the second is based on using a passive multiband filter and focuses on multispectral extraction rather than hyperspectral. A detailed comparative study of nematic and ferroelectric devices is presented. The study is carried out using a 9-spectral bands passive spectral filter, covering the visible and near-infrared ranges. We propose the concept of multispectral rather than hyperspectral extraction, where a small number of wavelengths are sufficient for specific applications.

Detection of pancreatic tumor cell nuclei via a hyperspectral analysis of pathological slides based on stain spectra

Hyperspectral imaging (HSI) provides more detailed information than red-green-blue (RGB) imaging, and therefore has potential applications in computer-aided pathological diagnosis. This study aimed to develop a pattern recognition method based on HSI, called hyperspectral analysis of pathological slides based on stain spectrum (HAPSS), to detect cancers in hematoxylin and eosin-stained pathological slides of pancreatic tumors. The samples, comprising hyperspectral cubes of 420-750 nm, were harvested for HSI and tissue microarray (TMA) analysis. As a result of conducting HAPSS experiments with a support vector machine (SVM) classifier, we obtained maximal accuracy of 94%, a 14% improvement over the widely used RGB images. Thus, HAPSS is a suitable method to automatically detect tumors in pathological slides of the pancreas.

Modeling Photo-Bleaching Kinetics to Create High Resolution Maps of Rod Rhodopsin in the Human Retina

We introduce and describe a novel non-invasive in-vivo method for mapping local rod rhodopsin distribution in the human retina over a 30-degree field. Our approach is based on analyzing the brightening of detected lipofuscin autofluorescence within small pixel clusters in registered imaging sequences taken with a commercial 488nm confocal scanning laser ophthalmoscope (cSLO) over a 1 minute period. We modeled the kinetics of rhodopsin bleaching by applying variational optimization techniques from applied mathematics. The physical model and the numerical analysis with its implementation are outlined in detail. This new technique enables the creation of spatial maps of the retinal rhodopsin and retinal pigment epithelium (RPE) bisretinoid distribution with an ≈ 50μm resolution.

Second derivative multispectral algorithm for quantitative assessment of cutaneous tissue oxygenation

We report a second derivative multispectral algorithm for quantitative assessment of cutaneous tissue oxygen saturation (StO₂). The algorithm is based on a forward model of light transport in multilayered skin tissue and an inverse algorithm for StO₂ reconstruction. Based on the forward simulation results, a parameter of a second derivative ratio (SDR) is derived as a function of cutaneous tissue StO₂. The SDR function is optimized at a wavelength set of 544, 552, 568, 576, 592, and 600 nm so that cutaneous tissue StO₂ can be derived with minimal artifacts by blood concentration, tissue scattering, and melanin concentration. The proposed multispectral StO₂ imaging algorithm is verified in both benchtop and in vivo experiments. The experimental results show that the proposed multispectral imaging algorithm is able to map cutaneous tissue StO₂ in high temporal resolution with reduced measurement artifacts induced by different skin conditions in comparison with other three commercial tissue oxygen measurement systems. These results indicate that the multispectral StO₂ imaging technique has the potential for noninvasive and quantitative assessment of skin tissue oxygenation with a high temporal resolution.

Evaluation of non-invasive multispectral imaging as a tool for measuring the effect of systemic therapy in Kaposi sarcoma

Diffuse multi-spectral imaging has been evaluated as a potential non-invasive marker of tumor response. Multi-spectral images of Kaposi sarcoma skin lesions were taken over the course of treatment, and blood volume and oxygenation concentration maps were obtained through principal component analysis (PCA) of the data. These images were compared with clinical and pathological responses determined by conventional means. We demonstrate that cutaneous lesions have increased blood volume concentration and that changes in this parameter are a reliable indicator of treatment efficacy, differentiating responders and non-responders. Blood volume decreased by at least 20% in all lesions that responded by clinical criteria and increased in the two lesions that did not respond clinically. Responses as assessed by multi-spectral imaging also generally correlated with overall patient clinical response assessment, were often detectable earlier in the course of therapy, and are less subject to observer variability than conventional clinical assessment. Tissue oxygenation was more variable, with lesions often showing decreased oxygenation in the center surrounded by a zone of increased oxygenation. This technique could potentially be a clinically useful supplement to existing response assessment in KS, providing an early, quantitative, and non-invasive marker of treatment effect.

Skin parameter map retrieval from a dedicated multispectral imaging system applied to dermatology/cosmetology

In vivo quantitative assessment of skin lesions is an important step in the evaluation of skin condition. An objective measurement device can help as a valuable tool for skin analysis. We propose an explorative new multispectral camera specifically developed for dermatology/cosmetology applications. The multispectral imaging system provides images of skin reflectance at different wavebands covering visible and near-infrared domain. It is coupled with a neural network-based algorithm for the reconstruction of reflectance cube of cutaneous data. This cube contains only skin optical reflectance spectrum in each pixel of the bidimensional spatial information. The reflectance cube is analyzed by an algorithm based on a Kubelka-Munk model combined with evolutionary algorithm. The technique allows quantitative measure of cutaneous tissue and retrieves five skin parameter maps: melanin concentration, epidermis/dermis thickness, haemoglobin concentration, and the oxygenated hemoglobin. The results retrieved on healthy participants by the algorithm are in good accordance with the data from the literature. The usefulness of the developed technique was proved during two experiments: a clinical study based on vitiligo and melasma skin lesions and a skin oxygenation experiment (induced ischemia) with healthy participant where normal tissues are recorded at normal state and when temporary ischemia is induced.

Locally learning biomedical data using diffusion frames

Diffusion geometry techniques are useful to classify patterns and visualize high-dimensional datasets. Building upon ideas from diffusion geometry, we outline our mathematical foundations for learning a function on high-dimension biomedical data in a local fashion from training data. Our approach is based on a localized summation kernel, and we verify the computational performance by means of exact approximation rates. After these theoretical results, we apply our scheme to learn early disease stages in standard and new biomedical datasets.