Universal in vivo Textural Model for Human Skin based on Optical Coherence Tomograms

Currently, diagnosis of skin diseases is based primarily on visual pattern recognition skills and expertise of the physician observing the lesion. Even though dermatologists are trained to recognize patterns of morphology, it is still a subjective visual assessment. Tools for automated pattern recognition can provide objective information to support clinical decision-making. Noninvasive skin imaging techniques provide complementary information to the clinician. In recent years, optical coherence tomography has become a powerful skin imaging technique. According to specific functional needs, skin architecture varies across different parts of the body, as do the textural characteristics in OCT images. There is, therefore, a critical need to systematically analyze OCT images from different body sites, to identify their significant qualitative and quantitative differences. Sixty-three optical and textural features extracted from OCT images of healthy and diseased skin are analyzed and in conjunction with decision-theoretic approaches used to create computational models of the diseases. We demonstrate that these models provide objective information to the clinician to assist in the diagnosis of abnormalities of cutaneous microstructure, and hence, aid in the determination of treatment. Specifically, we demonstrate the performance of this methodology on differentiating basal cell carcinoma (BCC) and squamous cell carcinoma (SCC) from healthy tissue

Intra-operative point-of-procedure delineation of oral cancer margins using optical coherence tomography.

ObjectivesSurgical margin status is a significant determinant of treatment outcome in oral cancer. Negative surgical margins can decrease the loco-regional recurrence by five-fold. The current standard of care of intraoperative clinical examination supplemented by histological frozen section, can result in a risk of positive margins from 5 to 17 percent. In this study, we attempted to assess the utility of intraoperative optical coherence tomography (OCT) imaging with automated diagnostic algorithm to improve on the current method of clinical evaluation of surgical margin in oral cancer.Materials and methodsWe have used a modified handheld OCT device with automated algorithm based diagnostic platform for imaging. Intraoperatively, images of 125 sites were captured from multiple zones around the tumor of oral cancer patients (n = 14) and compared with the clinical and pathologic diagnosis.ResultsOCT showed sensitivity and specificity of 100%, equivalent to histological diagnosis (kappa, ĸ = 0.922), in detection of malignancy within tumor and tumor margin areas. In comparison, for dysplastic lesions, OCT-based detection showed a sensitivity of 92.5% and specificity of 68.8% and a moderate concordance with histopathology diagnosis (ĸ = 0.59). Additionally, the OCT scores could significantly differentiate squamous cell carcinoma (SCC) from dysplastic lesions (mild/moderate/severe; p ≤ 0.005) as well as the latter from the non-dysplastic lesions (p ≤ 0.05).ConclusionThe current challenges associated with clinical examination-based margin assessment could be improved with intra-operative OCT imaging. OCT is capable of identifying microscopic tumor at the surgical margins and demonstrated the feasibility of mapping of field cancerization around the tumor

2D Fourier Fractal Analysis of Optical Coherence Tomography Images of Basal Cell Carcinomas and Melanomas

The optical coherence tomography (OCT) technique is applied in the diagnosis of the skin tissue. In general, quantitative imaging features obtained from OCT images have already been used as biomarkers to categorize skin tumors. Particularly, the fractal dimension (FD) could be capable of providing an efficient approach for analyzing OCT images of skin tumors. The 2D Fourier fractal analysis (FFA) as well as the differential box counting method (DBCM) was used in this paper to classify the basal cell carcinomas (BCC), melanomas, and benign melanocytic nevi. Generalized estimating equations were used to test for differences between skin tumors. Our results showed that the significant decrease of the 2D FD was detected in the benign melanocytic nevi and basal cell carcinomas as compared with the melanomas. Our results also suggested that the 2D FFA could provide a more efficient way to calculating FD to differentiate the basal cell carcinomas, melanomas, and benign melanocytic nevi as compared to the 2D DBCM

<i>In vivo</i> assessment of optical properties of basal cell carcinoma and differentiation of BCC subtypes by high-definition optical coherence tomography

High-definition optical coherence tomography (HD-OCT) features of basal cell carcinoma (BCC) have recently been defined. We assessed in vivo optical properties (IV-OP) of BCC, by HD-OCT. Moreover their critical values for BCC subtype differentiation were determined. The technique of semi-log plot whereby an exponential function becomes linear has been implemented on HD-OCT signals. The relative attenuation factor (µ(raf)) at different skin layers could be assessed.(.) IV-OP of superficial BCC with high diagnostic accuracy (DA) and high negative predictive values (NPV) were (i) decreased µ(raf) in lower part of epidermis and (ii) increased epidermal thickness (E-T). IV-OP of nodular BCC with good to high DA and NPV were (i) less negative µ(raf) in papillary dermis compared to normal adjacent skin and (ii) significantly decreased E-T and papillary dermal thickness (PD-T). In infiltrative BCC (i) high µ(raf) in reticular dermis compared to normal adjacent skin and (ii) presence of peaks and falls in reticular dermis had good DA and high NPV. HD-OCT seems to enable the combination of in vivo morphological analysis of cellular and 3-D micro-architectural structures with IV-OP analysis of BCC. This permits BCC sub-differentiation with higher accuracy than in vivo HD-OCT analysis of morphology alone

Dynamic Optical Coherence Tomography in Dermatology

Optical coherence tomography (OCT) represents a non-invasive imaging technology, which may be applied to the diagnosis of non-melanoma skin cancer and which has recently been shown to improve the diagnostic accuracy of basal cell carcinoma. Technical developments of OCT continue to expand the applicability of OCT for different neoplastic and inflammatory skin diseases. Of these, dynamic OCT (D-OCT) based on speckle variance OCT is of special interest as it allows the in vivo evaluation of blood vessels and their distribution within specific lesions, providing additional functional information and consequently greater density of data. In an effort to assess the potential of D-OCT for future scientific and clinical studies, we have therefore reviewed the literature and preliminary unpublished data on the visualization of the microvasculature using D-OCT. Information on D-OCT in skin cancers including melanoma, as well as in a variety of other skin diseases, is presented in an atlas. Possible diagnostic features are suggested, although these require additional validation

Towards an Effective Imaging-Based Decision Support System for Skin Cancer

The usage of expert systems to aid in medical decisions has been employed since 1980s in distinct ap plications. With the high demands of medical care and limited human resources, these technologies are required more than ever. Skin cancer has been one of the pathologies with higher growth, which suf fers from lack of dermatology experts in most of the affected geographical areas. A permanent record of examination that can be further analyzed are medical imaging modalities. Most of these modalities were also assessed along with machine learning classification methods. It is the aim of this research to provide background information about skin cancer types, medical imaging modalities, data mining and machine learning methods, and their application on skin cancer imaging, as well as the disclosure of a proposal of a multi-imaging modality decision support system for skin cancer diagnosis and treatment assessment based in the most recent available technology. This is expected to be a reference for further implementation of imaging-based clinical support systems.info:eu-repo/semantics/publishedVersio

In-vivo usefulness of optical coherence tomography in atrophic-erosive oral lichen planus: Comparison between histopathological and ultrastructural findings

Oral lichen planus (OLP) is a common premalignant chronic inflammatory disorder. Optical Coherence Tomography (OCT) provides a real-time, non-invasive, and in-situ optical signature using light of varying wavelengths to examine tissue. Aim of the present study was to assess the possible role of OCT as diagnostic tool for atrophic-erosive OLP by examining OCT scans of healthy buccal mucosa, and comparing their ultrastructural features with those of a buccal mucosa affected by atrophic-erosive OLP, using their histopathological counterparts as the gold standard. Through grayscale (enface scan) and an application in which the vascularization of the tissue is visible (dynamic scan), it was possible to distinguish the healthy from the lichenoid pattern from 20 controls (12 M; 8 F; mean age: 41.32 years) and 20 patients with histologically confirmed atrophic-erosive OLP (7 M; 13 F; mean age: 64.27 years). In detail, mean width of stratified squamous epithelium (EP) and lamina propria (LP) were evaluated. Among controls, EP and LP showed a mean width of 300 (±50) and of 600 (±50) μm respectively; among cases, disruption of membrane basement prevented from any measurement. Furthermore, a differential pattern of EP and LP emerged between the two groups: a light-grayish, hypo-reflective, homogeneous area of EP recurring in controls turned into a hyper-reflective, non-homogeneous area among cases. Dynamic scan showed a differential profile of LP vascularization, varying from a hypo-reflective red area with small blood vessels in the control group, to a hypo/hyper-reflective area, completely overrun by a denser, wider blood flow amid OLP cases. Although histopathological examination remains the gold standard for OLP diagnosis, OCT could be a potentially helpful tool for the clinician and the pathologist, since it allows analysis of the vascularization of the sample without adversely affecting histological processing

A roadmap for the clinical implementation of optical-imaging biomarkers

Clinical workflows for the non-invasive detection and characterization of disease states could benefit from optical-imaging biomarkers. In this Perspective, we discuss opportunities and challenges towards the clinical implementation of optical-imaging biomarkers for the early detection of cancer by analysing two case studies: the assessment of skin lesions in primary care, and the surveillance of patients with Barrett’s oesophagus in specialist care. We stress the importance of technical and biological validations and clinical-utility assessments, and the need to address implementation bottlenecks. In addition, we define a translational roadmap for the widespread clinical implementation of optical imaging-technologies