Optical Coherence Tomography in the Diagnosis of Skin Cancer

Improving skin cancer detection by Raman spectroscopy using convolutional neural networks and data augmentation

Background

Our previous studies have demonstrated that Raman spectroscopy could be used for skin cancer detection with good sensitivity and specificity. The objective of this study is to determine if skin cancer detection can be further improved by combining deep neural networks and Raman spectroscopy.

Patients and methods

Raman spectra of 731 skin lesions were included in this study, containing 340 cancerous and precancerous lesions (melanoma, basal cell carcinoma, squamous cell carcinoma and actinic keratosis) and 391 benign lesions (melanocytic nevus and seborrheic keratosis). One-dimensional convolutional neural networks (1D-CNN) were developed for Raman spectral classification. The stratified samples were divided randomly into training (70%), validation (10%) and test set (20%), and were repeated 56 times using parallel computing. Different data augmentation strategies were implemented for the training dataset, including added random noise, spectral shift, spectral combination and artificially synthesized Raman spectra using one-dimensional generative adversarial networks (1D-GAN). The area under the receiver operating characteristic curve (ROC AUC) was used as a measure of the diagnostic performance. Conventional machine learning approaches, including partial least squares for discriminant analysis (PLS-DA), principal component and linear discriminant analysis (PC-LDA), support vector machine (SVM), and logistic regression (LR) were evaluated for comparison with the same data splitting scheme as the 1D-CNN.

Results

The ROC AUC of the test dataset based on the original training spectra were 0.886±0.022 (1D-CNN), 0.870±0.028 (PLS-DA), 0.875±0.033 (PC-LDA), 0.864±0.027 (SVM), and 0.525±0.045 (LR), which were improved to 0.909±0.021 (1D-CNN), 0.899±0.022 (PLS-DA), 0.895±0.022 (PC-LDA), 0.901±0.020 (SVM), and 0.897±0.021 (LR) respectively after augmentation of the training dataset (p<0.0001, Wilcoxon test). Paired analyses of 1D-CNN with conventional machine learning approaches showed that 1D-CNN had a 1-3% improvement (p<0.001, Wilcoxon test).

Conclusions

Data augmentation not only improved the performance of both deep neural networks and conventional machine learning techniques by 2-4%, but also improved the performance of the models on spectra with higher noise or spectral shifting. Convolutional neural networks slightly outperformed conventional machine learning approaches for skin cancer detection by Raman spectroscopy.

Machine Learning Analysis of Human Skin by Optoacoustic Mesoscopy for Automated Extraction of Psoriasis and Aging Biomarkers

Ultra-wideband raster-scan optoacoustic mesoscopy (RSOM) is a novel modality that has demonstrated unprecedented ability to visualize epidermal and dermal structures in-vivo. However, an automatic and quantitative analysis of three-dimensional RSOM datasets remains unexplored. In this work we present our framework: Deep Learning RSOM Analysis Pipeline (DeepRAP), to analyze and quantify morphological skin features recorded by RSOM and extract imaging biomarkers for disease characterization. DeepRAP uses a multi-network segmentation strategy based on convolutional neural networks with transfer learning. This strategy enabled the automatic recognition of skin layers and subsequent segmentation of dermal microvasculature with an accuracy equivalent to human assessment. DeepRAP was validated against manual segmentation on 25 psoriasis patients under treatment and our biomarker extraction was shown to characterize disease severity and progression well with a strong correlation to physician evaluation and histology. In a unique validation experiment, we applied DeepRAP in a time series sequence of occlusion-induced hyperemia from 10 healthy volunteers. We observe how the biomarkers decrease and recover during the occlusion and release process, demonstrating accurate performance and reproducibility of DeepRAP. Furthermore, we analyzed a cohort of 75 volunteers and defined a relationship between aging and microvascular features in-vivo. More precisely, this study revealed that fine microvascular features in the dermal layer have the strongest correlation to age. The ability of our newly developed framework to enable the rapid study of human skin morphology and microvasculature in-vivo promises to replace biopsy studies, increasing the translational potential of RSOM.

Segmentation and quantitative analysis of optical coherence tomography (OCT) images of laser burned skin based on deep learning

Evaluation of skin recovery is an important step in the treatment of burns. However, conventional methods only observe the surface of the skin and cannot quantify the injury volume. Optical coherence tomography (OCT) is a non-invasive, non-contact, real-time technique. Swept source OCT uses near infrared light and analyzes the intensity of light echo at different depths to generate images from optical interference signals. To quantify the dynamic recovery of skin burns over time, laser induced skin burns in mice were evaluated using deep learning of Swept source OCT images. A laser-induced mouse skin thermal injury model was established in thirty Kunming mice, and OCT images of normal and burned areas of mouse skin were acquired at day 0, day 1, day 3, day 7, and day 14 after laser irradiation. This resulted in 7000 normal and 1400 burn B-scan images which were divided into training, validation, and test sets at 8:1.5:0.5 ratio for the normal data and 8:1:1 for the burn data. Normal images were manually annotated, and the deep learning U-Net model (verified with PSPNe and HRNet models) was used to segment the skin into three layers: the dermal epidermal layer, subcutaneous fat layer, and muscle layer. For the burn images, the models were trained to segment just the damaged area. Three-dimensional reconstruction technology was then used to reconstruct the damaged tissue and calculate the damaged tissue volume. The average IoU value and f-score of the normal tissue layer U-Net segmentation model were 0.876 and 0.934 respectively. The IoU value of the burn area segmentation model reached 0.907 and f-score value reached 0.951. Compared with manual labeling, the U-Net model was faster with higher accuracy for skin stratification. OCT and U-Net segmentation can provide rapid and accurate analysis of tissue changes and clinical guidance in the treatment of burns.

Combining Reflectance Confocal Microscopy, Optical Coherence Tomography and Ex-Vivo Fluorescence Confocal Microscopy for Margin Assessment in Basal Cell Carcinoma Excision

INTRODUCTION

Recent developments of noninvasive, high-resolution imaging techniques, such as reflectance confocal microscopy (RCM) and optical coherence tomography (OCT), have enhanced skin cancer detection and precise tumor excision particularly in highly aggressive and poorly defined basal cell carcinomas (BCCs).

OBJECTIVES

The aim of this pilot study is to assess the feasibility and reproducibility of a systematic clinical workflow combining noninvasive (RCM-OCT) and invasive fluorescence confocal microscopy (FCM) imaging modalities in pre- and intra-surgical evaluations of the lateral and deep margins of BCC.

METHODS

Superficial incisions were made 2 mm beyond the clinical-dermoscopic BCC margins. Lateral margins were then explored with OCT and RCM. In positive margins, a further cut was made 2 mm distal from the previous. A final RCM/OCT-based double-negative margin was drawn around the entire perimeter of the lesion before referring to surgery. The freshly excised specimen was then examined with FCM (ex-vivo) for the evaluation of the deep margin. Histopathologic examination eventually confirmed margin involvement.

RESULTS

The study included 22 lesions from 13 patients. At the end of the study, 146 margins-106 negative (73%) and 40 positive (27%) at RCM/OCT-were collected. The RCM/OCT margin evaluation showed an overall sensitivity of 100% and a specificity of 96.3%. The overall positive margins diagnostic accuracy was 98.2%. Reproducibility was evaluated on recorded images and the raters showed a substantial inter-observer agreement on both RCM (κ = 0.752) and OCT images (κ = 0.724).

CONCLUSIONS

The combined RCM/OCT/FCM ex-vivo approach noninvasively facilitates the presurgical and intrasurgical lateral and deep margin assessment of poorly defined BCCs.

Use of Dermoscopy among Greek Dermatologists in Everyday Clinical Practice: A National Questionnaire-Based Study

Background: Dermatoscopy has been established as an important diagnostic tool for a wide range of skin diseases. This study aims to evaluate the use of dermatoscopy in clinical practice among Greek dermatologists. Methods: A nationwide questionnaire-based survey was conducted collecting data on the frequency of dermatoscopic examinations, the types of lesions examined, training and educational resources, as well as factors influencing the choice to incorporate dermatoscopy into daily clinical routines. Results: A total of 366 Greek dermatologists participated in the survey. Most of the respondents reported the daily use of dermatoscopy in their practice. Pigmented and non-pigmented lesions, inflammatory diseases, cutaneous infectious, hair disorders, and nail lesions were the most common indications for dermatoscopy. Factors influencing the utilization of dermatoscopy included increased diagnostic accuracy, enhanced patient care, better patient communication and general compliance, and improved satisfaction among dermatologists. Conclusions: This national questionnaire-based study demonstrates that dermatoscopy has become an integral part of daily dermatological practice in Greece. The findings highlight the significance of structured training and education to promote dermoscopy's effective and routine use. Incorporating dermatoscopy into clinical practice not only improves diagnostic precision but also enhances patient care, contributing to the overall quality of dermatological services in Greece.

Polarization-sensitive optical coherence tomography for renal tumor detection in ex vivo human kidneys

Kidney cancer is a kind of high mortality cancer because of the difficulty in early diagnosis and the high metastatic dissemination in treatments. The surgical resection of tumors is the most effective treatment for renal cancer patients. However, precise assessment of tumor margins is a challenge during surgical resection. The objective of this study is to demonstrate an optical imaging tool in precisely distinguishing kidney tumor borders and identifying tumor zones from normal tissues to assist surgeons in accurately resecting tumors from kidneys during the surgery. 30 samples from six human kidneys were imaged using polarization-sensitive optical coherence tomography (PS-OCT). Cross-sectional, enface, and spatial information of kidney samples were obtained for microenvironment reconstruction. Polarization parameters (phase retardation, optic axis direction, and degree of polarization uniformity (DOPU) and Stokes parameters (Q, U, and V) were utilized for multi-parameter analysis. To verify the detection accuracy of PS-OCT, H&E histology staining and dice-coefficient was utilized to quantify the performance of PS-OCT in identifying tumor borders and regions. In this study, tumor borders were clearly identified by PS-OCT imaging, which outperformed the conventional intensity-based OCT. With H&E histological staining as golden standard, PS-OCT precisely identified the tumor regions and tissue distributions at different locations and different depths based on polarization and Stokes parameters. Compared to the traditional attenuation coefficient quantification method, PS-OCT demonstrated enhanced contrast of tissue characteristics between normal and cancerous tissues due to the birefringence effects. Our results demonstrated that PS-OCT was promising to provide imaging guidance for the surgical resection of kidney tumors and had the potential to be used for other human kidney surgeries in clinics such as renal biopsy.

High-resolution full-field optical coherence tomography microscope for the evaluation of freshly excised skin specimens during Mohs surgery: A feasibility study

Histopathology for tumor margin assessment is time-consuming and expensive. High-resolution full-field optical coherence tomography (FF-OCT) images fresh tissues rapidly at cellular resolution and potentially facilitates evaluation. Here, we define FF-OCT features of normal and neoplastic skin lesions in fresh ex vivo tissues and assess its diagnostic accuracy for malignancies. For this, normal and neoplastic tissues were obtained from Mohs surgery, imaged using FF-OCT, and their features were described. Two expert OCT readers conducted a blinded analysis to evaluate their diagnostic accuracies, using histopathology as the ground truth. A convolutional neural network was built to distinguish and outline normal structures and tumors. Of the 113 tissues imaged, 95 (84%) had a tumor (75 basal cell carcinomas [BCCs] and 17 squamous cell carcinomas [SCCs]). The average reader diagnostic accuracy was 88.1%, with a sensitivity of 93.7%, and a specificity of 58.3%. The artificial intelligence (AI) model achieved a diagnostic accuracy of 87.6 ± 5.9%, sensitivity of 93.2 ± 2.1%, and specificity of 81.2 ± 9.2%. A mean intersection-over-union of 60.3 ± 10.1% was achieved when delineating the nodular BCC from normal structures. Limitation of the study was the small sample size for all tumors, especially SCCs. However, based on our preliminary results, we envision FF-OCT to rapidly image fresh tissues, facilitating surgical margin assessment. AI algorithms can aid in automated tumor detection, enabling widespread adoption of this technique.

Line-Field Confocal Optical Coherence Tomography (LC-OCT) for Skin Imaging in Dermatology

Line-field confocal optical coherence tomography (LC-OCT) is a non-invasive optical imaging technique based on a combination of the principles of optical coherence tomography and reflectance confocal microscopy with line-field illumination, which can generate cell-resolved images of the skin in vivo. This article reports on the LC-OCT technique and its application in dermatology. The principle of the technique is described, and the latest technological innovations are presented. The technology has been miniaturized to fit within an ergonomic handheld probe, allowing for the easy access of any skin area on the body. The performance of the LC-OCT device in terms of resolution, field of view, and acquisition speed is reported. The use of LC-OCT in dermatology for the non-invasive detection, characterization, and therapeutic follow-up of various skin pathologies is discussed. Benign and malignant melanocytic lesions, non-melanocytic skin tumors, such as basal cell carcinoma, squamous cell carcinoma and actinic keratosis, and inflammatory and infectious skin conditions are considered. Dedicated deep learning algorithms have been developed for assisting in the analysis of LC-OCT images of skin lesions.

Line-field confocal optical coherence tomography coupled with artificial intelligence algorithms to identify quantitative biomarkers of facial skin ageing

Quantitative biomarkers of facial skin ageing were studied from one hundred healthy Caucasian female volunteers, aged 20-70 years, using in vivo 3D Line-field Confocal Optical Coherence Tomography (LC-OCT) imaging coupled with Artificial Intelligence (AI)-based quantification algorithms. Layer metrics, i.e. stratum corneum thickness (SC), viable epidermal thickness and Dermal-Epidermal Junction (DEJ) undulation, as well as cellular metrics were measured for the temple, cheekbone and mandible. For all three investigated facial areas, minimal age-related variations were observed in the thickness of the SC and viable epidermis layers. A flatter and more homogeneous epidermis (decrease in the standard deviation of the number of layers means), a less dense cellular network with fewer cells per layer (decrease in cell surface density), and larger and more heterogeneous nuclei within each layer (increase in nuclei volume and their standard deviation) were found with significant variations with age. The higher atypia scores further reflected the heterogeneity of nuclei throughout the viable epidermis. The 3D visualisation of fine structures in the skin at the micrometric resolution and the 1200 µm × 500 µm field of view achieved with LC-OCT imaging enabled to compute relevant quantitative biomarkers for a better understanding of skin biology and the ageing process in vivo.

Optical coherence tomography-guided Nd:YAG laser treatment and follow-up of basal cell carcinoma

OBJECTIVES

Basal cell carcinoma (BCC) is the most common skin tumor with an annually increasing incidence. Standard care requires several visits for diagnosis and treatment. Optical coherence tomography (OCT) as a diagnostic tool increases the sensitivity (95%) and specificity (77%) of the diagnosis of BCC. Although laser therapy is not the standard of care, the long-pulsed 1064 nm Nd:YAG laser seems to be a promising option. However, data are scarce. The published papers had a short follow-up (FU) time and used to some extent inferior methods to detect complete tumor clearance. To address this research gap, this study evaluates the efficiency of laser treatment by FU OCT. We pursue a patient-focused approach and combine OCT with Nd:YAG laser treatment in one procedure.

MATERIALS AND METHODS

The study was conducted as a prospective, single-center trial that recruited biopsy-confirmed or OCT-proven BCC with a tumor thickness of less than 1.2 mm. Patients underwent two or three repeated sessions with the Nd:YAG laser (5-6 mm spot, fluence of 120-140 J/cm² , pulse duration of 8-10 milliseconds). Each BCC was assessed at baseline, and 3 and 12 months after laser treatment by clinical image, dermoscopy, and OCT. Incomplete tumor clearance (ITC) was defined as a clearly detectable BCC on the OCT image or a biopsy-confirmed BCC in the treated area.

RESULTS

Forty-five patients completed the 12-month FU (46.7% women; median age of 74.0 [52-88] years) with a total number of 78 BCC lesions. At baseline, all patients had their BCC diagnosed by OCT (tumor thickness of 0.6 [0.4; 0.8] mm), 15.4% lesions were additionally diagnosed by histopathology. The most common subtype of BCC was superficial (48.7%), followed by nodular (47.4%) and infiltrative (3.8%). ITC rate after the treatment using Nd:YAG laser was 30.8% (95% CI: 20.8%-42.2%) (24/78) after 3 months and 7.4% (95% CI: 2.1%-17.9%) (4/54) after 12 months. ITC was not associated with histological subtype, tumor thickness, or location. If ITC was detected, the lesion was treated again. Out of 19 lesions with at least one additional laser treatment, 7 lesions (36.8%) suffered from incomplete tumor removal. In 46.7% of the treated lesions, the cosmetic outcome was rated as moderate or severe scarring after 12 months.

CONCLUSION

Our results demonstrate that the ITC rate of BCC treated with the Nd:YAG laser is much higher (up to one-third) than reported, although the laser settings were identical to prior studies. This is especially evident at the 3-month FU. In addition, we witnessed a larger number of side effects and a worse cosmetic outcome compared to previous studies.

GPU-accelerated image registration algorithm in ophthalmic optical coherence tomography

Limited to the power of the light source in ophthalmic optical coherence tomography (OCT), the signal-to-noise ratio (SNR) of the reconstructed images is usually lower than OCT used in other fields. As a result, improvement of the SNR is required. The traditional method is averaging several images at the same lateral position. However, the image registration average costs too much time, which limits its real-time imaging application. In response to this problem, graphics processing unit (GPU)-side kernel functions are applied to accelerate the reconstruction of the OCT signals in this paper. The SNR of the images reconstructed from different numbers of A-scans and B-scans were compared. The results demonstrated that: 1) There is no need to realize the axial registration with every A-scan. The number of the A-scans used to realize axial registration is suitable to set as ∼25, when the A-line speed was set as ∼12.5kHz. 2) On the basis of ensuring the quality of the reconstructed images, the GPU can achieve 43× speedup compared with CPU.

Melanoma Detection by Non-Specialists: An Untapped Potential for Triage?

INTRODUCTION

The incidence of melanoma increased considerably in recent decades, representing a significant public health problem. We aimed to evaluate the ability of non-specialists for the preliminary screening of skin lesions to identify melanoma-suspect lesions.

MATERIALS AND METHODS

A medical student and a dermatologist specialist examined the total body scans of 50 patients.

RESULTS

The agreement between the expert and the non-specialist was 87.75% (κ = 0.65) regarding the assessment of clinical significance. The four parameters of the ABCD rule were evaluated on the 129 lesions rated as clinically significant by both observers. Asymmetry was evaluated similarly in 79.9% (κ = 0.59), irregular borders in 74.4% (κ = 0.50), color in 81.4% (κ = 0.57), and diameter in 89.9% (κ = 0.77) of the cases. The concordance of the two groups was 96.9% (κ = 0.83) in the case of the detection of the Ugly Duckling Sign.

CONCLUSIONS

Although the involvement of GPs is part of routine care worldwide, emphasizing the importance of educating medical students and general practitioners is crucial, as many European countries lack structured melanoma screening training programs targeting non-dermatologists.

Skin cancer margin detection using nanosensitive optical coherence tomography and a comparative study with confocal microscopy

Excision biopsy and histology represent the gold standard for morphological investigation of the skin, in particular for cancer diagnostics. Nevertheless, a biopsy may alter the original morphology, usually requires several weeks for results, is non-repeatable on the same site and always requires an iatrogenic trauma. Hence, diagnosis and clinical management of diseases may be substantially improved by new non-invasive imaging techniques. Optical Coherence Tomography (OCT) is a non-invasive depth-resolved optical imaging modality based on low coherence interferometry that enables high-resolution, cross-sectional imaging in biological tissues and it can be used to obtain both structural and functional information. Beyond the resolution limit, it is not possible to detect structural and functional information using conventional OCT. In this paper, we present a recently developed technique, nanosensitive OCT (nsOCT), improved using broadband supercontinuum laser, and demonstrate nanoscale sensitivity to structural changes within ex vivo human skin tissue. The extended spectral bandwidth permitted access to a wider distribution of spatial frequencies and improved the dynamic range of the nsOCT. Firstly, we demonstrate numerical and experimental detection of a few nanometers structural difference using the nsOCT method from single B-scan images of phantoms with sub-micron periodic structures, acting like Bragg gratings, along the depth. Secondly, our study shows that nsOCT can distinguish nanoscale structural changes at the skin cancer margin from the healthy region in en face images at clinically relevant depths. Finally, we compare the nsOCT en face image with a high-resolution confocal microscopy image to confirm the structural differences between the healthy and lesional/cancerous regions, allowing the detection of the skin cancer margin.

A 3D Analysis of Cleared Human Melanoma

Cutaneous melanoma is one of the most aggressive and deadliest cancers in human beings due to its invasiveness and other factors. Histopathological analysis is crucial for a proper diagnosis. Optical tissue clearing is a novel field that allows 3D image acquisition of large-scale biological tissues. Optical clearing and immunolabeling for 3D fluorescence imaging has yet to be extensively applied to melanoma. In the present manuscript, we establish, for the first time, an optical clearing and immunostaining procedure for human melanoma and human cell line-derived melanoma xenograft models using the CUBIC (clear, unobstructed brain imaging cocktails) technique. We have successfully cleared the samples and achieved 3D volumetric visualization of the tumor microenvironment, vasculature, and cell populations.

Spatially adaptive blind deconvolution methods for optical coherence tomography

Optical coherence tomography (OCT) is a powerful noninvasive imaging technique for detecting microvascular abnormalities. Following optical imaging principles, an OCT image will be blurred in the out-of-focus domain. Digital deconvolution is a commonly used method for image deblurring. However, the accuracy of traditional digital deconvolution methods, e.g., the Richardson-Lucy method, depends on the prior knowledge of the point spread function (PSF), which varies with the imaging depth and is difficult to determine. In this paper, a spatially adaptive blind deconvolution framework is proposed for recovering clear OCT images from blurred images without a known PSF. First, a depth-dependent PSF is derived from the Gaussian beam model. Second, the blind deconvolution problem is formalized as a regularized energy minimization problem using the least squares method. Third, the clear image and imaging depth are simultaneously recovered from blurry images using an alternating optimization method. To improve the computational efficiency of the proposed method, an accelerated alternating optimization method is proposed based on the convolution theorem and Fourier transform. The proposed method is numerically implemented with various regularization terms, including total variation, Tikhonov, and l₁ norm terms. The proposed method is used to deblur synthetic and experimental OCT images. The influence of the regularization term on the deblurring performance is discussed. The results show that the proposed method can accurately deblur OCT images. The proposed acceleration method can significantly improve the computational efficiency of blind demodulation methods.

Optical coherence tomography

During the past decade, noninvasive imaging has emerged as a valuable tool in clinical dermatology and dermatologic research. Optical coherence tomography (OCT) is one such type of noninvasive imaging. OCT uses the principle of interferometry to produce real-time images. A low-power diode laser shines infrared light onto tissues, which reflects back to an optical fiber interferometer. Using time delay and the backscattered light intensity, a two-dimensional image akin to an ultrasound is rendered. We review the history, types, and modalities of OCT, plus the many applications of frequency domain, high definition, and dynamic OCT in practice, including its utility in diagnosis, monitoring, and grading disease severity in a variety of cutaneous conditions.

Delineating papillary dermis around basal cell carcinomas by high and ultrahigh resolution optical coherence tomography-A pilot study

Bedside diagnosis of skin cancer remains a challenging task. The real-time noninvasive technology of optical coherence tomography (OCT) masters a high diagnostic accuracy in basal cell carcinoma (BCC) but a lower specificity in recognizing imitators and other carcinomas. We investigate the delicate signal of papillary dermis using an in-house developed ultrahigh resolution OCT (UHR-OCT) system with shadow compensation and a commercial multi-focus high resolution OCT (HR-OCT) system for clinical BCC imaging. We find that the HR-OCT system struggled to resolve the dark band signal of papillary dermis where the UHR-OCT located this in all cases and detected changes in signal width. UHR-OCT is able to monitor extension and position of papillary dermis suggesting a novel feature for delineating superficial BCCs in pursuit of a fast accurate diagnosis. Comprehensive studies involving more patients are imperative in order to corroborate results.

Combining Reflective Confocal Microscopy and Dynamic Optical Coherence Tomography to Diagnose Melanoacanthoma: Case Report

ABSTRACT

Few reported cases discuss distinguishing between melanoma and melanoacanthoma, a seborrheic keratosis (SK) variant, using noninvasive imaging devices. We present a case of a 38-year-old man with Fitzpatrick skin type IV with an asymmetric black papule showing clinical and dermoscopic features of both melanoma and SK. Reflectance confocal microscopy (RCM) and dynamic optical coherence tomography (d-OCT) were used for further evaluation. RCM revealed acanthotic epidermis with a mixed honeycomb and cobblestone pattern, polycyclic bulbous rete ridges, and bright plump cells within entrapped, edged, dermal papillae, compatible with pigmented SK. Also noted were a population of fairly uniform bright dendritic cells scattered quite evenly at all levels of the epidermis and the notable absence of concomitant features of a melanocytic neoplasm (roundish Pagetoid cells, sheets of roundish or dendritic cells at the dermal-epidermal junction, junctional thickenings, and melanocytic nests), suggesting melanoacanthoma. d-OCT showed well-circumscribed, regular, epidermal acanthosis, superficial rounded hypodense structures, normal vascular flow, and notable absence of wiry or contoured vessels, features typically seen in SKs and benign lesions, respectively. Similarly, histologic examination revealed characteristics of pigmented SK containing a population of evenly dispersed dendritic melanocytes (decorated using Melan-A stain) confirming a diagnosis of melanoacanthoma. This case highlights the advantages of incorporating both RCM and d-OCT into clinical practice to noninvasively differentiate melanoma from its clinical mimickers.

Lymph vessels visualization from optical coherence tomography data using depth-resolved attenuation coefficient calculation

Multimodal optical coherent tomography grows popularity with researchers and clinicians over the past decade. One of the modalities is lymphangiography, which allows visualization of the lymphatic vessel networks within optical coherence tomography (OCT) imaging volume. In the present study, it is shown that lymphatic vessel visualization obtained from the depth-resolved attenuation coefficient distributions, corrected for the noise, shows improved contrast and detail in comparison with previously proposed approaches. We also argue that the two most popular approaches for lymphatic vessel visualization, namely simple intensity thresholding and vesselness calculation based on local Hessian matrix eigenvalues, imply different definitions of the lymphatic vessel's appearance in the OCT volume and lead to the different networks.

Combining Nd:YAG laser with optical coherence tomography for nonsurgical treatment of basal cell carcinoma

BACKGROUND

Effective and aesthetically appealing management options are needed for basal cell carcinoma (BCC), the most common skin cancer. The Nd:YAG laser shows promise, but most studies use biopsy to demonstrate tumor clearance. Optical coherence tomography (OCT) could allow good tumor margin control while enabling recurrence monitoring.

OBJECTIVE

Determine the efficacy of the Nd:YAG laser to treat BCCs while controlling for tumor margin with OCT.

METHODS

A 1064-nm Nd:YAG laser was applied to treat 119 BCCs in 102 patients, where tumor margins were approximated using OCT. Lesions were treated every 2 months until no residual tumor remained; patients were monitored for 1 year after treatment completion for clinical and subclinical recurrences. Outcomes were analyzed retrospectively.

RESULTS

Most BCCs cleared after one treatment (85/119, 70.4%). Several factors were significantly associated with a suboptimal response, that is, those with recurrence or requiring ≥2 treatments: lesion size >5 mm (p = 0.03), focal sclerosing subtype (p = 0.018), and immunosuppression (p = 0.039). Midface location, patient compliance, and diagnosis method were codependent variables (r²  = 0.2011, p = 0.0008). All BCCs (119/119) demonstrated complete clinical and subclinical tumor clearance 2 months after final laser treatment. By 1 year, overall clinical recurrence rate (RR) was 1.7% (2/119) and cumulative subclinical RR was 4.2% (5/119). Upon excluding immunosuppressed patients, clinical RR and combined subclinical RR for primary BCC were 1% (1/98) and 2% (2/98), respectively, and 0% (0/17) and 11.8% (2/17), respectively, for recurrent BCC.

CONCLUSIONS

The Nd:YAG nonablative laser can offer an effective treatment for BCCs when used with noninvasive diagnostic tools such as OCT.

Antibody-Based Targeted Interventions for the Diagnosis and Treatment of Skin Cancers

BACKGROUND

Cutaneous malignancies most commonly arise from skin epidermal cells. These cancers may rapidly progress from benign to a metastatic phase. Surgical resection represents the gold standard therapeutic treatment of non-metastatic skin cancer while chemo- and/or radiotherapy are often used against metastatic tumors. However, these therapeutic treatments are limited by the development of resistance and toxic side effects, resulting from the passive accumulation of cytotoxic drugs within healthy cells.

OBJECTIVE

This review aims to elucidate how the use of monoclonal Antibodies (mAbs) targeting specific Tumor Associated Antigens (TAAs) is paving the way to improved treatment. These mAbs are used as therapeutic or diagnostic carriers that can specifically deliver cytotoxic molecules, fluorophores or radiolabels to cancer cells that overexpress specific target antigens.

RESULTS

mAbs raised against TAAs are widely in use for e.g. differential diagnosis, prognosis and therapy of skin cancers. Antibody-Drug Conjugates (ADCs) particularly show remarkable potential. The safest ADCs reported to date use non-toxic photo-activatable Photosensitizers (PSs), allowing targeted Photodynamic Therapy (PDT) resulting in targeted delivery of PS into cancer cells and selective killing after light activation without harming the normal cell population. The use of near-infrared-emitting PSs enables both diagnostic and therapeutic applications upon light activation at the specific wavelengths.

CONCLUSION

Antibody-based approaches are presenting an array of opportunities to complement and improve current methods employed for skin cancer diagnosis and treatment.

Optical coherence tomography-based non-invasive evaluation of premalignant lesions in SKH-1 mice

Non-invasively diagnosis of actinic keratoses (AK) is important for preventing cutaneous squamous cell carcinoma (cSCC). Optical coherence tomography (OCT) can be used to detect the cross-sectional skin micromorphology with sufficient resolution and imaging depth. It has the capability to reveal the changes in skin microstructure during the development of AK. Therefore, OCT can serve as a tool for diagnosing AK. This study explores the feasibility of OCT in evaluating the structural changes in mouse skin at the different stages following exposure to ultraviolet radiation. The performance of OCT is compared with histology, the gold standard in this context. The imaging results demonstrate that a wave-shaped irregular dermo-epidermal junction (DEJ), as well as the continuous thickening of the epidermis, are useful diagnostic parameters for diagnosing AK. Histological examinations confirm these observations. These findings emphasize the need for effective skin protection or medical treatment once changes in the DEJ and epidermis are detected. OCT shows strong potential for non-invasive evaluation of such changes and AK development, and can be used for the prevention of cSCC without the necessity of taking biopsies.

Optical Technologies for the Improvement of Skin Cancer Diagnosis: A Review

The worldwide incidence of skin cancer has risen rapidly in the last decades, becoming one in three cancers nowadays. Currently, a person has a 4% chance of developing melanoma, the most aggressive form of skin cancer, which causes the greatest number of deaths. In the context of increasing incidence and mortality, skin cancer bears a heavy health and economic burden. Nevertheless, the 5-year survival rate for people with skin cancer significantly improves if the disease is detected and treated early. Accordingly, large research efforts have been devoted to achieve early detection and better understanding of the disease, with the aim of reversing the progressive trend of rising incidence and mortality, especially regarding melanoma. This paper reviews a variety of the optical modalities that have been used in the last years in order to improve non-invasive diagnosis of skin cancer, including confocal microscopy, multispectral imaging, three-dimensional topography, optical coherence tomography, polarimetry, self-mixing interferometry, and machine learning algorithms. The basics of each of these technologies together with the most relevant achievements obtained are described, as well as some of the obstacles still to be resolved and milestones to be met.

Dermal epidermal junction detection for full-field optical coherence tomography data of human skin by deep learning

Full-field optical coherence tomography (FF-OCT) has been developed to obtain three-dimensional (3D) OCT data of human skin for early diagnosis of skin cancer. Detection of dermal epidermal junction (DEJ), where melanomas and basal cell carcinomas originate, is an essential step for skin cancer diagnosis. However, most existing DEJ detection methods consider each cross-sectional frame of the 3D OCT data independently, leaving the relationship between neighboring frames unexplored. In this paper, we exploit the continuity of 3D OCT data to enhance DEJ detection. In particular, we propose a method for noise reduction of the training data and a multi-directional convolutional neural network to predict the probability of epidermal pixels in the 3D OCT data, which is more stable than one-directional convolutional neural network for DEJ detection. Our crosscheck refinement method also exploits the domain knowledge to generate a smooth DEJ surface. The average mean error of the entire DEJ detection system is approximately 6 μm.

Line-field confocal optical coherence tomography for three-dimensional skin imaging

This paper reports on the latest advances in line-field confocal optical coherence tomography (LC-OCT), a recently invented imaging technology that now allows the generation of either horizontal (x × y) section images at an adjustable depth or vertical (x × z) section images at an adjustable lateral position, as well as three-dimensional images. For both two-dimensional imaging modes, images are acquired in real-time, with real-time control of the depth and lateral positions. Three-dimensional (x × y × z) images are acquired from a stack of horizontal section images. The device is in the form of a portable probe. The handle of the probe has a button and a scroll wheel allowing the user to control the imaging modes. Using a supercontinuum laser as a broadband light source and a high numerical microscope objective, an isotropic spatial resolution of ∼1 µm is achieved. The field of view of the three-dimensional images is 1.2 mm × 0.5 mm × 0.5 mm (x × y × z). Images of skin tissues are presented to demonstrate the potential of the technology in dermatology.

Evaluation of ultrahigh-resolution optical coherence tomography for basal cell carcinoma, seborrheic keratosis, and nevus

BACKGROUND

Basal cell carcinoma, seborrheic keratosis, and nevus are common skin conditions. Though most of the skin diseases can be distinguished from each other by physician's naked eyes, the diagnostic accuracy is not 100%. The accurate diagnosis and assessment of three diseases make a big difference on the clinical management. Nowadays, biopsy is still the gold standard for diagnosis even it is invasive, time-consuming, and painful. Ultrahigh-resolution optical coherence tomography is an emerging technology that can produce in situ, cellular-resolution, real-time, continuous, 3D images in a noninvasive way.

MATERIALS AND METHODS

In our study, four basal cell carcinoma patients, five seborrheic keratosis patients, and 10 nevus patients who were diagnosed by histology were studied by ultrahigh-resolution optical coherence tomography after visual examination by experienced dermatologists. Cellular contrast was utilized to clearly identify the features of the three skin diseases.

RESULTS

The features including such as hyperkeratosis (horn pseudocysts), papillomatosis, intraepidermal nests, elongated, and expanded rete ridge can be visualized in seborrheic keratosis. Tumor nodular, mucin surrounding with tumor (retraction space in histopathology), tumor subtype, and necrosis were featured in basal cell carcinoma. Pigment was characterized in epidermis and dermis. The comparison of ultrahigh-resolution optical coherence tomography images reveals a strong correlation with histological images.

CONCLUSION

Ultrahigh-resolution optical coherence tomography can complement existing diagnostic techniques for investigating seborrheic keratosis, basal cell carcinoma and nevus, and show enormous potential in vivo applications for the three skin diseases in the future.

Multimodal imaging of skin lesions by using methylene blue as cancer biomarker

This study aimed the optical imaging of malignant and normal skin tissues with multimodal wide-field fluorescence polarization imaging (WF) technique, by using methylene blue as fluorescence dye. We present optical imaging of skin tissues by different techniques, including reflectance, fluorescence, and polarization imaging for early detection of skin cancer. We collected the reflectance confocal images at 390 and 500 nm. For wide-field fluorescence images, specimens were stimulated at 640 nm and images were collected between 670 and 710 nm. The correlation of the regarded optical modalities with histopathology (H&E), their potentials, capabilities, and limitations to detect skin lesions are discussed. The advantages of multimodal imaging of skin tissues are analyzed to divulge possibilities for precise tumor boundary detection and their classification for malignant and nonmalignant skin tissues. Prior to imaging, the cells were stained in aqueous MB (a dye approved by FDA).

[Possibilities of ultrasound methods in diagnostics of eyelid tumors]

PURPOSE

To determine the informative value of ultrasound biomicroscopy (UBM) with A-scan for assessment of qualitative and quantitative characteristics of eyelid tumors less than 5 mm in size.

MATERIAL AND METHODS

The study included 25 patients (25 eyes) with eyelid tumors less than 5 mm in size. In addition to standard ophthalmic examination, complex ultrasound diagnostics including B-scan, Color Doppler imaging and UBM with A-scan were performed. The localization, size, structure of eyelid tumors and the state of perifocal tissues were evaluated. All patients underwent surgical treatment with following histological examinations of dissected tissues. Due to qualitative analysis of the studied formations and small number of included patients, there was no need in statistical analysis of the data.

RESULTS

Complex application of UBM and A-scan allowed specifying the localization, size, structure of the small-sized tumors and detecting typical echographic signs of benign or malignant properties of the pathological process. Ultrasound data (UBM and A-scan) of eyelid tumors was highly correlated to histological features.

CONCLUSION

UBM with A-scan can be recommended for differential diagnostics of small-sized tumors and optimizing their management.

Mirau-based line-field confocal optical coherence tomography

Line-field confocal optical coherence tomography (LC-OCT) is an imaging technique in which A-scans are acquired in parallel through line illumination with a broadband laser and line detection with a line-scan camera. B-scan imaging at high spatial resolution is achieved by dynamic focusing in a Linnik interferometer. This paper presents an LC-OCT device based on a custom-designed Mirau interferometer that offers similar spatial resolution and detection sensitivity. The device has the advantage of being more compact and lighter. In vivo imaging of human skin with a resolution of 1.3 µm × 1.1 µm (lateral × axial) is demonstrated over a field of 0.9 mm × 0.4 mm (lateral × axial) at 12 frames per second.

Ex vivo full-field cellular-resolution optical coherence tomography of basal cell carcinomas: A pilot study of quality and feasibility of images and diagnostic accuracy in subtypes

BACKGROUND

Studies have reported the application of conventional optical coherence tomography (OCT) in the diagnosis of basal cell carcinoma (BCC). The new OCT provides cellular details similar to those in pathology slides and may reduce user learning time. This study aimed to demonstrate the quality of ex vivo full-field cellular-resolution OCT images and compare the diagnostic accuracy between physicians with varying pathology experience.

MATERIALS AND METHODS

Sixty histologically confirmed BCCs were selected. Tissue samples were sectioned and scanned using OCT, and their features were compared with those of hematoxylin and eosin (H&E)-stained sections. Thirty images were selected for the test administered to dermatology residents, dermatopathology fellows, and board-certified general pathologists without any OCT experience. The pretest learning included a 3-min instruction and 10-min self-study of four BCC variants.

RESULTS

Histopathological BCC and normal histological features were clearly recognizable on the OCT images. The pathological BCC features observed in the OCT images correlated with those found in the H&E-stained sections. Seven participants completed the test. The correct answer rates of the residents, fellows, and pathologists were 71%, 68%, and 83% for BCC and 44%, 57%, and 57% for the BCC subtypes, respectively.

CONCLUSION

All the participants identified BCC in >70% cases with a learning time of only 13 minutes. The results indicated that cellular-resolution OCT provided high-quality images similar to the conventional pathology slides. Pathology experience did reflect the diagnostic accuracy. However, a longer training time is still needed at all levels to recognize the BCC subtypes correctly.

Early detection of enamel demineralization by optical coherence tomography

Enamel is the outermost layer of the tooth that protects it from invasion. In general, an acidic environment accelerates tooth demineralization, leading to the formation of cavities. Scanning electron microscopy (SEM) is conventionally used as an in vitro tool for the observation of tooth morphology changes with acid attacks. Yet, SEM has intrinsic limitations for the potential application of in vivo detection in the early demineralization process. In this study, a high-resolution optical coherence tomography (OCT) system with the axial and transverse resolutions of 2.0 and 2.7 μm in teeth has been utilized for characterizing the effect of the acidic environment (simulated by phosphoric acid) on the enamel topology. The scattering coefficient and the surface roughness of enamel can be directly derived from the OCT results, enabling a quantitative evaluation of the topology changes with demineralization. The dynamic process induced by the acid application is also recorded and analyzed with OCT, depicting the evolution of the demineralization process on enamel. Notably, the estimated enamel scattering coefficient and surface roughness significantly increase with the application time of acid and the results illustrate that the values of both parameters after demineralization are significantly larger than those obtained before the demineralization, illustrating both parameters could be effective to differentiate the healthy and demineralized teeth and determine the severity. The obtained results unambiguously illustrate that demineralization of the tooth surface can be successfully detected by OCT and further used as an indicator of early-stage cavity formation.

Early diagnosis of skin cancer by ultrasound frequency analysis

The diagnosis of cancer by modern computer tools, at the very first stages of the incident, is a very important issue that has involved many researchers. In the meantime, skin cancer is a great deal of research because many people are involved with it. The purpose of this paper is to introduce an innovative method based on tissue frequency analyzes to obtain the accurate and real-time evaluation of skin cancers. According to the Biological resonance theory, body cells have natural and unique frequencies based on their biological fluctuations, which, if the structure, profile and cellular status change, its frequency also varies. This concept and theory is considered as the basis for analyzing skin tissue health in the proposed method. Reflected ultrasound waves from tissue have been processed and studied based on frequency analysis as a new method for early detection and diagnosis of accurate location and type of skin diseases. The developed algorithm was approved through 400 patients from CRED; its ability to evaluate benign and malignant skin lesions was shown (AUC = 0.959), with comparable clinical precision; as for the selected threshold, sensitivity, and specificity were 93.8% and 97.3%, respectively. Therefore, this method can detect skin malignancy with an accurate, noninvasive and real-time procedure.

High-Resolution Episcopic Microscopy (HREM): Looking Back on 13 Years of Successful Generation of Digital Volume Data of Organic Material for 3D Visualisation and 3D Display

High-resolution episcopic microscopy (HREM) is an imaging technique that permits the simple and rapid generation of three-dimensional (3D) digital volume data of histologically embedded and physically sectioned specimens. The data can be immediately used for high-detail 3D analysis of a broad variety of organic materials with all modern methods of 3D visualisation and display. Since its first description in 2006, HREM has been adopted as a method for exploring organic specimens in many fields of science, and it has recruited a slowly but steadily growing user community. This review aims to briefly introduce the basic principles of HREM data generation and to provide an overview of scientific publications that have been published in the last 13 years involving HREM imaging. The studies to which we refer describe technical details and specimen-specific protocols, and provide examples of the successful use of HREM in biological, biomedical and medical research. Finally, the limitations, potentials and anticipated further improvements are briefly outlined.

Optical coherence tomography angiography and photoacoustic imaging in dermatology

Optical coherence tomography angiography (OCTA) is a relatively novel functional extension of the widely accepted ophthalmic imaging tool named optical coherence tomography (OCT). Since OCTA's debut in ophthalmology, researchers have also been trying to expand its translational application in dermatology. The ability of OCTA to resolve microvasculature has shown promising results in imaging skin diseases. Meanwhile, photoacoustic imaging (PAI), which uses laser pulse induced ultrasound waves as the signal, has been studied to differentiate human skin layers and to help in skin disease diagnosis. This perspective article gives a short review of OCTA and PAI in the field of photodermatology. After an introduction to the principles of OCTA and PAI, we describe the most updated results of skin disease imaging using these two optical imaging modalities. We also place emphasis on dual modality imaging combining OCTA and photoacoustic tomography (PAT) for dermatological applications. In the end, the challenges and prospects of these two imaging modalities in dermatology are discussed.

Classification of established atopic dermatitis in children with the in vivo imaging methods

Atopic dermatitis (AD) is a cutaneous disease resulting from a defective barrier and dysregulated immune response. The severity scoring of atopic dermatitis (SCORAD) is used to classify AD. Noninvasive imaging approaches supplementary to SCORAD were investigated. Cr:forsterite laser-based microscopy was employed to analyze endogenous third-harmonic generation (THG) and second-harmonic generation (SHG) signals from skin. Imaging parameters were compared between different AD severities. Three-dimensional reconstruction of imaged skin layers was performed. Finally, statistic models from quantitative imaging parameters were developed for predicting disease severity. Our data demonstrate that THG signal intensity of lesional skin in AD were significantly increased and was positively correlated with AD severity. Characteristic gray level co-occurrence matrix (GLCM) values were observed in more severe AD. In the 3D reconstruction video, individual dermal papilla and obvious fibrosis in the upper papillary dermis were easily identified. Our estimation models could predict the disease severity of AD patients with an accuracy of nearly 85%. The THG signal intensity and characteristic GLCM patterns are associated with AD severity and can serve as quantitative predictive parameters. Our imaging approach can be used to identify the histopathological changes of AD objectively, and to complement the SCORAD index, thus improving the accuracy of classifying AD severity.

Simultaneous dual-band line-field confocal optical coherence tomography: application to skin imaging

Line-field confocal optical coherence tomography (LC-OCT) operating in two distinct spectral bands centered at 770 nm and 1250 nm is reported, using a single supercontinuum light source and two different line-scan cameras. B-scans are acquired simultaneously in the two bands at 4 frames per second. Greyscale representation and color fusion of the images are performed to either produce a single image with both high resolution (1.3 µm × 1.2 µm, lateral × axial, measured at the surface) in the superficial part of the image and deep penetration, or to highlight the spectroscopic properties of the sample. In vivo images of fair and dark skin are presented with a penetration depth of ∼700 µm.

Line-field confocal time-domain optical coherence tomography with dynamic focusing

A time-domain optical coherence tomography technique is introduced for high-resolution B-scan imaging in real-time. The technique is based on a two-beam interference microscope with line illumination and line detection using a broadband spatially coherent light source and a line-scan camera. Multiple (2048) A-scans are acquired in parallel by scanning the sample depth while adjusting the focus. Quasi-isotropic spatial resolution of 1.3 µm × 1.1 µm (lateral × axial) is achieved. In vivo cellular-level resolution imaging of human skin is demonstrated at 10 frames per second with a penetration depth of ∼500 µm.

Role of modern imaging techniques for the in vivo diagnosis of lichen planus

Lichen planus (LP) is a chronic inflammatory skin disease that can sometimes affect mucosal surfaces, with unknown pathogenesis, even though it appears to be an autoimmune disease. The diagnosis of lichen planus is usually based on histopathological examination of the lesions. Nowadays, the classical invasive diagnostic methods are replaced by modern non-invasive techniques. In this review, we present the main non-invasive imaging methods (dermoscopy, reflectance confocal microscopy, optical coherence tomography, ultrasound and diffuse reflection spectrophotometry) used in the diagnosis and therapeutic monitoring of lichen planus. Dermoscopy is a non-invasive method initially used for diagnosis of pigmented tumors but now is used also for inflammatory and infectious skin diseases. In lichen planus, the dermoscopy increases the accuracy of diagnosis, avoids skin biopsies commonly used and can be useful in the therapeutic monitoring by repeated investigation at different stages of treatment. Reflectance confocal microscopy (RCM) is a novel non-invasive imaging technique that is prevalently used for the diagnosis of skin tumors and inflammatory skin diseases. This technology has been mostly employed for bedside, real-time microscopic evaluation of psoriasis, lichen planus, contact dermatitis, revealing specific confocal features to support clinical diagnosis and assist with patient management. Optical coherence tomography (OCT) is an emergent imaging technique, developed over the last decade, based on the interaction of the infrared radiation (900–1,500 nm) and the living tissues. A limited information exists on the benefits of OCT technology for the in vivo diagnosis of LP but could be a useful auxiliary tool in the in vivo differential diagnosis, especially in clinical equivocal settings like mucosal lesions, and in monitoring the response to treatment. Our review shows the possibility of using modern imaging techniques for the in vivo diagnosis and also for evaluation of the treatment response.

Line-field confocal optical coherence tomography for high-resolution noninvasive imaging of skin tumors

An optical technique called line-field confocal optical coherence tomography (LC-OCT) is introduced for high-resolution, noninvasive imaging of human skin in vivo. LC-OCT combines the principles of time-domain optical coherence tomography and confocal microscopy with line illumination and detection using a broadband laser and a line-scan camera. LC-OCT measures the echo-time delay and amplitude of light backscattered from cutaneous microstructures through low-coherence interferometry associated with confocal spatial filtering. Multiple A-scans are acquired simultaneously while dynamically adjusting the focus. The resulting cross-sectional B-scan image is produced in real time at 10  frame  /  s. With an isotropic spatial resolution of ∼1  μm, the LC-OCT images reveal a comprehensive structural mapping of skin at the cellular level down to a depth of ∼500  μm. LC-OCT has been applied to the imaging of various skin lesions, in vivo, including carcinomas and melanomas. LC-OCT images are found to strongly correlate with conventional histopathological images. The use of LC-OCT as an adjunct tool in medical practice could significantly improve clinical diagnostic accuracy while reducing the number of biopsies of benign lesions.