The value of ultrahigh resolution OCT in dermatology - delineating the dermo-epidermal junction, capillaries in the dermal papillae and vellus hairs

Suction-Based Optical Coherence Elastography for the Biomechanical Characterization of Pathological Skin Conditions: A Pilot Study

Accurate characterization of mechanical properties is crucial in the evaluation of therapeutic effects for problematic skin conditions. A pilot study was carried out using a novel optical coherence elastography (OCE) device, combining mechanical characterization through suction-based deformation and imaging through optical coherence tomography. Using AI-assisted image segmentation and a power-law model, we were able to describe the mechanical behavior, comparing with measurements from the most commonly used commercial instrument (Cutometer) and subjective analyses of stiffness using the Patient and Observer Scar Assessment Scale. Twenty subjects were included with either keloids or hypertrophic scars. Measurements were fast and produced no discomfort. Mechanical and structural (epidermal thickness and rugosity) descriptors in pathologic skin conditions differed significantly from those in control tissue. We showed for the first time, the clinical feasibility of this novel suction-based OCE device in evaluating mechanical and structural properties in pathological skin conditions such as scars.

BCC and Immunocryosurgery scar differentiation through computational resolution-enhanced OCT images and skin optical attenuation: A proof-of-concept study

Monitoring medical therapy remains a challenging task across all non-surgical skin cancer treatment modalities. In addition, confirmation of residual tumours after treatment is essential for the early detection of potential relapses. Optical coherence tomography (OCT), a non-invasive method for real-time cross-sectional imaging of living tissue, is a promising imaging approach for assessing relatively flat, near-surface skin lesions, such as those that occur in most basal cell carcinomas (BCCs), at the time of diagnosis. However, the skin's inherent property of strong light scattering impedes the implementation of OCT in these cases due to the poor image quality. Furthermore, translating OCT's optical parameters into practical use in routine clinical settings is complicated due to substantial observer subjectivity. In this retrospective pilot study, we developed a workflow based on the upscale of the OCT images resolution using a deep generative adversarial network and the estimation of the skin optical attenuation coefficient. At the site of immunocryosurgery-treated BCC, the proposed methodology can extract optical parameters and discriminate objectively between tumour foci and scar tissue.

Flat visible spectrum by a genetic algorithm optimized photonic crystal fiber in the GHz comb spacing

Coherent and flat supercontinuum (SC) sources are demanded for applications of metrology, spectroscopy, and bio-imaging. However, the process of SC generation is usually very complicated. We demonstrated a convenient and efficient method based on a genetic algorithm (GA). According to an objective spectrum, this algorithm could reverse-design the geometry of a fiber or waveguide without knowing the specific non-linear processes involved. Using this method, we designed a dispersion-managed photonic crystal fiber (PCF) for SC generation at 1 GHz comb spacing. With an input pulse of ∼150 fs, 450 pJ at 1050 nm, a 3 dB fluctuation spectrum ranging from 510 nm to 850 nm is obtained, which is absolutely fit to the calibration of an astronomical spectrograph.

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.

Semisupervised representative learning for measuring epidermal thickness in human subjects in optical coherence tomography by leveraging datasets from rodent models

SIGNIFICANCE

Morphological changes in the epidermis layer are critical for the diagnosis and assessment of various skin diseases. Due to its noninvasiveness, optical coherence tomography (OCT) is a good candidate for observing microstructural changes in skin. Convolutional neural network (CNN) has been successfully used for automated segmentation of the skin layers of OCT images to provide an objective evaluation of skin disorders. Such method is reliable, provided that a large amount of labeled data is available, which is very time-consuming and tedious. The scarcity of patient data also puts another layer of difficulty to make the model more generalizable.

AIM

We developed a semisupervised representation learning method to provide data augmentations.

APPROACH

We used rodent models to train neural networks for accurate segmentation of clinical data.

RESULT

The learning quality is maintained with only one OCT labeled image per volume that is acquired from patients. Data augmentation introduces a semantically meaningful variance, allowing for better generalization. Our experiments demonstrate the proposed method can achieve accurate segmentation and thickness measurement of the epidermis.

CONCLUSION

This is the first report of semisupervised representative learning applied to OCT images from clinical data by making full use of the data acquired from rodent models. The proposed method promises to aid in the clinical assessment and treatment planning of skin diseases.

Deep-learning approach for automated thickness measurement of epithelial tissue and scab using optical coherence tomography

SIGNIFICANCE

In order to elucidate therapeutic treatment to accelerate wound healing, it is crucial to understand the process underlying skin wound healing, especially re-epithelialization. Epidermis and scab detection is of importance in the wound healing process as their thickness is a vital indicator to judge whether the re-epithelialization process is normal or not. Since optical coherence tomography (OCT) is a real-time and non-invasive imaging technique that can perform a cross-sectional evaluation of tissue microstructure, it is an ideal imaging modality to monitor the thickness change of epidermal and scab tissues during wound healing processes in micron-level resolution. Traditional segmentation on epidermal and scab regions was performed manually, which is time-consuming and impractical in real time.

AIM

We aim to develop a deep-learning-based skin layer segmentation method for automated quantitative assessment of the thickness of in vivo epidermis and scab tissues during a time course of healing within a rodent model.

APPROACH

Five convolution neural networks were trained using manually labeled epidermis and scab regions segmentation from 1000 OCT B-scan images (assisted by its corresponding angiographic information). The segmentation performance of five segmentation architectures was compared qualitatively and quantitatively for validation set.

RESULTS

Our results show higher accuracy and higher speed of the calculated thickness compared with human experts. The U-Net architecture represents a better performance than other deep neural network architectures with 0.894 at F1-score, 0.875 at mean intersection over union, 0.933 at Dice similarity coefficient, and 18.28  μm at an average symmetric surface distance. Furthermore, our algorithm is able to provide abundant quantitative parameters of the wound based on its corresponding thickness maps in different healing phases. Among them, normalized epidermal thickness is recommended as an essential hallmark to describe the re-epithelialization process of the rodent model.

CONCLUSIONS

The automatic segmentation and thickness measurements within different phases of wound healing data demonstrates that our pipeline provides a robust, quantitative, and accurate method for serving as a standard model for further research into effect of external pharmacological and physical factors.

Bedside Differentiation Between Benign and Malignant Pigmented Skin Tumours by Four Diagnostic Imaging Technologies - A Pilot Study

Fast diagnosis of suspicious pigmented skin lesions is imperative, but current bedside skin imaging technologies are either limited in penetration depth or resolution. Combining imaging methods is therefore highly relevant for skin cancer diagnostics. This pilot study evaluates the ability of optical coherence tomography, reflectance confocal microscopy, photoacoustic imaging and high-frequency ultrasound to differentiate malignant from benign pigmented skin lesions. A total of 41 pigmented skin tumours were scanned prior to excision. Morphologic features and blood vessel characteristics were analysed in reflectance confocal microscopy, optical coherence tomography, high-frequency ultrasound and photoacoustic imaging images and diagnostic accuracy assessed. Three novel photoacoustic imaging features, 7 reflectance confocal microscopy features and two optical coherence tomography features were detected with a high correlation to malignancy, diagnostic accuracy > 71%. No significant features were found in high-frequency ultrasound. Conclusively, optical coherence tomography, reflectance confocal microscopy and photoacoustic imaging in combination enables image-guided evaluation of suspicious pigmented skin tumours at the bedside. Combining these advanced techniques may help to diagnose skin cancer more efficiently.

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.

A novel automatic 3D stitching algorithm for optical coherence tomography angiography and its application in dermatology

Optical coherence tomography (OCT) and OCT angiography (OCTA) techniques offer numerous advantages in clinical skin applications but the field of view (FOV) of current commercial systems are relatively limited to cover the entire skin lesion. The typical method to expand the FOV is to apply wide field objective lens. However, lateral resolution is often sacrificed when scanning with these lenses. To overcome this drawback, we developed an automated 3D stitching method for creating high-resolution skin structure and vascular volumes with large field of view, which was realized by montaging multiple adjacent OCT and OCTA volumes. The proposed stitching method is demonstrated by montaging 3 × 3 OCT and OCTA volumes (nine OCT/OCTA volumes as one data set with each volume covers 2.5 cm × 2.5 cm area) of healthy thin and thick skin from six volunteers. The proposed stitching protocol achieves high flexibility and repeatable for all the participants. Moreover, according to evaluation of structural similarity index and feature similarity index, our proposed stitched result has a superior similarity to single scanning protocol in large-scaled. We had also verified its improved performance through assessing metrics of vessel contrast-noise-ratio (CNR) from 2.07 ± 0.44 (single large-scaled scanning protocol) to 3.05 ± 0.51 (proposed 3 × 3 sub-volume stitching method).

New diagnostic and imaging technologies in dermatology

INTRODUCTION

Diagnosis of dermatological disorders is primarily based on clinical examination in combination with histopathology. However, clinical findings alone may not be sufficient for accurate diagnosis and cutaneous biopsies are being associated with morbidity.

OBJECTIVE

The objective of this article is to review the newer technologies along with their applications, limitation and future prospectus.

METHODOLOGY

Comprehensive literature search was performed using electronic online databases "PubMed" and "Google Scholar". Articles published in English language were considered for the review.

RESULTS

In order to improve and/or widen the armamentarium in dermatologic disease diagnosis and therapy, newer emerging technologies are being made available which aid in diagnosis and management. New emerging technologies include confocal microscopy, digital photographic imaging, optical coherence tomography, high frequency ultrasonography, and artificial intelligence. There have been advancements in the dermoscopes.

CONCLUSION

Significant progress is seen in the diagnostic methods and imaging technologies in dermatology, each having its advantages and limitations. Artificial intelligence/machine-based learning software may have a great scope to influence the dermatological practice.

High-resolution mid-infrared optical coherence tomography with kHz line rate

We report on mid-infrared optical coherence tomography (OCT) at 4 µm based on collinear sum-frequency upconversion and promote the A-scan scan rate to 3 kHz. We demonstrate the increased imaging speed for two spectral realizations, one providing an axial resolution of 8.6 µm, and one providing a record axial resolution of 5.8 µm. Image performance is evaluated by sub-surface micro-mapping of a plastic glove and real-time monitoring of CO₂ in parallel with OCT imaging.

Non-Destructive Subsurface Inspection of Marine and Protective Coatings Using Near- and Mid-Infrared Optical Coherence Tomography

Near- and mid-infrared optical coherence tomography (OCT) is evaluated as a non-destructive and non-contact reflection imaging modality for inspection of industrial and marine coatings. Near-infrared OCT was used to obtain high-resolution images (~6/2 µm lateral/axial) of hidden subsurface cracks and defects in a resin base coating, which had been exposed to high pressure and high temperature to study coating degradation in hostile environments. Mid-infrared OCT was employed for high-resolution (~15/8.5 µm lateral/axial) subsurface inspection of highly scattering marine coatings, demonstrating monitoring of wet film thickness and particle dispersion during curing of a 210 µm layer of antifouling coating, and detection of substrate corrosion through 369 µm of high-gloss alkyd enamel. Combining high-resolution and fast, non-invasive scanning, OCT is therefore considered a promising tool for studying coating performance and for industrial inspection.

Shot-noise limited, supercontinuum-based optical coherence tomography

We present the first demonstration of shot-noise limited supercontinuum-based spectral domain optical coherence tomography (SD-OCT) with an axial resolution of 5.9 μm at a center wavelength of 1370 nm. Current supercontinuum-based SD-OCT systems cannot be operated in the shot-noise limited detection regime because of severe pulse-to-pulse relative intensity noise of the supercontinuum source. To overcome this disadvantage, we have developed a low-noise supercontinuum source based on an all-normal dispersion (ANDi) fiber, pumped by a femtosecond laser. The noise performance of our 90 MHz ANDi fiber-based supercontinuum source is compared to that of two commercial sources operating at 80 and 320 MHz repetition rate. We show that the low-noise of the ANDi fiber-based supercontinuum source improves the OCT images significantly in terms of both higher contrast, better sensitivity, and improved penetration. From SD-OCT imaging of skin, retina, and multilayer stacks we conclude that supercontinuum-based SD-OCT can enter the domain of shot-noise limited detection.

Rapid Ultrasound Optical Clearing of Human Light and Dark Skin

Application of optical clearing of biological tissue in humans in vivo is challenging due to toxicity of chemical agents, long processing time (≥30 min), and moderate (1.3-1.5-fold) imaging depth improvement. Here, we introduce novel, robust, and rapid ultrasound-based optical clearing of human skin without chemical agents that provides dramatic (up to 10-fold) reducing processing time down to 2-5 min. We discovered that ultrasound alone can increase a light depth penetration for optical coherence tomography (OCT) up to ~1.5-fold during 2 min. Nevertheless, sequent application of microdermabrasion, oleic acid and ultrasound allowed increasing OCT signal amplitude up to 3.3-fold with more than twice improved depth penetration during 30 min that was not demonstrated with other approaches. Comparison of these effects in light and dark skin revealed similarity of the optical clearing mechanisms. However, for combined optical clearing, only 1.34-fold increase in OCT signal amplitude was achieved for dark skin.

Morphometric Optical Imaging of Microporated Nail Tissue: An Investigation of Intermethod Agreement, Reliability, and Technical Limitations

BACKGROUND AND OBJECTIVES

While optical imaging is a useful technique to quantitate morphological differences and treatment effects, comparative investigations of the various techniques are lacking. This study aimed at evaluating intermethod agreement, reliability, and technical limitations of wide-field microscopy (WFM), reflectance confocal microscopy (RCM), and optical coherence tomography (OCT) for morphometry by assessing fractionally ablated nail tissue.

STUDY DESIGN/MATERIALS AND METHODS

Fifty healthy nail clippings were processed with a fractionated CO₂ -laser (20 mJ/microbeam, density 15%), measured with calipers, and imaged using WFM, OCT, and RCM. Images were assessed for nail plate thickness, micropore dimensions, degree of poration, and artifacts. Repeated measurements (2-5) were taken to evaluate method repeatability using Cronbach's α and coefficients of variation (CoV), and estimate the intermethod correlation through linear correlation assessment (Pearson correlation coefficient [PCC]), ranked correlation (Kendall's tau; tau-c), and intraclass correlation (Shrout-Fleiss reliability coefficient; ICC).

RESULTS

The repeatability varied substantially between methods and target measurements. The level of intermethod agreement for thickness measurements performed with calipers, WFM, and OCT was high (tau-c ≥ 0.7; ICC ≥ 0.8; PCC ≥ 0.9). RCM could only image 28 out of 50 samples due to its limited penetration depth. OCT demonstrated the highest repeatability of all imaging techniques (CoV 4-7%) and nail thickness showed the highest measurement reliability (α = 0.92). Micropore dimensions correlated strongest between OCT and RCM (tau-c/ICC/PCC ≥ 0.5). All modalities were prone to artifacts, which may have adversely affected measurement variation and intermethod agreement.

CONCLUSION

Intermethod agreement and reliability appear to be highly dependent on the specific modality and target measurement. To reap the benefits of each technique while mitigating their limitations, an integrated approach to optical imaging is recommended. Lasers Surg. Med. © 2020 Wiley Periodicals LLC.

Automatic Segmentation of Epidermis and Hair Follicles in Optical Coherence Tomography Images of Normal Skin by Convolutional Neural Networks

Optical coherence tomography (OCT) is a well-established bedside imaging modality that allows analysis of skin structures in a non-invasive way. Automated OCT analysis of skin layers is of great relevance to study dermatological diseases. In this paper, an approach to detect the epidermal layer along with the follicular structures in healthy human OCT images is presented. To the best of the authors' knowledge, the approach presented in this paper is the only epidermis detection algorithm that segments the pilosebaceous unit, which is of importance in the progression of several skin disorders such as folliculitis, acne, lupus erythematosus, and basal cell carcinoma. The proposed approach is composed of two main stages. The first stage is a Convolutional Neural Network based on U-Net architecture. The second stage is a robust post-processing composed by a Savitzky-Golay filter and Fourier Domain Filtering to fully define the borders belonging to the hair follicles. After validation, an average Dice of 0.83 ± 0.06 and a thickness error of 10.25 μm is obtained on 270 human skin OCT images. Based on these results, the proposed method outperforms other state-of-the-art methods for epidermis segmentation. It demonstrates that the proposed image segmentation method successfully detects the epidermal region in a fully automatic way in addition to defining the follicular skin structures as main novelty.

In-amplifier and cascaded mid-infrared supercontinuum sources with low noise through gain-induced soliton spectral alignment

The pulse-to-pulse relative intensity noise (RIN) of near-infrared (near-IR) in-amplifier supercontinuum (SC) sources and mid-IR cascaded SC sources was experimentally and numerically investigated and shown to have significantly lowered noise due to the fundamental effect of gain-induced soliton-spectral alignment. The mid-IR SC source is based on a near-IR in-amplifier SC pumping a cascade of thulium-doped and ZBLAN fibers. We demonstrate that the active thulium-doped fiber not only extend the spectrum, but also to significantly reduce the RIN by up to 22% in the long wavelength region above 2 μm. Using numerical simulations, we demonstrate that the noise reduction is the result of an interplay between absorption-emission processes and nonlinear soliton dynamics leading to the soliton-spectral alignment. In the same way we show that the RIN of the near-IR in-amplifier SC source is already significantly reduced because the spectral broadening takes place in an active fiber that also introduces soliton-spectral alignment. We further show that the low noise properties are transferred to the subsequent fluoride SC, which has a RIN lower than 10% (5%) in a broad region from 1.1-3.6 μm (1.4-3.0 μm). The demonstrated low noise significantly improves the applicability of these broadband sources for mid-IR imaging and spectroscopy.

Ultrahigh-resolution optical coherence tomography/angiography with an economic and compact supercontinuum laser

In this study, a Q-switch pumped supercontinuum laser (QS-SCL) is used as a light source for in vivo imaging via ultrahigh-resolution optical coherence tomography and angiography (UHR-OCT/OCTA). For this purpose, an OCT system based on a spectral-domain detection scheme is constructed, and a spectrometer with a spectral range of 635 - 875 nm is designed. The effective full-width at half maximum of spectrum covers 150 nm, and the corresponding axial and transverse resolutions are 2 and 10 µm in air, respectively. The relative intensity noise of the QS-SCL and mode-locked SCL is quantitatively compared. Furthermore, a special processing algorithm is developed to eliminate the intrinsic noise of QS-SCL. This work demonstrates that QS-SCLs can effectively reduce the cost and size of UHR-OCT/OCTA instruments, making clinical applications feasible.

Multioctave supercontinuum from visible to mid-infrared and bend effects on ultrafast nonlinear dynamics in gas-filled hollow-core fiber

Broadband supercontinuum generation is numerically investigated in a Xe-filled nested hollow-core antiresonant (HC-AR) fiber pumped at 3 μm with pulses of 100 fs duration and 15 μJ energy. For a 25 cm long fiber, under 7 bar pressure, the supercontinuum spectrum spans multiple octaves from 400 nm to 5000 nm. Furthermore, the influence of bending on ultrafast nonlinear pulse propagation dynamics is investigated for two types of HC-AR fibers (nested and non-nested capillaries). Our results predict similar nonlinear dynamics for both fiber types and a significant reduction of the spectral broadening under tight bending conditions.

Supercontinuum noise reduction by fiber undertapering

We demonstrate that the Relative Intensity Noise (RIN) of a supercontinuum source can be significantly reduced using the new concept of undertapering, where the fiber is tapered to a diameter that is smaller than the diameter that gives the shortest blue edge, which is typically regarded as the optimum. We show that undertapering allows to control the second zero dispersion wavelength and use it as a soliton barrier to stop the redshifting solitons at a pre-defined wavelength, and thereby strongly reduce the RIN. We demonstrate how undertapering can reduce the spectrally averaged RIN in the optical coherence tomography bands, 500-800nm and 1150-1450nm, by more than a factor two.

Real-time high-resolution mid-infrared optical coherence tomography

The potential for improving the penetration depth of optical coherence tomography systems by using light sources with longer wavelengths has been known since the inception of the technique in the early 1990s. Nevertheless, the development of mid-infrared optical coherence tomography has long been challenged by the maturity and fidelity of optical components in this spectral region, resulting in slow acquisition, low sensitivity, and poor axial resolution. In this work, a mid-infrared spectral-domain optical coherence tomography system operating at a central wavelength of 4 µm and an axial resolution of 8.6 µm is demonstrated. The system produces two-dimensional cross-sectional images in real time enabled by a high-brightness 0.9- to 4.7-µm mid-infrared supercontinuum source with a pulse repetition rate of 1 MHz for illumination and broadband upconversion of more than 1-µm bandwidth from 3.58-4.63 µm to 820-865 nm, where a standard 800-nm spectrometer can be used for fast detection. The images produced by the mid-infrared system are compared with those delivered by a state-of-the-art ultra-high-resolution near-infrared optical coherence tomography system operating at 1.3 μm, and the potential applications and samples suited for this technology are discussed. In doing so, the first practical mid-infrared optical coherence tomography system is demonstrated, with immediate applications in real-time non-destructive testing for the inspection of defects and thickness measurements in samples that exhibit strong scattering at shorter wavelengths.

All-depth dispersion cancellation in spectral domain optical coherence tomography using numerical intensity correlations

In ultra-high resolution (UHR-) optical coherence tomography (OCT) group velocity dispersion (GVD) must be corrected for in order to approach the theoretical resolution limit. One approach promises not only compensation, but complete annihilation of even order dispersion effects, and that at all sample depths. This approach has hitherto been demonstrated with an experimentally demanding ‘balanced detection’ configuration based on using two detectors. We demonstrate intensity correlation (IC) OCT using a conventional spectral domain (SD) UHR-OCT system with a single detector. IC-SD-OCT configurations exhibit cross term ghost images and a reduced axial range, half of that of conventional SD-OCT. We demonstrate that both shortcomings can be removed by applying a generic artefact reduction algorithm and using analytic interferograms. We show the superiority of IC-SD-OCT compared to conventional SD-OCT by showing how IC-SD-OCT is able to image spatial structures behind a strongly dispersive silicon wafer. Finally, we question the resolution enhancement of \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\sqrt{2}$$\end{document}2 that IC-SD-OCT is often believed to have compared to SD-OCT. We show that this is simply the effect of squaring the reflectivity profile as a natural result of processing the product of two intensity spectra instead of a single spectrum.