7.2 Optical coherence tomography (OCT)

Optical coherence tomography (OCT) is a game-changing imaging technique in medicine. It uses low-coherence light to create high-resolution, 3D images of biological tissue without invasive procedures. OCT has revolutionized fields like ophthalmology by providing detailed cross-sections of the eye's structures.

The tech behind OCT relies on interferometry and coherence gating. These allow it to selectively image specific depths in tissue while rejecting scattered light from other areas. This results in crisp, depth-resolved images that reveal intricate tissue microstructures in real-time.

Principles of optical coherence tomography

• Optical coherence tomography (OCT) is a non-invasive imaging technique that uses low-coherence light to capture micrometer-resolution, three-dimensional images from within optical scattering media (biological tissue)
• OCT is based on the principles of low coherence interferometry and employs coherence gating to select light only scattered from a specific depth, rejecting scattered light from other depths in the sample
• OCT has become a widely used imaging modality in various biomedical applications, particularly in ophthalmology, due to its ability to provide high-resolution cross-sectional images of tissue microstructure in real-time

Michelson interferometer setup

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• OCT systems typically employ a Michelson interferometer setup, which consists of a low-coherence light source, a beam splitter, a reference arm, and a sample arm
• The beam splitter divides the light into two paths: one towards the reference arm (usually a mirror) and the other towards the sample arm (containing the tissue to be imaged)
• Light reflected from the reference arm and backscattered from the sample arm interferes at the beam splitter, creating an interference pattern that is detected by a photodetector
• The interference signal contains information about the depth-resolved reflectivity profile of the sample, which is used to reconstruct the OCT image

Low coherence interferometry

• Low coherence interferometry (LCI) is the fundamental principle behind OCT imaging
• LCI uses a broadband light source with a short coherence length (typically in the range of micrometers) to achieve high axial resolution
• The short coherence length ensures that interference occurs only when the optical path lengths of the reference and sample arms are closely matched within the coherence length of the light source
• This property allows OCT to selectively image specific depths within the sample, rejecting scattered light from other depths

Coherence gating

• Coherence gating is the mechanism by which OCT achieves depth selectivity in imaging
• By scanning the reference arm mirror, the optical path length difference between the reference and sample arms is varied
• Interference occurs only when the path length difference is within the coherence length of the light source, effectively "gating" the detected signal to a specific depth in the sample
• Coherence gating enables OCT to reject out-of-focus light and provide high-resolution, depth-resolved images of the sample

Axial vs lateral resolution

• OCT imaging resolution is characterized by two parameters: axial resolution and lateral resolution
• Axial resolution, also known as depth resolution, is determined by the coherence length of the light source and is inversely proportional to the bandwidth of the source spectrum
• Broader bandwidth light sources (superluminescent diodes, ultrashort pulse lasers) provide higher axial resolution (typically 1-15 μm)
• Lateral resolution is determined by the focusing properties of the sample arm optics and is similar to that of conventional microscopy techniques
• Lateral resolution can be improved by using high numerical aperture (NA) focusing optics, but this comes at the cost of reduced depth of field

OCT system components

• A typical OCT system consists of several key components that work together to generate high-resolution, depth-resolved images of the sample
• These components include a low coherence light source, an optical fiber coupler, a reference mirror, and a photodetector with associated signal processing electronics
• The specific configuration and choice of components may vary depending on the OCT technique employed (time domain, Fourier domain, or swept source) and the intended application

Low coherence light sources

• Low coherence light sources are essential for achieving high axial resolution in OCT imaging
• These sources have a broad spectral bandwidth and a short coherence length, typically in the range of micrometers
• Common low coherence light sources used in OCT include superluminescent diodes (SLDs), ultrashort pulse lasers (femtosecond lasers), and supercontinuum sources
• SLDs are the most widely used light sources in OCT due to their relatively low cost, high output power, and ease of use
• Ultrashort pulse lasers and supercontinuum sources offer even broader bandwidths and higher axial resolution but are more complex and expensive

Optical fiber coupler

• An optical fiber coupler is used to split the light from the low coherence source into the reference and sample arms of the interferometer
• The coupler also recombines the reflected light from the reference arm and the backscattered light from the sample arm, directing the interference signal to the photodetector
• Fiber couplers are typically 2x2 or 3x3 fused-fiber couplers with a 50:50 or 33:33:33 splitting ratio, respectively
• The use of optical fibers in OCT systems enables flexible sample arm designs, such as handheld probes or endoscopic catheters, for various biomedical applications

Reference mirror

• The reference mirror is a critical component in the reference arm of the OCT interferometer
• In time domain OCT, the reference mirror is mechanically scanned to vary the optical path length difference between the reference and sample arms, enabling depth scanning
• In Fourier domain OCT, the reference mirror is fixed, and depth information is encoded in the spectral interference pattern
• The reference mirror is typically a high-reflectivity, flat mirror mounted on a translation stage or a galvanometer for precise positioning and scanning

Photodetector and signal processing

• The photodetector is responsible for converting the optical interference signal into an electrical signal for further processing
• Common photodetectors used in OCT include photodiodes, avalanche photodiodes (APDs), and balanced detectors
• Balanced detection, using two matched photodiodes, is often employed to suppress common-mode noise and improve the signal-to-noise ratio (SNR)
• The electrical signal from the photodetector undergoes analog-to-digital conversion (ADC) and digital signal processing to extract the depth-resolved sample reflectivity profile
• Signal processing techniques may include bandpass filtering, envelope detection, and Fourier transformation, depending on the OCT technique employed

OCT scanning methods

• OCT scanning methods refer to the different approaches used to acquire depth-resolved sample information and generate OCT images
• The choice of scanning method depends on factors such as imaging speed, sensitivity, and system complexity
• The main OCT scanning methods are time domain OCT, Fourier domain OCT (spectral domain and swept source), and full field OCT
• Each method has its advantages and limitations, and the selection depends on the specific application requirements

Time domain OCT

• Time domain OCT (TD-OCT) was the first generation of OCT technology and is based on the mechanical scanning of the reference arm mirror
• In TD-OCT, the reference mirror is translated to vary the optical path length difference between the reference and sample arms
• Depth-resolved sample information is acquired sequentially by detecting the interference signal at each depth position
• TD-OCT has a relatively slow imaging speed (hundreds of A-scans per second) due to the mechanical scanning of the reference mirror
• However, TD-OCT systems are generally simpler and less expensive compared to Fourier domain OCT systems

Fourier domain OCT

• Fourier domain OCT (FD-OCT) is a more advanced OCT technique that offers significantly higher imaging speeds and sensitivity compared to TD-OCT
• In FD-OCT, the reference mirror is fixed, and depth information is encoded in the spectral interference pattern
• FD-OCT can be further divided into two subcategories: spectral domain OCT (SD-OCT) and swept source OCT (SS-OCT)
• SD-OCT uses a broadband light source and a spectrometer to detect the spectral interference pattern, while SS-OCT employs a rapidly tunable laser source and a single photodetector
• FD-OCT enables imaging speeds of tens to hundreds of thousands of A-scans per second, enabling real-time, high-resolution imaging of dynamic biological processes

Swept source OCT

• Swept source OCT (SS-OCT) is a variant of Fourier domain OCT that uses a rapidly tunable laser source (swept source) to scan the optical frequency or wavelength over time
• The swept source generates a narrow-bandwidth optical output that is rapidly swept across a broad spectral range
• A single photodetector is used to detect the interference signal as a function of time, which is then converted to the depth-resolved sample reflectivity profile through Fourier transformation
• SS-OCT offers several advantages over SD-OCT, including a longer imaging depth range, reduced sensitivity roll-off, and compatibility with longer wavelength light sources (1.3 μm and 1.7 μm) for improved tissue penetration

Full field OCT

• Full field OCT (FF-OCT) is a variant of OCT that acquires en face images of the sample without the need for beam scanning
• In FF-OCT, the entire sample is illuminated with a low coherence light source, and the backscattered light is detected using a 2D camera (CCD or CMOS) instead of a single photodetector
• Depth scanning is achieved by mechanically translating the reference mirror or the sample along the optical axis
• FF-OCT offers the advantage of simplified system design and the ability to acquire high-resolution en face images without the need for complex scanning mechanisms
• However, FF-OCT typically has a slower imaging speed compared to other OCT scanning methods due to the mechanical depth scanning

OCT image formation

• OCT image formation involves the acquisition, processing, and display of depth-resolved sample information to generate cross-sectional or volumetric images of the sample
• The fundamental building blocks of OCT images are A-scans (axial scans) and B-scans (cross-sectional scans)
• Advanced OCT image formation techniques include en face imaging, 3D volumetric imaging, and speckle reduction methods
• These techniques aim to enhance the visualization and interpretation of OCT images for various biomedical applications

A-scans and B-scans

• An A-scan (axial scan) represents the depth-resolved reflectivity profile of the sample at a single lateral position
• A-scans are acquired by measuring the interference signal as a function of depth, either by scanning the reference mirror (TD-OCT) or by detecting the spectral interference pattern (FD-OCT)
• A B-scan (cross-sectional scan) is formed by laterally scanning the sample beam and acquiring multiple A-scans at adjacent lateral positions
• B-scans provide a 2D cross-sectional image of the sample, displaying the depth-resolved reflectivity profiles along the lateral scan direction
• The lateral scanning is typically achieved using galvanometer mirrors or microelectromechanical systems (MEMS) scanners

En face imaging

• En face OCT imaging generates depth-resolved 2D images of the sample in the lateral plane, perpendicular to the optical axis
• En face images are constructed by extracting and displaying the OCT signal at a specific depth or depth range from a series of B-scans
• This imaging mode provides a view of the sample that is similar to that of conventional microscopy techniques
• En face OCT imaging is particularly useful for visualizing and quantifying tissue morphology and pathology in the lateral dimensions

3D volumetric imaging

• 3D volumetric OCT imaging involves the acquisition of a series of B-scans at adjacent lateral positions to form a 3D dataset of the sample
• The 3D dataset consists of a stack of B-scans, with each B-scan representing a cross-sectional image at a specific lateral position
• Volumetric imaging enables the visualization and analysis of sample morphology and pathology in three dimensions
• Advanced visualization techniques, such as volume rendering and segmentation, can be applied to 3D OCT datasets to extract quantitative information and enhance the understanding of sample structure and function

Speckle reduction techniques

• Speckle noise is a common issue in OCT imaging, arising from the coherent nature of the light source and the interference of multiple scattered waves within the sample
• Speckle noise can degrade image quality, reduce contrast, and hinder the interpretation of OCT images
• Various speckle reduction techniques have been developed to mitigate the effects of speckle noise and improve OCT image quality
• These techniques include spatial compounding (averaging multiple B-scans acquired at slightly different angles), frequency compounding (averaging multiple B-scans acquired with different center frequencies), and digital filtering methods (e.g., median filtering, wavelet denoising)
• Speckle reduction techniques can significantly enhance the visual quality and interpretability of OCT images, facilitating more accurate diagnosis and quantitative analysis

OCT image interpretation

• OCT image interpretation involves the analysis of OCT images to extract clinically relevant information about the sample's structure, composition, and pathology
• Key aspects of OCT image interpretation include understanding tissue scattering properties, boundary detection and segmentation, quantitative measurements, and artifact identification and correction
• Proper interpretation of OCT images requires knowledge of the underlying tissue biology, the principles of OCT imaging, and the potential sources of image artifacts
• Advanced image processing and machine learning techniques are increasingly being applied to OCT image interpretation to improve accuracy, reproducibility, and efficiency

Tissue scattering properties

• Tissue scattering properties play a crucial role in determining the appearance and contrast of OCT images
• Biological tissues exhibit varying degrees of scattering, depending on their composition and structure (e.g., cell density, collagen content, and organization)
• Highly scattering tissues (e.g., collagen-rich dermis) appear bright in OCT images due to the strong backscattering of light
• Low scattering tissues (e.g., clear cornea) appear dark in OCT images due to the reduced backscattering and increased transmission of light
• Understanding the relationship between tissue scattering properties and OCT image contrast is essential for accurate image interpretation and tissue characterization

Boundary detection and segmentation

• Boundary detection and segmentation are important tasks in OCT image interpretation, enabling the delineation and quantification of specific tissue layers, structures, or pathologies
• Boundary detection involves identifying the interfaces between different tissue layers or structures based on changes in OCT signal intensity or texture
• Segmentation refers to the process of partitioning the OCT image into distinct regions corresponding to specific tissue types or pathological features
• Various image processing techniques, such as edge detection, thresholding, and graph-based methods, can be employed for boundary detection and segmentation
• Machine learning algorithms, particularly deep learning approaches, have shown promise in automating boundary detection and segmentation tasks, improving accuracy and reproducibility

Quantitative measurements

• Quantitative measurements derived from OCT images provide objective and reproducible metrics for assessing tissue structure, composition, and pathology
• Common quantitative measurements in OCT image interpretation include layer thickness, attenuation coefficients, and texture parameters
• Layer thickness measurements (e.g., retinal nerve fiber layer thickness in glaucoma assessment) can be obtained by segmenting the boundaries of specific tissue layers and calculating the distance between them
• Attenuation coefficients, which describe the rate of OCT signal decay with depth, can be estimated by fitting exponential models to the depth-resolved OCT signal profile
• Texture parameters, such as contrast, correlation, and homogeneity, can be extracted from OCT images to characterize tissue organization and detect pathological changes
• Quantitative measurements enable more precise and objective comparisons between normal and pathological tissues, aiding in diagnosis, treatment planning, and monitoring

Artifact identification and correction

• OCT images are susceptible to various artifacts that can degrade image quality, lead to misinterpretation, or hinder quantitative analysis
• Common OCT image artifacts include motion artifacts, refraction artifacts, shadowing, and speckle noise
• Motion artifacts arise from patient movement or physiological motion (e.g., breathing, heartbeat) during image acquisition, resulting in image distortion or blurring
• Refraction artifacts occur when light propagates through tissues with different refractive indices, causing image distortion and displacement
• Shadowing artifacts appear as dark regions in OCT images, caused by the attenuation of light by highly scattering or absorbing structures (e.g., blood vessels, pigmented lesions)
• Speckle noise, as discussed earlier, is inherent to OCT imaging due to the coherent nature of the light source
• Identifying and correcting these artifacts is crucial for accurate image interpretation and quantitative analysis
• Artifact correction techniques include image registration (for motion artifacts), refraction correction algorithms, adaptive compensation (for shadowing), and speckle reduction methods (e.g., compounding, filtering)

Biomedical applications of OCT

• OCT has found widespread application in various biomedical fields due to its ability to provide high-resolution, non-invasive imaging of tissue microstructure
• The main biomedical applications of OCT include ophthalmology, dermatology, cardiovascular imaging, and gastrointestinal and endoscopic imaging
• OCT's unique capabilities, such as depth-resolved imaging, real-time acquisition, and compatibility with fiber-optic delivery systems, have made it a valuable tool for diagnosis, treatment planning, and monitoring in these fields
• Ongoing research and technological advancements continue to expand the range of OCT applications and improve its clinical utility

Ophthalmology and retinal imaging

• Ophthalmology is one of the most well-established and successful applications of OCT imaging
• OCT has revolutionized the diagnosis and management of various retinal diseases, such as age-related macular degeneration (AMD), diabetic retinopathy, and glaucoma
• In retinal imaging, OCT provides high-resolution, cross-sectional images of the retina, enabling the visualization of individual retinal layers and the detection of pathological changes
• Quantitative measurements, such as retinal nerve fiber layer thickness and macular thickness, can be derived from OCT images to aid in