A review of low-cost and portable optical coherence tomography

Design of an endoscopic OCT probe based on piezoelectric tube with quartered outside electrodes

Introduction: Optical coherence tomography (OCT) is a pivotal imaging modality in ophthalmology for real-time, in vivo visualization of retinal structures. To enhance the capability and safety of OCT, this study focuses on the development of a micro intraocular OCT probe. The demand for minimal invasiveness and precise imaging drives the need for advanced probe designs that can access tight and sensitive areas, such as the ocular sclera. Methods: A novel OCT probe was engineered using a piezoelectric tube with quartered electrodes to drive Lissajous scanning movements at the end of a single-mode fiber. This design allows the probe to enter the eyeball through a scleral opening. Structural innovation enables the outer diameter of the endoscopic OCT probe to be adjusted from 13G (2.41 mm) to 25G (0.51 mm), accommodating various imaging field sizes and ensuring compatibility with different scleral incisions. Results: The fabricated micro intraocular OCT probe successfully performed preliminary imaging experiments on in vivo fingers. The Lissajous scanning facilitated comprehensive coverage of the target area, enhancing the imaging capabilities. Discussion: The integration of a piezoelectric tube with quartered outside electrodes into the OCT probe design proved effective for achieving precise control over scanning movements and adaptability to different surgical needs. The design characteristics and practical applications demonstrated the probe's potential in clinical settings.

Ultraviolet-Visible-Near Infrared Spectroscopy May Aid in the Qualitative Assessment of Early-Stage Cartilage Degradation

Purpose

To assess the potential of ultraviolet-visible near-infrared spectroscopy to provide quantitative information on the cartilage surface at early osteoarthritis.

Methods

We used a similar source and optical path to a standard arthroscope and constraining input to the range available to a standard detector/camera, further capturing and analyzing spectral information quantitatively in terms of specific electronic absorbance bands and scattering from the cartilage surface, with a focus on the early stages of degradation.

Results

The ratio of the 320-nm and longer than 500-nm absorbances produced a distinct change from the normal to diseased states. The slopes between the wavelengths of 600 and 980 nm may show the transition of the single fibril to fibril bundles that occurs during early stages disease.

Conclusions

Ultraviolet-visible near-infrared spectroscopy has good potential for use in integrated arthroscopic assessment.

Clinical Relevance

This raises the possibility of advancing arthroscopy from a qualitative to a quantitative tool, without requiring modification of either the radiation (the light source and path) or instrumentation (the arthroscope itself) delivered to the patient, thus allowing a low-cost yet potentially high-value technology.

High-accuracy noninvasive continuous glucose monitoring using OCT angiography-purified blood scattering signals in human skin

The accuracy of noninvasive continuous glucose monitoring (CGM) through near-infrared scattering is challenged by mixed scattering signals from different compartments, where glucose has a positive correlation with a blood scattering coefficient but a negative correlation with a tissue scattering coefficient. In this study, we developed a high-accuracy noninvasive CGM based on OCT angiography (OCTA)-purified blood scattering signals. The blood optical scattering coefficient (BOC) was initially extracted from the depth attenuation of backscattered light in OCT and then purified by eliminating the scattering signals from the surrounding tissues under the guidance of a 3D OCTA vascular map in human skin. The purified BOC was used to estimate the optical blood glucose concentration (BGC) through a linear calibration. The optical and reference BGC measurements were highly correlated (R = 0.94) without apparent time delay. The mean absolute relative difference was 6.09%. All optical BGC measurements were within the clinically acceptable Zones A + B, with 96.69% falling in Zone A on Parke's error grids. The blood glucose response during OGTT was mapped with a high spatiotemporal resolution of the single vessel and 5 seconds. This noninvasive OCTA-based CGM shows promising accuracy for clinical use. Future research will involve larger sample sizes and diabetic participants to confirm these preliminary findings.

Rapid imaging and product screening with low-cost line-field Fourier domain optical coherence tomography

Fourier domain optical coherence tomography (FD-OCT) is a well-established imaging technique that provides high-resolution internal structure images of an object at a fast speed. Modern FD-OCT systems typically operate at speeds of 40,000-100,000 A-scans/s, but are priced at least tens of thousands of pounds. In this study, we demonstrate a line-field FD-OCT (LF-FD-OCT) system that achieves an OCT imaging speed of 100,000 A-scan/s at a hardware cost of thousands of pounds. We demonstrate the potential of LF-FD-OCT for biomedical and industrial imaging applications such as corneas, 3D printed electronics, and printed circuit boards.

Long-range frequency domain low-coherence interferometry detector for industrial applications

A low-cost long-range frequency domain low-coherence interferometry (LCI) detector is presented: time Fourier domain LCI (TFD-LCI). Combining ideas of time domain and frequency domain techniques, the TFD-LCI detects the analog Fourier transform of the optical interference signal with no limitation for the maximum optical path, measuring the thickness of several centimeters with micrometer resolution. A complete characterization of the technique is presented with a mathematical demonstration, simulations, and experimental results. An evaluation of repeatability and accuracy is also included. Measurements of small and large monolayer and multilayer thicknesses were done. Characterization of the internal and external thicknesses of industrial products such as transparent packages and glass windshield is presented, showing the potentiality of TFD-LCI for industrial applications.

Automatic detection of glaucoma via fundus imaging and artificial intelligence: A review

Glaucoma is a leading cause of irreversible vision impairment globally, and cases are continuously rising worldwide. Early detection is crucial, allowing timely intervention that can prevent further visual field loss. To detect glaucoma an examination of the optic nerve head via fundus imaging can be performed, at the center of which is the assessment of the optic cup and disc boundaries. Fundus imaging is noninvasive and low-cost; however, image examination relies on subjective, time-consuming, and costly expert assessments. A timely question to ask is: "Can artificial intelligence mimic glaucoma assessments made by experts?" Specifically, can artificial intelligence automatically find the boundaries of the optic cup and disc (providing a so-called segmented fundus image) and then use the segmented image to identify glaucoma with high accuracy? We conducted a comprehensive review on artificial intelligence-enabled glaucoma detection frameworks that produce and use segmented fundus images and summarized the advantages and disadvantages of such frameworks. We identified 36 relevant papers from 2011 to 2021 and 2 main approaches: 1) logical rule-based frameworks, based on a set of rules; and 2) machine learning/statistical modeling-based frameworks. We critically evaluated the state-of-art of the 2 approaches, identified gaps in the literature and pointed at areas for future research.

Non-invasive biomedical sensors for early detection and monitoring of bacterial biofilm growth at the point of care

Bacterial infections have long been a serious global health issue. Biofilm formation complicates matters even more. The biofilm's extracellular polymeric substances (EPSs) matrix protects bacteria from the host's immune responses, yielding strong adhesion and drug resistance as the biofilm matures. Early bacterial biofilm detection and bacterial biofilm growth monitoring are crucial to treating biofilm-associated infections. Current detection methods are highly sensitive but not portable, are time-consuming, and require expensive equipment and complex operating procedures, limiting their use at the point of care. Therefore, there is an urgent need to develop affordable, on-body, and non-invasive biomedical sensors to continuously monitor and detect early biofilm growth at the point of care through personalized telemedicine. Herein, recent advances in developing non-invasive biomedical sensors for early detection and monitoring bacterial biofilm growth are comprehensively reviewed. First, biofilm's life cycle and its impact on the human body, such as biofilm-associated disease and infected medical devices, are introduced together with the challenges of biofilm treatment. Then, the current methods used in clinical and laboratory settings for biofilm detection and their challenges are discussed. Next, the current state of non-invasive sensors for direct and indirect detection of bacterial biofilms are summarized and highlighted with the detection parameters and their design details. Finally, commercially available products, challenges of current devices, and the further trend in biofilm detection sensors are discussed.

Stochastic Differential Equations for Automatic Quality Control of Retinal Optical Coherence Tomography images

Optical coherence tomography is widely used to provide high resolution images from retina. During data acquisition, several artifacts may be associated with OCT images which clearly remove information of retinal layers and degrade the quality of images. Manual assessment of the acquired OCT images is hard and time consuming. Therefore, an automatic quality control step is necessary to detect poor images for next decisions of eliminating them and even re-scanning. In this study, a novel automatic quality control methodology is proposed for early assessment of the OCT images quality by employing stochastic differential equations (SDE). In this method α-stable nature of OCT images is represented by applying a fractional Laplacian filter and parameters of the obtained α-stable are fed to an SVM to automatically detect high quality vs poor quality images. The simulation results on a large dataset of normal and abnormal OCT images show that proposed method has outstanding performance in detection of poor vs high quality images. The methodology is applicable to the image quality assessment of other OCT scanning devices as well. Clinical Relevance- Automatic quality control assessment of retinal OCT images provides reliable data for diagnosis of retinal and systematic diseases in clinical applications.

A clinical perspective on the expanding role of artificial intelligence in age-related macular degeneration

In recent years, there has been intense development of artificial intelligence (AI) techniques, which have the potential to improve the clinical management of age-related macular degeneration (AMD) and facilitate the prevention of irreversible vision loss from this condition. Such AI techniques could be used as clinical decision support tools to: (i) improve the detection of AMD by community eye health practitioners, (ii) enhance risk stratification to enable personalised monitoring strategies for those with the early stages of AMD, and (iii) enable early detection of signs indicative of possible choroidal neovascularisation allowing triaging of patients requiring urgent review. This review discusses the latest developments in AI techniques that show promise for these tasks, as well as how they may help in the management of patients being treated for choroidal neovascularisation and in accelerating the discovery of new treatments in AMD.

Multimodal Handheld Probe for Characterizing Otitis Media - Integrating Raman Spectroscopy and Optical Coherence Tomography

Otitis media (OM) is a common disease of the middle ear, affecting 80% of children before the age of three. The otoscope, a simple illuminated magnifier, is the standard clinical diagnostic tool to observe the middle ear. However, it has limited contrast to detect signs of infection, such as clearly identifying and characterizing middle ear fluid or biofilms that accumulate within the middle ear. Likewise, invasive sampling of every subject is not clinically indicated nor practical. Thus, collecting accurate noninvasive diagnostic factors is vital for clinicians to deliver a precise diagnosis and effective treatment regimen. To address this need, a combined benchtop Raman spectroscopy (RS) and optical coherence tomography (OCT) system was developed. Together, RS-OCT can non-invasively interrogate the structural and biochemical signatures of the middle ear under normal and infected conditions.In this paper, in vivo RS scans from pediatric clinical human subjects presenting with OM were evaluated in parallel with RS-OCT data of physiologically relevant in vitro ear models. Component-level characterization of a healthy tympanic membrane and malleus bone, as well as OM-related middle ear fluid, identified the optimal position within the ear for RS-OCT data collection. To address the design challenges in developing a system specific to clinical use, a prototype non-contact multimodal handheld probe was built and successfully tested in vitro. Design criteria have been developed to successfully address imaging constraints imposed by physiological characteristics of the ear and optical safety limits. Here, we present the pathway for translation of RS-OCT for non-invasive detection of OM.

Diabetic Macular Edema Screened by Handheld Smartphone-based Retinal Camera and Artificial Intelligence

Our aim was to assess the tomographic presence of diabetic macular edema in type 2 diabetes patients screened for diabetic retinopathy with color fundus photographs and an artificial intelligence algorithm. Color fundus photographs obtained with a low-cost smartphone-based handheld retinal camera were analyzed by the algorithm; patients with suspected macular lesions underwent ocular coherence tomography. A total of 366 patients were screened; diabetic macular edema was suspected in 34 and confirmed in 29 individuals, with average age 60.5 ± 10.9 years and glycated hemoglobin 9.8 ± 2.4%; use of insulin, statins, and aspirin were reported in 44.8%, 37.9%, and 34.5% of individuals, respectively; systemic blood hypertension, dyslipidemia, abdominal obesity, chronic kidney disease, and risk for diabetic foot ulcers were present in 100%, 58.6%, 62.1%, 48.3%, and 27.5% of individuals, respectively. Proliferative diabetic retinopathy was present in 31% of patients with macular edema; severity level was associated with albuminuria (p = 0.028). Eyes with macular edema had average central macular thickness 329.89 ± 80.98 m[Formula: see text]; intraretinal cysts, sub retinal fluid, hyper-reflective foci, epiretinal membrane, and vitreomacular traction were found in 87.2%, 6.4%, 85.1%, 10.6%, and 6.4% of eyes, respectively. Diabetic retinopathy screening overwhelms health systems and is typically based on color fundus photographs, with high false-positive rates for the detection of diabetic macular edema. The present, semi-automated strategy comprising artificial intelligence algorithms integrated with smartphone-based retinal cameras could improve screening in low-resource settings with limited availability of ocular coherence tomography, allowing increased access rates and ultimately contributing to tackle preventable blindness.

Deep imaging with 1.3 µm dual-axis optical coherence tomography and an enhanced depth of focus

For many clinical applications, such as dermatology, optical coherence tomography (OCT) suffers from limited penetration depth due primarily to the highly scattering nature of biological tissues. Here, we present a novel implementation of dual-axis optical coherence tomography (DA-OCT) that offers improved depth penetration in skin imaging at 1.3 µm compared to conventional OCT. Several unique aspects of DA-OCT are examined here, including the requirements for scattering properties to realize the improvement and the limited depth of focus (DOF) inherent to the technique. To overcome this limitation, our approach uses a tunable lens to coordinate focal plane selection with image acquisition to create an enhanced DOF for DA-OCT. This improvement in penetration depth is quantified experimentally against conventional on-axis OCT using tissue phantoms and mouse skin. The results presented here suggest the potential use of DA-OCT in situations where a high degree of scattering limits depth penetration in OCT imaging.

Optical coherence tomography of small intestine allograft biopsies using a handheld surgical probe

SIGNIFICANCE

The current gold standard for monitoring small intestinal transplant (IT) rejection is endoscopic visual assessment and biopsy of suspicious lesions; however, these lesions are only superficially visualized by endoscopy. Invasive biopsies provide a coarse sampling of tissue health without depicting the true presence and extent of any pathology. Optical coherence tomography (OCT) presents a potential alternative approach with significant advantages over traditional white-light endoscopy.

AIM

The aim of our investigation was to evaluate OCT performance in distinguishing clinically relevant morphological features associated with IT graft failure.

APPROACH

OCT was applied to evaluate the small bowel tissues of two rhesus macaques that had undergone IT of the ileum. The traditional assessment from routine histological observation was compared with OCT captured using a handheld surgical probe during the days post-transplant and subsequently was compared with histophaology.

RESULTS

The reported OCT system was capable of identifying major biological landmarks in healthy intestinal tissue. Following IT, one nonhuman primate (NHP) model suffered a severe graft ischemia, and the second NHP graft failed due to acute cellular rejection. OCT images show visual evidence of correspondence with histological signs of IT rejection.

CONCLUSIONS

Results suggest that OCT imaging has significant potential to reveal morphological changes associated with IT rejection and to improve patient outcomes overall.